Search results for: artificial potential approach

Authors: Xiaoyun Zhao, Rami Darwish, Anna Pernestål

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Automated vehicles (AVs) have the potential to enhance road capacity, improving road safety and traffic efficiency. Research and development on AVs have been going on for many years. However, when the complicated traffic rules and real situations interacted, AVs fail to make decisions on contradicting situations, and are not able to have control in all conditions due to highly dynamic driving scenarios. This limits AVs’ usage and restricts the full potential benefits that they can bring. Furthermore, regulations, infrastructure development, and public acceptance cannot keep up at the same pace as technology breakthroughs. Facing these challenges, this paper proposes automated vehicle traffic control tower (AVTCT) acting as a safe, efficient and integrated solution for AV control. It introduces a concept of AVTCT for control, management, decision-making, communication and interaction with various aspects in transportation. With the prototype demonstrations and simulations, AVTCT has the potential to overcome the control challenges with AVs and can facilitate AV reaching their full potential. Possible functionalities, benefits as well as challenges of AVTCT are discussed, which set the foundation for the conceptual model, simulation and real application of AVTCT.

Keywords: automated vehicle, connectivity and automation, intelligent transport system, traffic control, traffic safety

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Authors: Sarra Roubi, Mohammed Erramdani, Samir Mbarki

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This paper presents an approach for the model-driven generating of Rich Internet Application (RIA) focusing on the graphical aspect. We used well known Model-Driven Engineering (MDE) frameworks and technologies, such as Eclipse Modeling Framework (EMF), Graphical Modeling Framework (GMF), Query View Transformation (QVTo) and Acceleo to enable the design and the code automatic generation of the RIA. During the development of the approach, we focused on the graphical aspect of the application in terms of interfaces while opting for the Model View Presenter pattern that is designed for graphics interfaces. The paper describes the process followed to define the approach, the supporting tool and presents the results from a case study.

Keywords: metamodel, model-driven engineering, MVP, rich internet application, transformation, user interface

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Authors: Gina L. Solano

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This project endeavors to enhance learning experiences for undergraduate pre-service teachers and graduate K-12 educators by leveraging artificial intelligence (AI). Firstly, the initiative delves into integrating AI within undergraduate education courses, fostering traditional literacy skills essential for academic success and extending their applicability beyond the classroom. Education students will explore AI tools to design literacy-focused activities aligned with their curriculum. Secondly, the project investigates the utilization of AI to craft instructional materials employing gamification strategies (e.g., digital and classic games, badges, quests) to amplify student engagement and motivation in mastering course content. Lastly, it aims to create a professional repertoire that can be applied by pre-service and current teachers in P-12 classrooms, promoting seamless integration for those already in teaching positions. The project's impact extends to benefiting college students, including pre-service and graduate teachers, as they enhance literacy and digital skills through AI. It also benefits current P-12 educators who can integrate AI into their classrooms, fostering innovative teaching practices. Moreover, the project contributes to faculty development, allowing them to cultivate low-risk and engaging classroom environments, ultimately enriching the learning journey. The insights gained from this project can be shared within and beyond the discipline to advance the broader field of study.

Keywords: artificial intelligence, gamification, learning experiences, literacy skills, engagement

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Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

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The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: action potential, myelinated segments, nonlinear models, Ranvier nodes, reduced order models, saltatory conduction

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Authors: Lipsa Dash, Gyanendra Sahu

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Intelligence is the cornerstone of humans, and now they have created a counterpart of themselves artificially. Our understanding of the word intelligence is a very perspective based and mostly superior understanding of what we read, write, perceive and understand the adversities around better. A wide range of industrial sectors have also started involving the technology to perceive, reason and act. Similarly, intellectual property is the product of human intelligence and creativity. The World Intellectual Property Organisation is currently working on technology trends across the globe, and AI tops the list in the digital frontier that will have a profound impact on the world, transforming the way we live and work. Coming to Intellectual Property, patents and creations of the AI’s itself have constantly been in question. This paper explores whether AI’s can fit in the flexibilities of Trade Related Intellectual Property Studies and gaps in the existing IP laws or rthere is a need of amendment to include them in the ambit. The researcher also explores the right of AI’s who create things out of their intelligence and whether they could qualify to be legal persons making the other laws applicable on them. Differentiation between AI creations and human creations are explored in the paper, and the need of amendments to determine authorship, ownership, inventorship, protection, and identification of beneficiary for remuneration or even for determining liability. The humans and humanoids are all indulged in matters related to Privacy, and that attracts another constitutional legal issue to be addressed. The authors will be focusing on the legal conundrums of AI, transhumanism, and the Internet of things.

Keywords: artificial intelligence, humanoids, healthcare, privacy, legal conundrums, transhumanism

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Authors: Mahmoud M. Tash

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The present study was undertaken to investigate the effect of aging parameters (time and temperature) on the mechanical properties of Be-and/or Zr- treated Al-Mg-Zn (7075) alloys. Ultimate tensile strength, 0.5% offset yield strength and % elongation measurements were carried out on specimens prepared from cast and heat treated 7075 alloys containing Be and/or Zr. Different aging treatment were carried out for the as solution treated (SHT) specimens. The specimens were aged at different conditions; Natural and artificial aging was carried out at room temperature, 120C, 150C, 180C and 220C for different periods of time. Duplex aging was performed for SHT conditions (pre-aged at different time and temperature followed by high temperature aging). Ultimate tensile strength, yield strength and % elongation data results as a function of different aging parameters are analysed. A statistical design of experiments (DOE) approach using fractional factorial design is applied to acquire an understanding of the effects of these variables and their interactions on the mechanical properties of Be- and/or Zr- treated 7075 alloys. Mathematical models are developed to relate the alloy mechanical properties with the different aging parameters.

Keywords: casting aging treatment, mechanical properties, Al-Mg-Zn alloys, Be- and/or Zr-treatment, experimental correlation

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Authors: Khizar Z. Choudhrya, Richard Coles, Salman Qureshi, Robert Ashford, Salim Khan, Rabia R. Mir

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Abstract: The majority of existing landscape research has been derived by conducting heuristic evaluations, without having empirical insight of real participant visual response. In this research, a modern multimodal measurement approach (using narratives and eye tracking) was applied to investigate visual behaviour in perceiving naturalistic and urban environments. This research is unique in exploring gaze behaviour on environmental images possessing different levels of saliency. Eye behaviour is predominantly attracted by salient locations. The concept of methodology of this research on naturalistic and urban environments is drawn from the approaches in market research. Borrowing methodologies from market research that examine visual responses and qualities provided a critical and hitherto unexplored approach. This research has been conducted by using mixed methodological quantitative and qualitative approaches. On the whole, the results of this research corroborated existing landscape research findings, but they also identified potential refinements. The research contributes both methodologically and empirically to human-environment interaction (HEI). This study focused on initial impressions of environmental images with the help of eye tracking. Taking under consideration the importance of the image, this study explored the factors that influence initial fixations in relation to expectations and preferences. In terms of key findings of this research it is noticed that each participant has his own unique navigation style while surfing through different elements of landscape images. This individual navigation style is given the name of ‘visual signature’. This study adds the necessary clarity that would complete the picture and bring an insight for future landscape researchers.

Keywords: human-environment interaction (HEI), multimodal measurement, narratives, eye tracking

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Authors: Chamnan Kumsap, Somsarit Sinnung, Suriyawate Boonthalarath, Teeranai Srithamarong

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This research paper addresses the GIS analysis approach to the investigation of suitable sites for a vertical takeoff and landing drone. The study manipulated GIS and terrain layers into a proper input before the spatial analysis that included slope, reclassify, classify, and buffer was applied to the individual layers. The output layers were weighted, and multi-criteria analyzed before those patches failing to comply with filtering out criteria were discarded. Field survey for each suitable candidate site was conducted to cross-check the proposed approach with the real world. Conclusion was extracted for the VTOL takeoff and landing sites, and discussion was provided with further study being suggested on the mission simulation of selected takeoff and landing sites.

Keywords: GIS approach, site selection, VTOL, takeoff and landing

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Authors: Clinton Adas

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Antibiotic resistance has been identified by the World Health Organisation as a real possibility for the 21st Century. While many factors contribute to this, one of the more significant is industrial animal farming and its effect on the food chain and environment. Livestock consumes a significant portion of antibiotics sold globally, and these are used to make animals grow faster for profit purposes, to prevent illness caused by inhumane living conditions, and to treat disease when it breaks out. Many of these antibiotics provide little benefit to animals, and most are the same as those used by humans - including those deemed critical to human health that should therefore be used sparingly. Antibiotic resistance contributes to growing numbers of illnesses and death in humans, and the excess usage of these medications results in waste that enters the environment and is harmful to many ecological processes. This combination of antimicrobial resistance and environmental degradation furthermore harms the economic well-being and prospects of many. Using an interdisciplinary approach including medical, environmental, economic, and legal studies, the paper evaluates the dynamic between animal welfare and commerce and argues that while animal welfare is not of great concern to many, this approach is ultimately harming human welfare too. It is, however, proposed that both could be addressed under a One Health and Welfare approach, as we cannot continue to ignore the linkages between animals, the environment, and people. The evaluation of industrial animal farming is therefore considered through three aspects – the environmental impact, which is measured by pollution that causes environmental degradation; the human impact, which is measured by the rise of illnesses from pollution and antibiotics resistance; and the economic impact, which is measured through costs to the health care system and the financial implications of industrial farming on the economic well-being of many. These three aspects are considered in light of the Sustainable Development Goals that provide additional tangible metrics to evidence the negative impacts. While the research addresses the welfare of farmed animals, there is potential for these principles to be extrapolated into other contexts, including wildlife and habitat protection. It must be noted that while the question of animal rights in industrial animal farming is acknowledged and of importance, this is a separate matter that is not addressed here.

Keywords: animal and human welfare, industrial animal farming, one health and welfare, sustainable development goals

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Authors: Sven Gehrke, Johannes Ruhland

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Data is the oil of our time, without them progress would come to a hold [1]. On the other hand, the mistrust of data mining is increasing [2]. The paper at hand shows different aspects of the concept of trust and describes the information asymmetry of the typical stakeholders of a data mining project using the CRISP-DM phase model. Based on the identified influencing factors in relation to trust, problematic aspects of the current approach are verified using various interviews with the stakeholders. The results of the interviews confirm the theoretically identified weak points of the phase model with regard to trust and show potential research areas.

Keywords: trust, data mining, CRISP DM, stakeholder management

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Authors: Alicja Kot-Niewiadomska

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Securing sustainable access to raw materials is vital for the growth of the European economy and for the goals laid down in Strategy Europe 2020. One of the most important sources of mineral raw materials are primary deposits. The efficient management of them, including extraction, will ensure competitiveness of the European economy. A critical element of this approach is mineral deposits safeguarding and the most important tool - spatial planning. The safeguarding of deposits should be understood as safeguarding of land access, and safeguarding of area against development, which may (potential) prevent the use of the deposit and the necessary mining activities. Many European Union countries successfully integrated their mineral policy and spatial policy, which has ensured the proper place of mineral deposits in their spatial planning systems. These, in turn, are widely recognized as the most important mineral deposit safeguarding tool, the essence of which is to ensure long-term access to its resources. The examples of Austria, Portugal, Slovakia, Czech Republic, Sweden, and the United Kingdom, discussed in the paper, are often mentioned as examples of good practices in this area. Although none of these countries managed to avoid cases of social and environmental conflicts related to mining activities, the solutions they implement certainly deserve special attention. And for many countries, including Poland, they can be a potential source of solutions aimed at improving the protection of mineral deposits.

Keywords: mineral deposits, land use planning, mineral deposit safeguarding, European practices

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Authors: Nur Iffika Ruslan, Ahmad Rosly Abbas, Munirah Stapah@Salleh, Nurfaziera Rahim

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Increased concerns and awareness of environmental hazards by fossil fuels burning for energy have become the major factor driving the transition toward green energy. It is expected that an additional of 2,000 MW of renewable energy is to be recorded from the renewable sources by 2025 following the implementation of Large Scale Solar projects in Peninsular Malaysia, including Large Scale Floating Solar projects. Floating Solar has better advantages over its landed counterparts such as the requirement for land acquisition is relatively insignificant. As part of the site selection process established by TNB Research Sdn. Bhd., a set of mandatory and rejection criteria has been developed in order to identify only sites that are feasible for the future development of Large Scale Floating Solar power plant. There are a total of 85 lakes and reservoirs identified within Peninsular Malaysia. Only lakes and reservoirs with a minimum surface area of 120 acres will be considered as potential sites for the development of Large Scale Floating Solar power plant. The result indicates a total of 10 potential Large Scale Floating Solar sites identified which are located in Selangor, Johor, Perak, Pulau Pinang, Perlis and Pahang. This paper will elaborate on the various mandatory and rejection criteria, as well as on the various site selection process required to identify potential (suitable) Large Scale Floating Solar sites in Peninsular Malaysia.

Keywords: Large Scale Floating Solar, Peninsular Malaysia, Potential Sites, Renewable Energy

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Authors: Michael Tilahun Mulugeta

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Pedestrians are the most vulnerable road users as they are more exposed to the risk of collusion. Pedestrian safety at road intersections still remains the most vital and yet unsolved issue in Addis Ababa, Ethiopia. One of the critical points in pedestrian safety is the occurrence of conflict between turning vehicle and pedestrians at un-signalized intersection. However, a better understanding of the factors that affect the likelihood of the conflicts would help provide direction for countermeasures aimed at reducing the number of crashes. This paper has sorted to explore a model to describe the relation between traffic conflicts and influencing factors using Multiple Linear regression methodology. In this research the main focus is to study the interaction of turning (left & right) vehicle with pedestrian at unsignalized intersections. The specific objectives also to determine factors that affect the number of potential conflicts and develop a model of potential conflict.

Keywords: potential, regression analysis, pedestrian, conflicts

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: Yogesh C. Sharma, A. Seetharaman

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The decision-making process in humans is a complicated system influenced by a variety of intrinsic and extrinsic factors. Human decisions have a ripple effect on subsequent decisions. In this study, the scope of human decision making is limited to employees. In an organisation, a person makes a variety of decisions from the time they are hired to the time they retire. The goal of this research is to identify various elements that influence decision-making. In addition, the environment in which a decision is made is a significant aspect of the decision-making process. Employees in today's workplace use artificial intelligence (AI) systems for automation and decision augmentation. The impact of AI systems on the decision-making process is examined in this study. This research is designed based on a systematic literature review. Based on gaps in the literature, limitations and the scope of future research have been identified. Based on these findings, a research framework has been designed to identify various factors affecting employee decision making. Employee decision making is influenced by technological advancement, data-driven culture, human trust, decision automation-augmentation, and workplace motivation. Hybrid human-AI systems require the development of new skill sets and organisational design. Employee psychological safety and supportive leadership influences overall job satisfaction.

Keywords: employee decision making, artificial intelligence (AI) environment, human trust, technology innovation, psychological safety

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Authors: Emejeamara Francis

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The future of potentials wind energy applications within suburban/urban areas are currently faced with various problems. These include insufficient assessment of urban wind resource, and the effectiveness of commercial gust control solutions as well as unavailability of effective and cheaper valuable tools for scoping the potentials of urban wind applications within built-up environments. In order to achieve effective assessment of the potentials of urban wind installations, an estimation of the total energy that would be available to them were effective control systems to be used, and evaluating the potential power to be generated by the wind system is required. This paper presents a methodology of predicting the power generated by a wind system operating within an urban wind resource. This method was developed by using high temporal resolution wind measurements from eight potential sites within the urban and suburban environment as inputs to a vertical axis wind turbine multiple stream tube model. A relationship between the unsteady performance coefficient obtained from the stream tube model results and turbulence intensity was demonstrated. Hence, an analytical methodology for estimating the unsteady power coefficient at a potential turbine site is proposed. This is combined with analytical models that were developed to predict the wind speed and the excess energy (EEC) available in estimating the potential power generated by wind systems at different heights within a built environment. Estimates of turbulence intensities, wind speed, EEC and turbine performance based on the current methodology allow a more complete assessment of available wind resource and potential urban wind projects. This methodology is applied to four major UK cities namely Leeds, Manchester, London and Edinburgh and the potential to map the turbine performance at different heights within a typical urban city is demonstrated.

Keywords: small-scale wind, turbine power, urban wind energy, turbulence intensity, excess energy content

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Tareq Nikzad

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Since the first bank was established in 1933, Afghanistan's banking sector has seen a number of variations but hasn't been able to grow to its full potential because of the civil war. The implementation of dual banks in Afghanistan is investigated in this study in relation to the effects of inflation and interest rates. This research took data from World Bank Data (WBD) over a period of nineteen years. For the banking sector, inflation, which is the general rise in prices of goods and services over time, presents considerable difficulties. The objectives of this research are to analyze the effect of inflation and interest rates on conventional and Islamic banks in Afghanistan, identify potential differences between these two banking models, and provide insights for policymakers and practitioners. A mixed-methods approach is used in the research to analyze quantitative data and qualitatively examine the unique difficulties that banks in Afghanistan's economic atmosphere encounter. The findings contribute to the understanding of the relationship between interest rate, inflation rate, and the performance of both banking systems in Afghanistan. The paper concludes with recommendations for policymakers and banking institutions to enhance the stability and growth of the banking sector in Afghanistan. Interest is described as "a prefixed rate for use or borrowing of money" from an Islamic perspective. This "prefixed rate," known in Islamic economics as "riba," has been described as "something undesirable." Furthermore, by using the time series regression data technique on the annual data from 2003 to 2021, this research examines the effect of CPI inflation rate and interest rate of Banking in Afghanistan.

Keywords: inflation, Islamic banking, conventional banking, interest, Afghanistan, impact

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Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani

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This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: chaotic approach, phase space, Cao method, local linear approximation method

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Authors: Alexander Scott English, Yilin Ma, Xiaoying Liu

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The widespread use of artificial intelligence in everyday life has triggered a fervent discussion covering a wide range of areas. However, to date, research on the influence of gender in various segments and factors from a social science perspective is still limited. This study aims to explore whether there are gender differences in human trust in AI for its application in basic everyday life and correlates with human perceived similarity, perceived emotions (including competence and warmth), and attractiveness. We conducted a study involving 321 participants using a two-subject experimental design with a two-factor (masculinized vs. feminized voice of the AI) multiplied by a two-factor (pitch level of the AI's voice) between-subject experimental design. Four contexts were created for the study and randomly assigned. The results of the study showed significant gender differences in perceived similarity, trust, and perceived emotion of the AIs, with females rating them significantly higher than males. Trust was higher in relation to AIs presenting the same gender (e.g., human female to female AI, human male to male AI). Mediation modeling tests indicated that emotion perception and similarity played a sufficiently mediating role in trust. Notably, although trust in AIs was strongly correlated with human gender, there was no significant effect on the gender of the AI. In addition, the study discusses the effects of subjects' age, job search experience, and job type on the findings.

Keywords: artificial intelligence, gender differences, human-robot trust, mediation modeling

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Authors: Yeliz Karaca, Carlo Cattani

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This study focuses on the local Holder exponent as a measure of the function regularity for time series related to finance data. In this study, the attributes of the finance dataset belonging to 13 countries (India, China, Japan, Sweden, France, Germany, Italy, Australia, Mexico, United Kingdom, Argentina, Brazil, USA) located in 5 different continents (Asia, Europe, Australia, North America and South America) have been examined.These countries are the ones mostly affected by the attributes with regard to financial development, covering a period from 2012 to 2017. Our study is concerned with the most important attributes that have impact on the development of finance for the countries identified. Our method is comprised of the following stages: (a) among the multi fractal methods and Brownian motion Holder regularity functions (polynomial, exponential), significant and self-similar attributes have been identified (b) The significant and self-similar attributes have been applied to the Artificial Neuronal Network (ANN) algorithms (Feed Forward Back Propagation (FFBP) and Cascade Forward Back Propagation (CFBP)) (c) the outcomes of classification accuracy have been compared concerning the attributes that have impact on the attributes which affect the countries’ financial development. This study has enabled to reveal, through the application of ANN algorithms, how the most significant attributes are identified within the relevant dataset via the Holder functions (polynomial and exponential function).

Keywords: artificial neural networks, finance data, Holder regularity, multifractals

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Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

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Authors: Joshi Rajiv, Shah Priyank, Thavkar Amit, Rohira Poonam, Mehta Suyog

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Topical formulation containing minoxidil and finasteride helps hair growth in the treatment of male androgenetic alopecia. The objective of this study is to compare the irritation potential of three conventional formulations of minoxidil 5% + finasteride 0.1% topical solution of in human patch test. The study was a single centre, double blind, non-randomized controlled study in 53 healthy adult Indian subjects. Occlusive patch test for 24 hours was performed with three formulations of minoxidil 5% + finasteride 0.1% topical solution. Products tested included aqueous based minoxidil 5% + finasteride 0.1% (AnasureTM-F, Sun Pharma, India – Brand A), lipid based minoxidil 5% + finasteride 0.1% (Brand B) and aqueous based minoxidil 5% + finasteride 0.1% (Brand C). Isotonic saline 0.9% and 1% w/w sodium lauryl sulphate were included as negative control and positive control respectively. Patches were applied and removed after 24 hours. The skin reaction was assessed and clinically scored 24 hours after the removal of the patches under constant artificial daylight source using the Draize scale (0-4 points scale for erythema/dryness//wrinkles and for oedema). Follow-up was scheduled after one week to confirm recovery for any reaction. A combined mean score up to 2.0/8.0 indicates a product is “non-irritant” and a score between 2.0/8.0 and 4.0/8.0 indicates “mildly irritant” and a score above 4.0/8.0 indicates “irritant”. The procedure of the patch test followed the principles outlined by the Bureau of Indian Standards (BIS) (IS 4011:2018; Methods of Test for safety evaluation of Cosmetics-3rd revision). Fifty three subjects with mean age 31.9 years (25 males and 28 females) participated in the study. The combined mean score ± standard deviation were: 0.06 ± 0.23 (Brand A), 0.81 ± 0.59 (Brand B), 0.38 ± 0.49 (Brand C), 2.92 ± 0.47 (positive control) and 0.0 ± 0.0 (Negative control). This means the score of Brand A (Sun Pharma product) was significantly lower than that of Brand B (p=0.001) and that of Brand C (p=0.001). The combined mean erythema score ± standard deviation were: 0.06 ± 0.23 (Brand A), 0.81 ± 0.59 (Brand B), 0.38 ± 0.49 (Brand C), 2.09 ± 0.4 (Positive control) and 0.0 ± 0.0 (Negative control). The mean erythema score of Brand A was significantly lower than Brand B (p=0.001) and that of Brand C (p=0.001). Any reaction observed at 24hours after patch removal subsided in a week. All the three topical formulations of minoxidil 5% + finasteride 0.1% were non-irritant. Brand A of minoxidil 5% + finasteride 0.1% (Sun Pharma) was found to be the least irritant than Brand B and Brand C based on the combined mean score and mean erythema score in the human patch test as per the BIS, IS 4011:2018

Keywords: erythema, finasteride, irritation, minoxidil, patch test

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Authors: A.Zitouni, S.Bentata, B.Bouadjemi, T.Lantri, W. Benstaali, Z.Aziz, S.Cherid, A. Sefir

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Using the first-principles method, we investigate the structural, electronic, and magnetic properties of the diluted magnetic semiconductors CdCoTe and CdMnTe in the zinc blende phase with 12.5% of Cr. The calculations are performed by a developed full potential augmented plane wave (FP-L/APW) method within the spin density functional theory (DFT). As exchange–correlation potential, we used the new generalized gradient approximation GGA. Structural properties are determined from the total energy calculations and we found that these compounds are stable in the ferromagnetic phase. We discuss the electronic structures, total and partial densities of states and local moments. Finally, CdCoTe and CdMnTe in the zinc-blend phase show the half-metallic ferromagnetic nature and are expected to be potential materials for spintronic devices.

Keywords: DFT, GGA, band structures, half-metallic, spintronics

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Authors: Atefeh Heydari, Mohammadali Tavakoli, Naomie Salim

Abstract:

In recent years, we have witnessed that online reviews are the most important source of customers’ opinion. They are progressively more used by individuals and organisations to make purchase and business decisions. Unfortunately, for the reason of profit or fame, frauds produce deceptive reviews to hoodwink potential customers. Their activities mislead not only potential customers to make appropriate purchasing decisions and organisations to reshape their business, but also opinion mining techniques by preventing them from reaching accurate results. Spam reviews could be divided into two main groups, i.e. multiple and singleton spam reviews. Detecting a singleton spam review that is the only review written by a user ID is extremely challenging due to lack of clue for detection purposes. Singleton spam reviews are very harmful and various features and proofs used in multiple spam reviews detection are not applicable in this case. Current research aims to propose a novel supervised technique to detect singleton spam reviews. To achieve this, various features are proposed in this study and are to be combined with the most appropriate features extracted from literature and employed in a classifier. In order to compare the performance of different classifiers, SVM and naive Bayes classification algorithms were used for model building. The results revealed that SVM was more accurate than naive Bayes and our proposed technique is capable to detect singleton spam reviews effectively.

Keywords: classification algorithms, Naïve Bayes, opinion review spam detection, singleton review spam detection, support vector machine

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Authors: Sule Pallavi, Shah Priyank, Thavkar Amit, Rohira Poonam, Mehta Suyog

Abstract:

Introduction: Minoxidil has been used topically for a long time to assist hair growth in the management of male androgenetic alopecia. The aim of this study was a comparative assessment of the irritation potential of three commercial formulations of minoxidil 2% topical solution in a human patch test. Methodology: The study was a non-randomized, double-blind, controlled, single-center study of 56 healthy adult Indian subjects. A 24-hour occlusive patch test was conducted with three formulations of minoxidil 2% topical solution. Products tested were aqueous-based minoxidil 2% (AnasureTM 2%, Sun Pharma, India – Brand A), alcohol-based minoxidil 2% (Brand B) and aqueous-based minoxidil 2% (Brand C). Isotonic saline 0.9% and 1% w/w sodium lauryl sulphate as a negative and positive control, respectively, were included. Patches were applied on the back, followed by removal after 24 hours. The Draize scale (0-4 points scale for erythema/dryness/wrinkles and for oedema) was used to evaluate and clinically score the skin reaction under constant artificial daylight 24 hours after the removal of the patches. The patch test was based on the principles outlined by Bureau of Indian Standards (BIS) (IS 4011:2018; Methods of Test for safety evaluation of Cosmetics-3rd revision). A mean combined score up to 2.0/8.0 indicates that a product is “non-irritant,” and a score between 2.0/8.0 and 4.0/8.0 indicates “mildly irritant” and a score above 4.0/8.0 indicates “irritant”. In case of any skin reaction that was observed, a follow-up was planned after one week to confirm recovery. Results: The 56 subjects who participated in the study had a mean age of 28.7 years (28 males and 28 females). The combined mean score ± standard deviation was: 0.09 ± 0.29 (Brand A), 0.29± 0.53 (Brand B), 0.30 ± 0.46 (Brand C), 3.25 ± 0.77 (positive control) and 0.02 ± 0.13 (negative control). This mean score of Brand A (Sun Pharma) was significantly lower than that of Brand B (p=0.016) and that of Brand C (p=0.004). The mean erythema score ± standard deviation was: 0.09 ± 0.29 (Brand A), 0.27 ± 0.49 (Brand B), 0.30 ± 0.46 (Brand C), 2.5 ± 0.66 (positive control) and 0.02 ± 0.13 (negative control). The mean erythema score of Brand A (Sun Pharma) was significantly lower than that of Brand B (p=0.019) and that of Brand C (p=0.004). Reactions that were observed 24 hours after patch removal subsided in a week’s time. Conclusion: Based on the human patch test as per the BIS, IS 4011:2018, all the three topical formulations of minoxidil 2% were found to be non-irritant. Brand A of 2% minoxidil (Sun Pharma) was found to be the least irritant than Brand B and Brand C based on the combined mean score and mean erythema score.

Keywords: erythema, irritation, minoxidil, patch test

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Authors: Maryam Kiani

Abstract:

This study focuses on the development of composite nanomaterials based on SiO2 and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO2/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques, including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO2 into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO2 facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO2/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: oxygen reduction reaction, batteries, fuel cells, electrrocatalyst

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Authors: Ahmed Raza Khan

Abstract:

Local-strain engineering is an exciting approach to tune the optoelectronic properties of materials and enhance the performance of devices. Two dimensional (2D) materials such as 2D transition metal dichalcogenides (TMDCs) are particularly well-suited for this purpose because they have high flexibility and can withstand high deformations before rupture. Wrinkles on thick TMDC layers have been reported to show the interesting photoluminescence enhancement due to bandgap modulation and funneling effect. However, the wrinkles in ultrathin TMDCs have not been investigated, because the wrinkles can easily fall down to form folds in these ultrathin layers of TMDCs. Here, we have achieved both wrinkle and fold nano-structures simultaneously on 1-3L WS₂ using a new fabrication technique. The comparable layer dependent reduction in surface potential is observed for both folded layers and corresponding perfect pack layers due to the dominant interlayer screening effect. The strains produced from the wrinkle nanostructures considerably vary semi conductive junction properties. Thermo-ionic modelling suggests that the strained (1.6%) wrinkles can lower the Schottky barrier height (SBH) by 20%. The photo-generated carriers would further significantly lower the SBH. These results present an important advance towards controlling the optoelectronic properties of atomically thin WS₂ using strain engineering, with important implications for practical device applications.

Keywords: strain engineering, folding, WS₂, Kelvin probe force microscopy, KPFM, surface potential, photo current, layer dependence

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Authors: Muhasin Koyiloth, Sathyanarayana N. Gummadi

Abstract:

Biological membranes are ordered association of lipids, proteins, and carbohydrates. Lipids except sterols possess asymmetric distribution across the bilayer. Eukaryotic membranes possess a group of lipid translocators called scramblases that disrupt phospholipid asymmetry. Their action is implicated in cell activation during wound healing and phagocytic clearance of apoptotic cells. Cholesterol is one of the major membrane lipids distributed evenly on both the leaflet and can directly influence the membrane fluidity through the ordering effect. The fluidity has an impact on the activity of several membrane proteins. The palmitoylated phospholipid scramblases localized to the lipid raft which is characterized by a higher number of sterols. Here we propose that cholesterol can interact with scramblases through putative CRAC motif and can modulate their activity. To prove this, we reconstituted phospholipid scramblase 1 of C. elegans (SCRM-1) in proteoliposomes containing different amounts of cholesterol (Liquid ordered/Lo). We noted that the presence of cholesterol reduced the scramblase activity of wild-type SCRM-1. The interaction between SCRM-1 and cholesterol was confirmed by fluorescence spectroscopy using NBD-Chol. Also, we observed loss of such interaction when one of I273 in the CRAC motif mutated to Asp. Interestingly, the point mutant has partially retained scramblase activity in Lo vesicles. The current study elucidated the important interaction between cholesterol and SCRM-1 to fine-tune its activity in artificial membranes.

Keywords: artificial membranes, CRAC motif, plasma membrane, PL scramblase

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