Search results for: recent lake sediment

Authors: Ali Raouli, Amin Chegenizadeh, Hamid Nikraz

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The Perth metropolitan area and its surrounding regions have been expanding rapidly in recent decades and it is expected that this growth will continue in the years to come. With this rapid growth and the resulting increase in population, consideration should be given to strategic planning and modelling for the future expansion of Perth. The accurate estimation of projected traffic volumes has always been a major concern for the transport modelers and planners. Development of a reliable strategic transport model depends significantly on the inputs data into the model and the calibrated parameters of the model to reflect the existing situation. Trip distribution is the second step in four-step modelling (FSM) which is complex due to its behavioral nature. Gravity model is the most common method for trip distribution. The spatial separation between the Origin and Destination (OD) zones will be reflected in gravity model by applying deterrence functions which provide an opportunity to include people’s behavior in choosing their destinations based on distance, time and cost of their journeys. Deterrence functions play an important role for distribution of the trips within a study area and would simulate the trip distances and therefore should be calibrated for any particular strategic transport model to correctly reflect the trip behavior within the modelling area. This paper aims to review the most common deterrence functions and propose a calibrated deterrence function for work trips within the Perth Metropolitan Area based on the information obtained from the latest available Household data and Perth and Region Travel Survey (PARTS) data. As part of this study, a four-step transport model using EMME software has been developed for Perth Metropolitan Area to assist with the analysis and findings.

Keywords: deterrence function, four-step modelling, origin destination, transport model

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Authors: V. N. Chebotkevich, E. E. Schetinkina, V. V. Burylev, E. I. Kaytandzhan, N. P. Stizhak

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Objective: Blood stream infections (BSI) are severe, life-threatening illness for immuno compromised patients with hematological malignancies. We report the trend in blood-stream infections in this group of patients in the period 1991-2013. Methods: A total of 4742 blood samples investigated. All blood cultures were incubated in a continuous monitoring system for 7 days before discarding negative. On signaled positive, organism was identified by conventional methods. The Real-time polymerase chain reaction (PCR) was used for the indication of human herpes virus 6 (HHV-6), Cytomegalovirus (CMV) and Epstein-Barr virus (EBV). Results: Between 1991 and 2001 the incidence of Gram-positive bacteria (Staphylococcus epidermidis, Staphylococcus aureus) being the most common germs isolated (70,9%) were as Gram-negative rods (Escherichia coli, Klebsiella spp., Pseudomonas spp.) – 29,1%. In next decade 2002-2012 the number of Gram-negative bacteria was increased up to 40.2%. It is shown that the incidence of bacteremia was significantly more frequent at the background of detectable Cytomegalovirus and Epstein-Barr virus-specific DNA in blood. Over recent years, an increased frequency of micro mycetes was registered in blood of the patients with hematological malignancies (Candida spp. was predominant). Conclusion: Accurate and timely detection of BSI is important in determining appropriate treatment of infectious complications in patients with hematological malignancies. The isolation of Staphylococcus epidermidis from blood cultures remains a clinical dilemma for physicians and microbiologists. But in many cases this agent is of the clinical significance in immunocompromised patients with hematological malignancies. The role of CMV and EBV in development of bacteremia was demonstrated.

Keywords: infectious complications, blood stream infections, bacteremia, hemoblastosis

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Authors: Amin Nazifi, Amir Raki, Doga Istanbulluoglu

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The incorporation of technological advancements into financial services, commonly referred to as Fintech, is primarily aimed at promoting services that are accessible, convenient, and inclusive, thereby benefiting both consumers and businesses. Fintech services employ a variety of technologies, including Artificial Intelligence (AI), blockchain, and big data, to enhance the efficiency and productivity of traditional services. Cryptocurrency, a component of Fintech, is projected to be a trillion-dollar industry, with over 320 million consumers globally investing in various forms of cryptocurrencies. However, these potentially transformative services can also lead to adverse outcomes. For instance, recent Fintech innovations have been increasingly linked to misconduct and disservice, resulting in serious implications for consumer well-being. This could be attributed to the ease of access to Fintech, which enables adults to trade cryptocurrencies, shares, and stocks via mobile applications. However, there is little known about the darker aspects of technological advancements, such as Fintech. Hence, this study aims to generate scholarly insights into the design of robust and resilient Fintech services that can add value to businesses and enhance consumer well-being. Using a mixed-method approach, the study will investigate the personal and contextual factors influencing consumers’ adoption and usage of technology innovations and their impacts on consumer well-being. First, semi-structured interviews will be conducted with a sample of Fintech users until theoretical saturation is achieved. Subsequently, based on the findings of the first study, a quantitative study will be conducted to develop and empirically test the impacts of these factors on consumers’ well-being using an online survey with a sample of 300 participants experienced in using Fintech services. This study will contribute to the growing Transformative Service Research (TSR) literature by addressing the latest priorities in service research and shedding light on the impact of fintech services on consumer well-being.

Keywords: consumer well-being, financial literacy, Fintech, service innovation

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Authors: Siti Anis Nadia Abu Bakar, Vani Tanggamani

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Over recent years, the quality and environmental management practices are the necessary tasks in hospitality industry in order to provide high quality services, a comfortable and safe environment for occupants as well as innovative nature and shareholders' satisfaction, its environmental and social added value sustainable. Numerous studies have observed and measured quality management program (QMProg) and environmental management practices (EMPrac) independently. This paper analyzed the level of QMProg, and EMPrac in hospitality industry, particularly on hotel performance, specifically in the context of Malaysia as hotel industry in Malaysia has contributed tremendously to the development in the Malaysia tourism industry.The research objectives are; (1) to analyze how the level of QMProg influences on firm performance; (2) to investigate the level of EMPrac and its influence on firm performance. This paper contributes to the literature by providing added-value to the service industry strategic decision-making processes by helping to predict the varying impacts of positive and negative corporate social responsibility (CSR) activities on financial performance in their respective industries. Further, this paper also contributes to develop more applicable CSR strategies. As a matter of fact, the findings of this paper has contributed towards an integrated management system that will assist a firm in implementation of their environmental strategy by creating a higher level of accountability for environmental performance. The best results in environmental systems have instigated managers to explore more options when dealing with problems, especially problems involving the reputation of their hotel. In conclusion, the results of the study infer that the best CSR strategies of the quality and environmental management practices influences hotel performance.

Keywords: corporate social responsibility (CSR), environmental management practices (EMPrac), performance (PERF), quality management program (QMProg)

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Authors: Tabussam Tufail

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Purpose: The core purpose of the current review article is to elaborate the phytochemicals present in turnip (brassica rapus l.) and also allied health claims. Plant-based foods contain a significant amount of bioactive compounds which provide desirable health benefits beyond the basic nutrition. Epidemiological evidence suggests that consumption of a diet rich in vegetables and fruits has positive implications for human health. Design: Potential of turnip peroxidase (TP) for the treatment of phenolic-contaminated solutions has been reviewed. However, issues of taste along with behavioral nutrition ought to be considered. So in the last decades, special attention has been paid towards edible plants, especially those that are rich in secondary metabolites (frequently called phytochemicals) and nowadays, there is an increasing interest in the antioxidant activity of such phytochemicals present in the diet. These chemicals favor nutritional and phytotherapy that is emerging as new concepts of health aid in recent years. Turnip is rich in these valuable ingredients though it can be employed as having health promoting and healing properties. Findings: Numerous bioactive components i.e. organic acids, phenolic compounds, turnip peroxidase, kaempeferol, vitamin-K, etc. are present in turnip. The review focused on the significance of plant derived (especially turnip) phenolic compounds as a source of certain beneficial compounds for human health. Owing to the presence of bioactive moieties, the turnip has high antioxidant activity, positive role in blood clotting, effectual in phenobarbital-induced sleeping time, effective against hepatic injury in diabetics and also have a good hepatoprotective role. Strong recommendations for consumption of nutraceuticals from turnip have become progressively popular to improve health, and to prevent from diseases.

Keywords: phytochemicals, turnip, antioxidants, health benefits

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Authors: M. Wangai

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Following the promulgation of a new Constitution of Kenya in 2010, wide-ranging proposals for reform of the criminal justice system have been made. Proposed measures include a clear and separate system of dealing with juvenile offenders with a greater focus on rehabilitation and reintegration. As part of a broader constitutional transition, this article considers the contribution of restorative justice to reforming the youth justice system. The paper analyses Kenya’s juvenile justice legal framework measured against current international trends in youth justice. It identifies the first post-independence juvenile justice system as a remnant of the colonial period and notes that the post-2001 system is a marked improvement. More recent legal and institutional efforts to incorporate restorative justice are also examined. The paper advocates further development of the juvenile justice system by mainstreaming of restorative justice principles through national level legislative amendments. International and comparative perspectives are used to inform a diversion centered model of restorative justice. In addition, a case is made for the use of existing forms of alternative dispute resolution. Conscious of a tense political climate, the paper also proposes strategies to address challenges posed by a punitive penal environment, chiefly the linking of restorative justice to wider democratic goals and community spirit. The article concludes that restorative justice led juvenile justice reform will contribute to better treatment of young offenders under the criminal justice system and has the potential to set a new precedent for fair, sustainable and effective justice. Further, as part of far-reaching criminal justice reform, the proposed efforts may strengthen democratic progress in Kenya’s ensuing phase of political transition.

Keywords: constitutional transition, criminal justice, restorative justice, young offenders

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Authors: Tsuneyuki Namekata, Yoko Namekata

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It is known that the mean investment evolves from a very low initial value to some high level in the Continuous Prisoner's Dilemma. We examine how the cooperation level evolves from a low initial level to a high level in our Demographic Multi-level Donor-Recipient situation. In the Multi-level Donor-Recipient game, one player is selected as a Donor and the other as a Recipient randomly. The Donor has multiple cooperative moves and one defective move. A cooperative move means the Donor pays some cost for the Recipient to receive some benefit. The more cooperative move the Donor takes, the higher cost the Donor pays and the higher benefit the Recipient receives. The defective move has no effect on them. Two consecutive Multi-level Donor-Recipient games, one as a Donor and the other as a Recipient, can be viewed as a discrete version of the Continuous Prisoner's Dilemma. In the Demographic Multi-level Donor-Recipient game, players are initially distributed spatially. In each period, players play multiple Multi-level Donor-Recipient games against other players. He leaves offspring if possible and dies because of negative accumulated payoff of him or his lifespan. Cooperative moves are necessary for the survival of the whole population. There is only a low level of cooperative move besides the defective move initially available in strategies of players. A player may modify and expand his strategy by his recent experiences or practices. We distinguish several types of a player about modification and expansion. We show, by Agent-Based Simulation, that introducing only the modification increases the emergence rate of cooperation and introducing both the modification and the expansion further increases it and a high level of cooperation does emerge in our Demographic Multi-level Donor-Recipient Game.

Keywords: agent-based simulation, donor-recipient game, emergence of cooperation, spatial structure, TFT, TF2T

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Authors: Romeu Bonk Mesquita

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Argentina is the South American number 1 country of destiny to intraregional migration flows. This research aims to shed light on the main trends of the Argentine immigrant policy from 2016 on, when Mauricio Marci was elected President, taking the approval of the current and fairly protective of human rights Ley de Migraciones (2003) as an analytical starting point. Foreign Policy Analysis (FPA) serves as the theoretical background, highlighting decision-making processes and institutional designs that encourage or constraint political and social actors. The analysis goes through domestic and international levels, observing how immigration policy is formulated as a public policy and is simultaneously connected to Mercosur and other international organizations, such as the International Organization for Migration (IOM) and the United Nations High Commissioner for Refugees (UNHCR). Thus, the study revolves around the Direccion Nacional de Migraciones, which is the state agency in charge of executing the country’s immigrant policy, as to comprehend how its internal processes and the connections it has with both domestic and international institutions shape Argentina’s immigrant policy formulation and execution. Also, it aims to locate the migration agenda within the country’s contemporary social and political context. The methodology is qualitative, case-based and oriented by process-tracing techniques. Empirical evidence gathered includes official documents and data, media coverage and interviews to key-informants. Recent events, such as the Decreto de Necesidad y Urgencia 70/2017 issued by President Macri, and the return of discursive association between migration and criminality, indicate a trend of nationalization and securitization of the immigration policy in contemporary Argentina.

Keywords: Argentine foreign policy, human rights, immigrant policy, Mercosur

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Authors: Sylvester Akpah, Selasi Vondee

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Unmanned Aerial Vehicles (UAV) as they are also known, drones have attracted increasing attention in recent years due to their ubiquitous nature and boundless applications in the areas of communication, surveying, aerial photography, weather forecasting, medical delivery, surveillance amongst others. Operated remotely in real-time or pre-programmed, drones can fly autonomously or on pre-defined routes. The application of these aerial vehicles has successfully penetrated the world due to technological evolution, thus a lot more businesses are utilizing their capabilities. Unfortunately, while drones are replete with the benefits stated supra, they are riddled with some problems, mainly attributed to the complexities in learning how to master drone flights, collision avoidance and enterprise security. Additional challenges, such as the analysis of flight data recorded by sensors attached to the drone may take time and require expert help to analyse and understand. This paper presents an autonomous drone control system using a chatbot. The system allows for easy control of drones using conversations with the aid of Natural Language Processing, thus to reduce the workload needed to set up, deploy, control, and monitor drone flight missions. The results obtained at the end of the study revealed that the drone connected to the chatbot was able to initiate flight missions with just text and voice commands, enable conversation and give real-time feedback from data and requests made to the chatbot. The results further revealed that the system was able to process natural language and produced human-like conversational abilities using Artificial Intelligence (Natural Language Understanding). It is recommended that radio signal adapters be used instead of wireless connections thus to increase the range of communication with the aerial vehicle.

Keywords: artificial ntelligence, chatbot, natural language processing, unmanned aerial vehicle

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Authors: Saif Obaid Alkaabi, Nabil Ayad

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Governments constantly seek to offer faster, more secure, efficient and effective services for their citizens. Recent changes and developments to communication services and technologies, mainly due the Internet, have led to immense improvements in the way governments of advanced countries carry out their interior operations Therefore, advances in e-government services have been broadly adopted and used in various developed countries, as well as being adapted to developing countries. The implementation of advances depends on the utilization of the most innovative structures of data techniques, mainly in web dependent applications, to enhance the main functions of governments. These functions, in turn, have spread to mobile and wireless techniques, generating a new advanced direction called m-government. This paper discusses a selection of available m-government applications and several business modules and frameworks in various fields. Practically, the m-government models, techniques and methods have become the improved version of e-government. M-government offers the potential for applications which will work better, providing citizens with services utilizing mobile communication and data models incorporating several government entities. Developing countries can benefit greatly from this innovation due to the fact that a large percentage of their population is young and can adapt to new technology and to the fact that mobile computing devices are more affordable. The use of models of mobile transactions encourages effective participation through the use of mobile portals by businesses, various organizations, and individual citizens. Although the application of m-government has great potential, it does have major limitations. The limitations include: the implementation of wireless networks and relative communications, the encouragement of mobile diffusion, the administration of complicated tasks concerning the protection of security (including the ability to offer privacy for information), and the management of the legal issues concerning mobile applications and the utilization of services.

Keywords: e-government, m-government, system dependability, system security, trust

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Authors: Eman Elsebaie, A. Sedrak, R. Ziada

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Introduction: In the recent decades, heart failure (HF) has become one of the most prevalent cardio-vascular disease (CVDs), especially in the elderly and the main cause of hospitalization in Egypt cardiology departments. By 2030, the prevalence of HF is expected to increase by 25%. Total direct costs will increase to $818 billion, and the total indirect cost in terms of lost productivity is close to $275 billion. The current study was conducted to estimate the economic costs of services delivered for heart failure patients at the cardiology department in Cairo University Hospitals (CUHs). Aim: To gain an understanding of the cost of heart failure disease and its main drivers aiming to minimize associated health care costs. Subjects and Methods: Economic cost analysis study was conducted for a prospective group of all cases of HF admitted to the cardiology department in CUHs from end of March till end of April 2016 and another retrospective randomized sample from patients with HF, during the first 3 months of 2016 to measure estimated average cost per patient per day. Results: The mean age of the prospective group was 48.6 ± 17.16 years versus 52.3 ± 11.5 years for the retrospective group. The median (IQR) of Length of stay was 15 (15) days in the prospective group versus 9 (16) days in the retrospective group. The average HF inpatient cost/day in the cardiology department during April 2016 was 362.32 (255.5) L.E. versus 391.2(255.9) L.E. during January and February 2016. Conclusion: Up to 70% of expenditure in the management of HF is related to hospital admission. The average cost of such an admission was 5540.03 (IQR=7507.8) L.E. and 4687.4 (IQR=7818.8) L.E. with the average cost per day estimated at 362.32 (IQR=255.5) L.E. and 386.2(IQR=255.9) L.E. in prospective and retrospective groups respectively.

Keywords: health care cost, heart failure, hospitalization, inpatient

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Authors: Fatemeh Daneshvartarigh

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New technologies and applications have radically altered construction techniques in recent years. In order to anticipate how the building will act, perform, and appear, these technologies encompass a wide range of visualization, simulation, and analytic tools. These new technologies and applications have a considerable impact on completing construction projects in today's (architecture, engineering and construction)AEC industries. The rate of changes in BIM-related topics is different worldwide, and it depends on many factors, e.g., the national policies of each country. Therefore, there is a need for comprehensive research focused on a specific area with common characteristics. Therefore, one of the necessary measures to increase the use of this new approach is to examine the challenges and obstacles facing it. In this research, based on the Delphi method, at first, the background and related literature are reviewed. Then, using the knowledge obtained from the literature, a primary questionnaire is generated and filled by experts who are selected using snowball sampling. It covered the experts' attitudes towards implementing BIM in renovation projects and their view of the benefits and obstacles in this regard. By analyzing the primary questionnaire, the second group of experts is selected among the participants to be interviewed. The results are analyzed using Theme analysis. Six themes, including Management support, staff resistance, client willingness, Cost of software and implementation, the difficulty of implementation, and other reasons, are obtained. Then a final questionnaire is generated from the themes and filled by the same group of experts. The result is analyzed by the Fuzzy Delphi method, showing the exact ranking of the obtained themes. The final results show that management support, staff resistance, and client willingness are the most critical barrier to BIM usage in renovation projects.

Keywords: building information modeling, BIM, BIM implementation, BIM barriers, BIM in renovation

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Authors: Narupot Putwattana

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Changes in global situation such as environmental and economic crisis brought the new perspective for science education called integrative biology. STEM has been increasingly mentioned for several educational researches as the approach which combines the concept in Science (S), Technology (T), Engineering (E) and Mathematics (M) to apply in teaching and learning process so as to strengthen the 21st-century skills such as creativity and critical thinking. Recent studies demonstrated STEM as the pedagogy which described the engineering process along with the science classroom activities. So far, pedagogical contents for STEM explaining the content in biology have been scarce. A qualitative literature review was conducted so as to gather the articles based on electronic databases (google scholar). STEM education, engineering design, teaching and learning of biology were used as main keywords to find out researches involving with the application of STEM in biology teaching and learning process. All articles were analyzed to obtain appropriate teaching and learning model that unify the core concept of biology. The synthesized model comprised of engineering design, inquiry-based learning, biological prototype and biologically-inspired design (BID). STEM content and context integration were used as the theoretical framework to create the integrative biology instructional model for STEM education. Several disciplines contents such as biology, engineering, and technology were regarded for inquiry-based learning to build biological prototype. Direct and indirect integrations were used to provide the knowledge into the biology related STEM strategy. Meanwhile, engineering design and BID showed the occupational context for engineer and biologist. Technological and mathematical aspects were required to be inspected in terms of co-teaching method. Lastly, other variables such as critical thinking and problem-solving skills should be more considered in the further researches.

Keywords: biomimicry, engineering approach, STEM education, teaching and learning model

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Authors: H. Taylan Selamlar, I. Yavuz, G. Yapar

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It is difficult to make predictions especially about the future and making accurate predictions is not always easy. However, better predictions remain the foundation of all science therefore the development of accurate, robust and reliable forecasting methods is very important. Numerous number of forecasting methods have been proposed and studied in the literature. There are still two dominant major forecasting methods: Box-Jenkins ARIMA and Exponential Smoothing (ES), and still new methods are derived or inspired from them. After more than 50 years of widespread use, exponential smoothing is still one of the most practically relevant forecasting methods available due to their simplicity, robustness and accuracy as automatic forecasting procedures especially in the famous M-Competitions. Despite its success and widespread use in many areas, ES models have some shortcomings that negatively affect the accuracy of forecasts. Therefore, a new forecasting method in this study will be proposed to cope with these shortcomings and it will be called ATA method. This new method is obtained from traditional ES models by modifying the smoothing parameters therefore both methods have similar structural forms and ATA can be easily adapted to all of the individual ES models however ATA has many advantages due to its innovative new weighting scheme. In this paper, the focus is on modeling the trend component and handling seasonality patterns by utilizing classical decomposition. Therefore, ATA method is expanded to higher order ES methods for additive, multiplicative, additive damped and multiplicative damped trend components. The proposed models are called ATA trended models and their predictive performances are compared to their counter ES models on the M3 competition data set since it is still the most recent and comprehensive time-series data collection available. It is shown that the models outperform their counters on almost all settings and when a model selection is carried out amongst these trended models ATA outperforms all of the competitors in the M3- competition for both short term and long term forecasting horizons when the models’ forecasting accuracies are compared based on popular error metrics.

Keywords: accuracy, exponential smoothing, forecasting, initial value

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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: Behzad Behnia, Noah LaRussa-Trott

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In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

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Authors: Eyob Messele Sefene, Atinkut Atinafu Yilma

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The highest strength-to-weight ratio criterion has fascinated increasing curiosity in virtually all areas where weight reduction is indispensable. One of the recent advances in manufacturing to achieve this intention endears friction stir welding (FSW). The process is widely used for joining similar and dissimilar non-ferrous materials. In FSW, the mechanical properties of the weld joints are impelled by property-selected process parameters. This paper presents verdicts of optimum process parameters in attempting to attain enhanced mechanical properties of the weld joint. The experiment was conducted on a 5 mm 6061 aluminum alloy sheet. A butt joint configuration was employed. Process parameters, rotational speed, traverse speed or feed rate, axial force, dwell time, tool material and tool profiles were utilized. Process parameters were also optimized, making use of a mixed L18 orthogonal array and the Grey relation analysis method with larger is better quality characteristics. The mechanical properties of the weld joint are examined through the tensile test, hardness test and liquid penetrant test at ambient temperature. ANOVA was conducted in order to investigate the significant process parameters. This research shows that dwell time, rotational speed, tool shape, and traverse speed have become significant, with a joint efficiency of about 82.58%. Nine confirmatory tests are conducted, and the results indicate that the average values of the grey relational grade fall within the 99% confidence interval. Hence the experiment is proven reliable.

Keywords: friction stir welding, optimization, 6061 AA, Taguchi

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Authors: Chen-Ya Juan

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In recent years, the increasing number of children with special needs has brought a lot of attention by many scholars and experts in education, which enforced the preschool teachers face the harsh challenge in the classroom. To protect the right of equal education for all children, enhance the quality of children learning, and take care of the needs of children with special needs, the special education paraprofessional becomes one of the future employment trends for students of the department of the early childhood care and education. Problem-based learning is a problem-oriented instruction, which is different from traditional instruction. The instructor first designed an ambiguous problem direction, following the basic knowledge of early intervention, students had to find clues to solve the problem defined by themselves. In the class, the total instruction included 20 hours, two hours per week. The primary purpose of this paper is to investigate the relationship of student academic scores, self-awareness, learning motivation, learning attitudes, and early intervention knowledge. A total of 105 college students participated in this study and 97 questionnaires were effective. The effective response rate was 90%. The student participants included 95 females and two males. The average age of the participants was 19 years old. The questionnaires included 125 questions divided into four major dimensions: (1) Self-awareness, (2) learning motivation, (3) learning attitudes, and (4) early intervention knowledge. The results indicated (1) the scores of self-awareness were 58%; the scores of the learning motivations was 64.9%; the scores of the learning attitudes was 55.3%. (2) After the instruction, the early intervention knowledge has been increased to 64.2% from 38.4%. (3) Student’s academic performance has positive relationship with self-awareness (p < 0.05; R = 0.506), learning motivation (p < 0.05; R = 0.487), learning attitudes (p < 0.05; R = 0.527). The results implied that although students had gained early intervention knowledge by using PBL instruction, students had medium scores on self-awareness and learning attitudes, medium high in learning motivations.

Keywords: college students, children with special needs, problem-based learning, learning motivation

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Authors: Hiroyuki Aoki, Toru Asada, Tomomi Tanii

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The properties of a spin-cast film of a polymer material are different from those in the bulk material because the polymer chains are frozen in an un-equilibrium state due to the rapid evaporation of the solvent. However, there has been little information on the un-equilibrated conformation and dynamics in a spin-cast film at the single chain level. The real-space observation of individual chains would provide direct information to discuss the morphology and dynamics of single polymer chains. The recent development of super-resolution fluorescence microscopy methods allows the conformational analysis of single polymer chain. In the current study, the conformation of a polymer chain in a spin-cast film by the super-resolution microscopy. Poly(methyl methacrylate) (PMMA) with the molecular weight of 2.2 x 10^6 was spin-cast onto a glass substrate from toluene and chloroform. For the super-resolution fluorescence imaging, a small amount of the PMMA labeled by rhodamine spiroamide dye was added. The radius of gyration (Rg) was evaluated from the super-resolution fluorescence image of each PMMA chain. The mean-square-root of Rg was 48.7 and 54.0 nm in the spin-cast films prepared from the toluene and chloroform solutions, respectively. On the other hand, the chain dimension in a bulk state (a thermally annealed 10- μm-thick sample) was observed to be 43.1 nm. This indicates that the PMMA chain in the spin-cast film takes an expanded conformation compared to the unperturbed chain and that the chain dimension is dependent on the solvent quality. In a good solvent, the PMMA chain has an expanded conformation by the excluded volume effect. The polymer chain is frozen before the relaxation from an un-equilibrated expanded conformation to an unperturbed one by the rapid solvent evaporation.

Keywords: chain conformation, polymer thin film, spin-coating, super-resolution optical microscopy

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Authors: Imad Abdelhamid El-Haci, Wissame Mazari, Fayçal Hassani, Fawzia Atik Bekkara

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Much attention has been paid to the antioxidants, which are expected to prevent food and living systems from peroxidative damage. Incorporation of synthetic antioxidants in food products is under strict regulation due to the potential health hazards caused by such compounds. The use of plants as traditional health remedies is very popular and important for 80% of the world’s population in African, Asian, Latin America and Middle Eastern Countries. Their use is reported to have minimal side effects. In recent years, pharmaceutical companies have spent considerable time and money in developing therapeutics based upon natural products extracted from plants. In other part, due to the continuous emergence of antibiotic-resistant strains there is continual demand for new antibiotics. Chemical compounds from medicinal plant especially are targeted by many researches. In this light, genus Polygonum (Polygonaceae), comprising about 45 genera (300 species), is distributed worldwide, mostly in north temperate regions. They have been reported to have uses in traditional medicine, such as anti-inflammation, promoting blood circulation, dysentery, diuretic, haemorrhage and many other uses. In our study, Polygonum maritimum (from Algerian coast) was extracted with 80% methanol to obtain a crude extract. P. maritimum extract (PME) had a very high content of total phenol, which was 352.49 ± 18.03 mg/g dry weight, expressed as gallic acid equivalent. PME exhibited excellent antioxidant activity, as measured using DPPH and H2O2 scavenging assays. It also showed a high antibacterial activity against gram positive bacterial strains: Bacillus cereus, Bacillus subtilis and Staphylococcus aureus with an MIC 0,12 mg/mL.

Keywords: Polygonum maritimum, crude extract, antioxidant activity, antibacterial activity

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

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Authors: Sujit Kumar Sinha, Madan Lal Regar

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Sewing thread plays an important role in the transformation of a two-dimensional fabric into a three-dimensional garment. The interaction of the sewing thread with the fabric at the seam not only influences the appearance of a garment but also its performance. Careful selection of sewing thread and associated parameters can only help in improvement. Over the years, ring spinning has been dominating the yarn market. In the pursuit of improvement to challenge its dominance alternative technology has also been developed. But no real challenge has been posed by the any of the developed spinning systems. Eli-Twist spinning system can be a new method of yarn manufacture to provide a product with improved mechanical and physical properties with respect to the conventional ring spun yarn. The system, patented by Suessen has gained considerable attention in the recent times. The process of produces a two-ply compact yarn with improved fiber utilization. It produces a novel structure combining all advantages of condensing and doubling. In the present study, sewing threads of three different counts each from cotton, polyester and polyester/cotton (50/50) blend were produced on a ring and Eli-Twist systems. A twist multiplier of 4.2 was used to produce all the yarns. A comparison of hairiness, tensile strength and coefficient of friction with conventional ring yarn was made. Eli-Twist yarn has shown better frictional characteristics, better tensile strength and less hairiness. The performance of the Eli-Twist sewing thread has also been found to be better than the conventional 2-ply sewing thread. The performance was estimated through seam strength, seam elongation and seam efficiency of sewn fabric. Eli-Twist sewing thread has shown less friction, less hairiness, and higher tensile strength. Eli-Twist sewing thread resulted in better seam characteristics in comparison to conventional 2-ply sewing thread.

Keywords: ring spun yarn, Eli-Twist yarn, sewing thread, seam strength, seam elongation, seam efficiency

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Authors: Mohd Tariq, Shyamal K. Nandi, Indra D. Bhatt

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Paris polyphylla Smith (Family- Liliaceae; English name-Love apple: Local name- Satuwa) is an important folk medicinal herb of the Indian subcontinent, being a source of number of bioactive compounds for drug formulation. The rhizomes are widely used as antihelmintic, antispasmodic, digestive stomachic, expectorant and vermifuge, antimicrobial, anti-inflammatory, heart and vascular malady, anti-fertility and sedative. Keeping in view of this, the species is being constantly removed from nature for trade and various pharmaceuticals purpose, as a result, the availability of the species in its natural habitat is decreasing. In this context, it would be pertinent to conserve this species and reintroduce them in its natural habitat. Predictive distribution modelling of this species was performed in Western Himalayan Region. One such recent method is Ecological Niche Modelling, also popularly known as Species distribution modelling, which uses computer algorithms to generate predictive maps of species distributions in a geographic space by correlating the point distributional data with a set of environmental raster data. In case of P. polyphylla, and to understand its potential distribution zones and setting up of artificial introductions, or selecting conservation sites, and conservation and management of their native habitat. Among the different districts of Uttarakhand (28°05ˈ-31°25ˈ N and 77°45ˈ-81°45ˈ E) Uttarkashi, Rudraprayag, Chamoli, Pauri Garhwal and some parts of Bageshwar, 'Maximum Entropy' (Maxent) has predicted wider potential distribution of P. polyphylla Smith. Distribution of P. polyphylla is mainly governed by Precipitation of Driest Quarter and Mean Diurnal Range i.e., 27.08% and 18.99% respectively which indicates that humidity (27%) and average temperature (19°C) might be suitable for better growth of Paris polyphylla.

Keywords: biodiversity conservation, Indian Himalayan region, Paris polyphylla, predictive distribution modelling

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Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi

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The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.

Keywords: almost strictly positive real (ASPR), doubly-fed induction generator (DIFG), simple adaptive control (SAC), subsynchronous oscillations, wind turbine

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Roopa Singh, Anurag Singh, Ajay

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Agriculture contributes a major share in the national economy of India. A major portion of Indian economy (about 70%) depends upon agriculture as it forms the main source of income. About 43% of India’s geographical area is used for agricultural activity which involves 65-75% of total population of India. The given work deals with the Fast moving Consumer Goods (FMCG) industries and their inventories which use agricultural produce as their raw material or input for their final product. Since the beginning of inventory practices, many developments took place which can be categorised into three phases, based on the review of various works. The first phase is related with development and utilization of Economic Order Quantity (EOQ) model and methods for optimizing costs and profits. Second phase deals with inventory optimization method, with the purpose of balancing capital investment constraints and service level goals. The third and recent phase has merged inventory control with electrical control theory. Maintenance of inventory is considered negative, as a large amount of capital is blocked especially in mechanical and electrical industries. But the case is different in food processing and agro-based industries and their inventories due to cyclic variation in the cost of raw materials of such industries which is the reason for selection of these industries in the mentioned work. The application of electrical control theory in inventory control makes the decision-making highly instantaneous for FMCG industries without loss in their proposed profits, which happened earlier during first and second phases, mainly due to late implementation of decision. The work also replaces various inventories and work-in-progress (WIP) related errors with their monetary values, so that the decision-making is fully target-oriented.

Keywords: control theory, inventory control, manufacturing sector, EOQ, feedback, FMCG sector

Procedia PDF Downloads 351

Authors: Omojokun G. Aju, Adedayo O. Sule

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ZigBee wireless sensor and control network is one of the most popularly deployed wireless technologies in recent years. This is because ZigBee is an open standard lightweight, low-cost, low-speed, low-power protocol that allows true operability between systems. It is built on existing IEEE 802.15.4 protocol and therefore combines the IEEE 802.15.4 features and newly added features to meet required functionalities thereby finding applications in wide variety of wireless networked systems. ZigBee‘s current focus is on embedded applications of general-purpose, inexpensive, self-organising networks which requires low to medium data rates, high number of nodes and very low power consumption such as home/industrial automation, embedded sensing, medical data collection, smart lighting, safety and security sensor networks, and monitoring systems. Although the ZigBee design specification includes security features to protect data communication confidentiality and integrity, however, when simplicity and low-cost are the goals, security is normally traded-off. A lot of researches have been carried out on ZigBee technology in which emphasis has mainly been placed on ZigBee network performance characteristics such as energy efficiency, throughput, robustness, packet delay and delivery ratio in different scenarios and applications. This paper investigate and analyse the data accuracy, network implementation difficulties and security challenges of ZigBee network applications in star-based and mesh-based topologies with emphases on its home monitoring application using the ZigBee ProBee ZE-10 development boards for the network setup. The paper also expose some factors that need to be considered when designing ZigBee network applications and suggest ways in which ZigBee network can be designed to provide more resilient to network attacks.

Keywords: home monitoring, IEEE 802.14.5, topology, wireless security, wireless sensor network (WSN), ZigBee

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Authors: Yaofei Jiang, Liangqing Wang, Yanjun Xu

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In recent years, geological explorations have been carried out on the Rumei hydropower station, China. After preliminary analysis of results, the mainly problem of slope in reservoir area is about the stability of accumulation body. It is found that there are 23 accumulations in various sizes in the reservoir area, and most of them are unfavorable geological bodies. Three typical (No. 1, 7, 17) accumulation body slopes were selected as subjects to investigate the stability of the slopes. Take No. 1 accumulation body slope as an example and basic geological condition investigation and formation mechanism analysis were carried out to study the stability and geological analysis of engineering influence of the slope. The accumulation body in the research area distributes along the river with natural slope of 32° ~ 37° which is the natural angle of repose of gravel. The formation mechanism is analyzed based on the composition and structure of the accumulation body. The middle and lower part of the body is dense full of gravel soil mixed with a small amount of sand gravel which is stable. In the upper part, gravel soil is interbedded with bad cemented gravel which as a weak surface is not conducive to slope stability. Under the natural condition before storing water, the underground water level is deep buried, mainly distributed in the bedrock, and the surface and groundwater discharge conditions of the accumulation body are good, which is beneficial to the stability of slope. The safety coefficient calculated by the limit equilibrium method is 1.14, which indicates the slope is basically stable. However, the safety coefficient drops to 1.02 when the normal storage level is 2895m, which is in a dangerous state. The accumulation body will be destabilized by a small-area instability to large-scale or overall instability.

Keywords: accumulation body slope, stability evaluation, geological engineering investigation, effect of storing water

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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: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

Procedia PDF Downloads 137