Search results for: advanced glycation end-products

Authors: Seval Yilmaz, Filiz Bayrakci Karel, Ali Savas Koparal

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Textile products produced by leather have been indispensable for human consumption. Various chemicals are used to enhance the durability of end-products in the processing of leather products. The wastewaters from the leather industry which contain these chemicals exhibit toxic effects on the receiving environment and threaten the natural ecosystem. In this study, leather industry wastewater (LIW), which has high loads of contaminants, was treated using advanced treatment techniques instead of conventional methods. During the experiments, the performance of electrochemical methods was investigated. During the electrochemical experiments, the performance of batch electrooxidation (EO) using boron-doped diamond (BDD) electrodes with monopolar configuration for removal of chemical oxygen demand (COD) from LIW were investigated. The influences of electrolysis time, current density (which varies as 5 mA/cm², 10 mA/cm², 20 mA/cm², 30 mA/cm², 50 mA/cm²) and initial pH (which varies as 3,80 (natural pH of LIW), 7, 9) on removal efficiency were investigated in a batch stirred cell to determine the best treatment conditions. The current density applied to the electrochemical reactors is directly proportional to the consumption of electric energy, so electrical energy consumption was monitored during the experiment. The best experimental conditions obtained in electrochemical studies were as follows: electrolysis time = 60 min, current density = 30.0 mA/cm², pH 7. Using these parameters, 53.59% COD removal rates for LIW was achieved and total energy consumption was obtained as 13.03 kWh/m³. It is concluded that electrooxidation process constitutes a plausible and developable method for the treatment of LIW.

Keywords: BDD electrodes, COD removal, electrochemical treatment, leather industry wastewater

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Authors: Ashraf Osman

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Effective deployable bridges that are characterized by an increased capacity to weight ratio are recently needed for post-disaster rapid mobility and military operations. In deployable bridging, replacing metals as the fabricating material with advanced composite laminates as lighter alternatives with higher strength is highly advantageous. This article presents a hierarchical optimization strategy of a composite bridge treadway considering maximum strength design and bridge weight minimization. Shape optimization of a generic deployable bridge beam cross-section is performed to achieve better stress distribution over the bridge treadway hull. The developed cross-section weight is minimized up to reserving the margins of safety of the deployable bridging code provisions. Hence, the strength of composite bridge plates is maximized through varying the plies orientation. Different loading cases are considered of a tracked vehicle patch load. The orthotropic plate properties of a composite sandwich core are used to simulate the bridge deck structural behavior. Whereas, the failure analysis is conducted using Tsai-Wu failure criterion. The naturally inspired particle swarm optimization technique is used in this study. The proposed technique efficiently reduced the weight to capacity ratio of the developed bridge beam.

Keywords: CFRP deployable bridges, disaster relief, military bridging, optimization of composites, particle swarm optimization

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Authors: Elaid Bouchetob, Bouchra Nadji

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This research paper compares the efficiency and reliability (R(t)) of SiC-based and Si-based DC-DC buck converters in thin layer PV systems with an AI-based MPPT controller. Using Simplorer/Simulink simulations, the study assesses their performance under varying conditions. Results show that the SiC-based converter outperforms the Si-based one in efficiency and cost-effectiveness, especially in high temperature and low irradiance conditions. It also exhibits superior reliability, particularly at high temperature and voltage. Reliability calculation (R(t)) is analyzed to assess system performance over time. The SiC-based converter demonstrates better reliability, considering factors like component failure rates and system lifetime. The research focuses on the buck converter's role in charging a Lithium battery within the PV system. By combining the SiC-based converter and AI-based MPPT controller, higher charging efficiency, improved reliability, and cost-effectiveness are achieved. The SiC-based converter proves superior under challenging conditions, emphasizing its potential for optimizing PV system charging. These findings contribute insights into the efficiency, reliability, and reliability calculation of SiC-based and Si-based converters in PV systems. SiC technology's advantages, coupled with advanced control strategies, promote efficient and sustainable energy storage using Lithium batteries. The research supports PV system design and optimization for reliable renewable energy utilization.

Keywords: efficiency, reliability, artificial intelligence, sic device, thin layer, buck converter

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Authors: Muhammad Mohsin, Fawad Ahmad, Fatima Batool, Muhammad Kaab Zarrar

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The integration of the Internet of Things (IoT) and edge computing devices offers a transformative approach to electronic waste management, particularly in the dismantling of printed circuit boards (PCBs). This paper explores how these technologies optimize operational efficiency and improve environmental sustainability by addressing challenges such as data security, interoperability, scalability, and real-time data processing. Proposed solutions include advanced machine learning algorithms for predictive maintenance, robust encryption protocols, and scalable architectures that incorporate edge computing. Case studies from leading e-waste management facilities illustrate benefits such as improved material recovery efficiency, reduced environmental impact, improved worker safety, and optimized resource utilization. The findings highlight the potential of IoT and edge computing to revolutionize e-waste dismantling and make the case for a collaborative approach between policymakers, waste management professionals, and technology developers. This research provides important insights into the use of IoT and edge computing to make significant progress in the sustainable management of electronic waste

Keywords: internet of Things, edge computing, waste PCB disassembly, electronic waste management, data security, interoperability, machine learning, predictive maintenance, sustainable development

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Authors: Ping Bo, Meng Yunshan

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Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

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Authors: S. Bilal, S. A. Bhat, I. Hussain, J. D. Parrah, S. P. Ahmad, M. R. Mir

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Background: The wound healing involves a highly coordinated cascade of cellular and immunological response over a period including coagulation, inflammation, granulation tissue formation, epithelialization, collagen synthesis and tissue remodeling. Wounds in aged heal more slowly than those in younger, mainly because of comorbidities that occur as one age. The present study is about the influence of age on wound healing. 1x1cm^2 (100 mm) wounds were created on the back of the animal. The animals were divided into two groups; one group had animals in the age group of 3-9 months while another group had animals in the age group of 15-21 months. Materials and Methods: 24 clinically healthy rabbits in the age group of 3-21 months were used as experimental animals and divided into two groups viz A and B. All experimental parameters, i.e., Excision wound model, Measurement of wound area, Protein extraction and estimation, Protein extraction and estimation and DNA extraction and estimation were done by standard methods. Results: The parameters studied were wound contraction, hydroxyproline, glucosamine, protein, and DNA. A significant increase (p<0.005) in the hydroxyproline, glucosamine, protein and DNA and a significant decrease in wound area (p<0.005) was observed in the age group of 3-9 months when compared to animals of an age group of 15-21 months. Wound contraction together with hydroxyproline, glucosamine, protein and DNA estimations suggest that advanced age results in retarded wound healing. Conclusion: The decrease wound contraction and accumulation of hydroxyproline, glucosamine, protein and DNA in group B animals may be associated with the reduction or delay in growth factors because of the advancing age.

Keywords: age, wound healing, excision wound, hydroxyproline, glucosamine

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Authors: Diamantino Ribeiro, António Pedro Costa, Jorge Remondes

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Dubai and the UAE governments have been investing in technology and digital communication for a long time. These governments are pioneers in introducing innovative strategies, policies and projects. They are also recognized worldwide for defining and implementing long term public programs. In terms of eGovernment Dubai and the UAE rank among the world’s most advanced. Both governments have surprised the world a few years ago by creating a Happiness Ministry. This paper focuses on UAE’s government digital strategies and its approach to the next era. The main goal of this exploratory study is to understand the new era of eGovernment and transfer of the happiness and wellness programs. Data were collected from the corpus latente and analysis was anchored in qualitative methodology using content analysis and observation as analysis techniques. The study allowed to highlight that the 2020 government reshuffle has a strong focus on digital reorganisation and digital sustainability, one of the newest trends in sustainability. Regarding happiness and wellbeing portfolio, we were able to observe that there has been a major change within the government organisation: The Ministry of Happiness was extinct and the Ministry of Community Development will manage the so-called ‘Happiness Portfolio’. Additionally, our observation allowed to note the government dual approach to governance: one through digital transformation, thus enhancing the digital sustainability process and, the second one trough government development.

Keywords: ministry of happiness, eGovernment, communication, digital sustainability

Procedia PDF Downloads 143

Authors: Bachir Nora

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Integrating vegetation into urban environments is crucial for enhancing quality of life, particularly through microclimate regulation and the reduction of urban heat islands. This study investigates the impact of different street tree species on the urban microclimate in the El-Houria neighborhood of Mostaganem, Algeria, using the ENVI-met software for advanced environmental simulations. it focused on three tree species—Robinia pseudo-acacia, Populus alba, and Jacaranda mimosifolia—to evaluate their effectiveness in influencing key meteorological parameters, including air temperature, mean radiant temperature, surface temperature, and the predicted percentage of dissatisfied (PPD) thermal comfort index. Statistical analyses were conducted to compare these parameters across different tree species, ensuring the robustness of our findings. Our results indicate that Robinia pseudo-acacia is the most effective species, capable of reducing air temperature by up to 1°C and surface temperature by up to 12°C. These findings underscore the importance of strategically selecting tree species to mitigate the effects of climate change, improve thermal comfort, and reduce energy consumption in urban settings. The study offers valuable insights for urban planners and policymakers, providing practical guidance for sustainable urban design practices tailored to the Algerian context.

Keywords: heat islands, microclimate simulation, street tree alignment, sustainable urban design, thermal comfort.

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Authors: Chaya B. M., C. Dhanush, Inti Sai Srikar, Akula Pavan Parvatalu, Chirag Gowda R

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Recently, there has been a lot of interest in µ-LED technology because of its exceptional qualities, including auto emission, high visibility, low consumption of power, rapid response and longevity. Light-emitting diodes (LED) using III-nitride, such as lighting sources, visible light communication (VLC) devices, and high-power devices, are finding increasing use as miniaturization technology advances. The use of micro-LED displays in place of traditional display technologies like liquid crystal displays (LCDs) and organic light-emitting diodes (OLEDs) is one of the most prominent recent advances, which may even represent the next generation of displays. The development of fully integrated, multifunctional devices and the incorporation of extra capabilities into micro-LED displays, such as sensing, light detection, and solar cells, are the pillars of advanced technology. Due to the wide range of applications for micro-LED technology, the effectiveness and dependability of these devices in numerous harsh conditions are becoming increasingly important. Enough research has been conducted to overcome the under-effectiveness of micro-LED devices. In this paper, different Micro LED design structures are proposed in order to achieve optimized optical properties. In order to attain improved external quantum efficiency (EQE), devices' light extraction efficiency (LEE) has also been boosted.

Keywords: finite difference time domain, light out coupling efficiency, far field intensity, power density, quantum efficiency, flat panel displays

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Authors: Mennatallah M. Hussein, Olivier de Weck

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The advancement of space exploration demands a robust space launch services program capable of reliably propelling payloads into orbit. Despite rigorous testing and quality assurance, launch failures still occur, leading to significant financial losses and jeopardizing mission objectives. Traditional failure prediction methods often lack the sophistication to account for multi-mode failure scenarios, as well as the predictive capability in complex dynamic systems. Traditional approaches also rely on expert judgment, leading to variability in risk prioritization and mitigation strategies. Hence, there is a pressing need for robust approaches that enhance launch vehicle reliability from lift-off until it reaches its parking orbit through comprehensive simulation techniques. In this study, the developed model proposes a multi-mode launch vehicle simulation framework for predicting failure scenarios when incorporating new technologies, such as new propulsion systems or advanced staging separation mechanisms in the launch system. To this end, the model combined a 6-DOF system dynamics with comprehensive data analysis to simulate multiple failure modes impacting launch performance. The simulator utilizes high-fidelity physics-based simulations to capture the complex interactions between different subsystems and environmental conditions.

Keywords: launch vehicle, failure prediction, propulsion anomalies, rocket launch simulation, rocket dynamics

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Authors: Amauri Josafat Gomez Aguilar, Jean Pierre Kenné

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This research presents the development of a self-sustainable manufacturing system from a circular economy perspective, structured by a multi-stage serial production system consisting of a series of machines under deterioration in charge of producing a single product and a reverse remanufacturing system constituted by the same productive systems of the first scheme and different tooling, fed by-products collected at the end of their life cycle, and non-conforming elements of the first productive scheme. Since the advanced production manufacturing system is unable to satisfy the customer's quality expectations completely, we propose the development of a mixed integer linear mathematical model focused on the optimal search and assignment of quality stations and preventive maintenance operation to the machines over a time horizon, intending to segregate the correct number of non-conforming parts for reuse in the remanufacturing system and thereby minimizing production, quality, maintenance, and customer non-conformance penalties. Numerical experiments are performed to analyze the solutions found by the model under different scenarios. The results showed that the correct implementation of a closed manufacturing system and allocation of quality inspection and preventive maintenance operations generate better levels of customer satisfaction and an efficient manufacturing system.

Keywords: closed loop, mixed integer linear programming, preventive maintenance, quality inspection

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Authors: Yin Hua Zhang

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Cardiac metabolism is essential in myocardial contraction. In addition to glucose, fatty acids (FA) are essential in producing energy in the myocardium since FA-dependent beta-oxidation accounts for > 70-90% of cellular ATP under resting conditions. However, metabolism shifts from FAs to glucose utilization during disease progression (e.g. hypertrophy and ischemic myocardium), where glucose oxidation and glycolysis become the predominant sources of cellular ATP. At advanced failing stage, both glycolysis and beta-oxidation are dysregulated, result in insufficient supply of intracellular ATP and weakened myocardial contractility. Undeniably, our understandings of myocyte function in healthy and diseased hearts are based on glucose (10 mM)-dependent metabolism because glucose is the “sole” metabolic substrate in most of the physiological experiments. In view of the importance of FAs in cardiovascular health and diseases, we aimed to elucidate the impacts of FA supplementation on myocyte contractility and evaluate cellular mechanisms those mediate the functions in normal heart and with pathological stress. In particular, we have investigated cardiac excitation-contraction (E-C) coupling in the presence and absence of FAs in normal and hypertensive rat left ventricular (LV) myocytes. Our results reveal that FAs increase mitochondrial activity, intracellular [Ca²+]i, and LV myocyte contraction in healthy LV myocytes, whereas FA-dependent cardiac inotropyis attenuated in hypertension. FA-dependent myofilament Ca²+ desensitization could be fundamental in regulating [Ca²+]i. Collectively, FAs supplementation resets cardiac E-C coupling scheme in healthy and diseased hearts.

Keywords: hypertension, fatty acid, heart, calcium

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Authors: Jutamas Wisansing, Thanakarn Vongvisitsin, Udom Hongchatikul

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Designated Areas for Sustainable Tourism Administration (DASTA) is a public organization, dedicating to sustainable tourism development in 6 designated areas in Thailand. This paper provides rich reflections from a decade of DASTA, formulating an advanced model to deepen our understanding of 2 key intertwining issues; 1) what are the new landscapes of actors for community based tourism and 2) who are the benefactors and beneficiaries of tourism development within the community? An action research approach was used, enabling the process and evidence-based cases to be better captured. The aim is to build theoretical foundation through 13 communities/cases, which have engaged in community based tourism pilot projects. Drawing from emic and qualitative research, specific and contextual phenomenon provides succinct patterns of ‘Community Benefitting through Tourism (CbtT)’ model. The re-definition of the 2 key issues helps shape the interlinking of actors; practicalities of inclusive tourism and inter-sectoral framework and its value chain will also be set forth. In tourism sector, community members could be active primarily on the supply side as employees, entrepreneurs and local heritage experts. CbtT when well defined stimulates the entire value chain of local economy while promoting social innovation through positive dialogue with wider actors. Collaboration with a new set of actors who are from the tourism-related businesses and non-tourism related businesses create better impacts on mutual benefits.

Keywords: community based tourism, community benefitting through tourism -CbtT DASTA model, sustainable tourism in thailand, value chain and inclusive business

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Mustafa Avsever

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Throughout history, states have attached great importance to seas in terms of economic and security. Advanced civilizations have always founded in coastal regions. Over time, human being has tended to trade and naturally always aimed get more and more. Seas by covering 71% of the earth, provide the greatest economic opportunities for access to raw material resources and the world market. As a result, seas have become the most important areas of conflict over the course of time. Coastal states, use seas as a tool for defense zone, trade, marine transportation and power transfer, they have acquired colonies overseas and increased their capital, raw materials and labor. Societies, have increased their economic prosperity, though their navies in order to retain their welfare and achieve their foreign policy objectives. Sometimes they have imposed their demands through the use or threat of limited naval force in accordance with their interests that is gunboat diplomacy. Today we can see samples of gunboat diplomacy used in the Eastern Mediterranean, during Ukraine crisis, in dispute between North Korea and South Korea and the ongoing power struggle in Asia-Pacific. Gunboat diplomacy has been and continues to be applied consistently in solving problems by the stronger side of the problem. The purpose of this article is to examine using navy under the gunboat diplomacy as an active instrument of foreign policy and security policy and reveal the strategic sea areas in which gunboat diplomacy is used effectively in the matrix of international politics in the 21st century.

Keywords: gunboat diplomacy, maritime strategy, sea power, strategic sea lands

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Authors: Meilee Shen

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Buddhist monks and nuns have changed within the dynamic culture of Taiwan that they find themselves in. The diverse cultures, economic development, and advanced educational levels of the island are all part of this. Buddhist education has become an interesting aspect in the history of Taiwanese Buddhism. In recent years, Buddhists in Taiwan have made significant contributions to both academic and religious studies. This paper will focus on the following questions: What is Buddhist education? How does a Buddhist education change monastic role in Taiwanese Buddhism? Finally, how has Buddhist education benefited Taiwanese society? Research indicates that Buddhist education in Taiwan possesses four features: 1. Master teaching disciple: Buddhist masters teach monastic rules to monastic disciples only. 2. Monastic education: It is mainly focused on Buddhist doctrines and sangha rules. 3. From Buddhist education to secular education: Buddhist studies were introduced into secular educational environments that were the beginning for outsiders to study Buddhism. It also opened a door to recruit young college students to enter the monastery. 4. Academic Buddhist training: Buddhist monks and nuns have begun to study at secular colleges in various programs besides Buddhist studies. In recent years, Buddhist colleges and secular universities’ religious studies programs have begun to admit overseas students due to the low birth-rate in Taiwan. Therefore, the relationship between Buddhism and Taiwanese society is dynamic.

Keywords: Buddhist college and university in Taiwan, Buddhist education, institutionalization in Taiwanese Buddhism, monastic and secular education, Taiwanese Buddhist monks and nuns

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Authors: Kais Nasser, Ronit Levine-Schnur

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Due to the prolonged negligence of planning institutions, a large portion of Palestinian localities in Israel lack basic infrastructure, development, and urbanism and suffer from a severe shortage of housing. In the past years, planning institutions in Israel began to promote master planning for Palestinian localities and for new neighborhoods. Land readjustment plans (PLIs) were the primary planning mechanism. According to Israel’s planning institutions, readjustment plans aimed to afford housing and to ensure that new neighborhoods enjoy developed infrastructure, modern construction, public lands and urbanism. However, a wide group of Palestinian landowners and stakeholders opposed PLIs. This article exposes the reasons behind such objections. Methodology: The research carried out an in-depth analysis of approximately 1,780 objections to PLIs that have been advanced in recent years. These objections reveal what really concerns landowners, what they defend indeed, and how planning institutions dealt with their arguments. Initial Findings: Exploring the objections submitted by landowners to readjustment plans reveals a conceptual and cultural conflict between landowners and the planning institutions. While planning institutions believe that these plans can transform landowners and Arab society in general from a rural, local, and conservative life to a modern- urban life, the landowners believe that planning institutions strive to change their way of life and force them to adopt an urban life without giving much attention and respect to their tradition, habits and cultural way of life.

Keywords: land readjustment, culture, urbanization, minority

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Authors: Youngjae Jin, Daeshik Kim

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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: Chris Ogwu Attah, Okpanachi Linus Odiji

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An election is no doubt a universally accepted means of resolving societal problems, particularly those with political connotations. While the process has often been conducted in advanced democracies without attacks on opponents and the populace, that ambiance of political tranquillity has hardly been enjoyed in many African states. While the violent nature of polls on this part of the globe have for long been linked among other things to monetization and the zero-sum character of politics, emerging trends show how the increasing rate of electoral violence may not be unconnected to the broadcasts of violent acts in the media. Anchored on the age-long complaints about the possible deleterious effects of mass media and Plato’s concern about the effects of plays on the youth, this study aims to interrogate the relationship between media and electoral violence in Nigeria using Kogi State as a case study. While the Social Cognitive Theory is adopted to guide the study to fruition, data was elicited primarily from a multi-stage sampling arrangement in which respondents from three purposively selected locations (Anyigba, Lokoja, and Okene) were randomly selected. Using chi-square to test the assumption that media violence catalyzes electoral violence in Kogi State, it was discovered among other revelations that electoral violence increases numerically with the depiction of violence in the media. As a recommendation, therefore, this paper advocate that Civil Society Organisations, as well as relevant governmental agencies, should carry out mass political education which aims at instilling political morals on the populace, especially the youths.

Keywords: electoral violence, media, media violence, violence

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Authors: Masahiro Miyaji

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When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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Authors: Amalka Nawarathna, Nirodha Fernando, Zaid Alwan

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Global carbon reduction is not merely a responsibility of environmentally advanced developed countries, but also a responsibility of developing countries regardless of their less impact on global carbon emissions. In recognition of that, Sri Lanka as a developing country has initiated promoting green building construction as one reduction strategy. However, notwithstanding the increasing attention on Embodied Carbon (EC) reduction in the global building sector, they still mostly focus on Operational Carbon (OC) reduction (through improving operational energy). An adequate attention has not yet been given on EC estimation and reduction. Therefore, this study aims to identify the reasons for the slow uptake of EC estimation in the Sri Lankan building sector. To achieve this aim, 16 numbers of global barriers to estimate EC were identified through existing literature. They were then subjected to a pilot survey to identify the significant reasons for the slow uptake of EC estimation in the Sri Lankan building sector. A questionnaire with a three-point Likert scale was used to this end. The collected data were analysed using descriptive statistics. The findings revealed that 11 out of 16 challenges/ barriers are highly relevant as reasons for the slow uptake in estimating EC in buildings in Sri Lanka while the other five challenges/ barriers remain as moderately relevant reasons. Further, the findings revealed that there are no low relevant reasons. Eventually, the paper concluded that all the known reasons are significant to the Sri Lankan building sector and it is necessary to address them in order to upturn the attention on EC reduction.

Keywords: embodied carbon emissions, embodied carbon estimation, global carbon reduction, Sri Lankan building sector

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Authors: Alex Hughes

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Patients with advanced heart failure develop specific palliative care needs due to the progressive symptom burden and unpredictable disease trajectory. NICE guidance advises that palliative care should be provided to patients with both cancer and non-cancer conditions as and when required. However, there is some way to go before this guidance is consistently and effectively implemented nationwide in conditions such as heart failure. The Ambitions for Palliative and End of Life Care: A national framework for local action in England provides a set of foundations and ambitions which outline a vision for what high-quality palliative and end-of-life care look like in England. This poster aims to critically consider how to improve access to palliative care for heart failure patients in England by analysing the foundations taken from this framework to generate specific recommendations using Soft Systems Methodology (SSM). The eight foundations analysed are: ‘Personalised care planning’, ‘Shared records’, ‘Evidence and information’, ‘Involving, supporting and caring for those important to the dying Person’, ‘Education and training’, ‘24/7 access’, ‘Co-design’ and ‘Leadership.’ A number of specific recommendations have been generated which highlight a need to close the evidence-policy gap and implement policy with sufficient evidence. These recommendations, alongside the creation of an evidence-based national strategy for palliative care and heart failure, should improve access to palliative care for heart failure patients in England. Once implemented, it will be necessary to evaluate the effect of these proposals to understand if access to palliative care for heart failure patients actually improves.

Keywords: access, health systems, heart failure, palliative care

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Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

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This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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Authors: Tayebeh Norouzi

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This study aims to investigate the acquisition process of intonation. It examines the intonation structure of Tokyo Japanese and its realization by Iranian learners of Japanese. Seven Iranian learners of Japanese, differing in fluency, and two Japanese speakers participated in the experiment. Two sentences were used to test the phonological and phonetic characteristics of lexical pitch-accent as well as the intonation patterns produced by the speakers. Both sentences consisted of similar words with the same number of syllables and lexical pitch-accents but different syntactic structure. Speakers were asked to read each sentence three times at normal speed, and the data were analyzed by Praat. The results show that lexical pitch-accent, Accentual Phrase (AP) and AP boundary tone realization vary depending on sentence type. For sentences of type XdeYwo, the lexical pitch-accent is realized properly. However, there is a rise in AP boundary tone regardless of speakers’ level of fluency. In contrast, in sentences of type XnoYwo, the lexical pitch-accent and AP boundary tone vary depending on the speakers’ fluency level. Advanced speakers are better at grouping words into phrases and produce more native-like intonation patterns, though they are not able to realize downstep properly. The non-native speakers tried to realize proper intonation patterns by making changes in lexical accent and boundary tone.

Keywords: intonation, Iranian learners, Japanese prosody, lexical accent, second language acquisition.

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Authors: Rimzhim Gupta, Bhanupriya Boruah, Jayant M. Modak, Giridhar Madras

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Microbial contamination is one of the major concerns in the field of water treatment. AOP (advanced oxidation processes) is well-established method to resolve the issue of removal of contaminants in water. A Z-scheme composite g-C₃N₄/CuWO₄ was synthesized by sol-gel method for the photocatalytic inactivation of a mixed population of Gram-positive bacteria (S. aureus) and Gram-negative bacteria (E. coli). The photoinactivation was observed for different types of bacteria in the same medium together and individually in the absence of the nutrients. The lattice structures and phase purities were determined by X-ray diffraction. For morphological and topographical features, scanning electron microscopy and transmission electron microscopy analyses were carried out. The band edges of the semiconductor (valence band and conduction band) were determined by ultraviolet photoelectron microscopy. The lifetime of the charge carriers and band gap of the semiconductors were determined by time resolved florescence spectroscopy and diffused reflectance spectroscopy, respectively. The effect of weight ratio of C₃N₄ and CuWO₄ was observed by performing photocatalytic experiments. To investigate the exact mechanism and major responsible radicals for photocatalysis, scavenger studies were performed. The rate constants and order of the inactivation reactions were obtained by power law kinetics. For E. coli and S. aureus, the order of reaction and rate constants are 1.15, 0.9 and 1.39 ± 0.03 (CFU/mL)⁻⁰.¹⁵ h⁻¹, 47.95 ± 1.2 (CFU/mL)⁰.¹ h⁻¹, respectively.

Keywords: z-scheme, E. coli, S. aureus, sol-gel

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Authors: Neha Ahirwar

Abstract:

In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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Authors: Ali Haratian, Soroosh Emami Meybodi

Abstract:

Using viable microbial cultures within hydrocarbon reservoirs so as to the enhancement of oil recovery through metabolic activities is exactly what we recognize as microbial enhanced oil recovery (MEOR). In similar to many other processes in industries, there are some cons and pros following with MEOR. The creation of sulfides such as hydrogen sulfide as a result of injecting the sulfate-containing seawater into hydrocarbon reservoirs in order to maintain the required reservoir pressure leads to production and growth of sulfate reducing bacteria (SRB) approximately near the injection wells, turning the reservoir into sour; however, SRB is not considered as the only microbial process stimulating the formation of sulfides. Along with SRB, thermochemical sulfate reduction or thermal redox reaction (TSR) is also known to be highly effective at resulting in having extremely concentrated zones of ?2S in the reservoir fluids eligible to cause corrosion. Owing to extent of the topic, more information on the formation of ?₂S is going to be put finger on. Besides, confronting the undesirable production of sulfide species in the reservoirs can lead to serious operational, environmental, and financial problems, in particular the transporting pipelines. Consequently, conjuring up reservoir souring control strategies on the way production of oil and gas is the only way to prevent possible damages in terms of environment, finance, and manpower which requires determining the compound’s reactivity, origin, and partitioning behavior. This article is going to provide a comprehensive review of progress made in this field and the possible advent of new strategies in this technologically advanced world of the petroleum industry.

Keywords: corrosion, hydrogen sulfide, NRB, reservoir souring, SRB

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Authors: Lin Li, Farshad Amini

Abstract:

The flipped classroom has been introduced to promote collaborative learning and higher-order learning objectives. In contrast to the traditional classroom, the flipped classroom has students watch prerecorded lecture videos before coming to class and then “class becomes the place to work through problems, advance concepts, and engage in collaborative learning”. In this paper, the active flipped learning combines flipped classroom with active learning that is to establish an active flipped learning (AFL) model, aiming to promote active learning, stress deep learning, encourage student engagement and highlight data-driven personalized learning. Because students have watched the lecture prior to class, contact hours can be devoted to problem-solving and gain a deeper understanding of the subject matter. The instructor is able to provide students with a wide range of learner-centered opportunities in class for greater mentoring and collaboration, increasing the possibility to engage students. Currently, little is known about the extent to which AFL improves engineering students’ performance. This paper presents the preliminary study on the core course of sophomore students in Engineering Mechanics. A series of survey and interviews have been conducted to compare students’ learning engagement, empowerment, self-efficacy, and satisfaction with the AFL. It was found that the AFL model taking advantage of advanced technology is a convenient and professional avenue for engineering students to strengthen their academic confidence and self-efficacy in the Engineering Mechanics by actively participating in learning and fostering their deep understanding of engineering statics and dynamics

Keywords: active learning, engineering mechanics, flipped classroom, performance

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Authors: Ahmad Umar, Sheikh Akbar, Ahmed A. Ibrahim, Mohsen A. Alhamami

Abstract:

The development of advanced materials for energy storage and gas sensing applications has gained significant attention in recent years. In this study, we synthesized and characterized PANI@MnO2@rGO ternary nanocomposites (NCs) to explore their potential in supercapacitors and gas sensing devices. The ternary NCs were synthesized through a multi-step process involving the hydrothermal synthesis of MnO2 nanoparticles, preparation of PANI@rGO composites and the assembly to the ternary PANI@MnO2@rGO ternary NCs. The structural, morphological, and compositional characteristics of the materials were thoroughly analyzed using techniques such as XRD, FESEM, TEM, FTIR, and Raman spectroscopy. In the realm of gas sensing, the ternary NCs exhibited excellent performance as NH3 gas sensors. The optimized operating temperature of 100 °C yielded a peak response of 15.56 towards 50 ppm NH3. The nanocomposites demonstrated fast response and recovery times of 6 s and 10 s, respectively, and displayed remarkable selectivity for NH3 gas over other tested gases. For supercapacitor applications, the electrochemical performance of the ternary NCs was evaluated using cyclic voltammetry and galvanostatic charge-discharge techniques. The composites exhibited pseudocapacitive behavior, with the capacitance reaching up to 185 F/g at 1 A/g and excellent capacitance retention of approximately 88.54% over 4000 charge-discharge cycles. The unique combination of rGO, PANI, and MnO2 nanoparticles in these ternary NCs offer synergistic advantages, showcasing their potential to address challenges in energy storage and gas sensing technologies.

Keywords: paniI@mnO2@rGO ternary NCs, synergistic effects, supercapacitors, gas sensing, energy storage

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Authors: Theresa N. Uzor

Abstract:

The word cardiovascular fitness is a topic of much interest to people of Nigeria, especially during this time, some heart diseases run in families. Cardiovascular fitness is the ability of the heart and lungs to supply-rich blood to the working muscle tissues. This type of fitness is a health-related component of physical fitness that is brought about by sustained physical activity such as plyometric training. Plyometric is a form of advanced fitness training that uses fast muscular contractions to improve power and speed in the sports performance by coaches and athletes. Plyometric training involves a rapid stretching of muscle (eccentric phase) immediately followed by a concentric or shortening action of the same muscle and connective tissue. However, the most basic example of true plyometric training is running and can be safe for a wide variety of populations. This paper focused on building cardiovascular health through Plyometric Training. The centre focus of the article is cardiovascular fitness and plyometric training with factors of cardiovascular fitness. Plyometric training at any age provides multiple benefits even beyond weight control and weight loss, decrease the risk of cardiovascular diseases, stroke, high blood pressure, diabetes, and other diseases, among other benefits of plyometric training to cardiovascular fitness. Participation in plyometric training will increase metabolism of an individual, thereby burning more calories even when at rest and reduces weight is also among the benefits of plyometric training. Some guidelines were recommended for planning plyometric training programme to minimise the chance of injury. With plyometric training in Nigeria, fortune can change for good, especially now that there has been an increase in cardiovascular diseases within the society for great savings would be saved.

Keywords: aerobic, cardiovascular, concentric, stretch-shortening cycle, plyometric

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