An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm

A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model

Simulating Vehicle Movement and Multi-Hop Connectivity from Basic Safety Messages

The Basic Safety Message (BSM) is a standardized communication packet that is sent every tenth of a second between connected vehicles using Dedicated Short Range Communication (DSRC). BSMs contain data about the sending vehicle's state, such as speed, location, and the status of the turn signal. Currently, many BSM datasets are available through the connected vehicle testbeds of U.S. Department of Transportation from all over the country. However, without a proper visualization tool, it is not possible to analyze or visually get an overview of the spatio-temporal distribution of the data. With this goal, a web application has been developed which can ingest a raw BSM dataset and display a time-based simulation of vehicle movement. The simulation also displays multi-hop vehicular network connectivity over DSRC. This paper gives details about the application, including an explanation of the multi-hop partitioning algorithm used to classify the vehicles into separate network partitions. A performance analysis for the simulation is included, in which it is suggested that calculating a connectivity matrix with the multi-hop partitioning algorithm is computationally expensive for large number of vehicles

Application of Computer Vision and Mobile Systems in Education: A Systematic Review

The computer vision industry has experienced a significant surge in growth, resulting in numerous promising breakthroughs in computer intelligence. The present review paper outlines the advantages and potential future implications of utilizing this technology in education. A total of 84 research publications have been thoroughly scrutinized and analyzed. The study revealed that computer vision technology integrated with a mobile application is exceptionally useful in monitoring students’ perceptions and mitigating academic dishonesty. Additionally, it facilitates the digitization of handwritten scripts for plagiarism detection and automates attendance tracking to optimize valuable classroom time. Furthermore, several potential applications of computer vision technology for educational institutions have been proposed to enhance students’ learning processes in various faculties, such as engineering, medical science, and others. Moreover, the technology can also aid in creating a safer campus environment by automatically detecting abnormal activities such as ragging, bullying, and harassment

Análise de desenhos experimentais com outliers

Primary purpose of the article is to develop outlier robust designs. As a matter of fact, negative effect of outliers in any experimental settings is established where the outliers at any specific design point can destroy the features of the design for which it is being developed. It is attempted here in this article to develop a version of robustness for central composite designs which may protect it for outliers by introducing the idea of minimax outlying effect. This involves the calculation of the degree of outlying effect(s) outlier(s) may produce and then minimize the maximum of these outlying effects in an attempt to equalize the influence of all design points. On comparison, these outlier robust designs are proved to be more optimal, on the scales of A, D, and E optimalities, against existing conventional rotatable, orthogonal, and other such designs. The outlier robust designs, developed here, are suitable for settings prone to outliers where conventional designs fail to represent and analyze the processes and systems.El objetivo principal del artículo es desarrollar diseños robustos atípicos. De hecho, el efecto negativo de los valores atípicos en cualquier configuración experimental se establece donde los valores atípicos en cualquier punto de diseño específico pueden destruir las características del diseño para el que se está desarrollando. En este artículo se intenta desarrollar una versión de robustez para los diseños compuestos centrales que pueden protegerlo de los valores atípicos mediante la introducción de la idea del efecto periférico minimax. Esto implica el cálculo del grado de efecto (s) externo (s) que puede producir un valor atípico y luego minimizar el máximo de estos efectos externos en un intento de igualar la influencia de todos los puntos de diseño. En comparación, se demuestra que estos diseños robustos atípicos son más óptimos, en las escalas de las optimidades A, D y E, frente a los diseños convencionales existentes, ortogonales, rotativos y otros similares. Los diseños robustos atípicos, desarrollados aquí, son adecuados para configuraciones propensas a los valores atípicos en los que los diseños convencionales no representan ni analizan los procesos y sistemas.Objetivo principal do artigo é desenvolver projetos robustos outlier. De fato, o efeito negativo de outliers em qualquer ambiente experimental é estabelecido onde os outliers em qualquer ponto de design específico podem destruir os recursos do design para o qual ele está sendo desenvolvido. Neste artigo, tenta-se desenvolver uma versão de robustez para projetos compostos centrais que possam protegê-lo de outliers, introduzindo a ideia de efeito periférico minimax. Isso envolve o cálculo do grau de efeito (s) outlier (s) outlier (s) pode produzir e, em seguida, minimizar o máximo desses efeitos periféricos em uma tentativa de equalizar a influência de todos os pontos do projeto. Em comparação, esses designs robustos discrepantes são comprovadamente mais otimizados, nas escalas de otimalidades A, D e E, contra os designs convencionais rotacionais, ortogonais e outros existentes. Os designs robustos outlier, desenvolvidos aqui, são adequados para configurações propensas a outliers em que projetos convencionais não representam e analisam os processos e sistemas

An online framework for civil unrest prediction using tweet stream based on tweet weight and event diffusion

Twitter is one of most popular Internet-based social networking platform to share feelings, views, and opinions. In recent years, many researchers have utilized the social dynamic property of posted messages or tweets to predict civil unrest in advance. However, existing frameworks fail to describe the low granularity level of tweets and how they work in offline mode. Moreover, most of them do not deal with cases where enough tweet information is not available. To overcome these limitations, this article proposes an online framework for analyzing tweet stream inpredicting future civil unrest events. The framework filters tweet stream and classifies tweets using linear Support Vector Machine (SVM) classifier. After that, the weight of the tweet is measured and distributed among extracted locations to update the overall weight in each location in a day in a fully online manner. The weight history is then used to predict the status of civil unrest in a location. The significant contributions of this article are (i) A new keyword dictionary with keyword score to quantify sentiment in extracting the low granularity level of knowledge (ii) A new diffusion model for extracting locations of interest and distributing the sentiment among the locations utilizing the concept of information diffusion and location graph to handle locations with insufficient information (iii) Estimating the probability of civil unrest and determining the stages of unrest in upcoming days. The performance of the proposed framework has been measured and compared with existing logistic regression based predictive framework. The results showed that the proposed framework outperformed the existing framework in terms of F1 score, accuracy, balanced accuracy, false acceptance rate, false rejection rate, and Matthews correlation coefficient

Estimation of the Healthcare Waste Generation During COVID-19 Pandemic in Bangladesh

COVID-19 pandemic-borne wastes imposed a severe threat to human lives as well as the total environment. Improper handling of these wastes increases the possibility of future transmission. Therefore, immediate actions are required from both local and international authorities to mitigate the amount of waste generation and ensure proper disposal of these wastes, especially for low-income and developing countries where solid waste management is challenging. In this study, an attempt is made to estimate healthcare waste generated during the COVID-19 pandemic in Bangladesh. This study includes infected, ICU, deceased, isolated and quarantined patients as the primary sources of medical waste. Results showed that COVID-19 medical waste from these patients was 658.08 tons in March 2020 and increased to 16164.74 tons in April 2021. A top portion of these wastes was generated from infected and quarantined patients. Based on survey data, approximate daily usage of face masks and hand gloves is also determined. Probable waste generation from COVID-19 confirmatory tests and vaccination has been simulated. Finally, several guidelines are provided to ensure the country\u27s proper disposal and management of COVID-related wastes

Age-Related Differences of Risk Profile and Angiographic Findings in Patients with Coronary Heart Disease

Background: Coronary heart disease (CHD) is a major health problem which imposes a significant burden on health caresystems because of high morbidity and mortality. Objectives: To compare the risk factors profile for coronary heartdisease in young and old subjects. Methods: Total 100 patients (50 subjects less than 40 years of age and 50 subjectsmore than 40 years of age) with acute coronary syndrome or stable angina who were undergoing coronary angiogram inthe Department of Cardiology, University Cardiac Center, Bangabandhu Sheikh Mujib Medical University Dhaka, fromJuly 2006 to June 2008 were evaluated for the presence coronary artery disease risk factors e.g. hypertension, dyslipidemiaand smoking. Results: The mean age of the study population in younger group was (33.0 ± 6.4) years and in older group(52.0±8.6). The male to female ratio in both groups was 4:1. Smokers were more in younger group (70.0% vs. 46.0%) (p =0.032). Hypertension was less in the younger group (38.0% vs. 58.0%) (p = 0.045). Presence of diabetes was higher in theolder age group (34.0% vs. 4.0%) (p = 0.001). Higher incidence of family history of coronary heart disease was in theyounger age group. The total cholesterol was higher in older group (182.9 ± 33.1) vs. (171.1 ± 24.8 mg/dl) (p = 0.047). 68%of patients of older group and 38% of younger group had stenosis in left anterior descending artery (p = 0.003). Theinvolvement of left circumflex and right coronary artery in older age group were higher (56% and 66% respectively) thanthose in younger group (36% and 40% respectively) (p = 0.045 and p = 0.009). Conclusion: Ischemic heart disease inyounger adults < 40 years had different risk profile characteristics than older patients.Key words: Coronary heart disease; acute coronary syndrome; stable angina; risk factors.DOI: 10.3329/bsmmuj.v3i1.5508BSMMU J 2010; 3(1): 13-1

Academic Use of Smartphones in Secondary Level Education in Bangladesh: A Non-Parametric Approach

This study aims to examine the use of smartphones for educational purposes and the acceptance of online learning among secondary students. To investigate the academic utilization of smartphones among secondary students in Bangladesh, a sample of 384 students from different districts of Bangladesh were surveyed. The survey was conducted using a selfadministered, semi-tailored computerized questionnaire. The collected data was analyzed using IBM SPSS statistics 26 and the Mann-Whitney U test. The findings indicate that male students used smartphones for educational purposes with greater confidence and less difficulty than female students. On the other hand, students in 8th to 10th grade classrooms reported a greater willingness to use smartphones for academic purposes, with urban students being more enthusiastic than their rural peers. The study’s findings have implications for the government, policymakers, educators, and non-governmental organizations (NGOs). They highlight the importance of ensuring equal access to resources and tools that support academic success, as well as addressing the adverse effects of excessive smartphone usage. In addition, the government and NGOs should prioritize the elimination of inequities between rural and urban areas and provide subsidies to rural students