Evaluation and Challenges of IoT Simulators for Intelligent Transportation System Applications

The Internet-of-Things (IoT) constructs a vast, intricate, and perpetually evolving ecosystem exerting profound societal implications. This labyrinthine nature often culminates in errors that directly impact human lives. A significant domain where this complexity materializes is Intelligent Transportation Systems (ITS). Present tools and methodologies inadequately accommodate the complex task of testing and validation, underscoring the urgency for comprehensive review and enhancement. This study aims to present a broad analysis of existing simulators utilized for ITS simulations. It delves into the role and effectiveness of such simulation tools, highlighting their limitations and proposing research directions. This paper scrutinizes both commercial and research-oriented IoT simulators for ITS, evaluating their features and simulation environment tools. We have detailed various ITS scenarios simulated within these frameworks, intending to gauge their readiness for real-world ITS applications and to elaborate on the challenges involved in ITS infrastructure implementation. The findings suggest that despite numerous simulators aiding the evolution of solutions for IoT challenges in recent years, their utility in actual ITS implementations remain uncertain. Consequently, we explore public cloud platforms offering IoT simulation capabilities, focusing particularly on the capabilities provided by the Amazon Web Services (AWS) IoT simulation for this study. Our research outlines the pressing challenges in this field, while proposing potential solutions and flagging opportunities for further research. This study paves the way towards improving the reliability and accuracy of IoT simulators in the context of ITS, which has immense potential to enhance the quality of human life

New rule induction algorithms with improved noise tolerance and scalability

As data storage capacities continue to increase due to rapid advances in information technology, there is a growing need for devising scalable data mining algorithms able to sift through large volumes of data in a short amount of time. Moreover, real-world data is inherently imperfect due to the presence of noise as opposed to artificially prepared data. Consequently, there is also a need for designing robust algorithms capable of handling noise, so that the discovered patterns are reliable with good predictive performance on future data. This has led to ongoing research in the field of data mining, intended to develop algorithms that are scalable as well as robust. The most straightforward approach for handling the issue of scalability is to develop efficient algorithms that can process large datasets in a relatively short time. Efficiency may be achieved by employing suitable rule mining constraints that can drastically cut down the search space. The first part of this thesis focuses on the improvement of a state-of-the-art rule induction algorithm, RULES-6, which incorporates certain search space pruning constraints in order to scale to large datasets. However, the constraints are insufficient and also have not been exploited to the maximum, resulting in the generation of specific rules which not only increases learning time but also the length of the rule set. In order to address these issues, a new algorithm RULES-7 is proposed which uses deep rule mining constraints from association learning. This results in a significant drop in execution time for large datasets while boosting the classification accuracy of the model on future data. A novel comparison heuristic is also proposed for the algorithm which improves classification accuracy while maintaining the execution time. Since an overwhelming majority of induction algorithms are unable to handle the continuous data ubiquitous in the real-world, it is also necessary to develop an efficient discretisation procedure whereby continuous attributes can be treated as discrete. By generalizing the raw continuous data, discretisation helps to speed up the induction process and results in a simpler and intelligible model that is also more accurate on future data. Many preprocessing discretisation techniques have been proposed to date, of which the entropy based technique has by far been accepted as the most accurate. However, the technique is suboptimal for classification because of failing to identify the cut points within the value range of each class for a continuous attribute, which deteriorates its classification accuracy. The second part of this thesis presents a new discretisation technique which utilizes the entropy based principle but takes a class-centered approach to discretisation. The proposed technique not only increases the efficiency of rule induction but also improves the classification accuracy of the induced model. Another issue with existing induction algorithms relates to the way covered examples are dealt with when a new rule is formed. To avoid problems such as fragmentation and small disjuncts, the RULES family of algorithms marks the examples instead of removing them. This tends to increase overlapping between rules. The third part of this thesis proposes a new hybrid pruning technique in order to address the overlapping issue so as to reduce the rule set size. It also proposes an incremental post-pruning technique designed specifically to handle the issue of noisy data. This leads to improved induction performance as well as better classification accuracy

Globalization and the Sociolinguistic Challenge of the 21st Century Critical Pedagogy: A Case for Language/Culture Minority Students

In spite of the fact that ours is a world of immigration, deepening ethnic textures, globalization, transnational histories, ethnolinguistic diversity, socioecono-mic rivalries, and intercultural complexities, the role and significance of bilingual and multicultural education are far from being adequately realized. These demographic imperatives and a host of other cross-cultural and transnational praxis are bringing about a growing percentage of students who speak a first language other than English. All over the world, classrooms are experiencing a radical transformation due to an unparalleled intercultural diversity which is spreading its tentacles all across the globe including Pakistan which, of late hit by the CPEC spectacle, is likely to experience an unprecedented influx of foreign students. These are paradigm shifting questions and call for a radical re-conceptualization not just of classrooms but also of the entire pedagogic space and curricular habitus. The paper makes a coherent appraisal of these questions and advances a plea for the greater inclusion of a broad-based, bilingual, and multicultural education by laying down key guidelines for teachers, administrators, policy-makers, educators, and parents at large

Geographical Evaluation of Socio-economic Condition of Sargodha City to Measure Urban Poverty

The current study presents the socio economic conditions of people of Sargodha city to analyze the urban poverty level. Research was accomplished during the year of 2016-2018. Urban poverty is a burning social issue in world when a person do not succeeds to carry out his family needs and wants. A survey was conducted in eleven different colonies and 188 households were visited. Poverty level was scrutinized according to international poverty line less than 1 Dollar per day. During the field survey it was perceived that 17 percent of the households have income of less than 1 Dollar per day and they were real poor. Different parameters were examined like slums, dependency ratio, income, transportation, drinking water scheme, sewerage system and literacy rate. These parameters have compared with poverty to analyze the affordability and living condition of people. It was examined that there were several reasons for poverty in city like unemployment / low income, less education, high dependency ratio etc. Most of the people have large families but low income due to not as much of education and more dependent people in households. It was also suggested that Government should make better living conditions for people by providing technical skills to uneducated person to diminish unemployment and should advance the sanitation problems for better lifestyle

Geographical Evaluation of Socio-economic Condition of Sargodha City to Measure Urban Poverty

The current study presents the socio economic conditions of people of Sargodha city to analyze the urban poverty level. Research was accomplished during the year of 2016-2018. Urban poverty is a burning social issue in world when a person do not succeeds to carry out his family needs and wants. A survey was conducted in eleven different colonies and 188 households were visited. Poverty level was scrutinized according to international poverty line less than 1 Dollar per day. During the field survey it was perceived that 17 percent of the households have income of less than 1 Dollar per day and they were real poor. Different parameters were examined like slums, dependency ratio, income, transportation, drinking water scheme, sewerage system and literacy rate. These parameters have compared with poverty to analyze the affordability and living condition of people. It was examined that there were several reasons for poverty in city like unemployment / low income, less education, high dependency ratio etc. Most of the people have large families but low income due to not as much of education and more dependent people in households. It was also suggested that Government should make better living conditions for people by providing technical skills to uneducated person to diminish unemployment and should advance the sanitation problems for better lifestyle

Impact of Internal Physical Environment on Academicians' Productivity in Pakistan: Higher Education Institutes Perspectives

This study empirically examines the impact of indoor physical environment on academicians' productivity in different higher education institutes of Khyber Pakhtoonkhawa (KPK) province of Pakistan. The study is based on primary data collected from one hundred and forty four educationists' of various institutes in Pakistan. A structured questionnaire was used for data collection. The data was analyzed using the techniques of rank correlation coefficient and multiple regression analysis. All the findings were tested at 0.01 and 0.05 level of significance. The finding of this study shows that office design is very important in terms of increasing employee's productivity. The study opines that comfortable and contented office design motivates and energized the employees to increase their performance. Keywords: Ergonomics, Productivity, Office design, Higher education institutes, Correlation, Regression, Pakistan

Impact of Internal Physical Environment on Academicians' Productivity in Pakistan: Higher Education Institutes Perspectives

This study empirically examines the impact of indoor physical environment on academicians' productivity in different higher education institutes of Khyber Pakhtoonkhawa (KPK) province of Pakistan. The study is based on primary data collected from one hundred and forty four educationists' of various institutes in Pakistan. A structured questionnaire was used for data collection. The data was analyzed using the techniques of rank correlation coefficient and multiple regression analysis. All the findings were tested at 0.01 and 0.05 level of significance. The finding of this study shows that office design is very important in terms of increasing employee's productivity. The study opines that comfortable and contented office design motivates and energized the employees to increase their performance. Keywords: Ergonomics, Productivity, Office design, Higher education institutes, Correlation, Regression, Pakistan

Ceramic-reinforced HEA matrix composites exhibiting an excellent combination of mechanical properties

CoCrFeNi is a well-studied face centered cubic (fcc) high entropy alloy (HEA) that exhibits excellent ductility but only limited strength. The present study focusses on improving the strength-ductility balance of this HEA by addition of varying amounts of SiC using an arc melting route. Chromium present in the base HEA is found to result in decomposition of SiC during melting. Consequently, interaction of free carbon with chromium results in the in-situ formation of chromium carbide, while free silicon remains in solution in the base HEA and/or interacts with the constituent elements of the base HEA to form silicides. The changes in microstructural phases with increasing amount of SiC are found to follow the sequence: fcc → fcc + eutectic → fcc + chromium carbide platelets → fcc + chromium carbide platelets + silicides → fcc + chromium carbide platelets + silicides + graphite globules/flakes. In comparison to both conventional and high entropy alloys, the resulting composites were found to exhibit a very wide range of mechanical properties (yield strength from 277 MPa with more than 60% elongation to 2522 MPa with 6% elongation). Some of the developed high entropy composites showed an outstanding combination of mechanical properties (yield strength 1200 MPa with 37% elongation) and occupied previously unattainable regions in a yield strength versus elongation map. In addition to their significant elongation, the hardness and yield strength of the HEA composites are found to lie in the same range as those of bulk metallic glasses. It is therefore believed that development of high entropy composites can help in obtaining outstanding combinations of mechanical properties for advanced structural applications.Financial support from the Higher Education Commission of Pakistan (HEC NRPU 6019) is acknowledged. FEDER National funds FCT under the project CEMMPRE, ref. “UIDB/00285/2020” is also acknowledged.info:eu-repo/semantics/publishedVersio