Search results for: higher education system

Authors: Lan Wu

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The declared transformation towards a ‘new electricity system dominated by renewable energy’ by China requires a cleaner electricity consumption mix with high shares of renewable energy sourced-electricity (RES-E). Unfortunately, integration of RES-E into Chinese electricity markets remains a problem pending more robust legal support, evidenced by the curtailment of wind and solar power as a consequence of integration constraints. The upcoming energy law of the PRC (energy law) is expected to provide such long-awaiting support and coordinate the existing diverse sector-specific laws to deal with the weak implementation that dampening the delivery of their desired regulatory effects. However, in the shadow of the COVID-19 crisis, it remains uncertain how this new energy law brings synergies to RES-E integration, mindful of the significant impacts of the pandemic. Through the theoretical lens of the interplay between China’s electricity reform and legislative development, the present paper investigates whether there is a paradigm shift in energy law regarding renewable energy integration compared with the existing sector-specific energy laws. It examines the 2020 draft for comments on the energy law and analyses its relationship with sector-specific energy laws focusing on RES-E integration. The comparison is drawn upon five key aspects of the RES-E integration issue, including the status of renewables, marketisation, incentive schemes, consumption mechanisms, access to power grids, and dispatching. The analysis shows that it is reasonable to expect a more open and well-organized electricity market enabling absorption of high shares of RES-E. The present paper concludes that a period of prosperous development of RES-E in the post-COVID-19 era can be anticipated with the legal support by the upcoming energy law. It contributes to understanding the signals China is sending regarding the transition towards a cleaner energy future.

Keywords: energy law, energy transition, electricity market reform, renewable energy integration

Procedia PDF Downloads 195

Authors: Ebru Dural, M. Zulfu Asık

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Laminated glass is a kind of safety glass, which is made by 'sandwiching' two glass sheets and a polyvinyl butyral (PVB) interlayer in between them. When the glass is broken, the interlayer in between the glass sheets can stick them together. Because of this property, the hazards of sharp projectiles during natural and man-made disasters reduces. They can be widely applied in building, architecture, automotive, transport industries. Laminated glass can easily undergo large displacements even under their own weight. In order to explain their true behavior, they should be analyzed by using large deflection theory to represent nonlinear behavior. In this study, a nonlinear mathematical model is developed for the analysis of laminated glass cylindrical shell which is free in radial directions and restrained in axial directions. The results will be verified by using the results of the experiment, carried out on laminated glass cylindrical shells. The behavior of laminated composite cylindrical shell can be represented by five partial differential equations. Four of the five equations are used to represent axial displacements and radial displacements and the fifth one for the transverse deflection of the unit. Governing partial differential equations are derived by employing variational principles and minimum potential energy concept. Finite difference method is employed to solve the coupled differential equations. First, they are converted into a system of matrix equations and then iterative procedure is employed. Iterative procedure is necessary since equations are coupled. Problems occurred in getting convergent sequence generated by the employed procedure are overcome by employing variable underrelaxation factor. The procedure developed to solve the differential equations provides not only less storage but also less calculation time, which is a substantial advantage in computational mechanics problems.

Keywords: laminated glass, mathematical model, nonlinear behavior, PVB

Procedia PDF Downloads 319

Authors: Vanja Skoric

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The paper examines whether the impacts of artificial intelligence (AI) can be meaningfully addressed through the rights-based approach to AI design, investigating in particular how the inclusive, participatory process of assessing the AI impact would make this viable. There is a significant gap between envisioning rights-based AI systems and their practical application. Plausibly, internalizing human rights approach within AI design process might be achieved through identifying and assessing implications of AI features human rights, especially considering the case of vulnerable individuals and communities. However, there is no clarity or consensus on how such an instrument should be operationalised to usefully identify the impact, mitigate harms and meaningfully ensure relevant stakeholders’ participation. In practice, ensuring the meaningful inclusion of those individuals, groups, or entire communities who are affected by the use of the AI system is a prerequisite for a process seeking to assess human rights impacts and risks. Engagement in the entire process of the impact assessment should enable those affected and interested to access information and better understand the technology, product, or service and resulting impacts, but also to learn about their rights and the respective obligations and responsibilities of developers and deployers to protect and/or respect these rights. This paper will provide an overview of the study and practice of the participatory design process for AI, including inclusive impact assessment, its main elements, propose a framework, and discuss the lessons learned from the existing theory. In addition, it will explore pathways for enhancing and promoting individual and group rights through such engagement by discussing when, how, and whom to include, at which stage of the process, and what are the pre-requisites for meaningful and engaging. The overall aim is to ensure using the technology that works for the benefit of society, individuals, and particular (historically marginalised) groups.

Keywords: rights-based design, AI impact assessment, inclusion, harm mitigation

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Authors: Selvam M., Vadthya Poornachandar, Surender Singh

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These Reclaimed Asphalt Pavement (RAP) aggregates are generally dumped in the open area after the demolition of Asphalt Pavements. The utilization of RAP aggregates in cement concrete pavements may provide several socio-economic-environmental benefits and could embrace the circular economy. The cross recycling of RAP aggregates in the concrete pavement could reduce the consumption of virgin aggregates and saves the fertile land. However, the structural, as well as functional properties of RAP-concrete could be significantly lower than the conventional Pavement Quality Control (PQC) pavements. This warrants judicious selection of RAP fraction (coarse and fine aggregates) along with the accurate proportion of the same for PQC highways. Also, the selection of the RAP fraction and its proportion shall not be solely based on the mechanical properties of RAP-concrete specimens but also governed by the structural and functional behavior of the pavement system. In this study, an effort has been made to predict the optimum RAP fraction and its corresponding proportion for cement concrete pavements by considering the low-volume and high-volume roads. Initially, the effect of inclusions of RAP on the fresh and mechanical properties of concrete pavement mixes is mapped through an extensive literature survey. Almost all the studies available to date are considered for this study. Generally, Indian Roads Congress (IRC) methods are the most widely used design method in India for the analysis of concrete pavements, and the same has been considered for this study. Subsequently, fatigue damage analysis is performed to evaluate the required safe thickness of pavement slab for different fractions of RAP (coarse RAP). Consequently, the performance of RAP-concrete is predicted by employing the AASHTO-1993 model for the following distresses conditions: faulting, cracking, and smoothness. The performance prediction and total cost analysis of RAP aggregates depict that the optimum proportions of coarse RAP aggregates in the PQC mix are 35% and 50% for high volume and low volume roads, respectively.

Keywords: concrete pavement, RAP aggregate, performance prediction, pavement design

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Authors: Juhi Sah

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Habitat is characterized by the inter-dependency of environmental elements. Anthropocentric development approach is increasing our vulnerability towards natural hazards. Hence, manmade interventions should have a higher level of sensitivity towards the natural settings. Sensitivity towards the environment can be assessed by the behavior of the stakeholders involved. This led to the establishment of a hypothesis: there exists a legitimate relationship between the behavioral sciences, land use evolution and environment conservation, in the planning process. An attempt has been made to establish this relationship by reviewing the existing set of knowledge and case examples pertaining to the three disciplines under inquiry. Understanding the scarce & deteriorating nature of fresh-water reserves of earth and experimenting the above concept, a case study of a growing urban center's river flood plain is selected, in a developing economy, India. Cases of urban flooding in Chennai, Delhi and other mega cities of India, imposes a high risk on the unauthorized settlement, on the floodplains of the rivers. The issue addressed here is the encroachment of floodplains, through psychological enlightenment and modification through knowledge building. The reaction of an individual or society can be compared to a cognitive process. This study documents all the stakeholders' behavior and perception for their immediate natural environment (water body), and produce various land uses suitable along a river in an urban settlement as per different stakeholder's perceptions. To assess and induce morally responsible behavior in a community (small scale or large scale), tools of psychological inquiry is used for qualitative analysis. The analysis will deal with varied data sets from two sectors namely: River and its geology, Land use planning and regulation. Identification of a distinctive pattern in the built up growth, river ecology degradation, and human behavior, by handling large quantum of data from the diverse sector and comments on the availability of relevant data and its implications, has been done. Along the whole river stretch, condition and usage of its bank vary, hence stakeholder specific survey questionnaires have been prepared to accurately map the responses and habits of the rational inhabitants. A conceptual framework has been designed to move forward with the empirical analysis. The classical principle of virtues says "virtue of a human depends on its character" but another concept defines that the behavior or response is a derivative of situations and to bring about a behavioral change one needs to introduce a disruption in the situation/environment. Owing to the present trends, blindly following the results of data analytics and using it to construct policy, is not proving to be in favor of planned development and natural resource conservation. Thus behavioral assessment of the rational inhabitants of the planet is also required, as their activities and interests have a large impact on the earth's pre-set systems and its sustenance.

Keywords: behavioral assessment, flood plain encroachment, land use planning, river sustenance

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Authors: Farideh Halakou, Emel Sen, Attila Gursoy, Ozlem Keskin

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Protein–Protein Interactions (PPIs) mediate major biological processes in living cells. The study of PPIs as networks and analyze the network properties contribute to the identification of genes and proteins associated with diseases. In this study, we have created the sub-networks of brain and lung metastasis from primary tumor in breast cancer. To do so, we used seed genes known to cause metastasis, and produced their interactions through a network-topology based prioritization method named GUILDify. In order to have the experimental support for the sub-networks, we further curated them using STRING database. We proceeded by modeling structures for the interactions lacking complex forms in Protein Data Bank (PDB). The functional enrichment analysis shows that KEGG pathways associated with the immune system and infectious diseases, particularly the chemokine signaling pathway, are important for lung metastasis. On the other hand, pathways related to genetic information processing are more involved in brain metastasis. The structural analyses of the sub-networks vividly demonstrated their difference in terms of using specific interfaces in lung and brain metastasis. Furthermore, the topological analysis identified genes such as RPL5, MMP2, CCR5 and DPP4, which are already known to be associated with lung or brain metastasis. Additionally, we found 6 and 9 putative genes that are specific for lung and brain metastasis, respectively. Our analysis suggests that variations in genes and pathways contributing to these different breast metastasis types may arise due to change in tissue microenvironment. To show the benefits of using structural PPI networks instead of traditional node and edge presentation, we inspect two case studies showing the mutual exclusiveness of interactions and effects of mutations on protein conformation which lead to different signaling.

Keywords: breast cancer, metastasis, PPI networks, protein conformational changes

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Authors: Zaide Montes Ortiz, Jorge Alberto Molina, Alejandro Reyes

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Insects are extremely successful organisms. A sophisticated olfactory system is in part responsible for their survival and reproduction. The detection of volatile organic compounds can positively or negatively affect many behaviors in insects. Compounds such as carbon dioxide (CO2), ammonium, indol, and lactic acid are essential for many species of mosquitoes like Anopheles gambiae in order to locate vertebrate hosts. For instance, in A. gambiae, the olfactory receptor AgOR2 is strongly activated by indol, which accounts for almost 30% of human sweat. On the other hand, in some insects of agricultural importance, the detection and identification of pheromone receptors (PRs) in lepidopteran species has become a promising field for integrated pest management. For example, with the disruption of the pheromone receptor, BmOR1, mediated by transcription activator-like effector nucleases (TALENs), the sensitivity to bombykol was completely removed affecting the pheromone-source searching behavior in male moths. Then, the detection and identification of olfactory receptors in the genomes of insects is fundamental to improve our understanding of the ecological interactions, and to provide alternatives in the integrated pests and vectors management. Hence, the objective of this study is to propose a bioinformatic workflow to enhance the detection and identification of potential olfactory receptors in genomes of relevant insects. Applying Hidden Markov models (Hmms) and different computational tools, potential candidates for pheromone receptors in Tuta absoluta were obtained, as well as potential carbon dioxide receptors in Rhodnius prolixus, the main vector of Chagas disease. This study showed the validity of a bioinformatic workflow with a potential to improve the identification of certain olfactory receptors in different orders of insects.

Keywords: bioinformatic workflow, insects, olfactory receptors, protein prediction

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Authors: Renata Roma, Christine Tardif-Williams

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Engaging in daily walks with a dog (f.e. Canis lupus familiaris) during the COVID-19 pandemic may be linked to feelings of greater social-connectedness and global self-worth, and lower stress after controlling for mental health issues, lack of physical contact with others, and other stressors associated with the current pandemic. Therefore, maintaining a routine of dog walking might mitigate the effects of stressors experienced during the pandemic and promote well-being. However, many dog owners do not walk their dogs for many reasons, which are related to the owner’s and the dog’s personalities. Note that the consistency of certain personality characteristics among dogs demonstrates that it is possible to accurately measure different dimensions of personality in both dogs and their human counterparts. In addition, behavioural ratings (e.g., the dog personality questionnaire - DPQ) are reliable tools to assess the dog’s personality. Clarifying the relevance of personality factors in the context of young adult-dog relationships can shed light on interactional aspects that can potentially foster protective behaviours and promote well-being among young adults during the pandemic. This study examines if and how nine combinations of dog- and young adult-related personality characteristics (e.g., neuroticism-fearfulness) can amplify the influence of personality factors in the context of dog walking during the COVID-19 pandemic. Responses to an online large-scale survey among 440 (389 females; 47 males; 4 nonbinaries, Mage=20.7, SD= 2.13 range=17-25) young adults living with a dog in Canada were analyzed using structural equation modeling (SEM). As extraversion, conscientiousness, and neuroticism, measured through the five-factor model (FFM) inventory, are related to maintaining a routine of physical activities, these dimensions were selected for this analysis. Following an approach successfully adopted in the field of dog-human interactions, the FFM was used as the organizing framework to measure and compare the human’s and the dog’s personality in the context of dog walking. The dog-related personality dimensions activity/excitability, responsiveness to training, and fearful were correlated dimensions captured through DPQ and were added to the analysis. Two questions were used to assess dog walking. The actor-partner interdependence model (APIM) was used to check if the young adult’s responses about the dog were biased; no significant bias was observed. Activity/excitability and responsiveness to training in dogs were greatly associated with dog walking. For young adults, high scores in conscientiousness and extraversion predicted more walks with the dog. Conversely, higher scores in neuroticism predicted less engagement in dog walking. For participants high in conscientiousness, the dog’s responsiveness to training (standardized=0.14, p=0.02) and the dog’s activity/excitability (standardized=0.15, p=0.00) levels moderated dog walking behaviours by promoting more daily walks. These results suggest that some combinations in young adult and dog personality characteristics are associated with greater synergy in the young adult-dog dyad that might amplify the impact of personality factors on young adults’ dog-walking routines. These results can inform programs designed to promote the mental and physical health of young adults during the Covid-19 pandemic by highlighting the impact of synergy and reciprocity in personality characteristics between young adults and dogs.

Keywords: Covid-19 pandemic, dog walking, personality, structural equation modeling, well-being

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Authors: Jonathan Martino, Kristof Harri

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In some cases, the increase in computing resources makes simulation methods more affordable. The increase in processing speed also allows real time analysis or even more rapid tests analysis offering a real tool for test prediction and design process optimization. Vibration tests are no exception to this trend. The so called ‘Virtual Vibration Testing’ offers solution among others to study the influence of specific loads, to better anticipate the boundary conditions between the exciter and the structure under test, to study the influence of small changes in the structure under test, etc. This article will first present a virtual vibration test modeling with a main focus on the shaker model and will afterwards present the experimental parameters determination. The classical way of modeling a shaker is to consider the shaker as a simple mechanical structure augmented by an electrical circuit that makes the shaker move. The shaker is modeled as a two or three degrees of freedom lumped parameters model while the electrical circuit takes the coil impedance and the dynamic back-electromagnetic force into account. The establishment of the equations of this model, describing the dynamics of the shaker, is presented in this article and is strongly related to the internal physical quantities of the shaker. Those quantities will be reduced into global parameters which will be estimated through experiments. Different experiments will be carried out in order to design an easy and practical method for the identification of the shaker parameters leading to a fully functional shaker model. An experimental modal analysis will also be carried out to extract the modal parameters of the shaker and to combine them with the electrical measurements. Finally, this article will conclude with an experimental validation of the model.

Keywords: lumped parameters model, shaker modeling, shaker parameters, state-space, virtual vibration

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Cristina Prandi, Piermichele Kobauri

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The present study is based on molecular modeling of a series of twelve 5-(4-substituent-phenoxy)-3-methylfuran-2(5H)-one derivatives which have potential of strigolactones mimics toward Striga hermonthica. The first step of the analysis included the calculation of molecular descriptors which numerically describe the structures of the analyzed compounds. The descriptors ALOGP (lipophilicity), AClogS (water solubility) and BBB (blood-brain barrier penetration), served as the input variables in multiple linear regression (MLR) modeling of germination activity toward S. hermonthica. Two MLR models were obtained. The first MLR model contains ALOGP and AClogS descriptors, while the second one is based on these two descriptors plus BBB descriptor. Despite the braking Topliss-Costello rule in the second MLR model, it has much better statistical and cross-validation characteristics than the first one. The ALOGP and AClogS descriptors are often very suitable predictors of the biological activity of many compounds. They are very important descriptors of the biological behavior and availability of a compound in any biological system (i.e. the ability to pass through the cell membranes). BBB descriptor defines the ability of a molecule to pass through the blood-brain barrier. Besides the lipophilicity of a compound, this descriptor carries the information of the molecular bulkiness (its value strongly depends on molecular bulkiness). According to the obtained results of MLR modeling, these three descriptors are considered as very good predictors of germination activity of the analyzed compounds toward S. hermonthica seeds. This article is based upon work from COST Action (FA1206), supported by COST (European Cooperation in Science and Technology).

Keywords: chemometrics, germination activity, molecular modeling, QSAR analysis, strigolactones

Procedia PDF Downloads 287

Authors: Aniekan Peter, ECS Naidu, Edidiong Akang, U. Offor, R. Kalhapure, A. A. Chuturgoon, T. Govender, O. O. Azu

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Introduction: Nano-drugs are novel innovations in the management of human immunodeficiency virus (HIV) pandemic, especially resistant strains of the virus in their sanctuary sites: testis and the brain. There are safety concerns to be addressed to achieve the full potential of this new drug delivery system. Aim of study: Our study was designed to investigate toxicity profile of Tenofovir Nanoparticle (TDF-N) synthesized by University of Kwazulu-Natal (UKZN) Nano-team for prevention and treatment of HIV infection. Methodology: Ten adult male Sprague-Dawley rats maintained at the Animal House of the Biomedical Resources Unit UKZN were used for the study. The animals were weighed and divided into two groups of 5 animal each. Control animals (A) were administered with normal saline. Therapeutic dose (4.3 mg/kg) of TDF-N was administered to group B. At the end of four weeks, animals were weighed and sacrificed. Liver and kidney were removed fixed in formal saline, processed and stained using H/E, PAS and MT stains for light microscopy. Serum was obtained for renal function test (RFT), liver function test (LFT) and full blood count (FBC) using appropriate analysers. Cellular measurements were done using ImageJ and Leica software 2.0. Data were analysed using graph pad 6, values < 0.05 were significant. Results: We reported no histological alterations in the liver, kidney, FBC, LFT and RFT between the TDF-N animals and saline control. There were no significant differences in weight, organo-somatic index and histological measurements in the treatment group when compared with saline control. Conclusion/recommendations: TDF-N is not toxic to the liver, kidney and blood cells in our study. More studies using human subjects is recommended.

Keywords: tenofovir nanoparticles, liver, kidney, blood cells

Procedia PDF Downloads 183

Authors: Smita Singh

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Objective: The Faculty of Chemistry Education at Humboldt University has developed ‘Studium’, a web application designed to enhance long-term self-regulated learning (SRL) and academic achievement. Leveraging advanced generative AI, ‘Studium’ offers a dynamic and adaptive educational experience tailored to individual learning preferences and languages. The application includes evolving tools for personalized notetaking from preferred sources, customizable presentation capabilities, and AI-assisted guidance from academic documents or textbooks. It also features workflow automation and seamless integration with collaborative platforms like Miro, powered by AI. This study aims to propose a model that combines generative AI with traditional features and customization options, empowering students to create personalized learning environments that effectively address the challenges of SRL. Method: To achieve this, the study included graduate and undergraduate students from diverse subject streams, with 15 participants each from Germany and India, ensuring a diverse educational background. An exploratory design was employed using a speed dating method with enactment, where different scenario sessions were created to allow participants to experience various features of ‘Studium’. The session lasted for 50 minutes, providing an in-depth exploration of the platform's capabilities. Participants interacted with Studium’s features via Zoom conferencing and were then engaged in semi-structured interviews lasting 10-15 minutes to gain deeper insights into the effectiveness of ‘Studium’. Additionally, online questionnaire surveys were conducted before and after the session to gather feedback and evaluate satisfaction with self-regulated learning (SRL) after using ‘Studium’. The response rate of this survey was 100%. Results: The findings of this study indicate that students widely acknowledged the positive impact of ‘Studium’ on their learning experience, particularly its adaptability and intuitive design. They expressed a desire for more tools like ‘Studium’ to support self-regulated learning in the future. The application significantly fostered students' independence in organizing information and planning study workflows, which in turn enhanced their confidence in mastering complex concepts. Additionally, ‘Studium’ promoted strategic decision-making and helped students overcome various learning challenges, reinforcing their self-regulation, organization, and motivation skills. Conclusion: This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like “Studium” can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners. This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like ‘Studium’ can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners.

Keywords: self-regulated learning (SRL), generative AI, AI-assisted educational platforms

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Authors: Muhammad Safi, Abdul Manan

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In recent years, research in aircraft avionics systems (i.e., radars and antennas) has grown revolutionary. Aircraft technology is experiencing an increasing inclination from all mechanical to all electrical aircraft, with the introduction of inhabitant air vehicles and drone taxis over the last few years. This develops an overriding need to summarize the history, latest trends, and future development in aircraft avionics research for a better understanding and development of new technologies in the domain of avionics systems. This paper focuses on the future trends in antennas and phased arrays for avionics systems. Along with the general overview of the future avionics trend, this work describes the review of around 50 high-quality research papers on aircraft communication systems. Electric-powered aircraft have been a hot topic in the modern aircraft world. Electric aircraft have supremacy over their conventional counterparts. Due to increased drone taxi and urban air mobility, fast and reliable communication is very important, so concepts of Broadband Integrated Digital Avionics Information Exchange Networks (B-IDAIENs) and Modular Avionics are being researched for better communication of future aircraft. A Ku-band phased array antenna based on a modular design can be used in a modular avionics system. Furthermore, integrated avionics is also emerging research in future avionics. The main focus of work in future avionics will be using integrated modular avionics and infra-red phased array antennas, which are discussed in detail in this paper. Other work such as reconfigurable antennas and optical communication, are also discussed in this paper. The future of modern aircraft avionics would be based on integrated modulated avionics and small artificial intelligence-based antennas. Optical and infrared communication will also replace microwave frequencies.

Keywords: AI, avionics systems, communication, electric aircrafts, infra-red, integrated avionics, modular avionics, phased array, reconfigurable antenna, UAVs

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Authors: Mustafa Metin Donma, Orkide Donma

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Childhood obesity is an important clinical problem because it may lead to chronic diseases during the adulthood period of the individual. Obesity is a metabolic disease associated with low-grade inflammation. The liver occurs at the center of metabolic pathways. Adropin, fibroblast growth factor-21 (FGF-21), and fetuin-A are hepatokines. Due to the immense participation of the liver in glucose metabolism, these liver-derived factors may be associated with insulin resistance (IR), which is a phenomenon discussed within the scope of obesity problems. The aim of this study is to determine the concentrations of adropin, FGF-21, and fetuin-A in childhood obesity, to point out possible differences between the obesity groups, and to investigate possible associations among these three hepatokines in obese and morbidly obese children. A total of one hundred and thirty-two children were included in the study. Two obese groups were constituted. The groups were matched in terms of mean ± SD values of ages. Body mass index values of obese and morbidly obese groups were 25.0 ± 3.5 kg/m² and 29.8 ± 5.7 kg/m², respectively. Anthropometric measurements including waist circumference, hip circumference, head circumference, and neck circumference were recorded. Informed consent forms were taken from the parents of the participants. The ethics committee of the institution approved the study protocol. Blood samples were obtained after overnight fasting. Routine biochemical tests, including glucose- and lipid-related parameters, were performed. Concentrations of the hepatokines (adropin, FGF-21, fetuin A) were determined by enzyme-linked immunosorbent assay. Insulin resistance indices such as homeostasis model assessment for IR (HOMA-IR), alanine transaminase-to aspartate transaminase ratio (ALT/AST), diagnostic obesity notation model assessment laboratory index, diagnostic obesity notation model assessment metabolic syndrome index as well as obesity indices such as diagnostic obesity notation model assessment-II index, and fat mass index were calculated using the previously derived formulas. Statistical evaluation of the study data as well as findings of the study was performed by SPSS for Windows. Statistical difference was accepted significant when p is smaller than 0.05. Statistically significant differences were found for insulin, triglyceride, high-density lipoprotein cholesterol levels of the groups. A significant increase was observed for FGF-21 concentrations in the morbidly obese group. Higher adropin and fetuin-A concentrations were observed in the same group in comparison with the values detected in the obese group (p > 0.05). There was no statistically significant difference between the ALT/AST values of the groups. In all of the remaining IR and obesity indices, significantly increased values were calculated for morbidly obese children. Significant correlations were detected between HOMA-IR and each of the hepatokines. The highest one was the association with fetuin-A (r=0.373, p=0.001). In conclusion, increased levels observed in adropin, FGF-21, and fetuin-A have shown that these hepatokines possess increasing potential going from obese to morbid obese state. Out of the correlations found with the IR index, the most affected hepatokine was fetuin-A, the parameter possibly used as the indicator of the advanced obesity stage.

Keywords: adropin, fetuin A, fibroblast growth factor-21, insulin resistance, pediatric obesity

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Authors: Magdi Elmessiry, Adel Elmessiry

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The fashion industry represents a significant portion of the global gross domestic product, however, it is plagued by cheap imitators that infringe on the trademarks which destroys the fashion industry's hard work and investment. While eventually the copycats would be found and stopped, the damage has already been done, sales are missed and direct and indirect jobs are lost. The infringer thrives on two main facts: the time it takes to discover them and the lack of tracking technologies that can help the consumer distinguish them. Blockchain technology is a new emerging technology that provides a distributed encrypted immutable and fault resistant ledger. Blockchain presents a ripe technology to resolve the infringement epidemic facing the fashion industry. The significance of the study is that a new approach leveraging the state of the art blockchain technology coupled with artificial intelligence is used to create a framework addressing the fashion infringement problem. It transforms the current focus on legal enforcement, which is difficult at best, to consumer awareness that is far more effective. The framework, Crypto CopyCat, creates an immutable digital asset representing the actual product to empower the customer with a near real time query system. This combination emphasizes the consumer's awareness and appreciation of the product's authenticity, while provides real time feedback to the producer regarding the fake replicas. The main findings of this study are that implementing this approach can delay the fake product penetration of the original product market, thus allowing the original product the time to take advantage of the market. The shift in the fake adoption results in reduced returns, which impedes the copycat market and moves the emphasis to the original product innovation.

Keywords: fashion, infringement, blockchain, artificial intelligence, textiles supply chain

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Authors: Dimpy Shah

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The global economy has substantially changed in last three decades. Now almost all markets are transparent and visible for global customers. The corporates are now no more reliant on local markets for trade. The information technology revolution has changed business dynamics and marketing practices of corporate. The markets are divided into two different formats: traditional and virtual. In very short span of time, many e-commerce portals have captured global market. This strategy is well supported by global delivery system of multinational logistic companies. Now the markets are dealing with global supply chain networks, which are more demand driven and customer oriented. The corporate have realized importance of supply chain integration and marketing in this competitive environment. The Indian markets are also significantly affected with all these changes. In terms of population, India is in second place after China. In terms of demography, almost half of the population is of youth. It has been observed that the Indian youth are more inclined towards e-commerce and prefer to buy goods from web portal. Initially, this trend was observed in Indian service sector, textile and electronic goods and now further extended in other product categories. The FMCG companies have also recognized this change and started integration of their supply chain with e-commerce platform. This paper attempts to understand contemporary marketing practices of corporate in e-commerce business in Indian food and beverages segment and also tries to identify innovative marketing practices for proper execution of their strategies. The findings are mainly focused on supply chain re-integration and brand building strategies with proper utilization of social media.

Keywords: FMCG (Fast Moving Consumer Goods), ISCM (Integrated supply chain management), RFID (Radio Frequency Identification), traditional and virtual formats

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Authors: Bitopi Dutta

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Development Induced Displacement (DID) of subaltern groups has been an issue of intense debate in India. This research will do a gender analysis of displacement induced by the mining projects in tribal indigenous societies of North East India, centering on the primary research question which is 'How does DID reorder gendered relationship in tribal matrilineal societies?' This paper will not focus primarily on the impacts of the displacement induced by coal mining on indigenous tribal women in the North East India; it will rather study 'what' are the processes that lead to these transformations and 'how' do they operate. In doing so, the paper will locate the cracks in traditional social systems that the discourse of displacement manipulates for its own benefit. DID in this sense will not only be understood as only physical displacement, but also as social and cultural displacement. The study will cover one matrilineal tribe in the state of Meghalaya in the North East India affected by several coal mining projects in the last 30 years. In-depth unstructured interviews used to collect life narratives will be the primary mode of data collection because the indigenous culture of the tribes in Meghalaya, including the matrilineal tribes, is based on oral history where knowledge and experiences produced under a tradition of oral history exist in a continuum. This is unlike modern societies which produce knowledge in a compartmentalized system. An interview guide designed around specific themes will be used rather than specific questions to ensure the flow of narratives from the interviewee. In addition to this, a number of focus groups will be held. The data collected through the life narrative will be supplemented and contextualized through documentary research using government data, and local media sources of the region.

Keywords: displacement, gender-relations, matriliny, mining

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Authors: K. Vrinda

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Coastal ecosystems across the world are facing a lot of challenges due to natural phenomena as well as from uncontrolled human interventions. Here, Alappad, a coastal island situated in Kerala, India is undergoing significant damage and is gradually losing its environmental and social sustainability. The area is blessed with very rare and precious black mineral sand deposits. Sand mining for these minerals started in 1911 and is still continuing. But, unfortunately all the problems that Alappad faces now, have its root on mining of this mineral sand. The land area is continuously diminishing due to sea erosion. The mining has also caused displacement of people and environmental degradation. Marine life also is getting affected by mining on beach and pollution. The inhabitants are fishermen who are largely dependent on the eco-system for a living. So loss of environmental sustainability subsequently affects social sustainability too. Now the damage has reached a point beyond which our actions may not be able to make any impact. This was one of the most affected areas of the 2004 tsunami and the environmental degradation has further increased the vulnerability. So this study focuses on understanding the concerns related to the resource utilization, environment and the indigenous community staying there, and on formulating suitable strategies to restore the sustainability of the area. An extensive study was conducted on site, to find out the physical, social, and economical characteristics of the area. A focus group discussion with the inhabitants shed light on different issues they face in their day-to-day life. The analysis of all these data, led to the formation of a new development vision for the area which focuses on environmental restoration and socio-economic development while allowing controlled exploitation of resources. A participatory approach is formulated which enables these three aspects through community based programs.

Keywords: Community development, Disaster resilience, Ecological restoration, Environmental sustainability, Social-environmental planning, Social Sustainability

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Authors: Hachaichi Mohamed Nour El-Islem, Baouni Tahar

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Environmental sustainability rather than a trans-disciplinary and a scientific issue, is the main problem that characterizes all modern cities nowadays. In developing countries, this concern is expressed in a plethora of critical urban ills: traffic congestion, air pollution, noise, urban decay, increase in energy consumption and CO₂ emissions which blemish cities’ landscape and might threaten citizens’ health and welfare. As in the same manner as developing world cities, the rapid growth of Algiers’ human population and increasing in city scale phenomena lead eventually to increase in daily trips, energy consumption and CO₂ emissions. In addition, the lack of proper and sustainable planning of the city’s infrastructure is one of the most relevant issues from which Algiers suffers. The aim of this contribution is to estimate the carbon deficit of the City of Algiers, Algeria, using the Ecological Footprint Model (carbon footprint). In order to achieve this goal, the amount of CO₂ from fuel combustion has been calculated and aggregated into five sectors (agriculture, industry, residential, tertiary and transportation); as well, Algiers’ biocapacity (CO₂ uptake land) has been calculated to determine the ecological overshoot. This study shows that Algiers’ transport system is not sustainable and is generating more than 50% of Algiers total carbon footprint which cannot be sequestered by the local forest land. The aim of this research is to show that the Carbon Footprint Assessment might be a relevant indicator to design sustainable strategies/policies striving to reduce CO₂ by setting in motion the energy consumption in the transportation sector and reducing the use of fossil fuels as the main energy input.

Keywords: biocapacity, carbon footprint, ecological footprint assessment, energy consumption

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Authors: Abdullah Al Mohiuddin

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Bangladesh is one of the poorest countries in the world, and ranks low on almost all measures of economic development, thus leaving the population extremely vulnerable to natural disasters and climate events. 20% of GDP come from agriculture but more than 60% of the population relies on agriculture as their main source of income making the entire economy vulnerable to climate change and natural disasters. High population density exacerbates the exposure to and effect of climate events, and increases the levels of vulnerability, as does the poor institutional development of the country. The most vulnerable sectors to climate change impacts in Bangladesh are agriculture, coastal zones, water resources, forestry, fishery, health, biomass, and energy. High temperatures, heavy rainfall, high humidity and fairly marked seasonal variations characterize the climate in Bangladesh: Mild winter, hot humid summer and humid, warm rainy monsoon. Much of the country is flooded during the summer monsoon. The Department of Environment (DOE) under the Ministry of Environment and Forestry (MoEF) is the focal point for the United Nations Framework Convention on Climate Change (UNFCCC) and coordinates climate related activities in the country. Recently, a Climate Change Cell (CCC) has been established to address several issues including adaptation to climate change. The climate change focus started with The National Environmental Management Action Plan (NEMAP) which was prepared in 1995 in order to initiate the process to address environmental and climate change issues as long-term environmental problems for Bangladesh. Bangladesh was one of the first countries to finalise a NAPA (Preparation of a National Adaptation Plan of Action) which addresses climate change issues. The NAPA was completed in 2005, and is the first official initiative for mainstreaming adaptation to national policies and actions to cope with climate change and vulnerability. The NAPA suggests a number of adaptation strategies, for example: - Providing drinking water to coastal communities to fight the enhanced salinity caused by sea level rise, - Integrating climate change in planning and design of infrastructure, - Including climate change issues in education, - Supporting adaptation of agricultural systems to new weather extremes, - Mainstreaming CCA into policies and programmes in different sectors, e.g. disaster management, water and health, - Dissemination of CCA information and awareness raising on enhanced climate disasters, especially in vulnerable communities. Bangladesh has geared up its environment conservation steps to save the world’s poorest countries from the adverse effects of global warming. Now it is turning towards green economy policies to save the degrading ecosystem. Bangladesh is a developing country and always fights against Natural Disaster. At the same time we also fight for establishing ecological environment through promoting Green Economy/Energy by Youth Networking. ANTAR is coordinating a big Youth Network in the southern part of Bangladesh where 30 Youth group involved. It can be explained as the economic development based on sustainable development which generates growth and improvement in human’s lives while significantly reducing environmental risks and ecological scarcities. Green economy in Bangladesh promotes three bottom lines – sustaining economic, environment and social well-being.

Keywords: resilience, networking, mobilizing, resource

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Authors: Lauren B. Birney

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The project utilizes the Billion Oyster Project (BOP-CCERS) place-based “restoration through education” model to promote computational thinking in NYC high school teachers and their students. Key learning standards such as Next Generation Science Standards and the NYC CS4All Equity and Excellence initiative are used to develop a computer science curriculum that connects students to their Harbor through hands-on activities based on BOP field science and educational programming. Project curriculum development is grounded in BOP-CCERS restoration science activities and data collection, which are enacted by students and educators at two Restoration Science STEM Hubs or conveyed through virtual materials. New York City Public School teachers with relevant experience are recruited as consultants to provide curriculum assessment and design feedback. The completed curriculum units are then conveyed to NYC high school teachers through professional learning events held at the Pace University campus and led by BOP educators. In addition, Pace University educators execute the Summer STEM Institute, an intensive two-week computational thinking camp centered on applying data analysis tools and methods to BOP-CCERS data. Both qualitative and quantitative analyses were performed throughout the five-year study. STEM+C – Community Based Restoration STEM Hubs. STEM Hubs are active scientific restoration sites capable of hosting school and community groups of all grade levels and professional scientists and researchers conducting long-term restoration ecology research. The STEM Hubs program has grown to include 14 STEM Hubs across all five boroughs of New York City and focuses on bringing in-field monitoring experience as well as coastal classroom experience to students. Restoration Science STEM Hubs activities resulted in: the recruitment of 11 public schools, 6 community groups, 12 teachers, and over 120 students receiving exposure to BOP activities. Field science protocols were designed exclusively around the use of the Oyster Restoration Station (ORS), a small-scale in situ experimental platforms which are suspended from a dock or pier. The ORS is intended to be used and “owned” by an individual school, teacher, class, or group of students, whereas the STEM Hub is explicitly designed as a collaborative space for large-scale community-driven restoration work and in-situ experiments. The ORS is also an essential tool in gathering Harbor data from disparate locations and instilling ownership of the research process amongst students. As such, it will continue to be used in that way. New and previously participating students will continue to deploy and monitor their own ORS, uploading data to the digital platform and conducting analysis of their own harbor-wide datasets. Programming the STEM Hub will necessitate establishing working relationships between schools and local research institutions. NYHF will provide introductions and the facilitation of initial workshops in school classrooms. However, once a particular STEM Hub has been established as a space for collaboration, each partner group, school, university, or CBO will schedule its own events at the site using the digital platform’s scheduling and registration tool. Monitoring of research collaborations will be accomplished through the platform’s research publication tool and has thus far provided valuable information on the projects’ trajectory, strategic plan, and pathway.

Keywords: environmental science, citizen science, STEM, technology

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Authors: Akanimo Emene, Robert Edyvean

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In developing countries, a low cost method of wastewater treatment is highly recommended. Adsorption is an efficient and economically viable treatment process for wastewater. The utilisation of this process is based on the understanding of the relationship between the growth environment and the metal capacity of the biomaterial. Luffa cylindrica (LC), a plant material, was used as an adsorbent in adsorption design system of heavy metals. The chemically modified LC was used to adsorb heavy metals ions, lead and cadmium, from aqueous environmental solution at varying experimental conditions. Experimental factors, adsorption time, initial metal ion concentration, ionic strength and pH of solution were studied. The chemical nature and surface area of the tissues adsorbing heavy metals in LC biosorption systems were characterised by using electron microscopy and infra-red spectroscopy. It showed an increase in the surface area and improved adhesion capacity after chemical treatment. Metal speciation of the metal ions showed the binary interaction between the ions and the LC surface as the pH increases. Maximum adsorption was shown between pH 5 and pH 6. The ionic strength of the metal ion solution has an effect on the adsorption capacity based on the surface charge and the availability of the adsorption sites on the LC. The nature of the metal-surface complexes formed as a result of the experimental data were analysed with kinetic and isotherm models. The pseudo second order kinetic model and the two-site Langmuir isotherm model showed the best fit. Through the understanding of this process, there will be an opportunity to provide an alternative method for water purification. This will be provide an option, for when expensive water treatment technologies are not viable in developing countries.

Keywords: adsorption, luffa cylindrica, metal-surface complexes, pH

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Authors: Okuyade Ighoroje Wilson Ata

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Magneto-hydrodynamic mixed convective chemically reacting fluid flow through two parallel vertical plates channel with Hall, radiation, and chemical reaction effects are examined. The fluid is assumed to be chemically reactive, electrically conducting, magnetically susceptible, viscous, incompressible, and Newtonian; the plates are porous, electrically conductive, and heated to a high-temperature regime to generate thermal rays. The flow system is highly interactive, such that cross/double diffusion is present. The governing equations are partial differential equations transformed into ordinary differential equations using similarity transformation and solved by the method of Homotopy Perturbation. Expressions for the concentration, temperature, velocity, Nusselt number, Sherwood number, and Wall shear stress are obtained, computed, and presented graphically and tabularly. The analysis of results shows, amongst others, that an increase in the Raleigh number increases the main velocity and temperature but decreases the concentration. More so, an increase in chemical reaction rate increases the main velocity, temperature, rate of heat transfer from the terminal plate, the rate of mass transfer from the induced plate, and Wall shear stress on both the induced and terminal plates, decreasing the concentration, and the mass transfer rate from the terminal plate. Some of the obtained results are benchmarked with those of existing literature and are in consonance.

Keywords: chemical reaction, hall effect, magneto-hydrodynamic, radiation, vertical plates channel

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Authors: Ruphi Naz, Altaf Ahmad, Mohammad Anis

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Sialic acid (5-Acetylneuraminic acid, Neu5Ac) is a common sugar found as a terminal residue on glycoconjugates in many animals. Humans brain and the central nervous system contain the highest concentration of sialic acid (as N-acetylneuraminic acid) where these acids play an important role in neural transmission and ganglioside structure in synaptogenesis. Due to its important biological function, sialic acid is attracting increasing attention. To understand metabolic networks, fluxes and regulation, it is essential to be able to determine the cellular and subcellular levels of metabolites. Genetically-encoded fluorescence resonance energy transfer (FRET) sensors represent a promising technology for measuring metabolite levels and corresponding rate changes in live cells. Taking this, we developed a genetically encoded FRET (fluorescence resonance energy transfer) based nanosensor to analyse the sialic acid level in living cells. Sialic acid periplasmic binding protein (sia P) from Haemophilus influenzae was taken and ligated between the FRET pair, the cyan fluorescent protein (eCFP) and Venus. The chimeric sensor protein was expressed in E. coli BL21 (DE3) and purified by affinity chromatography. Conformational changes in the binding protein clearly confirmed the changes in FRET efficiency. So any change in the concentration of sialic acid is associated with the change in FRET ratio. This sensor is very specific to sialic acid and found stable with the different range of pH. This nanosensor successfully reported the intracellular level of sialic acid in bacterial cell. The data suggest that the nanosensors may be a versatile tool for studying the in vivo dynamics of sialic acid level non-invasively in living cells

Keywords: nanosensor, FRET, Haemophilus influenzae, metabolic networks

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Authors: Sumayya S.

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Making cities adaptive and inclusive is one among the inherent goal and challenge for contemporary cities. This is a serious concern when the urban transformations occur in varying magnitude due to visible and invisible factors. One type of visibly invisible factor is ecommerce and its expanding operation that is understood to cause changes to the conventional spatial structure positively and negatively. With the continued growth in e-commerce activities and its future potential, market analysts, media, and even retailers have questioned the importance of a future presence of traditional Brick-and-mortar stores in cities as a critical element, with some even referring to the repeated announcement of the closure of some store chains as the end of the online shopping era. Essentially this raises the question of how adaptive and inclusive the cities are to the dynamics of transformative changes that are often unseen. People have become more comfortable with seating inside and door delivery systems, and this increased change in usage of public spaces, especially the commercial corridors. Through this research helped in presetting a new approach for planning and designing commercial activities centers and also presents the impact of ecommerce on the urban fabric, such as division and fragmentation of space, showroom syndrome, reconceptualization of space, etc., in a critical way. The changes are understood by analyzing the e-commerce logistic process. Based on the inferences reach at the conclusion for the need of an integrated approach in the field of planning and designing of public spaces for the sustainable omnichannel retailing. This study was carried out with the following objectives Monitoring the impact of e commerce on the traditional shopping space. Explore the new challenges and opportunities faced by the urban form. Explore how adaptive and inclusive our cities are to the dynamics of transformative changes caused by ecommerce.

Keywords: E-commerce, shopping streets, online environment, offline environment, shopping factors

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Authors: Gaurav Bhanjana, Ganga Ram Chaudhary, Sandeep Kumar, Neeraj Dilbaghi

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Main sources of endocrine disrupting compounds in the ecosystem are hormones, pesticides, phthalates, flame retardants, dioxins, personal-care products, coplanar polychlorinated biphenyls (PCBs), bisphenol A, and parabens. These endocrine disrupting compounds are responsible for learning disabilities, brain development problems, deformations of the body, cancer, reproductive abnormalities in females and decreased sperm count in human males. Although discharge of these chemical compounds into the environment cannot be stopped, yet their amount can be retarded through proper evaluation and detection techniques. The available techniques for determination of these endocrine disrupting compounds mainly include high performance liquid chromatography (HPLC), mass spectroscopy (MS) and gas chromatography-mass spectrometry (GC–MS). These techniques are accurate and reliable but have certain limitations like need of skilled personnel, time consuming, interference and requirement of pretreatment steps. Moreover, these techniques are laboratory bound and sample is required in large amount for analysis. In view of above facts, new methods for detection of endocrine disrupting compounds should be devised that promise high specificity, ultra sensitivity, cost effective, efficient and easy-to-operate procedure. Nowadays, electrochemical sensors/biosensors modified with nanomaterials are gaining high attention among researchers. Bioelement present in this system makes the developed sensors selective towards analyte of interest. Nanomaterials provide large surface area, high electron communication feature, enhanced catalytic activity and possibilities of chemical modifications. In most of the cases, nanomaterials also serve as an electron mediator or electrocatalyst for some analytes.

Keywords: electrochemical, endocrine disruptors, microscopy, nanoparticles, sensors

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

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Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: damage level monitoring, drift ratio, fragility curve, smart grid, transmission tower

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Authors: Yi Yang, Jiasong Sun

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Almost every aspect of our daily lives is now intertwined with some degree of human-computer interaction (HCI). HCI courses draw on knowledge from disciplines as diverse as computer science, psychology, design principles, anthropology, and more. Our HCI courses, named the Media and Cognition course, are constantly updated to reflect state-of-the-art technological advancements such as virtual reality, augmented reality, and artificial intelligence-based interactions. For more than a decade, our course has used an interest-based approach to teaching, in which students proactively propose some research-based questions and collaborate with teachers, using course knowledge to explore potential solutions. Semantic communication plays a key role in facilitating understanding and interaction between users and computer systems, ultimately enhancing system usability and user experience. The advancements in AI-generated technology, which have gained significant attention from both academia and industry in recent years, are exemplified by language models like GPT-3 that generate human-like dialogues from given prompts. Our latest version of the Human-Computer Interaction course practices a semantic communication platform based on AI-generated techniques. The purpose of this semantic communication is twofold: to extract and transmit task-specific information while ensuring efficient end-to-end communication with minimal latency. An AI-generated semantic communication platform evaluates the retention of signal sources and converts low-retain ability visual signals into textual prompts. These data are transmitted through AI-generated techniques and reconstructed at the receiving end; on the other hand, visual signals with a high retain ability rate are compressed and transmitted according to their respective regions. The platform and associated research are a testament to our students' growing ability to independently investigate state-of-the-art technologies.

Keywords: human-computer interaction, media and cognition course, semantic communication, retainability, prompts

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Authors: Nindyo Cahyo Kresnanto, Muhamad Willdan, Wika Harisa Putri

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Gunungkidul is one of the emerging tourism industry areas in Yogyakarta Province, Indonesia. This article describes how GIS can predict the development of tourism potential in Gunungkidul. The tourism sector in Gunungkidul Regency contributes 3.34% of the total gross regional domestic product and is the economic sector with the highest growth with a percentage of 18.37% in the post-Covid-19 period. This contribution makes researchers consider that several tourist sites need to be explored more to increase regional economic development gradually. This research starts by collecting spatial data from tourist locations tourists want to visit in Gunungkidul Regency based on survey data from 571 respondents. Then the data is visualized with ArcGIS software. This research shows an overview of tourist destinations interested in travellers depicted from the lowest to the highest from the data visualization. Based on the data visualization results, specific tourist locations potentially developed to influence the surrounding economy positively. The visualization of the data displayed is also in the form of a desire line map that shows tourist travel patterns from the origin of the tourist to the destination of the tourist location of interest. From the desire line, the prediction of the path of tourist sites with a high frequency of transportation activity can figure out. Predictions regarding specific tourist location routes that high transportation activities can burden can consider which routes will be chosen. The route also needs to be improved in terms of capacity and quality. The goal is to provide a sense of security and comfort for tourists who drive and positively impact the tourist sites traversed by the route.

Keywords: tourism development, GIS and survey, transportation, potential desire line

Procedia PDF Downloads 66