Search results for: infrastructure challenges

Authors: Uzma Rashid, Mommnah Asad

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As more and more people fall victim to the intolerance that has become a plague globally, academicians are faced with the herculean task of sowing the roots for more tolerant individuals. Being the multilayered task that it is, promoting an acceptance of diversity and pushing an agenda to push back hate requires efforts on multiple levels. Not only does the curriculum need to be in line with such goals, but teachers also need to be trained to cater to the sensitivities surrounding conversations of tolerance and diversity. In addition, institutional support needs to be there to provide conducive conditions for a diversity driven learning process to take place. In reality, teachers have to struggle with forwarding ideas about diversity and tolerance which do not sound particularly risky to be shared but given the current socio-political and religious milieu, can put the teacher in a difficult position and can make the task exponentially challenging. This paper is based on an auto-ethnographic account of teaching undergraduate and graduate courses at a private university in Pakistan. These courses were aimed at teaching tolerance to adult learners through classes focused on key notions pertaining to religion, culture, gender, and society. Authors’ classroom experiences with the students in these courses indicate a marked heightening of religious sensitivities that can potentially threaten a teacher’s life chances and become a hindrance in deep, meaningful conversations, thus lending a superficiality to the whole endeavor. The paper will discuss in detail the challenges that this teacher dealt with in the process, how those were addressed, and locate them in the larger picture of how tolerance can be materialized in current times in the universities in Pakistan and in similar contexts elsewhere.

Keywords: tolerance, diversity, gender, Pakistani Universities

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Authors: Mette Evelyn Bjerre

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Nordic Exceptionalism is a racial paradigm that inhibits a critical examination of structural discrimination and the daily experiences of minority-racialised Danes. As a result, the category ethnic-Danish is a White hegemonic construct that limits access for multiracial ethnic Danes irrespective of their multigenerational Danish heritage. An anti-immigrant public discourse and frequent racialisation as ‘other’ in social interactions are part of a boundary-making process that sustains White hegemony and excludes multiracial ethnic Danes from a collective national identity. With an analysis of interview data with 40 multiracial ethnic Danes, this research finds that the understanding of race as a category and the salience of race for multiracial ethnic Danes has changed over time concurrently with demographic changes and a heightened awareness of racialisation processes. The older generation is more likely to conform to White hegemony by trivialising racialised experiences. In contrast, younger multiracial ethnic Danes have the knowledge and cultural capital to challenge Whiteness actively. They do this by claiming their multiracial identity as a crucial part of their Danish identity and acknowledging race as a social fact that impacts their lives. Many young multiracial participants also dispute that the public immigration debate is race-neutral and is active in organisations supporting immigrants and refugees. These findings suggest that young multiracial Danes are uniquely positioned to push public discourse toward a better understanding of how Whiteness is integral to national identity and advocate for a broader Danish identity type that challenges White hegemony and Nordic exceptionalism.

Keywords: multiracial Danes, nordic exceptionalism, racial identity, white hegemony

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Authors: Tapiwa Shumba, Nyaradzo D. T. Karubwa

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Dispute resolution is the plinth of regional integration initiatives anchored on the rule of law and compliance with obligations. Without effective and reliable despite resolution mechanisms, it may be difficult to foster deeper integration. Within the Southern African Development Community (SADC) legal and institutional framework exists an apparent recognition that dispute resolution is an integral part of the regional integration. Almost all legal instruments of SADC include some provision for dispute resolution. Institutionally, the somewhat now defunct SADC Tribunal is meant to be the fulcrum for resolving disputes that arise under SADC instruments. However, after a closer analysis of the substance of these legal provisions and the attendant procedural mechanisms for addressing disputes, an argument can be made that dispute resolution in SADC is somewhat scant, fragmented and neglected. In most instruments, the common provision on dispute resolution appears to be a ‘mid-night clause’. In other instruments which have specialised provisions and procedures, questions of practicality and genius cannot be avoided. Worse still there now appears to be a lack of magnanimity between the substantive provisions in various instruments and the role of the transformed Tribunal. This scant, fragmented and neglected dispute resolution system may have an impact on the observance of the rule of law and compliance with obligations in the rules-based SADC system. This all, in turn, has an effect on the common agenda for deeper regional integration. This article seeks to expose this scant, fragmented and neglected SADC dispute resolution system and to propose a harmonised system that addresses these challenges. A ‘one stop shop’ system under a strengthened SADC tribunal is proposed as a responsive solution.

Keywords: regional integration, harmonisation, SADC tribunal, dispute resolution

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Authors: Prachi Bhatt

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Motivated workforce is an important asset of an organisation. Intrinsic motivation is one of the key aspects of people operations and performance. Researches have emphasized the significance of internal factors in individuals’ motivation. In the changing business scenario, it is a challenge for the organizations’ leaders to inspire and motivate their workforce. The present study deals with the intrinsic motivation potential of an individual which govern the innate capability of an individual driving him or her to behave or perform in the changing work environment, tasks, teams. Differences at individual level significantly influence differences in levels of motivation. In the above context, the present research attempts to explore behavioral trait dimensions which influence motivational potential of an individual. The present research emphasizes the significance of intrinsic motivational potential and the significance of exploring the differences in the intrinsic motivational potential levels of individuals at work places. Thus, this paper empirically tests the framework of behavioral traits which affects motivational potential of an individual. With the help of two studies i.e., Study 1 and Study 2, exploratory factor analysis and confirmatory factor analysis, respectively, indicated a reliable measure assessing intrinsic motivational potential of an individual. Given the variety of challenges of motivating contemporary workforce, and with increasing importance of intrinsic motivation, the paper discusses the relevance of the findings and of the measure assessing intrinsic motivational potential. Assessment of such behavioral traits would assist in the effective realization of intrinsic motivational potential of individuals. Additionally, the paper discusses the practical implications and furnishes scope for future research.

Keywords: behavioral traits, individual differences, intrinsic motivational potential, intrinsic motivation, motivation, workplace motivation

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Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

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The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

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Authors: Sofina Faith C. Navarro, Luke V. Subala, Rica H. Gatus, Alfonzo Ramon DG. Burguete

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Roof tiles, as integral components of buildings, play a crucial role in protecting structures from many things. The study focuses on the production of sustainable roof tiles that address the waste disposal challenges associated with Manila clam shells and mitigate the environmental impact of conventional roof tile materials. Various concentrations of roof tiles are developed, incorporating different proportions of powdered clam shell that contains calcium carbonate and shredded raffia palm fiber. Subsequently, the roof tiles are cast using standard methods and transported to the University of the Philippines Institute of Civil Engineering (UP-ICE) for flexural strength testing. In conclusion, the research aimed to assess the flexural durability of concrete roof tiles with varying concentrations of Raffia Palm Fiber and Manila Clam Shells additives. The findings indicate notable differences in maximum load capacities among the specimens, with C3.1 emerging as the concentration with the highest load-bearing capacity at 313.59729 N. This concentration, with a flexural strength of 2.15214, is identified as the most durable option, with a slightly heavier weight of 1.10 kg. On the other hand, C2.2, with a flexural strength of 0.366 and a weight of 0.80 kg, is highlighted for its impressive durability performance while maintaining a lighter composition. Therefore, for the production of concrete roof tile, C3.1 is recommended for optimal durability, while C2.2 is suggested as a preferable option considering both durability and lightweight characteristics.

Keywords: raffia palm fiber, flexural strength, lightweightness, Manila Clam Shells

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Authors: Alfonzo Ramon Burguete, Rica Gatus, Sofina Faith Navarro, Luke Subala

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Roof tiles, as integral components of buildings, play a crucial role in protecting structures from many things. The study focuses on the production of sustainable roof tiles that address the waste disposal challenges associated with Manila clam shells and mitigate the environmental impact of conventional roof tile materials. Various concentrations of roof tiles are developed, incorporating different proportions of powdered clam shell that contains calcium carbonate and shredded raffia palm fiber. Subsequently, the roof tiles are cast using standard methods and transported to the University of the Philippines Institute of Civil Engineering (UP-ICE) for flexural strength testing. In conclusion, the research aimed to assess the flexural durability of concrete roof tiles with varying concentrations of Raffia Palm Fiber and Manila Clam Shells additives. The findings indicate notable differences in maximum load capacities among the specimens, with C3.1 emerging as the concentration with the highest load-bearing capacity at 313.59729 N. This concentration, with a flexural strength of 2.15214, is identified as the most durable option, with a slightly heavier weight of 1.10 kg. On the other hand, C2.2, with a flexural strength of 0.366 and a weight of 0.80 kg, is highlighted for its impressive durability performance while maintaining a lighter composition. Therefore, for the production of concrete roof tile C3.1 is recommended for optimal durability, while C2.2 is suggested as a preferable option considering both durability and lightweight characteristics.

Keywords: manila clam shells, raffia palm fiber, flexural strength, lightweightness

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Authors: Sylvia Mac

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This ethnographic case study examines disaster capitalism, neoliberal market-based school reforms, and disability through the lens of Disability Studies in Education. More specifically, it explores neoliberalism and special education at a small, urban charter school in a large city in California and the (re)production of social inequality. The study uses Sociology of Special Education to examine the ways in which special education is used to sort and stratify disabled students. At a time when rhetoric surrounding public schools is framed in catastrophic and dismal language in order to justify the privatization of public education, small urban charter schools must be examined to learn if they are living up to their promise or acting as another way to maintain economic and racial segregation. The study concludes that neoliberal contexts threaten successful inclusive education and normalize poor, disabled students’ continued low achievement and poor post-secondary outcomes. This ethnographic case study took place at a small urban charter school in a large city in California. Participants included three special education students, the special education teacher, the special education assistant, a regular education teacher, and the two founders and charter writers. The school claimed to have a push-in model of special education where all special education students were fully included in the general education classroom. Although presented as fully inclusive, some special education students also attended a pull-out class called Study Skills. The study found that inclusion and neoliberalism are differing ideologies that cannot co-exist. Successful inclusive environments cannot thrive while under the influences of neoliberal education policies such as efficiency and cost-cutting. Additionally, the push for students to join the global knowledge economy means that more and more low attainers are further marginalized and kept in poverty. At this school, neoliberal ideology eclipsed the promise of inclusive education for special education students. This case study has shown the need for inclusive education to be interrogated through lenses that consider macro factors, such as neoliberal ideology in public education, as well as the emerging global knowledge economy and increasing income inequality. Barriers to inclusion inside the school, such as teachers’ attitudes, teacher preparedness, and school infrastructure paint only part of the picture. Inclusive education is also threatened by neoliberal ideology that shifts the responsibility from the state to the individual. This ideology is dangerous because it reifies the stereotypes of disabled students as lazy, needs drains on already dwindling budgets. If these stereotypes persist, inclusive education will have a difficult time succeeding. In order to more fully examine the ways in which inclusive education can become truly emancipatory, we need more analysis on the relationship between neoliberalism, disability, and special education.

Keywords: case study, disaster capitalism, inclusive education, neoliberalism

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Authors: D. Shamatov

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Becoming a teacher is a journey with significant learning experiences. Exploring teachers’ lives and experiences can provide much-needed insights into the multiple realities of teaching. Teachers’ stories through qualitative narrative studies help understand and appreciate the complexities of the socio-political, economic and practical realities facing teachers. Events and experiences, both past and present, that take place at home, school, and in the broader social sphere help to shape these teachers’ lives and careers. Researchers and educators share the responsibility of listening to these teachers’ stories and life experiences and being sensitive to their voices in order to develop effective models for teacher development. A better understanding of how teachers learn to become teachers can help teacher educators prepare more effective teacher education programs. This paper is based on qualitative research which includes individual and focus group interviews, as well as auto-biography stories of Master of Science in School Leadership students at Graduate School of Education of Nazarbayev University. Twenty five MSc students from across Kazakhstan reflected on their professional journey and wrote their professional autobiographies as teachers. Their autobiographies capture the richness of their experiences and beliefs as a teacher, but also serve as window to understand broader socio-economic and political contexts where these teachers live and work. The study also provides an understanding of the systemic and socio-economic challenges of teachers in the context of post-Soviet Kazakhstan. It helps the reader better understand how wider societal forces interact and frame the development of teachers. The paper presents the findings from these stories of MSc students and offers some practical and policy implications for teacher preparation and teacher development.

Keywords: becoming a teacher, Kazakhstan, teacher stories, teacher development

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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Although older drivers (defined as those of age 65 and above) are less involved with speeding, alcohol use as well as night driving, they are more vulnerable to severe crashes. The major contributing factors for severe crashes include frailty and medical complications. Several studies have evaluated the contributing factors on severity of crashes. However, few studies have established the impact of travel time reliability (TTR) on road safety. In particular, the impact of TTR on senior adults who face several challenges including hearing difficulties, decreasing of the processing skills and cognitive problems in driving is not well established. Therefore, this study focuses on determining possible impacts of TTR on the traffic safety with focus on elderly drivers. Historical travel speed data from freeway links in the study area were used to calculate travel time and the associated TTR metrics that is, planning time index, the buffer index, the standard deviation of the travel time and the probability of congestion. Four-year information on crashes occurring on these freeway links was acquired. The binary logit model estimated using the Markov Chain Monte Carlo (MCMC) sampling technique was used to evaluate variables that could be influencing elderly crash severity. Preliminary results of the analysis suggest that TTR is statistically significant in affecting the severity of a crash involving an elderly driver. The result suggests that one unit increase in the probability of congestion reduces the likelihood of the elderly severe crash by nearly 22%. These findings will enhance the understanding of TTR and its impact on the elderly crash severity.

Keywords: highway safety, travel time reliability, elderly drivers, traffic modeling

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Authors: Hassan Ibrahim

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The prevalence of hyperacusis, an auditory condition characterized by heightened sensitivity to sounds, continues to rise, posing challenges for effective diagnosis and intervention. It is believed that this work deepens will deepens the understanding of hyperacusis etiology by employing graph theory as a novel analytical framework. We constructed a comprehensive graph wherein nodes represent various factors associated with hyperacusis, including aging, head or neck trauma, infection/virus, depression, migraines, ear infection, anxiety, and other potential contributors. Relationships between factors are modeled as edges, allowing us to visualize and quantify the interactions within the etiological landscape of hyperacusis. it employ the concept of the metric dimension of a connected graph to identify key nodes (landmarks) that serve as critical influencers in the interconnected web of hyperacusis causes. This approach offers a unique perspective on the relative importance and centrality of different factors, shedding light on the complex interplay between physiological, psychological, and environmental determinants. Visualization techniques were also employed to enhance the interpretation and facilitate the identification of the central nodes. This research contributes to the growing body of knowledge surrounding hyperacusis by offering a network-centric perspective on its multifaceted causes. The outcomes hold the potential to inform clinical practices, guiding healthcare professionals in prioritizing interventions and personalized treatment plans based on the identified landmarks within the etiological network. Through the integration of graph theory into hyperacusis research, the complexity of this auditory condition was unraveled and pave the way for more effective approaches to its management.

Keywords: auditory condition, connected graph, hyperacusis, metric dimension

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Authors: Mustafa Mabruk

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Groups such as Al-Shabaab have managed to radicalize many individuals abroad, including the first American citizen to ever be radicalized. Yet the pathways of radicalization for these foreign individuals are understudied. Moreover, current measures to prevent foreign radicalization are ineffective, with privacy, screening and profiling implications that render current counter-radicalization efforts counterproductive. Such measures exhibit strictness, political bias, and harshness. As confirmed by recent studies, such counter-radicalization issues exacerbate existing grievances and channel fresh recruits to Al-Shabaab. Addressing these challenges is paramount, requiring alternative strategies to effectively reduce radicalization without triggering further harm. The development of counter-narratives emerges as a potential measure with minimal risk of exacerbating grievances, yet the development of such counter-narratives necessitates a thorough understanding of the radicalization pathways of foreign individuals that are understudied. This study investigates the success of Al-Shabaab in recruiting individuals abroad by analyzing their propaganda in conjunction with analyzing identity-focused theories of radicalization, including Framing Theory and Social Identity Theory. Qualitative content analysis is used to analyze various propaganda material, including tweets, speeches, and webpages. The analysis reveals that issues of identity are of major significance in the radicalization patterns identified and that grievances of Muslims worldwide are used to exploit identity-related grievances. Based on these findings, the paper argues that such evidence enhances our understanding of potential deradicalization pathways and present counter-narratives based on Islamic scripture.

Keywords: counter-narratives, foreign radicalization, identity grievances, propaganda analysis

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Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

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This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

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Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

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Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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Authors: Noriyuki Suyama

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The progress and spread of digitalization have led to the provision of a variety of new services. The recent progress in digitization can be attributed to rapid developments in science and technology. First, the research and diffusion of artificial intelligence (AI) has made dramatic progress. Around 2000, the third wave of AI research, which had been underway for about 50 years, arrived. Specifically, machine learning and deep learning were made possible in AI, and the ability of AI to acquire knowledge, define the knowledge, and update its own knowledge in a quantitative manner made the use of big data practical even for commercial PCs. On the other hand, with the spread of social media, information exchange has become more common in our daily lives, and the lending and borrowing of goods and services, in other words, the sharing economy, has become widespread. The scope of this trend is not limited to any industry, and its momentum is growing as the SDGs take root. In addition, the Social Network Service (SNS), a part of social media, has brought about the evolution of the retail business. In the past few years, social network services (SNS) involving users or companies have especially flourished. The People's Republic of China (hereinafter referred to as "China") is a country that is stimulating enormous consumption through its own unique SNS, which is different from the SNS used in developed countries around the world. This paper focuses on the effectiveness and challenges of influencer marketing by focusing on the influence of influencers on users' behavior and satisfaction with Chinese SNSs. Specifically, Conducted was the quantitative survey of Tik Tok users living in China, with the aim of gaining new insights from the analysis and discussions. As a result, we found several important findings and knowledge.

Keywords: customer satisfaction, social networking services, influencer marketing, Chinese consumers’ behavior

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Authors: Zoran Herceg, Tomislava Vukušić, Anet Režek Jambrak, Višnja Stulić

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Today one of the greatest challenges are directed to the safety of food supply. If food pathogens are ingested they can cause human illnesses. Because of that new technologies that are effective in microbial reduction are developing to be used in food industries. One of such technology is cold gas phase plasma. Salmonella enterica was studied as one of the pathogenes that can be found in food. The aim of this work was to examine the inactivation rate and stress response of plasma treated cells of Salmonella enterica inoculated in apple juice. After the treatment cellular leakage, phenotypic changes in plasma treated cells-biofilm formation and degree of recovery were conducted. Sample volume was inoculated with 5 mL of pure culture of Salmonella enterica and 15 mL of apple juice. Statgraphics Centurion software (StatPoint Technologies, Inc., VA, USA) was used for experimental design and statistical analyses. Treatment time (1, 3, 5 min) and gas flow (40, 60, 80 L/min) were changed. Complete inactivation and 0 % of recovery after the 48 h was observed at these experimental treatments: 3 min; 40 L/min, 3 min; 80 L/min, 5 min; 40 L/min. Biofilm reduction was observed at all treated samples. Also, there was an increase in cellular leakage with a longer plasma treatment. Although there were a significant reduction and 0 % of recovery after the plasma treatments further investigation of the method is needed to clarify whether there are sensorial, physical and chemical changes in juices after the plasma treatment. Acknowledgments: The authors would like to acknowledge the support by Croatian Science Foundation and research project 'Application of electrical discharge plasma for the preservation of liquid foods'.

Keywords: salmonella enterica serotype typhimurium lt21, gas-phase plasma treatment, inactivation, stress response

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Authors: Milad Abbasi

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Carbon fiber-reinforced polymer (CFRP) composite structures are increasingly being utilized in the automotive industry due to their lightweight and specific energy absorption capabilities. Although it is impossible to predict composite mechanical properties directly using theoretical methods, various research has been conducted so far in the literature for accurate simulation of CFRP structures' energy-absorbing behavior. In this research, axial compression experiments were carried out on hand lay-up unidirectional CFRP composite tubes. The fabrication method allowed the authors to extract the material properties of the CFRPs using ASTM D3039, D3410, and D3518 standards. A neural network machine learning algorithm was then utilized to build a robust prediction model to forecast the axial compressive properties of CFRP tubes while reducing high-cost experimental efforts. The predicted results have been compared with the experimental outcomes in terms of load-carrying capacity and energy absorption capability. The results showed high accuracy and precision in the prediction of the energy-absorption capacity of the CFRP tubes. This research also demonstrates the effectiveness and challenges of machine learning techniques in the robust simulation of composites' energy-absorption behavior. Interestingly, the proposed method considerably condensed numerical and experimental efforts in the simulation and calibration of CFRP composite tubes subjected to compressive loading.

Keywords: CFRP composite tubes, energy absorption, crushing behavior, machine learning, neural network

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Authors: Zheng Yi

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Among the attempts made worldwide to foster urban and transport sustainability, transit-oriented development certainly is one of the most successful. Residents' travel behavior is a concern in the researches about the impacts of transit-oriented development. The study takes 620 English journal papers in the core collection database of Web of Science as the study objects; the paper tries to map out the scientific knowledge mapping in the field and draw the basic conditions by co-citation analysis, co-word analysis, a total of citation network analysis and visualization techniques. This study teases out the research hotspots and evolution of the relationship between urban rail transit and resident's travel behavior from 1999 to 2019. According to the results of the analysis of the time-zone view and burst-detection, the paper discusses the trend of the next stage of international study. The results show that in the past 20 years, the research focuses on these keywords: land use, behavior, model, built environment, impact, travel behavior, walking, physical activity, smart card, big data, simulation, perception. According to different research contents, the key literature is further divided into these topics: the attributes of the built environment, land use, transportation network, transportation policies. The results of this paper can help to understand the related researches and achievements systematically. These results can also provide a reference for identifying the main challenges that relevant researches need to address in the future.

Keywords: urban rail transit, travel behavior, knowledge map, evolution of researches

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Authors: Carol S. Binnekade, Deon Scott, Christina C. Shuttleworth, Annelien A. Van Rooyen

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Higher education institutions are constantly challenged to deliver skilled graduates into the workplace. Employers expect graduates to have the required technical knowledge as well as various pervasive skills. This also applies to accountants who need to know the technical requirements of financial reporting and be able to communicate with individuals, teams and clients at a high level. Accountants need to develop effective business conversational skills and use these skills to communicate up, down and across organizations, taking into consideration cultural and gender diversity. In addition, they need to master business writing and presentation skills. However, providing students with these skills in a distance-learning environment where interaction between students and instructors is limited, is a challenge for academics. The study on which this paper reports, forms part of a larger body of research, which explored the perceptions of accounting practitioners of the communication skills (or lack thereof) of recently qualified accounting students. Feedback (qualitative and quantitative) was obtained from various accounting practitioners in South Africa. Taking into consideration that distance learners communicate mainly with their instructors via email communication and their assignments are submitted using various word processor software, the researchers were of the opinion that the accounting graduates would be capable of communicating effectively once they entered the workplace. However, the research findings, inter alia, suggested that the accounting graduates lacked communication skills and that training was needed to differentiate between business and social communication once they entered the workplace. Recommendations on how these communication challenges may be addressed by higher education institutions are provided.

Keywords: accounting practitioners, communication skills, distance education, pervasive skills

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Authors: Abewardhana Arachchi Bandula Dimuthu Priyadarshana Abewardhana, Rasika Nirosh Gonapinuwala Vithanage, Karawe Thanthreege Amila Madusanka Perera, Asanka Sanjeewa Karunarathne, Navullage Mayuri Radhika Perera

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The phenomenon of irregular migration and human trafficking presents multifaceted challenges to Sri Lanka, with specific focus on the migration routes to the United Arab Emirates (UAE), the Sultanate of Oman, and Malaysia. This research critically assesses the efficacy of a pilot project instituted at Bandaranaike International Airport aimed at the identification and deterrence of potential irregular migrants. Additionally, the study conducts a nuanced analysis of the geographical tendencies pertaining to passengers who revise their migration intentions at the airport. Pertinently, the findings indicate that Colombo and Gampaha Districts emerge as the most susceptible to human trafficking, with Galle, Nuwaraeliya, Rathnapura, and Polonnaruwa Districts following as areas of elevated concern, particularly within the framework of the 'visit visa' scenario. These insights emanate from an extensive data collection period spanning 50 days of the pilot project, encompassing 1,479 passengers, of which 46 returnees reported to the Safe Migration Promotion Unit. The research is founded on the twin objectives of comprehending the motivations of passengers and evaluating the effectiveness of interventions, with a view to devising precision-targeted prevention strategies. Through this endeavor, the study actively contributes to the safeguarding of the rights and welfare of migrants, significantly advancing the ongoing battle against irregular migration.

Keywords: irregular migration, human trafficking, airport interventions, geographic trends

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Authors: Homa Hedayat

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In the dynamic urban landscape of Toronto, the concept of belonging assumes paramount importance. As global challenges—such as the pandemic, financial instability, and geopolitical shifts—reshape our world, understanding how different generations of immigrants establish connections within this multicultural metropolis becomes increasingly vital. Our research delves into forming a sense of belonging in urban spaces, specifically focusing on the experiences of Iranian immigrants residing in Toronto. By examining their perceptions of public places, attachment to residential neighborhoods, and the impact of the urban environment, we contribute to a more holistic understanding of social sustainability and community well-being. We unravel the intricate interplay between individual characteristics, housing context, and neighborhood dynamics through qualitative interviews and a quantitative survey. This research presents a study of the perception of public places and sense of belonging in residential neighbourhoods by younger and older Iranian immigrants living in the Toronto metropolitan area. Few works in the existing literature have investigated the relationship immigrants develop with the shared spaces of the city and their residential environment and how that relationship can impact the development of a ‘sense of belonging’ in the city. Ultimately, our findings pave the way for inclusive and cohesive urban environments, fostering connections across generations and enhancing Toronto’s resilience and harmony. As Toronto continues to evolve, nurturing a sense of belonging becomes paramount. Our research emphasizes the importance of social cohesion and community well-being. By fostering connections across generations, we pave the way for a more resilient and harmonious city.

Keywords: sense of belonging, multigenerational, urban spaces, social sustainability

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Authors: Raghava Dhanya, Shashank S.

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This paper delves into the intersection of chess and computer science, specifically focusing on the efficient representation of chess game states. We propose two methods: the Static Method and the Dynamic Method, each offering unique advantages in terms of space efficiency and computational complexity. The Static Method aims to represent the game state using a fixedlength encoding, allocating 192 bits to capture the positions of all pieces on the board. This method introduces a protocol for ordering and encoding piece positions, ensuring efficient storage and retrieval. However, it faces challenges in representing pieces no longer in play. In contrast, the Dynamic Method adapts to the evolving game state by dynamically adjusting the encoding length based on the number of pieces in play. By incorporating Alive Bits for each piece kind, this method achieves greater flexibility and space efficiency. Additionally, it includes provisions for encoding additional game state information such as castling rights and en passant squares. Our findings demonstrate that the Dynamic Method offers superior space efficiency compared to traditional Forsyth-Edwards Notation (FEN), particularly as the game progresses and pieces are captured. However, it comes with increased complexity in encoding and decoding processes. In conclusion, this study provides insights into optimizing the representation of chess game states, offering potential applications in chess engines, game databases, and artificial intelligence research. The proposed methods offer a balance between space efficiency and computational overhead, paving the way for further advancements in the field.

Keywords: chess, optimisation, encoding, bit manipulation

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Authors: Oluseun A. Akinsorotan, Louise K. Gentle, Md. Mofakkarul Islam, Richard W. Yarnell

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High levels of anthropogenic activity such as habitat destruction, poaching and encroachment into natural habitat have resulted in significant global wildlife declines. In order to protect wildlife, many protected areas such as national parks have been created. However, it is argued that many protected areas are only protected in name and are often exposed to continued, and often illegal, anthropogenic pressure. In West African protected areas, declines of large mammals have been documented between 1962 and 2008. This study aimed to produce occupancy estimates of the remaining large mammal fauna in the third largest National Park in Nigeria, Old Oyo, and to compare the estimates with historic estimates while also attempting to quantify levels of illegal anthropogenic activity using a multi-disciplinary approach. Large mammal populations and levels of illegal anthropogenic activity were assessed using empirical field data (camera trapping and transect surveys) in combination with data from questionnaires completed by local villagers and park rangers. Four of the historically recorded species in the park, lion (Panthera leo), hunting dog (Lycaon pictus), elephant (Loxodonta africana) and buffalo (Syncerus caffer) were not detected during field studies nor were they reported by respondents. In addition, occupancy estimates of hunters and illegal grazers were higher than the majority of large mammal species inside the park. This finding was reinforced by responses from the villagers and rangers who’s perception was that large mammal densities in the park were declining, and that a large proportion of the local people were entering the park to hunt wild animals and graze their domestic livestock. Our findings also suggest that widespread poverty and a lack of alternative livelihood opportunities, culture of consuming bushmeat, lack of education and awareness of the value of protected areas, and weak law enforcement are some of the reasons for the illegal activity. Law enforcement authorities were often constrained by insufficient on-site personnel and a lack of modern equipment and infrastructure to deter illegal activities. We conclude that there is a need to address the issue of illegal hunting and livestock grazing, via provision of alternative livelihoods, in combination with community outreach programmes that aim to improve conservation education and awareness and develop the capacity of the conservation authorities in order to achieve conservation goals. Our findings have implications for the conservation management of all protected areas that are available for exploitation by local communities.

Keywords: camera trapping, conservation, extirpation, illegal grazing, large mammals, national park, occupancy estimates, poaching

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Authors: Bahram Siavashpor, Zeynab Haji Abdolhadi

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The issue of the worn out textures is one of the urban community challenges in which, undoubtedly, the intervention is impossible without the social involvement. Some believe that in the worn out areas the most important intervention challenge is the social issues, and the most important social issue, in the intervention in the worn out areas, is how to attract public participation. Participation by itself has a widespread literature and despite relative acceptance, it should be said that planners, managers and designers are not always successful in attracting public participation. If participation means the intervention of all the residents in the neighborhood, women’s community forms half of these residents, but they are neglected in the participatory planning. It is important to know that to what extent the presence of women’s community in the related participation to the worn out textures affects the success of the projects. The present study hypotheses emphasize the effectiveness of women than men in involvement of the renovation and reforming projects. A case study was selected to investigate this hypothesis in order to test it through doing a questionnaire and visiting the place. Tehran Helal Ahmar region located in district 11 has 2740 households in which 51% are men and 49% women. The statistical population consists of 150 men and women of this area selected randomly. In the present study, interview technique with the executives was used as well as questionnaire along collecting the related research. The hypothesis analysis was carried out through SPSS and Excel software, in which two tests ‘Man-Whitney’ and ‘chi-square’ were used. The results indicate that women are empowered in the participation and renovation of the area, but it is necessary to rectify men’s attitude towards women’s ability in terms of women participation.

Keywords: renovation, social involvement, women’s participation, worn out texture

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Authors: Flavio Gazzani

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Nitrogen is an important agricultural input that is critical for the production. However, the introduction of large amounts of nitrogen into the environment has a number of undesirable impacts such as: the loss of biodiversity, eutrophication of waters and soils, drinking water pollution, acidification, greenhouse gas emissions, human health risks. It is a challenge to sustain or increase food production and at the same time reduce losses of reactive nitrogen to the environment, but there are many potential benefits associated with improving nitrogen use efficiency. Reducing nutrient losses from agriculture is crucial to the successful implementation of agricultural policy. Traditional regulatory instruments applied to implement environmental policies to reduce environmental impacts from nitrogen fertilizers, despite some successes, failed to address many environmental challenges and imposed high costs on the society to achieve environmental quality objectives. As a result, economic instruments started to be recognized for their flexibility and cost-effectiveness. The objective of the research project is to analyze the potential for increased use of market-based instruments in nitrogen control policy. The report reviews existing knowledge, bringing different studies together to assess the global nitrogen situation and the most relevant environmental management policy that aims to reduce pollution in a sustainable way without affect negatively agriculture production and food price. This analysis provides some guidance on how different market based instruments might be orchestrated in an overall policy framework to the development and assessment of sustainable nitrogen management from the economics, environmental and food security point of view.

Keywords: nitrogen emissions, chemical fertilizers, eutrophication, non-point of source pollution, dairy farm

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Authors: Hassan Ibrahim

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The prevalence of hyperacusis, an auditory condition characterized by heightened sensitivity to sounds, continues to rise, posing challenges for effective diagnosis and intervention. It is believed that this work deepens will deepens the understanding of hyperacusis etiology by employing graph theory as a novel analytical framework. it constructed a comprehensive graph wherein nodes represent various factors associated with hyperacusis, including aging, head or neck trauma, infection/virus, depression, migraines, ear infection, anxiety, and other potential contributors. Relationships between factors are modeled as edges, allowing us to visualize and quantify the interactions within the etiological landscape of hyperacusis. it employ the concept of the metric dimension of a connected graph to identify key nodes (landmarks) that serve as critical influencers in the interconnected web of hyperacusis causes. This approach offers a unique perspective on the relative importance and centrality of different factors, shedding light on the complex interplay between physiological, psychological, and environmental determinants. Visualization techniques were also employed to enhance the interpretation and facilitate the identification of the central nodes. This research contributes to the growing body of knowledge surrounding hyperacusis by offering a network-centric perspective on its multifaceted causes. The outcomes hold the potential to inform clinical practices, guiding healthcare professionals in prioritizing interventions and personalized treatment plans based on the identified landmarks within the etiological network. Through the integration of graph theory into hyperacusis research, the complexity of this auditory condition was unraveled and pave the way for more effective approaches to its management.

Keywords: auditory condition, connected graph, hyperacusis, metric dimension

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Authors: Enido Fabiano de Ramos, Ieda Kanashiro Makiya, Francisco I. Giocondo Cesar

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This study investigates the application of Digital Twins (DT) in Smart Hospital Environments (SHE), through a bibliometric study and literature review, including comparison with the principles of Industry 4.0. It aims to analyze the current state of the implementation of digital twins in clinical and non-clinical operations in healthcare settings, identifying trends and challenges, comparing these practices with Industry 4.0 concepts and technologies, in order to present a basic framework including stages and maturity levels. The bibliometric methodology will allow mapping the existing scientific production on the theme, while the literature review will synthesize and critically analyze the relevant studies, highlighting pertinent methodologies and results, additionally the comparison with Industry 4.0 will provide insights on how the principles of automation, interconnectivity and digitalization can be applied in healthcare environments/operations, aiming at improvements in operational efficiency and quality of care. The results of this study will contribute to a deeper understanding of the potential of Digital Twins in Smart Hospitals, in addition to the future potential from the effective integration of Industry 4.0 concepts in this specific environment, presented through the practical framework, after all, the urgent need for changes addressed in this article is undeniable, as well as all their value contribution to human sustainability, designed in SDG3 – Health and well-being: ensuring that all citizens have a healthy life and well-being, at all ages and in all situations. We know that the validity of these relationships will be constantly discussed, and technology can always change the rules of the game.

Keywords: digital twin, smart hospital, healthcare operations, industry 4.0, SDG3, technology

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Authors: Vivek Hokam, Vishrut Landge

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An ideal maintenance program for an industrial road network is one that would maintain all sections at a sufficiently high level of functional and structural conditions. However, due to various constraints such as budget, manpower and equipment, it is not possible to carry out maintenance on all the needy industrial road sections within a given planning period. A rational and systematic priority scheme needs to be employed to select and schedule industrial road sections for maintenance. Priority analysis is a multi-criteria process that determines the best ranking list of sections for maintenance based on several factors. In priority setting, difficult decisions are required to be made for selection of sections for maintenance. It is more important to repair a section with poor functional conditions which includes uncomfortable ride etc. or poor structural conditions i.e. sections those are in danger of becoming structurally unsound. It would seem therefore that any rational priority setting approach must consider the relative importance of functional and structural condition of the section. The maintenance priority index and pavement performance models tend to focus mainly on the pavement condition, traffic criteria etc. There is a need to develop the model which is suitably used with respect to limited budget provisions for maintenance of pavement. Linear programming is one of the most popular and widely used quantitative techniques. A linear programming model provides an efficient method for determining an optimal decision chosen from a large number of possible decisions. The optimum decision is one that meets a specified objective of management, subject to various constraints and restrictions. The objective is mainly minimization of maintenance cost of roads in industrial area. In order to determine the objective function for analysis of distress model it is necessary to fix the realistic data into a formulation. Each type of repair is to be quantified in a number of stretches by considering 1000 m as one stretch. A stretch considered under study is having 3750 m length. The quantity has to be put into an objective function for maximizing the number of repairs in a stretch related to quantity. The distress observed in this stretch are potholes, surface cracks, rutting and ravelling. The distress data is measured manually by observing each distress level on a stretch of 1000 m. The maintenance and rehabilitation measured that are followed currently are based on subjective judgments. Hence, there is a need to adopt a scientific approach in order to effectively use the limited resources. It is also necessary to determine the pavement performance and deterioration prediction relationship with more accurate and economic benefits of road networks with respect to vehicle operating cost. The infrastructure of road network should have best results expected from available funds. In this paper objective function for distress model is determined by linear programming and deterioration model considering overloading is discussed.

Keywords: budget, maintenance, deterioration, priority

Procedia PDF Downloads 207