TAKEN: A Traffic Knowledge-Based Navigation System for Connected and Autonomous Vehicles

Connected and autonomous vehicles (CAVs) have witnessed significant attention from industries, and academia for research and developments towards the on-road realisation of the technology. State-of-the-art CAVs utilise existing navigation systems for mobility and travel path planning. However, reliable connectivity to navigation systems is not guaranteed, particularly in urban road traffic environments with high-rise buildings, nearby roads and multi-level flyovers. In this connection, this paper presents TAKEN-Traffic Knowledge-based Navigation for enabling CAVs in urban road traffic environments. A traffic analysis model is proposed for mining the sensor-oriented traffic data to generate a precise navigation path for the vehicle. A knowledge-sharing method is developed for collecting and generating new traffic knowledge from on-road vehicles. CAVs navigation is executed using the information enabled by traffic knowledge and analysis. The experimental performance evaluation results attest to the benefits of TAKEN in the precise navigation of CAVs in urban traffic environments.

An Approach Using E-Khool User Log Data for E-Learning Recommendation System

The personalised learning is growing rapidly with the help of mobile and online technology. The e-learning recommendation scheme provides the suggestion concerning the courses to the students from numerous countries without past information of the courses online. The accuracy is an important issue in the e-learning course recommendation method. Hence, in this paper, Fuzzy-c-means clustering (FCM) and collaborative filtering are applied in the E-Khool user log data for effective e-learning recommendation system. The training phase and testing phase are the two phases of the devised method. During training, the relationship among the data in clustering is determined using the weighted cosine similarity and the data clustering is carried out with the help of FCM. During testing, the rating of the course is calculated using collaborative filtering. At last, the deep RNN classifier is used to evaluate prediction measure of the course recommendation. The devised e-learning recommendation method based on FCM and collaborative filtering offered a higher accuracy of 0.97 and less mean square error of 0.00115, respectively.

Performance Study on Indexing and Accessing of Small File in Hadoop Distributed File System

Hadoop Distributed File System (HDFS) is developed to efficiently store and handle the vast quantity of files in a distributed environment over a cluster of computers. Various commodity hardware forms the Hadoop cluster, which is inexpensive and easily available. The large number of small files stored in HDFS consumed more memory which lags the performance because small files consumed heavy load on NameNode. Thus, the efficiency of indexing and accessing the small files on HDFS is improved by several techniques, such as archive files, New Hadoop Archive (New HAR), CombineFileInputFormat (CFIF), and Sequence file generation. The archive file combines the small files into single blocks. The new HAR file combines the smaller files into a single large file. The CFIF module merges the multiple files into a single split using NameNode, and the sequence file combines all the small files into a single sequence. The indexing and accessing of a small file in HDFS are evaluated using performance metrics, such as processing time and memory usage. The experiment shows that the sequence file generation approach is efficient when compared to other approaches concerning file access time is 1.5[Formula: see text]s, memory usage is 20 KB in multi-node, and the processing time is 0.1[Formula: see text]s.

ADOFL: Multi-Kernel-Based Adaptive Directive Operative Fractional Lion Optimisation Algorithm for Data Clustering

The progress of databases in fields such as medical, business, education, marketing, etc., is colossal because of the developments in information technology. Knowledge discovery from such concealed bulk databases is a tedious task. For this, data mining is one of the promising solutions and clustering is one of its applications. The clustering process groups the data objects related to each other in a similar cluster and diverse objects in another cluster. The literature presents many clustering algorithms for data clustering. Optimisation-based clustering algorithm is one of the recently developed algorithms for the clustering process to discover the optimal cluster based on the objective function. In our previous method, direct operative fractional lion optimisation algorithm was proposed for data clustering. In this paper, we designed a new clustering algorithm called adaptive decisive operative fractional lion (ADOFL) optimisation algorithm based on multi-kernel function. Moreover, a new fitness function called multi-kernel WL index is proposed for the selection of the best centroid point for clustering. The experimentation of the proposed ADOFL algorithm is carried out over two benchmarked datasets, Iris and Wine. The performance of the proposed ADOFL algorithm is validated over existing clustering algorithms such as particle swarm clustering (PSC) algorithm, modified PSC algorithm, lion algorithm, fractional lion algorithm, and DOFL. The result shows that the maximum clustering accuracy of 79.51 is obtained by the proposed method in data clustering.

Family-led rehabilitation after stroke in India (ATTEND): a randomised controlled trial

BACKGROUND

Most people with stroke in India have no access to organised rehabilitation services. The effectiveness of training family members to provide stroke rehabilitation is uncertain. Our primary objective was to determine whether family-led stroke rehabilitation, initiated in hospital and continued at home, would be superior to usual care in a low-resource setting.

METHODS

The Family-led Rehabilitation after Stroke in India (ATTEND) trial was a prospectively randomised open trial with blinded endpoint done across 14 hospitals in India. Patients aged 18 years or older who had had a stroke within the past month, had residual disability and reasonable expectation of survival, and who had an informal family-nominated caregiver were randomly assigned to intervention or usual care by site coordinators using a secure web-based system with minimisation by site and stroke severity. The family members of participants in the intervention group received additional structured rehabilitation training-including information provision, joint goal setting, carer training, and task-specific training-that was started in hospital and continued at home for up to 2 months. The primary outcome was death or dependency at 6 months, defined by scores 3-6 on the modified Rankin scale (range, 0 [no symptoms] to 6 [death]) as assessed by masked observers. Analyses were by intention to treat. This trial is registered with Clinical Trials Registry-India (CTRI/2013/04/003557), Australian New Zealand Clinical Trials Registry (ACTRN12613000078752), and Universal Trial Number (U1111-1138-6707).

FINDINGS

Between Jan 13, 2014, and Feb 12, 2016, 1250 patients were randomly assigned to intervention (n=623) or control (n=627) groups. 33 patients were lost to follow-up (14 intervention, 19 control) and five patients withdrew (two intervention, three control). At 6 months, 285 (47%) of 607 patients in the intervention group and 287 (47%) of 605 controls were dead or dependent (odds ratio 0·98, 95% CI 0·78-1·23, p=0·87). 72 (12%) patients in the intervention group and 86 (14%) in the control group died (p=0·27), and we observed no difference in rehospitalisation (89 [14%]patients in the intervention group vs 82 [13%] in the control group; p=0·56). We also found no difference in total non-fatal events (112 events in 82 [13%] intervention patients vs 110 events in 79 [13%] control patients; p=0·80).

INTERPRETATION

Although task shifting is an attractive solution for health-care sustainability, our results do not support investment in new stroke rehabilitation services that shift tasks to family caregivers, unless new evidence emerges. A future avenue of research should be to investigate the effects of task shifting to health-care assistants or team-based community care.

FUNDING

The National Health and Medical Research Council of Australia.

Spectral and conformational studies on 3-pyridinealdazine by DFT approach

3-Pyridinealdazine was synthesized and characterized by FT-IR, (1)H, (13)C NMR and mass spectroscopy. The conformations of azine was determined theoretically besides selected geometrical parameters, HOMO-LUMO energies, polarizability, hyperpolarizability, natural bond orbital (NBO), atomic charges, Mulliken charges and atom in molecule (AIM) analysis were also calculated. The optimized geometry of the symmetrical azine, HOMO-LUMO and molecular electrostatic potential (MEP) surface were also evaluated using B3LYP/6-31G(d,p) basis set. (13)C NMR data were also computed using Gaussian-03 package and compared with the observed values according to density functional theory (DFT) method and analyzed.

A combined experimental and DFT study of a novel unsymmetrical azine 2-(4-methoxybenzylidene)-1-(1-(4-isobutylphenyl) ethylidene) hydrazine

A novel unsymmetrical azine 2-(4-methoxybenzylidene)-1-(1-(4-isobutylphenyl) ethylidene) hydrazine (UA) was prepared and characterized by IR, (1)H and (13)C NMR spectral studies. A 2D - potential energy scan (PES) of p-isobutylacetophenone (IBAP) was the portal to the conformational analysis of UA by density functional theory (DFT) methods using 6-31G(d,p) basis set by Gaussian 03 program. The theoretical IR frequencies were found to be in good agreement with the experimental values. The IR frequencies of UA were analyzed by means of Potential energy Distribution (PED %) calculation using Vibrational Energy Distribution Analysis (VEDA 4) program. The experimental NMR chemical shift values of UA were compared with the theoretical values obtained by DFT method. Nonlinear optical behavior of the unsymmetrical azine is also examined by the theoretically predicted values of dipole moment (μ), polarizability (α0) and first hyperpolarizability (βtot). Stability of the UA molecule has been analyzed using NBO analysis. The electrochemistry of UA studied experimentally by cyclic voltammetry is complemented by the computational analysis of the anionic form of the molecule UA. The determination of various global and local reactivity descriptors in the context of chemical reactivity is also performed and the electrophilicity at the vital atomic sites in UA is revealed. Bader's Atoms in molecules (AIM) theory of UA indicated the presence of intramolecular hydrogen bonding in the molecule. The molecular electrostatic potential (MEP) and HOMO-LUMO orbital analysis are also performed for the molecule UA.

Fructose, 1,6-diphosphate mitigates CCl4 suppressed nitric oxide synthase activity in rats

Effect of fructose 1,6-diphosphate (FDP) and carbon tetrachloride (CCl4) were studied individually and in combination on rat endothelial (ET) and smooth muscle cell (SMC) nitric oxide synthase (NOS) activities in vivo, inhibition of ET and SMC NOS activity in CCl4 treated rats was reversed in FDP + CCl4 treated animals. Cellular based NOS activity was significantly increased in FDP treated group of rats when compared to non treated controls. The results suggest a significant increase in NOS in rats treated with a combination of FDP + CCl4 thus overcoming the suppression of NOS exposed to CCl4 alone.