Computer Vision Algorithms, Vehicle Navigation and Remote Sensing Technologies, and Smart Traffic Planning and Analytics in Urban Transportation Systems

Author(s): Susan Gordon / Language(s): English Issue: 1/2022

I draw on a substantial body of theoretical and empirical research on computer vision algorithms, vehicle navigation and remote sensing technologies, and smart traffic planning and analytics in urban transportation systems. With increasing evidence of motion planning and data visualization tools, autonomous vehicle perception sensors, and crash avoidance technologies, there is an essential demand for comprehending whether intelligent traffic monitoring systems require simulation and virtualization technologies, connected car data, and autonomous vehicle planning algorithms. In this research, prior findings were cumulated indicating that sensing and computing technologies integrate location tracking algorithms, simulation modeling and mobility data processing tools, and monitoring and predictive capabilities. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2022, with search terms including “urban transportation systems” + “computer vision algorithms,” “vehicle navigation and remote sensing technologies,” and “smart traffic planning and analytics.” As I analyzed research published in 2021 and 2022, only 92 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, I decided on 15, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR.

Learning Object Detection Technology in Smart Sustainable Urban Transport Systems

Author(s): Miloš Poliak,Rafał Jurecki,Kathryn Buckner / Language(s): English Issue: 1/2022

Based on an in-depth survey of the literature, the purpose of the paper is to explore autonomous vehicle routing and navigation, mobility simulation and traffic flow prediction tools, and deep learning object detection technology in smart sustainable urban transport systems. We contribute to the literature by indicating that multi-sensor environmental data fusion, environment perception systems, and deep convolutional neural networks are pivotal in connected autonomous vehicles. Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “smart sustainable urban transport systems” + “autonomous vehicle routing and navigation,” “mobility simulation and traffic flow prediction tools,” and “deep learning object detection technology.” As research published between 2021 and 2022 was inspected, only 89 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 15 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.

Machine and Deep Learning Technologies, Location Tracking and Obstacle Avoidance Algorithms, and Cognitive Wireless Sensor Networks in Intelligent Transportation Planning and Engineering

Author(s): Susan Beckett / Language(s): English Issue: 1/2022

Despite the relevance of machine and deep learning technologies, location tracking and obstacle avoidance algorithms, and cognitive wireless sensor networks in intelligent transportation planning and engineering, only limited research has been conducted on this topic. In this article, I cumulate previous research findings indicating that visual recognition tools, cloud computing algorithms, and spatial data analytics articulate urban driving environments. I contribute to the literature on object detection and tracking, vehicular communication technologies, and sensor fusion algorithms by showing that smart mobility technologies develop on computational object instantiation and recognition, sensor data processing algorithms, predictive simulation tools, and urban traffic modeling. Throughout March 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “intelligent transportation planning and engineering” + “machine and deep learning technologies,” “location tracking and obstacle avoidance algorithms,” and “cognitive wireless sensor networks.” As I inspected research published between 2021 and 2022, only 82 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 13, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, Distiller SR, and MMAT.

Autonomous Vehicle Interaction Control Software, Urban Sensing and Computing Technologies, and Trajectory Planning and Route Detection Algorithms in Networked Transport Systems

Author(s): Doina Popescu LJungholm / Language(s): English Issue: 1/2022

This paper provides a systematic literature review of studies investigating autonomous vehicle interaction control software, urban sensing and computing technologies, and trajectory planning and route detection algorithms in networked transport systems. The analysis highlights that intelligent transportation infrastructures develop on mobility simulation and geospatial data visualization tools and blockchain and extended reality technologies. Throughout April 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “networked transport systems” + “autonomous vehicle interaction control software,” “urban sensing and computing technologies,” and “trajectory planning and route detection algorithms.” As I inspected research published between 2021 and 2022, only 93 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstan- tiated by replication, too imprecise material, or having similar titles, I decided upon 13, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

Big Geospatial Data Analytics, Connected Vehicle Technologies, and Visual Perception and Sensor Fusion Algorithms in Smart Transportation Networks

Author(s): Ellen Peters / Language(s): English Issue: 1/2022

The present study systematically reviews the existing research on big geospatial data analytics, connected vehicle technologies, and visual perception and sensor fusion algorithms in smart transportation networks. My findings indicate that deep reinforcement learning techniques and location tracking algorithms decrease traffic collisions and fatalities. I contribute to the literature by clarifying that cognitive artificial intelligence and collision avoidance algorithms, simulation and virtualization technologies, and geospatial mapping tools further self-driving car acceptance and adoption. Throughout March 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “smart transportation networks” + “big geospatial data analytics,” “connected vehicle technologies,” and “visual perception and sensor fusion algorithms.” As research published between 2019 and 2022 was inspected, only 95 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, I selected 14 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR.

Motion Planning and Object Recognition Algorithms, Vehicle Navigation and Collision Avoidance Technologies, and Geospatial Data Visualization in Network Connectivity Systems

Author(s): Vladimir Konečný,Marek Jaśkiewicz,Steve Downs / Language(s): English Issue: 1/2022

This article reviews and advances existing literature concerning motion planning and object recognition algorithms, vehicle navigation and collision avoidance technologies, and geospatial data visualization in network connectivity systems. In this research, previous findings were cumulated showing that sensor data processing and accurate path tracking tools, autonomous vehicle decision-making algorithms, and predictive urban analytics shape networked transport systems. Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “network connectivity systems” + “motion planning and object recognition algorithms,” “vehicle navigation and collision avoidance technologies,” and “geospatial data visualization.” As research published between 2019 and 2022 was inspected, only 89 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 13 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR.

Multi-Sensor Fusion Technology, Spatial Simulation and Environment Mapping Algorithms, and Real-World Connected Vehicle Data in Smart Sustainable Urban Mobility Systems

Author(s): Ana-Mădălina Potcovaru (Bîgu),Jana Majerova / Language(s): English Issue: 1/2022

The aim of this systematic review is to synthesize and analyze multi-sensor fusion technology, spatial simulation and environment mapping algorithms, and real-world connected vehicle data in smart sustainable urban mobility systems. With increasing evidence of autonomous vehicle planning algorithms, object localization and mapping tools, and spatial computing technology, there is an essential demand for comprehending whether road anomaly detection tools, blockchain and data fusion technologies, and trajectory estimation algorithms assist smart traffic planning and analytics. In this research, prior findings were cumulated indicating that automated collision avoidance systems, data monitoring algorithms, and virtual navigation tools reduce crash severities. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2022, with search terms including “smart sustainable urban mobility systems” + “multi-sensor fusion technology,” “spatial simulation and environment mapping algorithms,” and “real-world connected vehicle data.” As we analyzed research published between 2019 and 2022, only 88 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 13, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Meth-odological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR.

Geospatial Data Mining, Computer Vision-based Lane Detection and Object Localization Algorithms, and Mapping and Navigation Tools in Smart Urban Mobility Systems

Author(s): Brian Carey / Language(s): English Issue: 1/2022

In this article, I cumulate previous research findings indicating that networked transport systems, autonomous mobility technologies, and multi-sensor environmental data fusion typify urban driving environments. I contribute to the literature on geospatial data mining, computer vision-based lane detection and object localization algorithms, and mapping and navigation tools in smart urban mobility systems by showing that big geospatial data analytics, mobility simulation tools, and sensor data processing algorithms shape vehicular communication technologies. Throughout April 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “smart urban mobility systems” + “geospatial data mining,” “computer vision-based lane detection and object localization algorithms,” and “mapping and navigation tools.” As I inspected research published between 2019 and 2022, only 93 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 15, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, ROBIS, and SRDR.

Analfabetyzm matematyczny – znaczenie społeczne

Author(s): Damian Bączkiewicz / Language(s): Polish Issue: 1/2022

The article shows the problem of the occurrence of mathematical illiteracy in modern societies. The starting point for the author’s remarks is the highlighting of the existence of cognitive limitations and methods of heuristic reasoning. The author presents the causes and consequences of this common problem.

Sustainable Student Consumer – Myth or Reality?

Author(s): Mariusz Chmielewski,Ewa Malinowska,Renata Płoska,Joanna Próchniak / Language(s): English Issue: 1/2023

Objective: To compare and assess the behaviours of students as consumers of food, cosmetics and clothing in order to understand attitudes to sustainability.Research Design & Methods: A survey was conducted in June 2022 using an online questionnaire. The link to the questionnaire was sent to a sample of n = 800 students studying in the Tricity area (Poland). 295 students completed the survey, representing a return rate of 36.9%. The responses received were analysed and conclusions were drawn.Findings: The study shows that the young consumers take sustainable criteria into consideration in their purchasing decisions depending on the particular products. They follow sustainable aspects to the greatest extent in shopping for food, and to the least extent in the case of clothes. In the case of food, issues such as natural ingredients, environmentally friendly packaging, and egg labelling proved to be relatively important. With cosmetics, natural ingredients and environmentally friendly packaging were relatively important, and to a lesser extent, that cosmetics have not been tested on animals. In the case of clothing, sustainable issues proved to be the least important, though environmentally friendly packaging was sometime considered. Implications/Recommendations: The consumers surveyed are insufficiently influenced by questions of sustainability in their consumer behaviours. This may prompt questions on the involvement of companies in introducing pro-ecological and pro-social changes to products and how they are produced, and consequently influence the pace and degree to which sustainable production and consumption are being brought about.Contribution: The article contributes to the literature on the attitude of young consumers to sustainable development. It indicates areas that should be improved with regards to the behaviour of students when making purchasing decisions.Article type: original article.

Ukrainian refugees in Bucharest: integration, obstacles, and future plans

Author(s): Alexandra Deliu,Elena Trifan / Language(s): English Issue: 4/2023

The war in Ukraine has multiple consequences, including a considerable number of people fleeing from conflict zones, becoming refugees. For the countries in proximity to Ukraine, including Romania, the main consequence is the transformation into host countries for refugees and, as such, the need to formulate social policies that consider the specific situation of those seeking refuge. In this context, the research that yielded the data presented in this article aims to investigate the perceptions of Ukrainian refugees in Bucharest regarding access to services (health, education, social services, etc.) and their needs, to contribute to the adequacy of policies and response actions. Here, we refer to employment, education, and future plans, as reported by the respondents at the time of the research.

Immigration, growth and unemployment nexus: a long-run analysis for Türkiye

Author(s): Kemal Erkişi,Melike Çetinkaya / Language(s): English Issue: 4/2023

This study employs VECM, FMOLS, DOLS, and CCR methods to comprehensively explore the diverse effects of total immigration, including regular, irregular, and refugee movements, on unemployment in Türkiye from 2000 to 2022. Model 1 analyzes the overall influence of immigration, revealing a quadratic relationship wherein immigration initially reduces unemployment before triggering subsequent growth. Notably, the study identifies a rise in GDP per capita following increased unemployment linked to immigration, attributed to a surge in refugees, especially post-2013. Refugees, with their informal employment contributions, are seen as positively influencing economic growth, but at the expense of higher unemployment rates. Conversely, Model 2 dissects the effects of regular and irregular immigration, coupled with economic, educational, and inflationary factors, on unemployment. The analysis discerns that irregular immigration heightens unemployment, while regular migration alleviates it. A significant proportion of regular immigration comprises short-term and student permits, contributing positively to economic development and mitigating unemployment. Irregular migration, akin to refugee influx, fosters economic growth through informal employment, adversely impacting formal unemployment rates. The model also reveals a negative association between education and unemployment, emphasizing that heightened education levels lead to skill development and reduced unemployment. Additionally, the study notes the simultaneous rise in unemployment and inflation, potentially linked to informal employment resulting from immigration.

Challenges in international humanitarian logistics: problem areas

Author(s): Derya Atlay Işik,Ferhat Dinler / Language(s): English Issue: 4/2023

The objective of this study is to identify crucial problem areas related to the logistics of international humanitarian aid by compiling and analyzing current academic literature. The study findings shed light on significant problem areas that need to be addressed in international humanitarian aid logistics. The study comprises an analysis and compilation study based on a sample of twenty qualitative studies published between 2000 and 2022. In the field of international humanitarian aid logistics, which includes multiple variables and a dynamic structure, we identified the three most emphasized problem areas as well as the fourth factor that had an impact. Our analysis determined that the most crucial issue is the lack of collaboration and coordination among the actors involved. Presenting a focused approach to the challenges encountered in humanitarian logistics, this qualitative compendium study will aid in developing improvement strategies in detail. It will contribute to subsequent studies, particularly the national literature on the subject, and benefit practitioners, particularly those involved in humanitarian aid, and public institutions. This study offers a valuable perspective.

An exploratory paper on civil society in Jiu Valley. The case of coalition ”Valea Jiului implicată”

Author(s): Edi Dragoș Beserman / Language(s): English Issue: 4/2023

Up to this date very few empirical studies that address the civil society sector in Jiu Valley have been conducted. If they touch upon this topic, they discuss only the associational life of the miners. However, this does constitute their main objective. Thus, civil society actors beyond the miners’ unions are neglected. Recognizing the scarcity of research on this topic, the paper seeks to address this gap, by taking the case of the coalition of Valea Jiului Implicată/Jiu Valley Involved. In order to find out more about this coalition and its members, I used a mixed method approach consisting of both quantitative and qualitative methods. Results show that the coalition was formed by educated individuals with an experience of migration, that managed to bring together volunteers and NGOs so that they can address different problems affecting the region.

Challenges enhancing healthy lifestyle behaviors in community settings in Indonesia: the role of social literacy, religious involvement, and technology-equipped systems

Author(s): Muria Herlina,Sukri Palutturi,Sri Putri Permata,Yusuf Husmiati,Laila Meiliyandrie Indah Wardani,Adi Fahrudin,M. Rezaul Islam / Language(s): English Issue: 4/2023

The primary objective of this study was to investigate the impact of social literacy, religious involvement, and technology-equipped systems on the promotion of healthy lifestyle behaviors in community settings in Indonesia. The study utilized a mixed-method research approach and was carried out in three villages within an Indonesian province. Quantitative data was gathered from 235 respondents through face-to-face structured interviews using a simple random sampling procedure, while qualitative data was collected from 28 respondents through a semi-structured interview schedule using a purposive sampling procedure. Additionally, observations were conducted in the three selected communities. The study found that socio-cultural factors, including religious systems, social systems, and technology, significantly influenced healthy lifestyle behaviors in Indonesian communities. Strong associations were observed between these factors and various aspects of healthy living, such as physical activity, fruit and vegetable consumption, not smoking or drinking alcohol, routine health checkups, environmental hygiene, and latrine use. These findings underscored the significance of social support, religious involvement, and technology-equipped systems in promoting and improving healthy behaviors within community settings. Findings would be important guidelines for policymakers and health practitioners for designing and implementing effective health promotion strategies to enhance healthy lifestyle behaviors in community settings.

Authoritative parenting styles as antecedent of entrepreneurial intentions for vocational high school students

Author(s): Maulana Amirul Adha,Ayatulloh Michael Musyaffi,Nova Syafira Ariyanti,Rudy Ansar,Eka Ary Wibawa / Language(s): English Issue: 4/2023

This research investigates the effect of authoritative parenting styles to early entrepreneurial competence, and students’ entrepreneurial intention by including self-efficacy and entrepreneurial personality as mediating variables. Vocational high school students in Jakarta province, Indonesia, are the population of this study and the sample size is 347 students. The software package AMOS 25 was employed to conduct structural equation modeling (SEM) for the purpose of data analysis. The results study indicate that the implementation of authoritative parenting styles has a positive effect on the development of early entrepreneurial competence. This, in turn, can foster the students’ entrepreneurial intention. Furthermore, the present research points out the significance of self-efficacy and entrepreneurial personality as mediators. This study makes both theoretical and practical contributions by presenting a tested model that serves as an alternative guide for promoting students' entrepreneurial intentions.

The WAPOR 76th Annual conference. Conference review, Journal of Community Positive Practices

Author(s): Elena Spiridon / Language(s): English Issue: 4/2023

The demographic outlook of Romania at regional level in 2019. The potential impact on national security. Alba Iulia “Carol I” National Defense University Press. Book review

Author(s): Irina Iustina Voicu / Language(s): English Issue: 4/2023

Understanding cultural and social influences on female entrepreneurship in Mandan village, China

Author(s): Mingjing QU / Language(s): English Issue: 1/2024

This qualitative study delves into the intricate interplay of cultural norms, social networks, and unique challenges impacting female entrepreneurship in Mandan Village, Yunnan Province, China. Amidst evolving economic realities and entrenched traditional values, this research aims to unravel how these factors shape women's entrepreneurial endeavors in a rural context. The study's objectives are threefold: (1) to explore the influence of cultural norms on female entrepreneurship, (2) to investigate the role of social networks in supporting or challenging female entrepreneur, and (3) to identify the unique challenges and opportunities faced by female entrepreneurs in Mandan Village. Employing semi-structured interviews, field observations, and analysis of government documents, the study captures diverse perspectives from 3 village committee members, 6 local residents, 3 NGO representatives, and 3 female entrepreneurs, totaling is 15 individuals. Results uncover that conventional social standards altogether impact ladies' choices to become entrepreneurs and the kinds of organizations they lay out. Social networks are found to assume an essential part, offering fluctuating levels of assistance and assets. Female entrepreneurs face difficulties like adjusting business and family obligations, restricted admittance to resources, and exploring the digital gap. These experiences add to a nuanced comprehension of the variables influencing rural female entrepreneurship, offering important ramifications for policymakers, educators, and local area leaders. This research enriches the academic discourse on gender, culture, and entrepreneurship and underscores the importance of considering local contexts in fostering female economic empowerment and entrepreneurial choices in rural settings.

Addressing the challenges of learner's persistence in a free basic education program in a developing country

Author(s): Kim Hyoduk,Ruth A. Ortega-Dela Cruz / Language(s): English Issue: 1/2024

The basic education in a developing country struggle with parental disinterest and resource limitations, hindering education access. Despite offering free tuition and food, the school has witnessed a worrisome increase in dropouts over the past five years. Hence, the study was conducted to examine the challenges of learner's persistence. Key informants consisting of the teachers, parents, and three former students formed part of the research participants. The findings showed that challenges to learner's persistence include family problems, financial difficulties, absence of a security guard, school location, lack of parental cooperation, and inadequate learning materials. Finally, the study recommended specific strategies to address these challenges. The implementation of these strategies can greatly contribute to improving the learner's persistence and their overall learning experience in a free basic education program.