Search results for: Network Time Protocol

Authors: Saeed Mahjoub Moghadas, Farhad Asadi, Shahed Torkamandi, Hassan Moradi, Mahmood Purgamshidian

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In this paper, we present real-time obstacle avoidance approach for both autonomous and non-autonomous DS-based controllers and also based on dynamical systems (DS) method. In this approach, we can modulate the original dynamics of the controller and it allows us to determine safety margin and different types of DS to increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle and especially when robot moves very fast in changeable complex environments. The method is validated in simulation and influence of different autonomous and non-autonomous DS such as limit cycles, and unstable DS on this algorithm and also the position of different obstacles in complex environment is explained. Finally, we describe how the avoidance trajectories can be verified through different parameters such as safety factor.

Keywords: limit cycles, nonlinear dynamical system, real time obstacle avoidance, DS-based controllers

Procedia PDF Downloads 371

Authors: Kwame Kodua-Ntim

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The study explored the authors self-archiving to create awareness of open-access institutional repositories in universities. The qualitative approach of the study was informed by the interpretive paradigm as well as the case research design. The target population for the study was all twelve (12) open-access institutional repositories managers and administrators purposively selected from the five (5) universities in Ghana. The universities were chosen since they were the only ones listed in the Directory of Open Access Repositories. Interviews were conducted using a semi-structured interview guide and data were analyzed using thematic analysis. The study revealed that academics had some information about self-archiving in open-access institutional repositories and university libraries with open-access institutional repositories were using DSpace software. Managers and administrators of open-access institutional repositories mediated content uploaded and believed that author self-archiving could improve awareness of open-access institutional repositories. The study recommended that universities should fully implement the author’s self-archiving protocol, and academics should be trained to be able to upload research works onto open-access institutional repositories. Furthermore, the university and university library should provide rigorous policies on author self-archiving and incentives for author self-archiving in the open access institutional repositories.

Keywords: author, awareness, institutional repositories, open access, open archive, self-archiving

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: Kay Thinzar Phu, Lwin Lwin Oo

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In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

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Authors: M. Tash, S. Alkahtani

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The present study was undertaken to investigate the effect of pre-aging and aging parameters (time and temperature) on the mechanical properties of 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. Duplex aging treatments were carried out for the as solution treated (SHT) specimens (pre-aged at different time and temperature followed by high temperature aging). A statistical design of experiments (DOE) approach using fractional factorial design was applied to determine the influence of controlling variables of pre-aging and aging treatment parameters and any interactions between them on the mechanical properties of 7075 alloys. A mathematical models are developed to relate the alloy ultimate tensile strength, yield strength and % elongation with the different pre-aging and aging parameters i.e. Pre-aging Temperature (PA T0C), Pre-aging time (PA t h), Aging temperature (AT0C), Aging time (At h), to acquire an understanding of the effects of these variables and their interactions on the mechanical properties of be-treated 7075 alloys.

Keywords: aging heat Treatment, tensile properties, be-treated cast Al-Mg-Zn (7075) alloys, experimental correlation

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Authors: R. Barbour

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Peace-building organisations act as a network of information for communities. Through fieldwork, it was highlighted that grassroots organisations and activists may cooperate with each other in their actions of peace-building; however, they would not collaborate. Within two divided societies; Nicosia in Cyprus and Jerusalem in Israel, there is a distinction made by organisations and activists with regards to activities being more ‘co-operative’ than ‘collaborative’. This theme became apparent when having informal conversations and semi-structured interviews with various members of the activist communities. This idea needs further exploration as these distinctions could impact upon the efficiency of peacebuilding activities within divided societies. Civil societies within divided landscapes, both physically and socially, play an important role in conflict resolution. How organisations and activists interact with each other has the possibility to be very influential with regards to peacebuilding activities. Working together sets a positive example for divided communities. Cooperation may be considered a primary level of interaction between CSOs. Therefore, at the beginning of a working relationship, organisations cooperate over basic agendas, parallel power structures and focus, which led to the same objective. Over time, in some instances, due to varying factors such as funding, more trust and understanding within the relationship, it could be seen that processes progressed to more collaborative ways. It is evident to see that NGOs and activist groups are highly independent and focus on their own agendas before coming together over shared issues. At this time, there appears to be more collaboration in Nicosia among CSOs and activists than Jerusalem. The aims and objectives of agendas also influence how organisations work together. In recent years, Nicosia, and Cyprus in general, have perhaps changed their focus from peace-building initiatives to more environmental issues which have become new-age reconciliation topics. Civil society does not automatically indicate like-minded organisations however solidarity within social groups can create ties that bring people and resources together. In unequal societies, such as those in Nicosia and Jerusalem, it is these ties that cut across groups and are essential for social cohesion. Societies are a collection of social groups; individuals who have come together over common beliefs. These groups in turn shape the identities and determine the values and structures within societies. At many different levels and stages, social groups work together through cooperation and collaboration. These structures in turn have the capabilities to open up networks to less powerful or excluded groups, with the aim to produce social cohesion which may contribute social stability and economic welfare over any extended period.

Keywords: collaboration, cooperation, grassroots activism, networks of communication

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Authors: Kwok W. Mui, Ling T. Wong, Chi T. Cheung

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Cooling energy consumption in the residential sector, different from shopping mall, office or commercial buildings, is significantly subject to occupant decisions where in-depth investigations are found limited. It shows that energy consumptions could be associated with housing types. Surveys have been conducted in existing Hong Kong public housings to understand the housing characteristics, apartment electricity demands, occupant’s thermal expectations, and air–conditioning usage patterns for further cooling energy-saving assessments. The aim of this study is to develop a hybrid cooling energy prediction model, which integrated by EnergyPlus (EP) and artificial neural network (ANN) to estimate cooling energy consumption in public residential sector. Sensitivity tests are conducted to find out the energy impacts with changing building parameters regarding to external wall and window material selection, window size reduction, shading extension, building orientation and apartment size control respectively. Assessments are performed to investigate the relationships between cooling demands and occupant behavior on thermal environment criteria and air-conditioning operation patterns. The results are summarized into a cooling energy calculator for layman use to enhance the cooling energy saving awareness in their own living environment. The findings can be used as a directory framework for future cooling energy evaluation in residential buildings, especially focus on the occupant behavioral air–conditioning operation and criteria of energy-saving incentives.

Keywords: artificial neural network, cooling energy, occupant behavior, residential buildings, thermal environment

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Authors: N. Ouslimani, T. Abadlia, M. Fadel

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This work focused on the elimination of acid textile dye (red bermacide acid dye BN-CL-200), widely used for dyeing wool and polyamide fibers, by adsorption on a natural material, wood sawdust, in the static mode by keeping under continuous stirring, a specific mass of the adsorbent, with a dye solution of known concentration. The influence of various parameters is studied like the influence of particle size, mass, pH and time. The best results were obtained with 0.4 mm grain size, mass of 3g, Temperature of 20 °C, pH 2 and Time contact of 120 min.

Keywords: acid dye, environment, wood sawdust, wastewater

Procedia PDF Downloads 420

Authors: Damanhur Munardi, Muhammad Hafiz, Dina Nurmalita Sari, Syarifah Ridani Alifa

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Purpose: This research aims to analyze the Benefits, Opportunity, Cost, and Risk aspects of applying the Green Finance concept and to obtain the right Green Finance financing strategy to be implemented within a long-term and short-term strategic framework.Methodology: This research method uses a qualitative-descriptive analysis approach. The analysis technique uses Analytical Network Process (ANP) with a BOCR network structure approach.Findings: The research results show that the most priority long-term strategic alternative based on the long-term BOCR analysis is increasing awareness among the public and industry by 52% and the importance of coordination between related institutions by 50%. Meanwhile, the most priority short-term strategic alternatives are the importance of coordination between related institutions 29%, increasing awareness among the public and industry 28%, the banking industry proactively funding environmentally friendly companies and technology 23%, the existence of Green Finance POS (Standard Operating Procedures) 20%.Implications: This research can be used as a reference for regulators and policymakers in making strategic decisions that can increase green finance financing. The novelty of this research is identifying problems that occur in green finance financing in Aceh province by analyzing opinions from experts in related fields and financial regulators in Aceh to create a strategy that can be implemented to increase green finance financing in Aceh province through BPD in Aceh, namely Bank Aceh.

Keywords: green financing, banking, sharia, islamic

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Authors: Elvan Ender Altay, Zeynep Pirselimoglu Batman, Murat Zencirkiran

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Ancient cities are, according to United Nations Educational, Scientific and Cultural Organization (UNESCO), landscape areas designed and created by people, at the same time naturally developing and constantly changing sustainable cultural landscapes. Ancient cities are the urban settlements where we can see the reflection of public lifestyle existed thousands of years ago. The conceptual and spatial traces in ancient cities, are crucial for examining the city history and its preservation. This study is intended to demonstrate the impacts of human life and physical environment on the cultural landscape. This research aims to protect and maintain cultural continuity of the ancient cities in Bursa which contain archeological and historical elements and could not majorly reach to the day because of not being protected and to show importance of landscape architecture to ensure this protection. In this context, ancient cities in Bursa were researched and a total of 7 ancient cities were identified. These ancient cities are; Apollonia, Lopadion, Nicaea, Myrleia, Cius, Daskyleion and Basilinopolis. In the next stage, the spatial performances of ancient cities were assessed by weighted criteria method. The highest score is the Nicaea Ancient City. Considering current situation of the ancient cities in Bursa, it is seen that most of them could not survive until our day due to lack of interest in these areas. As a result, according to the findings, it is a priority to create a protective band with green areas around the archaeological sites, thus adapting to nearby areas and emphasizing culture. In addition, proposals have been made to provide a transportation network that does not harm the ancient cities and the cultural landscape.

Keywords: ancient cities, Bursa, landscape, spatial performance

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Authors: Abdurrahman Arslanyilmaz, Salman Al Matouq, Durmus V. Doner

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Level 3 autonomous vehicles are able to take full responsibility over the control of the vehicle unless a system boundary is reached or a system failure occurs, in which case, the driver is expected to take-over the control of the vehicle. While this happens, the driver is often not aware of the traffic situation or is engaged in a secondary task. Factors affecting the duration and quality of take-overs in these situations have included secondary task type and nature, traffic density, take-over request (TOR) time, and TOR warning type and modality. However, to the best of the authors’ knowledge, no prior study examined time buffer for TORs when a system failure occurs immediately before intersections. The first objective of this study is to investigate the effect of time buffer (3 and 7 seconds) on the duration and quality of take-overs when a system failure occurs just prior to intersections. In addition, eye-tracking has become one of the most popular methods to report what individuals view, in what order, for how long, and how often, and it has been utilized in driving simulations with various objectives. However, to the extent of authors’ knowledge, none has compared drivers’ eye gaze behavior in the two different time buffers in order to examine drivers’ attention and comprehension of salient information. The second objective is to understand the driver’s attentional focus on comprehension of salient traffic-related information presented on different parts of the dashboard and on the roads.

Keywords: autonomous vehicles, driving simulation, eye gaze, attention, comprehension, take-over duration, take-over quality, time buffer

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: Maryam Tajadod

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The treatment of cancer is one of the main challenges of nuclear medicine; while cancer begins in an organ, such as the breast or prostate, it spreads to the bone, resulting in metastatic bone. In the treatment of cancer with radiotherapy, the determination of the involved tissues’ dose is one of the important steps in the treatment protocol. Comparing absorbed doses for Lu-177 and Ra-223 and Ac-225 in the bone marrow and soft tissue of bone phantom with evaluating energetic emitted particles of these radionuclides is the important aim of this research. By the use of MCNPX computer code, a model for bone phantom was designed and the values of absorbed dose for Ra-223 and Ac-225, which are Alpha emitters & Lu-177, which is a beta emitter, were calculated. As a result of research, in comparing gamma radiation for three radionuclides, Lu-177 released the highest dose in the bone marrow and Ra-223 achieved the lowest level. On the other hand, the result showed that although the figures of absorbed dose for Ra and Ac in the bone marrow are near to each other, Ra spread more energy in cortical bone. Moreover, The alpha component of the Ra-223 and Ac-225 have very little effect on bone marrow and soft tissue than a beta component of the lu-177 and it leaves the highest absorbed dose in the bone where the source is located.

Keywords: bone metastases, lutetium-177, radium-223, actinium-225, absorbed dose

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Authors: Matthew Kostawich, Mohammed Elmorsy, Mohamed Sayed Sifat, Shoukry Shams, Mahmoud Elsaadany

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6G communication systems represent the nominal future extension of current wireless technology, where its impact is extended to touch upon all human activities, including medical, security, and entertainment applications. As a result, human needs are allocated among the highest priority aspects of the system design and requirements. 6G communications is expected to replace all the current video conferencing with interactive virtual reality meetings involving high data-rate transmission merged with massive distributed computing resources. In addition, the current expansion of IoT applications must be mitigated with significant network changes to provide a reasonable Quality of Service (QoS). This directly implies a high demand for Human-Computer Interaction (HCI) through mobile computing modules in future wireless communication systems. This article proposes the utilization of a Printed Ridge Gap Waveguide (PRGW) to host the wearable nodes. To the best of our knowledge, we propose for the first time a physical layer analysis within the context of a complete architecture. A thorough study is provided on the impact of the distortion of the guiding structure on the overall system performance. The proposed structure shows small latency and small losses, highlighting its compatibility with future applications.

Keywords: ridge gap waveguide, edge computing module, 6G, multimedia IoT applications

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Authors: Tran Gia Khanh, Dao Phuong Nam, Do Trong Tan, Nguyen Van Huong, Mai Xuan Sinh

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This work presents the problem of tube-based robust model predictive controller for a class of continuous-time systems in the presence of input disturbances. The main objective is to point out the state trajectory of closed system being maintained inside a sequence of tubes. An estimation of attraction region of the closed system is pointed out based on input state stability (ISS) theory and linearized model in each time interval. The theoretical analysis and simulation results demonstrate the performance of the proposed algorithm for a wheeled inverted pendulum system.

Keywords: input state stability (ISS), tube-based robust MPC, continuous-time nonlinear systems, wheeled inverted pendulum

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Authors: Muhammad Abubakar Alhassan, Diane Pennington

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Social networking sites have become a space for people to discuss public health issues such as non-suicidal self-injury (NSSI). There are thousands of tweets containing self-harm and self-injury hashtags on Twitter. It is difficult to distinguish between different users who participate in self-injury discussions on Twitter and how their opinions change over time. Also, it is challenging to understand the topics surrounding NSSI discussions on Twitter. We retrieved tweets using #selfham and #selfinjury hashtags and investigated those from the United kingdom. We applied inductive coding and grouped tweeters into different categories. This study used the Latent Dirichlet Allocation (LDA) algorithm to infer the optimum number of topics that describes our corpus. Our findings revealed that many of those participating in NSSI discussions are non-professional users as opposed to medical experts and academics. Support organisations, medical teams, and academics were campaigning positively on rais-ing self-injury awareness and recovery. Using LDAvis visualisation technique, we selected the top 20 most relevant terms from each topic and interpreted the topics as; children and youth well-being, self-harm misjudgement, mental health awareness, school and mental health support and, suicide and mental-health issues. More than 50% of these topics were discussed in England compared to Scotland, Wales, Ireland and Northern Ireland. Our findings highlight the advantages of using the Twitter social network in tackling the problem of self-injury through awareness. There is a need to study the potential risks associated with the use of social networks among self-injurers.

Keywords: self-harm, non-suicidal self-injury, Twitter, social networks

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Authors: Gyeong-Suk Jo, Soo-Hyun Ji, You-Seok Lee, Jeong-Hwa Kang

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To develop an flavor oil using Sarcodon aspratus (Sarcodon aspratus Berk. S. Ito), infiltration extraction method was used to add dried mushroom flavor of Sarcodon aspratus to base olive oil. Edible base oil used during infiltration extraction was pressed olive oil, and infiltration extraction was done while varying extraction temperature to 20, 30, 40 and 50(℃) extraction time to 24 hours, 48 hours and 72 hours. Amount of Sarcodon aspratus added to base oil was 20% compared to 100% of base oil. Production yield of Sarcodon aspratus flavor oil decreased with increasing extraction frequency. Aroma intensity was 2195~2447 (A.U./1㎖), and it increased with increasing extraction temperature and extraction time. Chromaticity of Sarcodon aspratus flavor oil was bright pale yellow with pH of 4.5, sugar content of 71~72 (°Brix), and highest average turbidity of 16.74 (Haze %) shown by the 40℃ group. In the aromatic evaluation, increasing extraction temperature and extraction time resulted in increase of cheese aroma, savory sweet aroma and beef jerky aroma, as well as spicy taste comprised of slight bitter taste, savory taste and slight acrid taste, to make aromatic oil with unique flavor.

Keywords: Flavor Characteristics, Flavor Oil, Infiltration extraction method, mushroom, Sarcodon aspratus (Sarcodon aspratus Berk. S. Ito)

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Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

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Authors: Sasangka Prasetyawan, Anna Roosdiana, Diah Mardiana, Suratmo

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Pectinase are enzymes that hydrolyze pectin compounds. The use of this enzyme is primarily to reduce the viscosity of the beverage thus simplifying the purification process. Pectinase activity influenced by microbial sources . Exploration of two types of microbes that Aspergillus spp. and Bacillus spp. pectinase give different performance, but the use of local strain is still not widely studied. The aim of this research is exploration of pectinase from A. niger and B. firmus include production conditions and characterization. Bacillus firmus incubated and shaken at a speed of 200 rpm at pH variation (5, 6, 7, 8, 9, 10), temperature (30, 35, 40, 45, 50) °C and incubation time (6, 12, 18, 24, 30, 36 ) hours. Media was centrifuged at 3000 rpm, pectinase enzyme activity determined. Enzyme production by A. niger determined to variations in temperature and pH were similar to B. firmus, but the variation of the incubation time was 24, 48, 72, 96, 120 hours. Pectinase crude extract was further purified by precipitation using ammonium sulfate saturation in fraction 0-20 %, 20-40 %, 40-60 %, 60-80 %, then dialyzed. Determination of optimum conditions pectinase activity performed by measuring the variation of enzyme activity on pH (4, 6, 7, 8, 10), temperature (30, 35, 40, 45, 50) °C, and the incubation time (10, 20, 30, 40, 50) minutes . Determination of kinetic parameters of pectinase enzyme reaction carried out by measuring the rate of enzyme reactions at the optimum conditions, but the variation of the concentration of substrate (pectin 0.1 % , 0.2 % , 0.3 % , 0.4 % , 0.5 % ). The results showed that the optimum conditions of production of pectinase from B. firmus achieved at pH 7-8.0, 40-50 ⁰C temperature and fermentation time 18 hours. Purification of pectinase showed the highest purity in the 40-80 % ammonium sulfate fraction. Character pectinase obtained : the optimum working conditions of A. niger pectinase at pH 5 , while pectinase from B. firmus at pH 7, temperature and optimum incubation time showed the same value, namely the temperature of 50 ⁰C and incubation time of 30 minutes. The presence of metal ions can affect the activity of pectinase , the concentration of Zn 2 + , Pb 2 + , Ca 2 + and K + and 2 mM Mg 2 + above 6 mM inhibit the activity of pectinase .

Keywords: pectinase, Bacillus firmus, Aspergillus niger, green chemistry

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Authors: Hassan Ibrahim

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

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

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Authors: Asieh Abbassi Daloii, Fatemeh Fani, Ahmad Abdi

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Objective: The aim of this study was to determine the effect of 8 weeks endurance training and L-NAME on apelin in adipose tissue, glucose and insulin in elderly male’s rats. Methods: For this purpose, 24 vistar elderly rats with average 20 months old purchased from Razi Institute and transferred to Research Center were randomly divided into four groups: 1. control, 2. training, 3.training and L-NAME and 4. L-NAME. Training protocol performed for 8 weeks and 5 days a week with 75-80 VO2 max. All rats were killed 72 hours after the final training session and after 24 hours of fasting adipose tissue samples were collected and kept in -80. Also, Data was analyzed with One way ANOVA and Tucky in p < 0/05. Results: The results showed that the inhibition of nitric oxide on apelin in adipose tissue of adult male rats after eight weeks of endurance training increased significantly compared to the control group (p < 0.00). Also, the results showed no significant difference between the levels of insulin and glucose groups. Conclusion: It is likely that the increased apelin in adipose tissue in mice independent of insulin and glucose.

Keywords: endurance training, L-NAME, apelin in adipose tissue, elderly male rats

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Authors: Yuichi Anada

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Electrical properties of polymer solid is characterized by dielectric relaxation phenomenon. Complex permittivity shows a high dependence on frequency of external stimulation in the broad frequency range from 0.1mHz to 10GHz. The complex-permittivity dispersion gives us a lot of useful information about the molecular motion of polymers and the structure of polymer aggregates. However, the large dispersion of permittivity at low frequencies due to DC conduction of impurity ions often covers the dielectric relaxation in polymer solid. In experimental investigation, many researchers have tried to remove the DC conduction experimentally or analytically for a long time. On the other hand, our laboratory chose another way of research for this problem from the point of view of a reversal in thinking. The way of our research is to use the impurity ions in the DC conduction as a probe to detect the motion of polymer molecules and to investigate the structure of polymer aggregates. In addition to the complex permittivity, the electric modulus and the conductivity relaxation time are strong tools for investigating the ionic motion in DC conduction. In a non-crystalline part of melt-crystallized polymers, free spaces with inhomogeneous size exist between crystallites. As the impurity ions exist in the non-crystalline part and move through these inhomogeneous free spaces, the motion of ions reflects the microstructure of non-crystalline part. The ionic motion of impurity ions in poly(vinylidene fluoride) (PVDF) is investigated in this study. Frequency dependence of the loss permittivity of PVDF shows a characteristic of the direct current (DC) conduction below 1 kHz of frequency at 435 K. The electric modulus-frequency curve shows a characteristic of the dispersion with the single conductivity relaxation time. Namely, it is the Debye-type dispersion. The conductivity relaxation time analyzed from this curve is 0.00003 s at 435 K. From the plot of conductivity relaxation time of PVDF together with the other polymers against permittivity, it was found that there are two group of polymers; one of the group is characterized by small conductivity relaxation time and large permittivity, and another is characterized by large conductivity relaxation time and small permittivity.

Keywords: conductivity relaxation time, electric modulus, ionic motion, permittivity, poly(vinylidene fluoride), DC conduction

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Authors: Nattawat Thongpraphai, Anusorn Boonpoke

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This study aimed to determine the removal of colour and curcuminoids from turmeric wastewater using granular activated carbon (GAC) adsorption. The adsorption isotherm and kinetic behavior of colour and curcuminoids was invested using batch and fixed bed columns tests. The results indicated that the removal efficiency of colour and curcuminoids were 80.13 and 78.64%, respectively at 8 hr of equilibrium time. The adsorption isotherm of colour and curcuminoids were well fitted with the Freundlich adsorption model. The maximum adsorption capacity of colour and curcuminoids were 130 Pt-Co/g and 17 mg/g, respectively. The continuous experiment data showed that the exhaustion concentration of colour and curcuminoids occurred at 39 hr of operation time. The adsorption characteristic of colour and curcuminoids from turmeric wastewater by GAC can be described by the Thomas model. The maximum adsorption capacity obtained from kinetic approach were 39954 Pt-Co/g and 0.0516 mg/kg for colour and curcuminoids, respectively. Moreover, the decrease of colour and curcuminoids concentration during the service time showed a similar trend.

Keywords: adsorption, turmeric, colour, curcuminoids, activated carbon

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Authors: Noriyuki Suyama

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

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

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Authors: Xuelin Zhang, Shouxiang Lu, Changhai Li

Abstract:

The commercial retardant flame polycarbonate samples as the main high speed train interior carriage material with different thicknesses were investigated in Fire Propagation Apparatus with different external heat fluxes under different oxygen concentration from 12% to 40% to study the fire characteristics and quantitatively analyze the ignition time, mass loss rate and heat blockage. The additives of commercial retardant flame polycarbonate were intumescent and maintained a steady height before ignition when heated. The results showed the transformed ignition time (1/t_ig)ⁿ increased linearly with external flux under different oxygen concentration after deducting the heat blockage due to pyrolysis products, the mass loss rate was taken on linearly with external heat fluxes and the slop of the fitting line for mass loss rate and external heat fluxes decreased with the enhanced oxygen concentration and the heat blockage independent on external heat fluxes rose with oxygen concentration increasing. The inquired data as the input of the fire simulation model was the most important to be used to evaluate the fire risk of commercial retardant flame polycarbonate.

Keywords: ignition time, mass loss rate, heat blockage, fire characteristic

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Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini

Abstract:

Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.

Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis

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Authors: Milad Abbasi

Abstract:

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

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

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Authors: Maulik L. Sisodia, Tirth K. Raval, Aarsh S. Mistry

Abstract:

This paper summarizes the ongoing researches about the defects in both flexible and rigid pavement and the maintenance in both flexible and rigid pavements. Various defects in pavements have been identified since the existence of both flexible and rigid pavement. Flexible Pavement failure is defined in terms of decreasing serviceability caused by the development of cracks, ruts, potholes etc. Flexible Pavement structure can be destroyed in a single season due to water penetration. Defects in flexible pavements is a problem of multiple dimensions, phenomenal growth of vehicular traffic (in terms of no. of axle loading of commercial vehicles), the rapid expansion in the road network, non-availability of suitable technology, material, equipment, skilled labor and poor funds allocation have all added complexities to the problem of flexible pavements. In rigid pavements due to different type of destress the failure like joint spalling, faulting, shrinkage cracking, punch out, corner break etc. Application of correction in the existing surface will enhance the life of maintenance works as well as that of strengthening layer. Maintenance of a road network involves a variety of operations, i.e., identification of deficiencies and planning, programming and scheduling for actual implementation in the field and monitoring. The essential objective should be to keep the road surface and appurtenances in good condition and to extend the life of the road assets to its design life. The paper describes lessons learnt from pavement failures and problems experienced during the last few years on a number of projects in India. Broadly, the activities include identification of defects and the possible cause there off, determination of appropriate remedial measures; implement these in the field and monitoring of the results.

Keywords: Flexible Pavements, Rigid Pavements, Defects, Maintenance

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

Abstract:

Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

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Authors: Anthony Credoz, Nathalie Nief, Remy Hedacq, Salvador Jordana, Laurent Cazes

Abstract:

Groundwater monitoring is classically performed in a network of piezometers in industrial sites. Groundwater flow parameters, such as direction, sense and velocity, are deduced from indirect measurements between two or more piezometers. Groundwater sampling is generally done on the whole column of water inside each borehole to provide concentration values for each piezometer location. These flow and concentration values give a global ‘static’ image of potential plume of contaminants evolution in the shallow aquifer with huge uncertainties in time and space scales and mass discharge dynamic. TOTAL R&D Subsurface Environmental team is challenging this classical approach with an innovative dynamic way of characterization of shallow aquifer groundwater. The current study aims at optimizing the tools and methodologies for (i) a direct and multilevel measurement of groundwater velocities in each piezometer and, (ii) a calculation of potential flux of dissolved contaminant in the shallow aquifer. Lab-scale experiments have been designed to test commercial and R&D tools in a controlled sandbox. Multiphysics modeling were performed and took into account Darcy equation in porous media and Navier-Stockes equation in the borehole. The first step of the current study focused on groundwater flow at porous media/piezometer interface. Huge uncertainties from direct flow rate measurements in the borehole versus Darcy flow rate in the porous media were characterized during experiments and modeling. The structure and location of the tools in the borehole also impacted the results and uncertainties of velocity measurement. In parallel, direct-push tool was tested and presented more accurate results. The second step of the study focused on mass flux of dissolved contaminant in groundwater. Several active and passive commercial and R&D tools have been tested in sandbox and reactive transport modeling has been performed to validate the experiments at the lab-scale. Some tools will be selected and deployed in field assays to better assess the mass discharge of dissolved contaminants in an industrial site. The long-term subsurface environmental strategy is targeting an in-situ, real-time, remote and cost-effective monitoring of groundwater.

Keywords: dynamic characterization, groundwater flow, lab-scale, mass flux

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