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Xiao Q, Tang W, Zhang C, Zhou L, Feng L, Shen J, Yan T, Gao P, He Y, Wu N. Spectral Preprocessing Combined with Deep Transfer Learning to Evaluate Chlorophyll Content in Cotton Leaves. PLANT PHENOMICS 2022; 2022:9813841. [PMID: 36158530 PMCID: PMC9489230 DOI: 10.34133/2022/9813841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 06/27/2022] [Indexed: 11/16/2022]
Abstract
Rapid determination of chlorophyll content is significant for evaluating cotton's nutritional and physiological status. Hyperspectral technology equipped with multivariate analysis methods has been widely used for chlorophyll content detection. However, the model developed on one batch or variety cannot produce the same effect for another due to variations, such as samples and measurement conditions. Considering that it is costly to establish models for each batch or variety, the feasibility of using spectral preprocessing combined with deep transfer learning for model transfer was explored. Seven different spectral preprocessing methods were discussed, and a self-designed convolutional neural network (CNN) was developed to build models and conduct transfer tasks by fine-tuning. The approach combined first-derivative (FD) and standard normal variate transformation (SNV) was chosen as the best pretreatment. For the dataset of the target domain, fine-tuned CNN based on spectra processed by FD + SNV outperformed conventional partial least squares (PLS) and squares-support vector machine regression (SVR). Although the performance of fine-tuned CNN with a smaller dataset was slightly lower, it was still better than conventional models and achieved satisfactory results. Ensemble preprocessing combined with deep transfer learning could be an effective approach to estimate the chlorophyll content between different cotton varieties, offering a new possibility for evaluating the nutritional status of cotton in the field.
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Affiliation(s)
- Qinlin Xiao
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
| | - Wentan Tang
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
| | - Chu Zhang
- School of Information Engineering, Huzhou University, Huzhou 313000, China
| | - Lei Zhou
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
- College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China
| | - Lei Feng
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
| | - Jianxun Shen
- Hangzhou Raw Seed Growing Farm, Hangzhou 311115, China
| | - Tianying Yan
- College of Information Science and Technology, Shihezi University, Shihezi 832000, China
| | - Pan Gao
- College of Information Science and Technology, Shihezi University, Shihezi 832000, China
| | - Yong He
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
| | - Na Wu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
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52
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Yahyaoui H, AboElfotoh H, Shu Y. A partial order framework for incomplete data clustering. APPL INTELL 2022. [DOI: 10.1007/s10489-022-03887-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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53
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Leyva López JC, Solares E, Figueira JR. An evolutionary approach for inferring the model parameters of the hierarchical Electre III method. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.06.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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54
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The Internet Shopping Optimization Problem with Multiple Item Units (ISHOP-U): Formulation, Instances, NP-Completeness, and Evolutionary Optimization. MATHEMATICS 2022. [DOI: 10.3390/math10142513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In this work, we investigate the variant of the Internet Shopping Optimization Problem (ISHOP) that considers different item units. This variant is more challenging than the original problem. The original ISHOP is already known as a combinatorial NP-hard problem. In this work, we present a formal proof that the ISHOP variant considering different item units belongs to the NP-Hard complexity class. The abovementioned variant is familiar to companies and consumers who need to purchase more than one unit of a specific product to satisfy their requirements. For example, companies buy different quantities of construction materials, medical equipment, office supplies, or chemical components. We propose two new evolutionary operators (crossover and mutation) and an unfeasible solution repair method for the studied ISHOP variant. Furthermore, we produce a new benchmark of 15 synthetic instances where item prices follow a random uniform distribution. Finally, to assess our evolutionary operators, we implemented two Evolutionary Algorithms, a Genetic Algorithm (GA) and a Cellular Genetic Algorithm (CGA), and an experimental evaluation against a Water Cycle Algorithm (WCA) from the state-of-the-art. Experimental results show that our proposed GA performs well with statistical significance.
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Effects of Pulsatile Flow Rate and Shunt Ratio in Bifurcated Distal Arteries on Hemodynamic Characteristics Involved in Two Patient-Specific Internal Carotid Artery Sidewall Aneurysms: A Numerical Study. Bioengineering (Basel) 2022; 9:bioengineering9070326. [PMID: 35877376 PMCID: PMC9311626 DOI: 10.3390/bioengineering9070326] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 07/05/2022] [Accepted: 07/15/2022] [Indexed: 01/08/2023] Open
Abstract
The pulsatile flow rate (PFR) in the cerebral artery system and shunt ratios in bifurcated arteries are two patient-specific parameters that may affect the hemodynamic characteristics in the pathobiology of cerebral aneurysms, which needs to be identified comprehensively. Accordingly, a systematic study was employed to study the effects of pulsatile flow rate (i.e., PFR−I, PFR−II, and PFR−III) and shunt ratio (i.e., 75:25 and 64:36) in bifurcated distal arteries, and transient cardiac pulsatile waveform on hemodynamic patterns in two internal carotid artery sidewall aneurysm models using computational fluid dynamics (CFD) modeling. Numerical results indicate that larger PFRs can cause higher wall shear stress (WSS) in some local regions of the aneurysmal dome that may increase the probability of small/secondary aneurysm generation than under smaller PFRs. The low WSS and relatively high oscillatory shear index (OSI) could appear under a smaller PFR, increasing the potential risk of aneurysmal sac growth and rupture. However, the variances in PFRs and bifurcated shunt ratios have rare impacts on the time-average pressure (TAP) distributions on the aneurysmal sac, although a higher PFR can contribute more to the pressure increase in the ICASA−1 dome due to the relatively stronger impingement by the redirected bloodstream than in ICASA−2. CFD simulations also show that the variances of shunt ratios in bifurcated distal arteries have rare impacts on the hemodynamic characteristics in the sacs, mainly because the bifurcated location is not close enough to the sac in present models. Furthermore, it has been found that the vortex location plays a major role in the temporal and spatial distribution of the WSS on the luminal wall, varying significantly with the cardiac period.
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56
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Wiedemann J, Kaczor J, Milostan M, Zok T, Blazewicz J, Szachniuk M, Antczak M. RNAloops: a database of RNA multiloops. Bioinformatics 2022; 38:4200-4205. [PMID: 35809063 PMCID: PMC9438955 DOI: 10.1093/bioinformatics/btac484] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 06/26/2022] [Accepted: 07/06/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Knowledge of the 3D structure of RNA supports discovering its functions and is crucial for designing drugs and modern therapeutic solutions. Thus, much attention is devoted to experimental determination and computational prediction targeting the global fold of RNA and its local substructures. The latter include multi-branched loops-functionally significant elements that highly affect the spatial shape of the entire molecule. Unfortunately, their computational modeling constitutes a weak point of structural bioinformatics. A remedy for this is in collecting these motifs and analyzing their features. RESULTS RNAloops is a self-updating database that stores multi-branched loops identified in the PDB-deposited RNA structures. A description of each loop includes angular data-planar and Euler angles computed between pairs of adjacent helices to allow studying their mutual arrangement in space. The system enables search and analysis of multiloops, presents their structure details numerically and visually, and computes data statistics. AVAILABILITY AND IMPLEMENTATION RNAloops is freely accessible at https://rnaloops.cs.put.poznan.pl. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jakub Wiedemann
- Institute of Computing Science, Poznan University of Technology, 60-965 Poznan, Poland
| | - Jacek Kaczor
- Institute of Computing Science, Poznan University of Technology, 60-965 Poznan, Poland
| | - Maciej Milostan
- Institute of Computing Science, Poznan University of Technology, 60-965 Poznan, Poland,Poznan Supercomputing and Networking Center, 61-131 Poznan, Poland
| | - Tomasz Zok
- Institute of Computing Science, Poznan University of Technology, 60-965 Poznan, Poland,Poznan Supercomputing and Networking Center, 61-131 Poznan, Poland
| | - Jacek Blazewicz
- Institute of Computing Science, Poznan University of Technology, 60-965 Poznan, Poland,Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
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57
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Social Sustainability in Production Planning: A Systematic Literature Review. SUSTAINABILITY 2022. [DOI: 10.3390/su14138198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Sustainable production includes economic, environmental, and social aspects. However, social sustainability has received less attention, especially compared to the economic aspects. Next to technical and organizational measures, social improvements within supply chains can also be achieved through suitable production planning. Within production planning, production programs are determined, and the assignment of available resources (e.g., employees) is specified. Thus, the utilization and workload of employees are defined. This systematic literature review investigates to what extent such employee-related social aspects are reflected in production planning and discusses whether economic aspects dominate them. For this, a Scopus database search was carried out and 76 identified approaches were analyzed and categorized regarding the occurring employee-related social aspects and their implementation. Thus far, the approaches mainly consider single aspects on single planning levels. A consideration of a broad set of aspects along the entire production planning has rarely been studied. In particular, health and safety aspects are considered on the levels of assembly line balancing and job rotation. However, their impact is primarily determined by the specific settings of the decision-maker. To support decision-makers, only a few studies have investigated the effects based on real application scenarios. Further potential might be an extended modeling of social and economic interdependencies and a consideration of employee-related social aspects in medium- to long-term production planning.
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58
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Dammen LV, Finseth TT, McCurdy BH, Barnett NP, Conrady RA, Leach AG, Deick AF, Van Steenis AL, Gardner R, Smith BL, Kay A, Shirtcliff EA. Evoking stress reactivity in virtual reality: A systematic review and meta-analysis. Neurosci Biobehav Rev 2022; 138:104709. [PMID: 35644278 DOI: 10.1016/j.neubiorev.2022.104709] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 04/08/2022] [Accepted: 05/21/2022] [Indexed: 01/04/2023]
Abstract
BACKGROUND Virtual reality (VR) research probes stress environments that are infeasible to create in the real world. However, because research simulations are applied to narrow populations, it remains unclear if VR simulations can stimulate a broadly applicable stress-response. This systematic review and meta-analysis was conducted on studies using VR stress tasks and biomarkers. METHODS Included papers (N = 52) measured cortisol, heart rate (HR), galvanic skin response (GSR), systolic blood pressure (SBP), diastolic blood pressure (DBP), respiratory sinus arrhythmia (RSA), parasympathetic activity (RMSSD), sympathovagal balance (LF/HF), and/or salivary alpha-amylase (sAA). Effect sizes (ES) and confidence intervals (CI) were calculated based on standardized mean change of baseline-to-peak biomarker levels. RESULTS From baseline-to-peak (ES, CI), analyses showed a statistically significant change in cortisol (0.56, 0.28-0.83), HR (0.68, 0.53-0.82), GSR (0.59, 0.36-0.82), SBP (.55, 0.19-0.90), DBP (.64, 0.23-1.05), RSA (-0.59, -0.88 to -0.30), and sAA (0.27, 0.092-0.45). There was no effect for RMSSD and LF/HF. CONCLUSION VR stress tasks elicited a varied magnitude of physiological stress reactivity. VR may be an effective tool in stress research.
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Affiliation(s)
- Lotte van Dammen
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
| | - Tor T Finseth
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA.
| | - Bethany H McCurdy
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
| | - Neil P Barnett
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
| | - Roselynn A Conrady
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
| | - Alexis G Leach
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
| | - Andrew F Deick
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
| | | | - Reece Gardner
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
| | - Brandon L Smith
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
| | - Anita Kay
- Iowa State University, Virtual Reality Applications Center, Ames, IA, USA
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59
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Ma X, Zhang Z. Research on Sports Health Care Information System Based on Computer Deep Learning Algorithm. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:1573562. [PMID: 35814577 PMCID: PMC9262469 DOI: 10.1155/2022/1573562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 05/30/2022] [Indexed: 11/18/2022]
Abstract
There are various problems in diagnosing and treating tumor diseases in significant hospitals. The content includes misjudgement and over-surgery issues. For example, the judgment of pulmonary nodules mainly relies on artificial experience, and most of the artificial experience is too radical. This paper is mainly based on the extensive medical data of significant hospitals, extracts the diagnosis and treatment data and digital images of similar cases from the extensive database, classifies them through the deep learning of the computer, and then proposes the control mechanism and the solution of the doctor's misjudgement and excessive medical treatment. This method mainly relies on the CT and MRI digital images of various types of tumor diseases accumulated in the history of major hospitals. Based on the preliminary judgment of each diagnosis and treatment and the results of surgical and pathological examinations, the accumulation of various types of digital images from the history is used. The features are analysed and extracted, the model is built, and finally, a predictive analysis system for this type of tumor is obtained, which can predict the benign and malignant cases of currently occurring cases and avoid the limitations and instability of artificial experience greatest extent. It is proved by experiments and combined with Spearman to remove redundancy. The redundancy removal method SVM_RFE is used for dimensionality reduction. The method can timely correct the misjudgement of the doctor's experience and effectively reduce the instability of the manual, which provides a solution for solving the contradiction between doctors and patients and improving the scientific of diagnosis and treatment.
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Affiliation(s)
- Xiaojun Ma
- School of Physical Education, South China University of Technology, Guangzhou 510640, Guangdong, China
| | - Zhenfeng Zhang
- Zhengzhou University of Aeronautics, Zhengzhou 450046, Henan, China
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60
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Enhancing the Speed of the Learning Vector Quantization (LVQ) Algorithm by Adding Partial Distance Computation. CYBERNETICS AND INFORMATION TECHNOLOGIES 2022. [DOI: 10.2478/cait-2022-0015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Abstract
Learning Vector Quantization (LVQ) is one of the most widely used classification approaches. LVQ faces a problem as when the size of data grows large it becomes slower. In this paper, a modified version of LVQ, which is called PDLVQ is proposed to accelerate the traditional version. The proposed scheme aims to avoid unnecessary computations by applying an efficient Partial Distance (PD) computation strategy. Three different benchmark datasets are used in the experiments. The comparisons have been done between LVQ and PDLVQ in terms of runtime and in result, it turns out that PDLVQ shows better efficiency than LVQ. PDLVQ has achieved up to 37% efficiency in runtime compared to LVQ when the dimensions have increased. Also, the enhanced algorithm (PDLVQ) shows clear enhancement to decrease runtime when the size of dimensions, the number of clusters, or the size of data becomes increased compared with the traditional one which is LVQ.
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61
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Liu Z, Jin W, Mu Y. Subspace embedding for classification. Neural Comput Appl 2022. [DOI: 10.1007/s00521-022-07409-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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62
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Wang J, Chen YH, Yang J, Sawan M. Intelligent Classification Technique of Hand Motor Imagery Using EEG Beta Rebound Follow-Up Pattern. BIOSENSORS 2022; 12:bios12060384. [PMID: 35735532 PMCID: PMC9221354 DOI: 10.3390/bios12060384] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 05/18/2022] [Accepted: 05/20/2022] [Indexed: 11/16/2022]
Abstract
To apply EEG-based brain-machine interfaces during rehabilitation, separating various tasks during motor imagery (MI) and assimilating MI into motor execution (ME) are needed. Previous studies were focusing on classifying different MI tasks based on complex algorithms. In this paper, we implement intelligent, straightforward, comprehensible, time-efficient, and channel-reduced methods to classify ME versus MI and left- versus right-hand MI. EEG of 30 healthy participants undertaking motional tasks is recorded to investigate two classification tasks. For the first task, we first propose a “follow-up” pattern based on the beta rebound. This method achieves an average classification accuracy of 59.77% ± 11.95% and can be up to 89.47% for finger-crossing. Aside from time-domain information, we map EEG signals to feature space using extraction methods including statistics, wavelet coefficients, average power, sample entropy, and common spatial patterns. To evaluate their practicability, we adopt a support vector machine as an intelligent classifier model and sparse logistic regression as a feature selection technique and achieve 79.51% accuracy. Similar approaches are taken for the second classification reaching 75.22% accuracy. The classifiers we propose show high accuracy and intelligence. The achieved results make our approach highly suitable to be applied to the rehabilitation of paralyzed limbs.
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Affiliation(s)
- Jiachen Wang
- Center of Excellence in Biomedical Research on Advanced Integrated-on-Chips Neurotechnologies (CenBRAIN Neurotech), School of Engineering, Westlake University, Hangzhou 310024, China; (J.W.); (J.Y.)
| | - Yun-Hsuan Chen
- Center of Excellence in Biomedical Research on Advanced Integrated-on-Chips Neurotechnologies (CenBRAIN Neurotech), School of Engineering, Westlake University, Hangzhou 310024, China; (J.W.); (J.Y.)
- Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou 310024, China
- Correspondence: (Y.-H.C.); (M.S.)
| | - Jie Yang
- Center of Excellence in Biomedical Research on Advanced Integrated-on-Chips Neurotechnologies (CenBRAIN Neurotech), School of Engineering, Westlake University, Hangzhou 310024, China; (J.W.); (J.Y.)
- Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou 310024, China
| | - Mohamad Sawan
- Center of Excellence in Biomedical Research on Advanced Integrated-on-Chips Neurotechnologies (CenBRAIN Neurotech), School of Engineering, Westlake University, Hangzhou 310024, China; (J.W.); (J.Y.)
- Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou 310024, China
- Correspondence: (Y.-H.C.); (M.S.)
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63
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Handling Dataset with Geophysical and Geological Variables on the Bolivian Andes by the GMT Scripts. DATA 2022. [DOI: 10.3390/data7060074] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
In this paper, an integrated mapping of the georeferenced data is presented using the QGIS and GMT scripting tool set. The study area encompasses the Bolivian Andes, South America, notable for complex geophysical and geological parameters and high seismicity. A data integration was performed for a detailed analysis of the geophysical and geological setting. The data included the raster and vector datasets captured from the open sources: the IRIS seismic data (2015 to 2021), geophysical data from satellite-derived gravity grids based on CryoSat, topographic GEBCO data, geoid undulation data from EGM-2008, and geological georeferences’ vector data from the USGS. The techniques of data processing included quantitative and qualitative evaluation of the seismicity and geophysical setting in Bolivia. The result includes a series of thematic maps on the Bolivian Andes. Based on the data analysis, the western region was identified as the most seismically endangered area in Bolivia with a high risk of earthquake hazards in Cordillera Occidental, followed by Altiplano and Cordillera Real. The earthquake magnitude here ranges from 1.8 to 7.6. The data analysis shows a tight correlation between the gravity, geophysics, and topography in the Bolivian Andes. The cartographic scripts used for processing data in GMT are available in the author’s public GitHub repository in open-access with the provided link. The utility of scripting cartographic techniques for geophysical and topographic data processing combined with GIS spatial evaluation of the geological data supported automated mapping, which has applicability for risk assessment and geological hazard mapping of the Bolivian Andes, South America.
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Peripheric sensors-based leaking source tracking in a chemical industrial park with complex obstacles. J Loss Prev Process Ind 2022. [DOI: 10.1016/j.jlp.2022.104828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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65
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Preface to the Special Issue on Computational Performance Analysis based on Novel Intelligent Methods: Exploration and Future Directions in Production and Logistics. FOUNDATIONS OF COMPUTING AND DECISION SCIENCES 2022. [DOI: 10.2478/fcds-2022-0005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Abstract
This special issue of the Foundations of Computing and Decision Sciences, titled “Computational Performance Analysis based on Novel Intelligent Methods: Exploration and Future Directions in Production and Logistics”, is devoted to the application of Computational Performance Analysis (CPA) for real-life phenomena. The special issue and its editorial present novel intelligent methods as they meet with various research topics in production and logistics, especially in terms of challenges, limitations and future trends. This special issue aims to bring together current progress on the CPA, organization management, and novel models and solution techniques that can contribute to a better understanding of the CPA systems and delineate useful practical strategies. Methodologically interesting and well-documented case studies are highly recommended. Additionally, the special issue covers innovative cutting-edge research methodologies and applications in the related research field.
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66
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Magnus M. rna-tools.online: a Swiss army knife for RNA 3D structure modeling workflow. Nucleic Acids Res 2022; 50:W657-W662. [PMID: 35580057 PMCID: PMC9252763 DOI: 10.1093/nar/gkac372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/20/2022] [Accepted: 05/02/2022] [Indexed: 11/15/2022] Open
Abstract
Significant improvements have been made in the efficiency and accuracy of RNA 3D structure prediction methods in recent years; however, many tools developed in the field stay exclusive to only a few bioinformatic groups. To perform a complete RNA 3D structure modeling analysis as proposed by the RNA-Puzzles community, researchers must familiarize themselves with a quite complex set of tools. In order to facilitate the processing of RNA sequences and structures, we previously developed the rna-tools package. However, using rna-tools requires the installation of a mixture of libraries and tools, basic knowledge of the command line and the Python programming language. To provide an opportunity for the broader community of biologists to take advantage of the new developments in RNA structural biology, we developed rna-tools.online. The web server provides a user-friendly platform to perform many standard analyses required for the typical modeling workflow: 3D structure manipulation and editing, structure minimization, structure analysis, quality assessment, and comparison. rna-tools.online supports biologists to start benefiting from the maturing field of RNA 3D structural bioinformatics and can be used for educational purposes. The web server is available at https://rna-tools.online.
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Affiliation(s)
- Marcin Magnus
- ReMedy International Research Agenda Unit, IMol Polish Academy of Sciences, Warsaw, Poland
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67
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Dai M, Feng X, Yu H, Guo W. A migratory behavior and emotional preference clustering algorithm based on learning vector quantization and gaussian mixture model. APPL INTELL 2022. [DOI: 10.1007/s10489-022-03325-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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68
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Santos MS, Abreu PH, Japkowicz N, Fernández A, Soares C, Wilk S, Santos J. On the joint-effect of class imbalance and overlap: a critical review. Artif Intell Rev 2022. [DOI: 10.1007/s10462-022-10150-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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69
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Console-Based Mapping of Mongolia Using GMT Cartographic Scripting Toolset for Processing TerraClimate Data. GEOSCIENCES 2022. [DOI: 10.3390/geosciences12030140] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This paper explores spatial variability of the ten climatic variables of Mongolia in 2019: average minimal and maximal temperatures, wind speed, soil moisture, downward surface shortwave radiation (DSRAD), snow water equivalent (SWE), vapor pressure deficit (VPD), vapor pressure anomaly (VAP), monthly precipitation and Palmer Drought Severity Index (PDSI). The PDSI demonstrates the simplified soil water balance estimating relative soil moisture conditions in Mongolia. The research presents mapping of the climate datasets derived from TerraClimate open source repository of the meteorological and climate measurements in NetCDF format. The methodology presented the compiled observations of Mongolia visualised by GMT coding approach using Generic Mapping Tools (GMT) cartographic scripting toolset. The results present 10 new maps of climate data over Mongolia made using automated cartographic techniques of GMT. Spatial environmental and climate analysis were conducted which determine relative distribution of PDSI and temperature extremes, precipitation and soil moisture, wind speed and DSRAD. The DSRAD showed minimum at 40 Wm−2, maximum at 113 Wm−2 in the Gobi Desert region, SWE (up to 491 mm), VAP and VPD compared with landmass parameters represent powerful cartographic tools to address complex regional climate and environmental issues in Mongolia, a country with contrasting topography, extreme climate conditions and unique environmental setting.
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Szczuko P, Harasimiuk A, Czyżewski A. Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application. SENSORS 2022; 22:s22062356. [PMID: 35336526 PMCID: PMC8951111 DOI: 10.3390/s22062356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/14/2022] [Accepted: 03/16/2022] [Indexed: 11/16/2022]
Abstract
An evaluation of decision fusion methods based on Dempster-Shafer Theory (DST) and its modifications is presented in the article, studied over real biometric data from the engineered multimodal banking client verification system. First, the approaches for multimodal biometric data fusion for verification are explained. Then the proposed implementation of comparison scores fusion is presented, including details on the application of DST, required modifications, base probability, and mass conversions. Next, the biometric verification process is described, and the engineered biometric banking system principles are provided. Finally, the validation results of three fusion approaches on synthetic and real data are presented and discussed, considering the desired outcome manifested by minimized false non-match rates for various assumed thresholds and biometric verification techniques.
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71
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Lewis T, Bhaganagar K. Configurable simulation strategies for testing pollutant plume source localization algorithms using autonomous multisensor mobile robots. INT J ADV ROBOT SYST 2022. [DOI: 10.1177/17298806221081325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In hazardous situations involving the dispersion of chemical, biological, radiological, and nuclear pollutants, timely containment of the emission is critical. A contaminant disperses as a dynamically evolving plume into the atmosphere, introducing complex difficulties in predicting the dispersion trajectory and potential evacuation sites. Strategies for predictive modeling of rapid contaminant dispersion demand localization of the emission source, a task performed effectively via unmanned mobile-sensing platforms. With vast possibilities in sensor configurations and source-seeking algorithms, platform deployment in real-world applications involves much uncertainty alongside opportunity. This work aims to develop a plume source detection simulator to offer a reliable comparison of source-seeking approaches and performance testing of ground-based mobile-sensing platform configurations prior to experimental field testing. Utilizing ROS, Gazebo, MATLAB, and Simulink, a virtual environment is developed for an unmanned ground vehicle with a configurable array of sensors capable of measuring plume dispersion model data mapped into the domain. For selected configurations, gradient-based and adaptive exploration algorithms were tested for source localization using Gaussian dispersion models in addition to large eddy simulation models incorporating the effects of atmospheric turbulence. A unique global search algorithm was developed to locate the true source with overall success allowing for further evaluation in field experiments. From the observations obtained in simulation, it is evident that source-seeking performance can improve drastically by designing algorithms for global exploration while incorporating measurements of meteorological parameters beyond solely concentration (e.g. wind velocity and vorticity) made possible by the inclusion of high-resolution large eddy simulation plume data.
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Affiliation(s)
- Tyrell Lewis
- Department of Mechanical Engineering, University of Texas, San Antonio, TX, USA
| | - Kiran Bhaganagar
- Department of Mechanical Engineering, University of Texas, San Antonio, TX, USA
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72
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Business Models for the Internet of Services: State of the Art and Research Agenda. FUTURE INTERNET 2022. [DOI: 10.3390/fi14030074] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
The relevance of the Internet of Services (IoS) comes from the global reach of the Internet into everyone’s home and daily activities and from the move from a manufacturing-based economy to a service-based economy. The IoS is seen as a new ecosystem where service providers and consumers explore their business networks for service provision and consumption. The scientific literature refers to IoS as an important cornerstone for Industry 4.0 and Future Internet; thus, it becomes relevant to study how IoS interacts with business models. Nevertheless, there is a lack of clarity on such an intersection. Moreover, a systematic review of IoS-based business models is still missing. This paper aims to make a systematic review of IoS-based business models and their application fields. We included studies from Scopus and Web of Science databases, we excluded duplicated papers and short conference versions of the later full paper journal publications. Twenty-three different studies are presented, categorized in the sub-areas of IoS, and then by the fields of applications. The main finding highlights the opportunities of IoS applications in different fields, offering directions for future research on this new arena.
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73
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Equilibrium stacks for a three-person game on a product of staircase-function continuous and finite strategy spaces. FOUNDATIONS OF COMPUTING AND DECISION SCIENCES 2022. [DOI: 10.2478/fcds-2022-0002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Abstract
A method of solving a three-person game defined on a product of staircase-function strategy spaces is presented. The spaces can be finite and continuous. The method is based on stacking equilibria of “short” three-person games, each defined on an interval where the pure strategy value is constant. In the case of finite three-person games, which factually are trimatrix games, the equilibria are considered in general terms, so they can be in mixed strategies as well. The stack is any interval-wise combination (succession) of the respective equilibria of the “short” trimatrix games. Apart from the stack, there are no other equilibria in this “long” trimatrix game. An example is presented to show how the stacking is fulfilled for a case of when every “short” trimatrix game has a pure-strategy equilibrium. The presented method, further “breaking” the initial “long” game defined on a product of staircase-function finite spaces, is far more tractable than a straightforward approach to solving directly the “long” trimatrix game would be.
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74
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Feature Transformation Framework for Enhancing Compactness and Separability of Data Points in Feature Space for Small Datasets. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12031713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Compactness and separability of data points are two important properties that contribute to the accuracy of machine learning tasks such as classification and clustering. We propose a framework that enhances the goodness criteria of the two properties by transforming the data points to a subspace in the same feature space, where data points of the same class are most similar to each other. Most related research about feature engineering in the input data points space relies on manually specified transformation functions. In contrast, our work utilizes a fully automated pipeline, in which the transformation function is learnt via an autoencoder for extraction of latent representation and multi-layer perceptron (MLP) regressors for the feature mapping. We tested our framework on both standard small datasets and benchmark-simulated small datasets by taking small fractions of their samples for training. Our framework consistently produced the best results in all semi-supervised clustering experiments based on K-means and different seeding techniques, with regards to clustering metrics and execution time. In addition, it enhances the performance of linear support vector machine (LSVM) and artificial neural network (ANN) classifier, when embedded as a preprocessing step before applying the classifiers.
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75
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Jastrzęb T, Czech ZJ, Wieczorek W. An adaptive parallel algorithm for finite language decomposition. APPL INTELL 2022. [DOI: 10.1007/s10489-021-02488-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
AbstractThe computationally hard problem of finite language decomposition is investigated. A finite language L is decomposable if there are two languages L1 and L2 such that L = L1L2. Otherwise, L is prime. The main contribution of the paper is an adaptive parallel algorithm for finding all decompositions L1L2 of L. The algorithm is based on an exhaustive search and incorporates several original methods for pruning the search space. Moreover, the algorithm is adaptive since it changes its behavior based on the runtime acquired data related to its performance. Comprehensive computational experiments on more than 4000 benchmark languages generated over alphabets of various sizes have been carried out. The experiments showed that by using the power of parallel computing the decompositions of languages containing more than 200000 words can be found. Decompositions of languages of that size have not been reported in the literature so far.
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76
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Bozhko DV, Myrov VO, Kolchanova SM, Polovian AI, Galumov GK, Demin KA, Zabegalov KN, Strekalova T, de Abreu MS, Petersen EV, Kalueff AV. Artificial intelligence-driven phenotyping of zebrafish psychoactive drug responses. Prog Neuropsychopharmacol Biol Psychiatry 2022; 112:110405. [PMID: 34320403 DOI: 10.1016/j.pnpbp.2021.110405] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 06/26/2021] [Accepted: 07/21/2021] [Indexed: 02/06/2023]
Abstract
Zebrafish (Danio rerio) are rapidly emerging in biomedicine as promising tools for disease modelling and drug discovery. The use of zebrafish for neuroscience research is also growing rapidly, necessitating novel reliable and unbiased methods of neurophenotypic data collection and analyses. Here, we applied the artificial intelligence (AI) neural network-based algorithms to a large dataset of adult zebrafish locomotor tracks collected previously in a series of in vivo experiments with multiple established psychotropic drugs. We first trained AI to recognize various drugs from a wide range of psychotropic agents tested, and then confirmed prediction accuracy of trained AI by comparing several agents with known similar behavioral and pharmacological profiles. Presenting a framework for innovative neurophenotyping, this proof-of-concept study aims to improve AI-driven movement pattern classification in zebrafish, thereby fostering drug discovery and development utilizing this key model organism.
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Affiliation(s)
| | | | | | | | | | - Konstantin A Demin
- Institite of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia; Almazov National Medical Research Center, St. Petersburg, Russia; Neurobiology Program, Sirius University, Sochi, Russia
| | - Konstantin N Zabegalov
- Institite of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia; Ural Federal University, Ekaterinburg, Russia; Neurobiology Program, Sirius University, Sochi, Russia; Group of Preclinical Bioscreening, Granov Russian Research Center of Radiology and Surgical Technologies, Ministry of Healthcare of Russian Federation, Pesochny, Russia
| | - Tatiana Strekalova
- Maastricht University, Maastricht, Netherlands; Laboratory of Psychiatric Neurobiology, Institute of Molecular Medicine and Department of Normal Physiology, Sechenov Moscow State Medical University, Moscow, Russia
| | - Murilo S de Abreu
- Bioscience Institute, University of Passo Fundo, Passo Fundo, Brazil; Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | | | - Allan V Kalueff
- School of Pharmacy, Southwest University, Chongqing, China; Ural Federal University, Ekaterinburg, Russia; ZENEREI, LLC, Slidell, LA, USA; Group of Preclinical Bioscreening, Granov Russian Research Center of Radiology and Surgical Technologies, Ministry of Healthcare of Russian Federation, Pesochny, Russia.
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78
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Abstract
Immense numbers of textual documents are available in a digital form. Research activities are focused on methods of how to speed up their processing to avoid information overloading or to provide formal structures for the problem solving or decision making of intelligent agents. Ontology learning is one of the directions which contributes to all of these activities. The main aim of the ontology learning is to semi-automatically, or fully automatically, extract ontologies—formal structures able to express information or knowledge. The primary motivation behind this paper is to facilitate the processing of a large collection of papers focused on disaster management, especially on tsunami research, using the ontology learning. Various tools of ontology learning are mentioned in the literature at present. The main aim of the paper is to uncover these tools, i.e., to find out which of these tools can be practically used for ontology learning in the tsunami application domain. Specific criteria are predefined for their evaluation, with respect to the “Ontology learning layer cake”, which introduces the fundamental phases of ontology learning. ScienceDirect and Web of Science scientific databases are explored, and various solutions for semantics extraction are manually “mined” from the journal articles. ProgrammableWeb site is used for exploration of the tools, frameworks, or APIs applied for the same purpose. Statistics answer the question of which tools are mostly mentioned in these journal articles and on the website. These tools are then investigated more thoroughly, and conclusions about their usage are made with respect to the tsunami domain, for which the tools are tested. Results are not satisfactory because only a limited number of tools can be practically used for ontology learning at present.
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79
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Ikram R, Khan A, Zahri M, Saeed A, Yavuz M, Kumam P. Extinction and stationary distribution of a stochastic COVID-19 epidemic model with time-delay. Comput Biol Med 2021; 141:105115. [PMID: 34922174 PMCID: PMC8654723 DOI: 10.1016/j.compbiomed.2021.105115] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 12/23/2022]
Abstract
We reformulate a stochastic epidemic model consisting of four human classes. We show that there exists a unique positive solution to the proposed model. The stochastic basic reproduction number R0s is established. A stationary distribution (SD) under several conditions is obtained by incorporating stochastic Lyapunov function. The extinction for the proposed disease model is obtained by using the local martingale theorem. The first order stochastic Runge-Kutta method is taken into account to depict the numerical simulations.
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Affiliation(s)
- Rukhsar Ikram
- Qurtuba University of Science and Information Technology Hayatabad Peshawar, Pakistan
| | - Amir Khan
- Department of Mathematics, Faculty of Science, King Mongkut's University of Technology, Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, Thrung Khru, Bangkok, 10 140, Thailand; Department of Mathematics and Statistics, University of Swat, KP, Pakistan
| | - Mostafa Zahri
- Department of Mathematics, Research Groups MASEP and BioInformatics FG, University of Sharjah, United Arab Emirates
| | - Anwar Saeed
- Center of Excellence in Theoretical and Computational Science (TaCS-CoE), Faculty of Science, King Mongkut's University of Technology Thonburi (KMUTT), 126 Pracha Uthit Rd., Bang Mod, Thung Khru, Bangkok, 10 140, Thailand
| | - Mehmet Yavuz
- Department of Mathematics, College of Engineering, Mathematics and Physical Sciences, University of Exeter, TR10, Cornwall, UK; Department of Mathematics and Computer Sciences, Necmettin Erbakan University, 42090, Konya, Turkey.
| | - Poom Kumam
- Center of Excellence in Theoretical and Computational Science (TaCS-CoE), Faculty of Science, King Mongkut's University of Technology Thonburi (KMUTT), 126 Pracha Uthit Rd., Bang Mod, Thung Khru, Bangkok, 10 140, Thailand; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40 402, Taiwan
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80
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Computational Fluid Dynamic Technique for Assessment of How Changing Character of Blood Flow and Different Value of Hct Influence Blood Hemodynamic in Dissected Aorta. Diagnostics (Basel) 2021; 11:diagnostics11101866. [PMID: 34679564 PMCID: PMC8534802 DOI: 10.3390/diagnostics11101866] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/02/2021] [Accepted: 10/04/2021] [Indexed: 11/17/2022] Open
Abstract
Using computer tomography angiography (CTA) and computational structural analysis, we present a non-invasive method of mass flow rate/velocity and wall stress analysis in type B aortic dissection. Three-dimensional (3D) computer models of the aorta were calculated using pre-operative (baseline) and post-operative CT data from 12 male patients (aged from 51 to 64 years) who were treated for acute type B dissection. A computational fluid dynamics (CFD) technique was used to quantify the displacement forces acting on the aortic wall in the areas of endografts placement. The mass flow rate and wall stress were measured and quantified using the CFD technique. The CFD model indicated the places with a lower value of blood velocity and shear rate, which corelated with higher blood viscosity and a probability of thrombus appearance. Moreover, with the increase in Hct, blood viscosity also increased, while the intensity of blood flow provoked changing viscosity values in these areas. Furthermore, the velocity gradient near the tear surface caused high wall WSS; this could lead to a decreased resistance in the aorta’s wall with further implications to a patient.
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81
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Cai S, Zhu K, Ban Y, Narumi T. Visual-Tactile Cross-Modal Data Generation Using Residue-Fusion GAN With Feature-Matching and Perceptual Losses. IEEE Robot Autom Lett 2021. [DOI: 10.1109/lra.2021.3095925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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82
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Popenda M, Zok T, Sarzynska J, Korpeta A, Adamiak R, Antczak M, Szachniuk M. Entanglements of structure elements revealed in RNA 3D models. Nucleic Acids Res 2021; 49:9625-9632. [PMID: 34432024 PMCID: PMC8464073 DOI: 10.1093/nar/gkab716] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 08/02/2021] [Accepted: 08/06/2021] [Indexed: 01/14/2023] Open
Abstract
Computational methods to predict RNA 3D structure have more and more practical applications in molecular biology and medicine. Therefore, it is crucial to intensify efforts to improve the accuracy and quality of predicted three-dimensional structures. A significant role in this is played by the RNA-Puzzles initiative that collects, evaluates, and shares RNAs built computationally within currently nearly 30 challenges. RNA-Puzzles datasets, subjected to multi-criteria analysis, allow revealing the strengths and weaknesses of computer prediction methods. Here, we study the issue of entangled RNA fragments in the predicted RNA 3D structure models. By entanglement, we mean an arrangement of two structural elements such that one of them passes through the other. We propose the classification of entanglements driven by their topology and components. It distinguishes two general classes, interlaces and lassos, and subclasses characterized by element types-loops, dinucleotide steps, open single-stranded fragments-and puncture multiplicity. Our computational pipeline for entanglement detection, applied for 1,017 non-redundant models from RNA-Puzzles, has shown the frequency of different entanglements and allowed identifying 138 structures with intersected assemblies.
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Affiliation(s)
- Mariusz Popenda
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
| | - Tomasz Zok
- Institute of Computing Science & European Centre for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
| | - Joanna Sarzynska
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
| | - Agnieszka Korpeta
- Institute of Computing Science & European Centre for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
| | - Ryszard W Adamiak
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
- Institute of Computing Science & European Centre for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
| | - Maciej Antczak
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
- Institute of Computing Science & European Centre for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
| | - Marta Szachniuk
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
- Institute of Computing Science & European Centre for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
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83
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Pilyugina N, Tsukahara A, Tanaka K. Comparing Methods of Feature Extraction of Brain Activities for Octave Illusion Classification Using Machine Learning. SENSORS 2021; 21:s21196407. [PMID: 34640727 PMCID: PMC8512176 DOI: 10.3390/s21196407] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 09/21/2021] [Accepted: 09/22/2021] [Indexed: 11/16/2022]
Abstract
The aim of this study was to find an efficient method to determine features that characterize octave illusion data. Specifically, this study compared the efficiency of several automatic feature selection methods for automatic feature extraction of the auditory steady-state responses (ASSR) data in brain activities to distinguish auditory octave illusion and nonillusion groups by the difference in ASSR amplitudes using machine learning. We compared univariate selection, recursive feature elimination, principal component analysis, and feature importance by testifying the results of feature selection methods by using several machine learning algorithms: linear regression, random forest, and support vector machine. The univariate selection with the SVM as the classification method showed the highest accuracy result, 75%, compared to 66.6% without using feature selection. The received results will be used for future work on the explanation of the mechanism behind the octave illusion phenomenon and creating an algorithm for automatic octave illusion classification.
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Affiliation(s)
- Nina Pilyugina
- Graduate School of Advanced Science and Technology, Tokyo Denki University, Hiki-gun, Saitama 350-0394, Japan
- Correspondence:
| | - Akihiko Tsukahara
- Graduate School of Science and Engineering, Tokyo Denki University, Hiki-gun, Saitama 350-0394, Japan; (A.T.); (K.T.)
| | - Keita Tanaka
- Graduate School of Science and Engineering, Tokyo Denki University, Hiki-gun, Saitama 350-0394, Japan; (A.T.); (K.T.)
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84
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An Introduction to the Special Issue on Numerical Techniques Meet with OR - Part II. FOUNDATIONS OF COMPUTING AND DECISION SCIENCES 2021. [DOI: 10.2478/fcds-2021-0013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Abstract
The special issue: “Numerical Techniques Meet with OR” of the Foundations of Computing and Decision Sciences consists of two parts which are of the main theme of numerical techniques and their applications in multi-disciplinary areas. The first part of this special issue was already collected in the FCDS Vol. 46, issue 1. In this second part of our special issue editorial, a description of the special issue presents numerical methods which can be used as alternative techniques for Scientific Computing and led Operational Research applications in many fields for further investigation.
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85
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Chouai M, Dolezel P, Stursa D, Nemec Z. New End-to-End Strategy Based on DeepLabv3+ Semantic Segmentation for Human Head Detection. SENSORS 2021; 21:s21175848. [PMID: 34502738 PMCID: PMC8434303 DOI: 10.3390/s21175848] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 08/16/2021] [Accepted: 08/25/2021] [Indexed: 11/16/2022]
Abstract
In the field of computer vision, object detection consists of automatically finding objects in images by giving their positions. The most common fields of application are safety systems (pedestrian detection, identification of behavior) and control systems. Another important application is head/person detection, which is the primary material for road safety, rescue, surveillance, etc. In this study, we developed a new approach based on two parallel Deeplapv3+ to improve the performance of the person detection system. For the implementation of our semantic segmentation model, a working methodology with two types of ground truths extracted from the bounding boxes given by the original ground truths was established. The approach has been implemented in our two private datasets as well as in a public dataset. To show the performance of the proposed system, a comparative analysis was carried out on two deep learning semantic segmentation state-of-art models: SegNet and U-Net. By achieving 99.14% of global accuracy, the result demonstrated that the developed strategy could be an efficient way to build a deep neural network model for semantic segmentation. This strategy can be used, not only for the detection of the human head but also be applied in several semantic segmentation applications.
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86
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Szczęsny S, Huderek D, Przyborowski Ł. Explainable spiking neural network for real time feature classification. J EXP THEOR ARTIF IN 2021. [DOI: 10.1080/0952813x.2021.1957024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Szymon Szczęsny
- Faculty of Computing and Telecommunications, Poznań University of Technology, Poznań, Poland
| | - Damian Huderek
- Faculty of Computing and Telecommunications, Poznań University of Technology, Poznań, Poland
| | - Łukasz Przyborowski
- Faculty of Computing and Telecommunications, Poznań University of Technology, Poznań, Poland
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87
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An efficient parallel block coordinate descent algorithm for large-scale precision matrix estimation using graphics processing units. Comput Stat 2021. [DOI: 10.1007/s00180-021-01127-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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88
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Orlandi S, House SC, Karlsson P, Saab R, Chau T. Brain-Computer Interfaces for Children With Complex Communication Needs and Limited Mobility: A Systematic Review. Front Hum Neurosci 2021; 15:643294. [PMID: 34335203 PMCID: PMC8319030 DOI: 10.3389/fnhum.2021.643294] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 05/18/2021] [Indexed: 11/13/2022] Open
Abstract
Brain-computer interfaces (BCIs) represent a new frontier in the effort to maximize the ability of individuals with profound motor impairments to interact and communicate. While much literature points to BCIs' promise as an alternative access pathway, there have historically been few applications involving children and young adults with severe physical disabilities. As research is emerging in this sphere, this article aims to evaluate the current state of translating BCIs to the pediatric population. A systematic review was conducted using the Scopus, PubMed, and Ovid Medline databases. Studies of children and adolescents that reported BCI performance published in English in peer-reviewed journals between 2008 and May 2020 were included. Twelve publications were identified, providing strong evidence for continued research in pediatric BCIs. Research evidence was generally at multiple case study or exploratory study level, with modest sample sizes. Seven studies focused on BCIs for communication and five on mobility. Articles were categorized and grouped based on type of measurement (i.e., non-invasive and invasive), and the type of brain signal (i.e., sensory evoked potentials or movement-related potentials). Strengths and limitations of studies were identified and used to provide requirements for clinical translation of pediatric BCIs. This systematic review presents the state-of-the-art of pediatric BCIs focused on developing advanced technology to support children and youth with communication disabilities or limited manual ability. Despite a few research studies addressing the application of BCIs for communication and mobility in children, results are encouraging and future works should focus on customizable pediatric access technologies based on brain activity.
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Affiliation(s)
- Silvia Orlandi
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
| | - Sarah C. House
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
| | - Petra Karlsson
- Cerebral Palsy Alliance, The University of Sydney, Sydney, NSW, Australia
| | - Rami Saab
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
| | - Tom Chau
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
- Institute of Biomedical Engineering (BME), University of Toronto, Toronto, ON, Canada
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89
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90
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91
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Zhang R. Research on the security of Web-based ideological and political education resource information system based on AMP. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-219156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
In order to improve the security of the Web-based ideological and political education resource information system, this paper analyzes the current privacy protection research and the privacy protection mechanism of Web services, and constructs a service framework of the ideological and political education resource information system based on the AMP module. Moreover, this paper explains the design and implementation of the overall framework, and then focuses on the design and implementation of AMP based on Agent, connection pool and sleep pool. In addition, this paper calculates the basic parameters related to the model, and describes the configuration and function of the parameters in detail. Finally, this paper applies AMP to the practice of the Web-based ideological and political education resource information system, and analyzes the system performance through experimental research. The results show that the system constructed in this paper has achieved a relatively perfect effect.
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Affiliation(s)
- Ruixue Zhang
- Harbin University of Science and Technology, Harbin, Heilongjiang, China
- Harbin Engineering University, Harbin, Heilongjiang, China
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92
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Li X. Web remote ideological and political education system constructed by using agent technology. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-219149] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
In order to improve the effect of remote ideological and political education, this paper builds a Web ideological and political education system based on Agent technology, and adopts a three-layer abstract system architecture including Web service layer, Agent processing layer and service process layer. Moreover, based on this architecture foundation, this paper proposes an Agent-based Web service integration structure, and illustrates the overall execution process of the system through the execution process of the system integration structure. Then, this paper proposes the organization structure of multi-agent in the Agent processing layer and the organization structure of service process in the service process layer of the system. In addition, this paper uses multi-agent system design to ensure the efficient operation of the entire system, and combines algorithms to implement system resource recommendation modules and practical teaching functions. Finally, this paper designs a control experiment to test the performance of the distance ideological and political education system constructed in this paper. The research results show that the system constructed in this paper has certain practical effects.
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Affiliation(s)
- Xiangyong Li
- Xinyang Institute of Vocational Technology, Marxist institute, Xinyang, Henan, China
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93
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Wölflein G, Arandjelović O. Determining Chess Game State from an Image. J Imaging 2021; 7:94. [PMID: 39080882 PMCID: PMC8321354 DOI: 10.3390/jimaging7060094] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/25/2021] [Accepted: 05/26/2021] [Indexed: 11/16/2022] Open
Abstract
Identifying the configuration of chess pieces from an image of a chessboard is a problem in computer vision that has not yet been solved accurately. However, it is important for helping amateur chess players improve their games by facilitating automatic computer analysis without the overhead of manually entering the pieces. Current approaches are limited by the lack of large datasets and are not designed to adapt to unseen chess sets. This paper puts forth a new dataset synthesised from a 3D model that is an order of magnitude larger than existing ones. Trained on this dataset, a novel end-to-end chess recognition system is presented that combines traditional computer vision techniques with deep learning. It localises the chessboard using a RANSAC-based algorithm that computes a projective transformation of the board onto a regular grid. Using two convolutional neural networks, it then predicts an occupancy mask for the squares in the warped image and finally classifies the pieces. The described system achieves an error rate of 0.23% per square on the test set, 28 times better than the current state of the art. Further, a few-shot transfer learning approach is developed that is able to adapt the inference system to a previously unseen chess set using just two photos of the starting position, obtaining a per-square accuracy of 99.83% on images of that new chess set. The code, dataset, and trained models are made available online.
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Affiliation(s)
- Georg Wölflein
- School of Computer Science, University of St Andrews, North Haugh, St Andrews KY16 9SX, Scotland, UK;
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94
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Pascual-Triana JD, Charte D, Andrés Arroyo M, Fernández A, Herrera F. Revisiting data complexity metrics based on morphology for overlap and imbalance: snapshot, new overlap number of balls metrics and singular problems prospect. Knowl Inf Syst 2021. [DOI: 10.1007/s10115-021-01577-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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95
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Large-Scale LiDAR SLAM with Factor Graph Optimization on High-Level Geometric Features. SENSORS 2021; 21:s21103445. [PMID: 34063368 PMCID: PMC8156327 DOI: 10.3390/s21103445] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 05/07/2021] [Accepted: 05/11/2021] [Indexed: 11/17/2022]
Abstract
Although visual SLAM (simultaneous localization and mapping) methods obtain very accurate results using optimization of residual errors defined with respect to the matching features, the SLAM systems based on 3-D laser (LiDAR) data commonly employ variants of the iterative closest points algorithm and raw point clouds as the map representation. However, it is possible to extract from point clouds features that are more spatially extended and more meaningful than points: line segments and/or planar patches. In particular, such features provide a natural way to represent human-made environments, such as urban and mixed indoor/outdoor scenes. In this paper, we perform an analysis of the advantages of a LiDAR-based SLAM that employs high-level geometric features in large-scale urban environments. We present a new approach to the LiDAR SLAM that uses planar patches and line segments for map representation and employs factor graph optimization typical to state-of-the-art visual SLAM for the final map and trajectory optimization. The new map structure and matching of features make it possible to implement in our system an efficient loop closure method, which exploits learned descriptors for place recognition and factor graph for optimization. With these improvements, the overall software structure is based on the proven LOAM concept to ensure real-time operation. A series of experiments were performed to compare the proposed solution to the open-source LOAM, considering different approaches to loop closure computation. The results are compared using standard metrics of trajectory accuracy, focusing on the final quality of the estimated trajectory and the consistency of the environment map. With some well-discussed reservations, our results demonstrate the gains due to using the high-level features in the full-optimization approach in the large-scale LiDAR SLAM.
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96
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Lee BD, Lee MS. Automated Bone Age Assessment Using Artificial Intelligence: The Future of Bone Age Assessment. Korean J Radiol 2021; 22:792-800. [PMID: 33569930 PMCID: PMC8076828 DOI: 10.3348/kjr.2020.0941] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 09/17/2020] [Accepted: 10/19/2020] [Indexed: 12/27/2022] Open
Abstract
Bone age assessments are a complicated and lengthy process, which are prone to inter- and intra-observer variabilities. Despite the great demand for fully automated systems, developing an accurate and robust bone age assessment solution has remained challenging. The rapidly evolving deep learning technology has shown promising results in automated bone age assessment. In this review article, we will provide information regarding the history of automated bone age assessments, discuss the current status, and present a literature review, as well as the future directions of artificial intelligence-based bone age assessments.
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Affiliation(s)
- Byoung Dai Lee
- Division of Computer Science and Engineering, Kyonggi University, Suwon, Korea
| | - Mu Sook Lee
- Department of Radiology, Keimyung University Dongsan Hospital, Daegu, Korea.
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97
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Kaden M, Bohnsack KS, Weber M, Kudła M, Gutowska K, Blazewicz J, Villmann T. Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences. Neural Comput Appl 2021; 34:67-78. [PMID: 33935376 PMCID: PMC8076884 DOI: 10.1007/s00521-021-06018-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 04/07/2021] [Indexed: 02/06/2023]
Abstract
We present an approach to discriminate SARS-CoV-2 virus types based on their RNA sequence descriptions avoiding a sequence alignment. For that purpose, sequences are preprocessed by feature extraction and the resulting feature vectors are analyzed by prototype-based classification to remain interpretable. In particular, we propose to use variants of learning vector quantization (LVQ) based on dissimilarity measures for RNA sequence data. The respective matrix LVQ provides additional knowledge about the classification decisions like discriminant feature correlations and, additionally, can be equipped with easy to realize reject options for uncertain data. Those options provide self-controlled evidence, i.e., the model refuses to make a classification decision if the model evidence for the presented data is not sufficient. This model is first trained using a GISAID dataset with given virus types detected according to the molecular differences in coronavirus populations by phylogenetic tree clustering. In a second step, we apply the trained model to another but unlabeled SARS-CoV-2 virus dataset. For these data, we can either assign a virus type to the sequences or reject atypical samples. Those rejected sequences allow to speculate about new virus types with respect to nucleotide base mutations in the viral sequences. Moreover, this rejection analysis improves model robustness. Last but not least, the presented approach has lower computational complexity compared to methods based on (multiple) sequence alignment. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s00521-021-06018-2.
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Affiliation(s)
- Marika Kaden
- University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany
- Saxon Institute for Computational Intelligence and Machine Learning, Technikumplatz 17, 09648 Mittweida, Germany
| | - Katrin Sophie Bohnsack
- University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany
- Saxon Institute for Computational Intelligence and Machine Learning, Technikumplatz 17, 09648 Mittweida, Germany
| | - Mirko Weber
- University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany
- Saxon Institute for Computational Intelligence and Machine Learning, Technikumplatz 17, 09648 Mittweida, Germany
| | - Mateusz Kudła
- University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany
- Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
| | - Kaja Gutowska
- Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
- European Centre for Bioinformatics and Genomics, Piotrowo 2, 60-965 Poznan, Poland
| | - Jacek Blazewicz
- Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland
- European Centre for Bioinformatics and Genomics, Piotrowo 2, 60-965 Poznan, Poland
| | - Thomas Villmann
- University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany
- Saxon Institute for Computational Intelligence and Machine Learning, Technikumplatz 17, 09648 Mittweida, Germany
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98
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Wang C, Yang X, Ding L. Sentiment classification based on weak tagging information and imbalanced data. INTELL DATA ANAL 2021. [DOI: 10.3233/ida-205408] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Sentiment classification aims to solve the problem of automatic judgment of sentiment polarity. In the sentiment classification task of text data, such as online reviews, traditional deep learning models are dedicated to algorithm optimization but ignore the characteristics of imbalanced distribution of the number of classified samples and the inclusion of weak tagging information such as ratings and tags. Based on the traditional deep learning model, the method of random oversampling and cost sensitivity is used to increase the contribution of a minority of samples to the model loss function and avoid the model biasing to the majority of samples. The model training is divided into two stages. In the first stage, a large amount of weak tagging data is used to train the model, therefore a model that captures the sentiment semantics of the data is obtained. After that, the model parameters trained in the first stage are used as the initial parameters of the second stage model training, and only a small amount of tagging data is used to continue training the model to reduce the impact of noise, thus reducing the use of manual tagging samples. The experimental results show that the method is considerably better than traditional deep learning models in the sentiment classification task of hotel review data.
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Affiliation(s)
- Chuantao Wang
- School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China
- Beijing Engineering Research Center of Monitoring for Construction Safety, Beijing, China
| | - Xuexin Yang
- School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China
- Beijing Engineering Research Center of Monitoring for Construction Safety, Beijing, China
| | - Linkai Ding
- School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China
- Beijing Engineering Research Center of Monitoring for Construction Safety, Beijing, China
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99
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Parallelization of Finding the Current Coordinates of the Lidar Based on the Genetic Algorithm and OpenMP Technology. Symmetry (Basel) 2021. [DOI: 10.3390/sym13040666] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
The problem of determining the position of the lidar with optimal accuracy is relevant in various fields of application. This is an important task of robotics that is widely used as a model when planning the route of vehicles, flight control systems, navigation systems, machine learning, and managing economic efficiency, a study of land degradation processes, planning and control of agricultural production stages, land inventory to evaluations of the consequences of various environmental impacts. The paper provides a detailed analysis of the proposed parallelization algorithm for solving the problem of determining the current position of the lidar. To optimize the computing process in order to accelerate and have the possibility of obtaining a real-time result, the OpenMP parallel computing technology is used. It is also possible to significantly reduce the computational complexity of the successive variant. A number of numerical experiments on the multi-core architecture of modern computers have been carried out. As a result, it was possible to accelerate the computing process about eight times and achieve an efficiency of 0.97. It is shown that a special difference in time of execution of a sequential and parallel algorithm manages to increase the number of measurements of lidar and iterations, which is relevant in simulating various problems of robotics. The obtained results can be substantially improved by selecting a computing system where the number of cores is more than eight. The main areas of application of the developed method are described, its shortcomings and prospects for further research are provided.
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100
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The impact of data difficulty factors on classification of imbalanced and concept drifting data streams. Knowl Inf Syst 2021. [DOI: 10.1007/s10115-021-01560-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
AbstractClass imbalance introduces additional challenges when learning classifiers from concept drifting data streams. Most existing work focuses on designing new algorithms for dealing with the global imbalance ratio and does not consider other data complexities. Independent research on static imbalanced data has highlighted the influential role of local data difficulty factors such as minority class decomposition and presence of unsafe types of examples. Despite often being present in real-world data, the interactions between concept drifts and local data difficulty factors have not been investigated in concept drifting data streams yet. We thoroughly study the impact of such interactions on drifting imbalanced streams. For this purpose, we put forward a new categorization of concept drifts for class imbalanced problems. Through comprehensive experiments with synthetic and real data streams, we study the influence of concept drifts, global class imbalance, local data difficulty factors, and their combinations, on predictions of representative online classifiers. Experimental results reveal the high influence of new considered factors and their local drifts, as well as differences in existing classifiers’ reactions to such factors. Combinations of multiple factors are the most challenging for classifiers. Although existing classifiers are partially capable of coping with global class imbalance, new approaches are needed to address challenges posed by imbalanced data streams.
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