Search results for: network capacity

Authors: Ehsan Yadegari

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While there are several metaheuristics and exact approaches to solving the Supply Chain Network Design (SCND) problem, there still remains an unfilled gap in using the Teaching-Learning-Based Optimization (TLBO) algorithm. The algorithm has demonstrated desirable results with problems with complicated combinational optimization. The present study introduces a Discrete Self-Study TLBO (DSS-TLBO) with priority-based solution representation that can solve a supply chain network configuration model to lower the total expenses of establishing facilities and the flow of materials. The network features four layers, namely suppliers, plants, distribution centers (DCs), and customer zones. It is designed to meet the customer’s demand through transporting the material between layers of network and providing facilities in the best economic Potential locations. To have a higher quality of the solution and increase the speed of TLBO, a distinct operator was introduced that ensures self-adaptation (self-study) in the algorithm based on the four types of local search. In addition, while TLBO is used in continuous solution representation and priority-based solution representation is discrete, a few modifications were added to the algorithm to remove the solutions that are infeasible. As shown by the results of experiments, the superiority of DSS-TLBO compared to pure TLBO, genetic algorithm (GA) and firefly Algorithm (FA) was established.

Keywords: supply chain network design, teaching–learning-based optimization, improved metaheuristics, discrete solution representation

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Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

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Authors: Paulu Saramge Shalika Nirupani Seram

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The study delves into the complex dynamics of social networks and how they affect paddy farmers’ adoption of agricultural technologies, which are included in Yaya Development program, Weedy rice program and Good Agricultural Practices (GAP) program in Matara district. Identify the social networks among the farmers of ongoing Extension Programs in Matara district, examine the farmers’ adoption level to the ongoing extension programs in Matara district, analyze the impacts of social networks for the adoption to the technologies of ongoing extension programs and give suggestions and recommendations to improve the social network of paddy farmers in Matara District for ongoing extension programs are the objectives of this research. A structured questionnaire survey was conducted with 25 farmers from Matara-North (Wilpita), 25 farmers from Matara-Central (Kamburupitiya), and 25 farmers from Matara-South (Malimbada). UCINET (Version -6.771) software was used for social network analysis, and other than that, descriptive statistics and inferential statistics were used to analyze the findings. Matara-North has the highest social network density, and Matara-South has the lowest social network density according to the social network analysis. Dissemination of intensive technologies requires the most prominent actors of the social network, and in Matara district, agricultural instructors have the highest ability to disseminate technologies. The influence of actors in the social network, the trustworthiness of AI officers, and the trust of indigenous knowledge about paddy cultivation have a significant effect on the technology adoption of farmers. The research endeavors to contribute a nuanced understanding of the social networks and agricultural technology adoption in Matara District, offering practical insights for stakeholders involved in agricultural extension services.

Keywords: agricultural extension, paddy cultivation, social network, technology adoption

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Authors: Saeed Delara, Kendra MacKay

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Varying methodologies are considered for pile design for both Russian and Western approaches. Although both approaches rely on toe and side frictional resistances, different calculation methods are proposed to estimate pile capacity. The Western approach relies on compactness (internal friction angle) of soil for cohesionless soils and undrained shear strength for cohesive soils. The Russian approach relies on grain size for cohesionless soils and liquidity index for cohesive soils. Though most recommended methods in the Western approaches are relatively simple methods to predict pile settlement, the Russian approach provides a detailed method to estimate single pile and pile group settlement. Details to calculate pile axial capacity and settlement using the Russian and Western approaches are discussed and compared against field test results.

Keywords: pile capacity, pile settlement, Russian approach, western approach

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Authors: А. I. Dovgyalo, S. O. Nekrasova, D. V. Sarmin, A. A. Shimanov, D. A. Uglanov

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Usually liquefied natural gas (LNG) gasification is performed due to atmospheric heat. In order to produce a liquefied gas a sufficient amount of energy is to be consumed (about 1 kW∙h for 1 kg of LNG). This study offers a number of solutions, allowing using a cold energy of LNG. In this paper it is evaluated the application turbines installed behind the evaporator in LNG complex due to its work additional energy can be obtained and then converted into electricity. At the LNG consumption of G=1000kg/h the expansion work capacity of about 10 kW can be reached. Herewith-open Rankine cycle is realized, where a low capacity cryo-pump (about 500W) performs its normal function, providing the cycle pressure. Additionally discussed an application of Stirling engine within the LNG complex also gives a possibility to realize cold energy. Considering the fact, that efficiency coefficient of Stirling engine reaches 50 %, LNG consumption of G=1000 kg/h may result in getting a capacity of about 142 kW of such a thermal machine. The capacity of the pump, required to compensate pressure losses when LNG passes through the hydraulic channel, will make 500 W. Apart from the above-mentioned converters, it can be proposed to use thermoelectric generating packages (TGP), which are widely used now. At present, the modern thermoelectric generator line provides availability of electric capacity with coefficient of efficiency up to 15%. In the proposed complex, it is suggested to install the thermoelectric generator on the evaporator surface is such a way, that the cold end is contacted with the evaporator’s surface, and the hot one – with the atmosphere. At the LNG consumption of G=1000 kgг/h and specified coefficient of efficiency the capacity of the heat flow Qh will make about 32 kW. The derivable net electric power will be P=4,2 kW, and the number of packages will amount to about 104 pieces. The carried out calculations demonstrate the research perceptiveness in this field of propulsion plant development, as well as allow realizing the energy saving potential with the use of liquefied natural gas and other cryogenics technologies.

Keywords: cold energy, gasification, liquefied natural gas, electricity

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Authors: Kenechi Kurtis Onochie

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This paper shows the use of filter paper technique in the measurement of matric suction of unsaturated expansive soil around the Haspolat region of Lefkosa, North Cyprus in other to establish the soil water characteristics curve (SWCC) or soil water retention curve (SWRC). The dry filter paper approach which is standardized by ASTM, 2003, D 5298-03 in which the filter paper is initially dry was adopted. The whatman No. 42 filter paper was used in the matric suction measurement. The maximum dry density of the soil was obtained as 2.66kg/cm³ and the optimum moisture content as 21%. The soil was discovered to have high air entry value of 1847.46KPa indicating finer particles and 25% hydraulic capacity using filter paper technique. The filter paper technique proved to be very useful for measuring the hydraulic capacity of unsaturated expansive soil.

Keywords: SWCC, matric suction, filter paper, expansive soil

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Authors: Thomas Abraham, Garcia de la Vega Felipe, Lubna Nishath, Nzekwe Nduka, Powell Anne-Marie

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Introduction: The purpose of this paper is to discuss the effectiveness of a peer support network created to provide medical education, pastoral support, and reliable resources to registrars to help them pass the MRCGP exams. This paper will include a description of the network and its purpose, discuss how it has been used by trainees since its creation, and explain how this methodology can be applied to other areas of medical education and primary care. Background: The peer support network was created in February 2021, using Facebook, Telegram, and WhatsApp platforms to facilitate discussion of cases and answer queries about the exams, share resources, and offer peer support from qualified GPs and specialists. The network was created and is maintained by the authors of this paper and is open to anyone who is registered with the General Medical Council (GMC) and is studying for the MRCGP exams. Purpose: The purpose of the network is to provide medical education, pastoral support, and reliable resources to registrars to help them pass the exams. The network is free to use and is designed to take the onus away from a single medical educator and collate a vast amount of information from multiple medical educators/trainers; thereby creating a digital library of information for all trainees - exam related or otherwise. Methodology The network is managed by a team of moderators who respond to queries and facilitate discussion. Smaller study groups are created from the main group and provide a platform for trainees to work together, share resources, and provide peer support. The network has had thousands of trainees using it since February 2021, with positive feedback from all trainees. Results: The feedback from trainees has been overwhelmingly positive. Word of mouth has spread rapidly, growing the groups exponentially. Trainees add colleagues to the groups and often stay after they pass their exams to 'give back' to their fellow trainees. To date, thousands of trainees have passed the MRCGP exams using the resources and support provided by the network. Conclusion The success of this peer support network demonstrates the effectiveness of creating a network of thousands of doctors to provide medical education and support.

Keywords: peer support, medical education, pastoral support, MRCGP exams

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Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

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This paper considers a robust stabilization problem of a single agent in a multi-agent consensus system composed of identical agents, when the network topology of the system is completely unknown. It is shown that the transfer function of an agent in a consensus system can be described as a multiplicative perturbation of the isolated agent transfer function in frequency domain. Applying known robust stabilization results, we present sufficient conditions for a robust stabilization of an agent against unknown network topology.

Keywords: single agent control, multi-agent system, transfer function, graph angle

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI

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Authors: A. GuhaRay, C. V. S. P. Kiranmayi, S. Rudraraju

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The present study considers the effect of variation of different geotechnical random variables in the design of stone column-foundation systems for assessing the bearing capacity and consolidation settlement of highly compressible soil. The soil and stone column properties, spacing, diameter and arrangement of stone columns are considered as the random variables. Probability of failure (P_f) is computed for a target degree of consolidation and a target safe load by Monte Carlo Simulation (MCS). The study shows that the variation in coefficient of radial consolidation (c_r) and cohesion of soil (c_s) are two most important factors influencing Pf. If the coefficient of variation (COV) of c_r exceeds 20%, P_f exceeds 0.001, which is unsafe following the guidelines of US Army Corps of Engineers. The bearing capacity also exceeds its safe value for COV of c_s > 30%. It is also observed that as the spacing between the stone column increases, the probability of reaching a target degree of consolidation decreases. Accordingly, design guidelines, considering both consolidation and bearing capacity of improved ground, are proposed for different spacing and diameter of stone columns and geotechnical random variables.

Keywords: bearing capacity, consolidation, geotechnical random variables, probability of failure, stone columns

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Authors: Zaouche Khelil, Talha Abdelaziz, Berkouk El Madjid

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In this paper, we present a grid-tied photovoltaic system. The studied topology is structured around a seven-level inverter, supplying a non-linear load. A three-stage step-up DC/DC converter ensures DC-link balancing. The presented system allows the extraction of all the available photovoltaic power. This extracted energy feeds the local load; the surplus energy is injected into the electrical network. During poor weather conditions, where the photovoltaic panels cannot meet the energy needs of the load, the missing power is supplied by the electrical network. At the common connexion point, the network current shows excellent spectral performances.

Keywords: seven-level inverter, multi-level DC/DC converter, photovoltaic, non-linear load

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Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

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Authors: Azli Bin Ariffin, Noor Amy Afiza Binti Mohd Yusof

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This study aims to identify effect of social network usage on the self-learning method in teaching and learning at Sultan Idris Education University. The study involved 270 respondents consisting of students in the pre-graduate and post-graduate levels from nine fields of study offered. Assessment instrument used is questionnaire which measures respondent’s background includes level of study, years of study and field of study. Also measured the extent to which social pages used for self-learning and effect received when using social network for self-learning in learning process. The results of the study showed that students always visit Facebook more than other social sites. But, it is not for the purpose of self-learning. Analyzed data showed that 45.5% students not sure about using social sites for self-learning. But they realize the positive effect that they will received when use social sites for self-learning to improve teaching and learning process when 72.7% respondent agreed with all the statements provided.

Keywords: facebook, self-learning, social network, teaching, learning

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Authors: Zahra Hatami, Hesham Ali, David Volkman

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Selecting a portfolio for investing is a crucial decision for individuals and legal entities. In the last two decades, with economic globalization, a stream of financial innovations has rushed to the aid of financial institutions. The importance of selecting stocks for the portfolio is always a challenging task for investors. This study aims to create a financial network to identify optimal portfolios using network centralities metrics. This research presents a community detection technique of superior stocks that can be described as an optimal stock portfolio to be used by investors. By using the advantages of a network and its property in extracted communities, a group of stocks was selected for each of the various time periods. The performance of the optimal portfolios compared to the famous index. Their Sharpe ratio was calculated in a timely manner to evaluate their profit for making decisions. The analysis shows that the selected potential portfolio from stocks with low centrality measurement can outperform the market; however, they have a lower Sharpe ratio than stocks with high centrality scores. In other words, stocks with low centralities could outperform the S&P500 yet have a lower Sharpe ratio than high central stocks.

Keywords: portfolio management performance, network analysis, centrality measurements, Sharpe ratio

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Faizan Khan, Xiaodong Yang

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Internet Service Providers are driving endless demands for higher bandwidth and data throughput as new services and applications require higher bandwidth. Users want immediate and accurate data delivery. This article focuses on converting old conventional networks into passive optical networks based on time division and wavelength division multiplexing. The main focus of this research is to use a hybrid of time-division multiplexing and wavelength-division multiplexing to improve network efficiency and performance. In this paper, we design an 80 Gbps Passive Optical Network (PON), which meets the need of the Next Generation PON Stage 2 (NGPON2) proposed in this paper. The hybrid of the Time and Wavelength division multiplexing (TWDM) is said to be the best solution for the implementation of NGPON2, according to Full-Service Access Network (FSAN). To co-exist with or replace the current PON technologies, many wavelengths of the TWDM can be implemented simultaneously. By utilizing 8 pairs of wavelengths that are multiplexed and then transmitted over optical fiber for 40 Kms and on the receiving side, they are distributed among 256 users, which shows that the solution is reliable for implementation with an acceptable data rate. From the results, it can be concluded that the overall performance, Quality Factor, and bandwidth of the network are increased, and the Bit Error rate is minimized by the integration of this approach.

Keywords: bit error rate, fiber to the home, passive optical network, time and wavelength division multiplexing

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Authors: Dimitra Alexiou

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In an urban area the allocation placement of an emergency service mobile units, such as ambulances, police patrol must be designed so as to achieve a prompt response to demand locations. In this paper, a partition of a given urban network into distinct sub-networks is performed such that; the vertices in each component are close and simultaneously the difference of the sums of the corresponding population in the sub-networks is almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in the framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.

Keywords: graph partition, emergency service, distances, location

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Authors: Jian Zheng

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Three-dimensional (3D) network structure has been recognized as an effective approach to enhance the mechanical and thermal conductive properties of polymeric composites. However, it has not been applied in energetic materials. In this work, a fluoropolymer based composite with vertically oriented and interconnected 3D graphite network was fabricated for polymer bonded explosives (PBXs). Here, the graphite and graphene oxide platelets were mixed, and self-assembled via rapid freezing and using crystallized ice as the template. The 3D structure was finally obtained by freezing-dry and infiltrating with the polymer. With the increasing of filler fraction and cooling rate, the thermal conductivity of the polymer composite was significantly improved to 2.15 W m⁻¹ K⁻¹ by 1094% than that of pure polymer. Moreover, the mechanical properties, such as tensile strength and elastic modulus, were enhanced by 82% and 310%, respectively, when the highly ordered structure was embedded in the polymer. We attribute the increased thermal and mechanical properties to this 3D network, which is beneficial to the effective heat conduction and force transfer. This study supports a desirable way to fabricate the strong and thermal conductive fluoropolymer composites used for the high-performance polymer bonded explosives (PBXs).

Keywords: mechanical properties, oriented network, graphite polymer composite, thermal conductivity

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Authors: Farhad Reyazat, Richard Werner

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This paper contributes to the existent literature by developing a framework that explains how to monitor potential threats to banking sector stability. The study explores structural vulnerabilities at the country level, but also look at bilateral exposures within a network context. The study contributes in analysing of the European banking systemic risk at aggregated level, which integrates the characteristics of bank size, and interconnectedness relative to the size of the economy which ultimate risk belong to, taking to account the concentration ratio of the banking industry within the whole economy. The nature of the systemic risk depends on the interplay of the network topology with the nature of financial transactions over the network, assets and buffer stemming from bank size, correlations, and the nature of the shocks to the financial system. The study’s results illustrate the contribution of banks’ size, size of economy and concentration of counterparty exposures to a given country’s banks in explaining its systemic importance, how much the banking network depends on a few traditional hubs activities and the changes of this dependencies over the last 9 years. The role of few of traditional hubs such as Swiss banks and British Banks and also Irish banks- where the financial sector is fairly new and grew strongly between 1990s till 2008- take the fourth position on 2014 reducing the relative size since 2006 where they had the first position. In-degree concentration index analysis in the study shows concentration index of banking network was not changed since financial crisis 2007-8. In-degree concentration index on first quarter of 2014 indicates that US, UK and Germany together, getting over 70% of the network exposures. The result of comparing the in-degree concentration index with 2007-4Q, shows the same group having over 70% of the network exposure, however the UK getting more important role in the hub and the market share of US and Germany are slightly diminished.

Keywords: systemic risk, counterparty risk, financial stability, interconnectedness, banking concentration, european banks risk, network effect on systemic risk, concentration risk

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Authors: Yuntao Liu, Lei Wang, Haoran Xia

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Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: Alibi Kilybay, Emad Alhseinat, Ibrahim Mustafa, Abdulfahim Arangadi, Pei Shui, Faisal Almarzooqi

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In this work, the electromagnetic field has been used for improving the performance of the capacitive deionization process. The effect of electromagnetic fields on the efficiency of the capacitive deionization (CDI) process was investigated experimentally. The results showed that treating the feed stream of the CDI process using an electromagnetic field can enhance the electrosorption capacity from 20% up to 70%. The effect of the degree of time of exposure, concentration, and type of ions have been examined. The electromagnetic field enhanced the salt adsorption capacity (SAC) of the Ca²⁺ ions by 70%, while the SAC enhanced 20% to the Na⁺ ions. It is hypnotized that the electrometric field affects the hydration shell around the ions and thus reduces their effective size and enhances the mass transfer. This reduction in ion effective size and increase in mass transfer enhanced the electrosorption capacity and kinetics of the CDI process.

Keywords: capacitive deionization, desalination, electromagnetic treatment, water treatment

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Authors: Andrey Lebedev, Ilya Dmitrenok, JooYoung Lee, Leonard Johard

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Top-k shortest path routing problem is an extension of finding the shortest path in a given network. Shortest path is one of the most essential measures as it reveals the relations between two nodes in a network. However, in many real world networks, whose diameters are small, top-k shortest path is more interesting as it contains more information about the network topology. Many variations to compute top-k shortest paths have been studied. In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Then, we also propose a top-k distance based graph matching algorithm.

Keywords: graph matching, link prediction, shortest path, similarity

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Authors: Zhen Wu, David Lupien St-Pierre, Georges Abdul-Nour

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In decision making under strict uncertainty, decision makers have to choose a decision without any information about the states of nature. The classic criteria of Laplace, Wald, Savage, Hurwicz and Starr are introduced and compared in a case study of sewer network planning. Furthermore, results from different criteria are discussed and analyzed. Moreover, this paper discusses the idea that decision making under strict uncertainty (DMUSU) can be viewed as a two-player game and thus be solved by a solution concept in game theory: Nash equilibrium.

Keywords: decision criteria, decision making, sewer network planning, decision making, strict uncertainty

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Authors: Mustafa Kamoona, Mohamed El-Sharkawy

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Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: K. Iskandar, N. H. Radzi, R. Aziz, M. S. Kamaruddin, M. N. Abdullah, S. A. Jumaat

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Nowadays many developing countries have been undergoing a restructuring process in the power electricity industry. This process has involved disaggregating former state-owned monopoly utilities both vertically and horizontally and introduced competition. The restructuring process has been implemented by the Australian National Electricity Market (NEM) started from 13 December 1998, began operating as a wholesale market for supply of electricity to retailers and end-users in Queensland, New South Wales, the Australian Capital Territory, Victoria and South Australia. In this deregulated market, one of the important issues is the transmission pricing. Transmission pricing is a service that recovers existing and new cost of the transmission system. The regulation of the transmission pricing is important in determining whether the transmission service system is economically beneficial to both side of the users and utilities. Therefore, an efficient transmission pricing methodology plays an important role in the Australian NEM. In this paper, the transmission pricing methodologies that have been implemented by the Australian NEM which are the Cost Reflective Network Pricing (CRNP) and Modified Cost Reflective Network Pricing (MCRNP) methods are investigated for allocating the transmission service charges to the transmission users. A case study using 6-bus system is used in order to identify the best method that reflects a fair and equitable transmission service charge.

Keywords: cost-reflective network pricing method, modified cost-reflective network pricing method, restructuring process, transmission pricing

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Authors: Yosika Dian Komala, Uke Kurniawan Usman, Yuyun Siti Rohmah

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The enable technology fills up needs of high-speed data service is Universal Mobile Telecommunications Service (UMTS). UMTS has a data rate up to 2Mbps.UMTS terrestrial system has a coverage area about 1-2km. High Altitude Platform Station (HAPS) can be built by a macro cell that is able to serve the wider area. Design method of UMTS using HAPS is planning base on coverage and capacity. The planning method is simulated with 2.8.1 Atoll’s software. Determination of radius of the cell based on the coverage uses free space loss propagation model. While the capacity planning to determine the average cell through put is available with the Offered Bit Quantity (OBQ).

Keywords: UMTS, HAPS, coverage planning, capacity planning, signal level, Ec/Io, overlapping zone, throughput

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Authors: Ting Kai Chia, Ruifeng Yan, Feifei Bai, Tapan Saha

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This research presents a real-world power system oscillation incident in 2022 originated by a hybrid solar photovoltaic (PV) and wind renewable energy farm with a rated capacity of approximately 300MW in Australia. The voltage and reactive power outputs recorded at the point of common coupling (PCC) oscillated at a sub-synchronous frequency region, which sustained for approximately five hours in the network. The reactive power oscillation gradually increased over time and reached a recorded maximum of approximately 250MVar peak-to-peak (from inductive to capacitive). The network service provider was not able to quickly identify the location of the oscillation source because the issue was widespread across the network. After the incident, the original equipment manufacturer (OEM) concluded that the oscillation problem was caused by the incorrect setting recovery of the hybrid power plant controller (HPPC) in the voltage and reactive power control loop after a loss of communication event. The voltage controller normally outputs a reactive (Q) reference value to the Q controller which controls the Q dispatch setpoint of PV and wind plants in the hybrid farm. Meanwhile, a feed-forward (FF) configuration is used to bypass the Q controller in case there is a loss of communication. Further study found that the FF control mode was still engaged when communication was re-established, which ultimately resulted in the oscillation event. However, there was no detailed explanation of why the FF control mode can cause instability in the hybrid farm. Also, there was no duplication of the event in the simulation to analyze the root cause of the oscillation. Therefore, this research aims to model and replicate the oscillation event in a simulation environment and investigate the underlying behavior of the HPPC and the consequent oscillation mechanism during the incident. The outcome of this research will provide significant benefits to the safe operation of large-scale renewable energy generators and power networks.

Keywords: PV, oscillation, modelling, wind

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Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak

Abstract:

This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.

Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow

Procedia PDF Downloads 333

Authors: Zhao Cai-qi, Ma Jun

Abstract:

Twin steel plates-concrete composite shear walls are composed of a pair of steel plate layers and a concrete layer sandwiched between them, which have the characteristics of both reinforced concrete shear walls and steel plate shear walls. Twin steel plates-composite shear walls contain very high ultimate bearing capacity and ductility, which have great potential to be applied in the super high-rise buildings and special structures. In this paper, we analyzed the basic characteristics and stress mechanism of the twin steel plates-composite shear walls. Specifically, we analyzed the effects of the steel plate thickness, wall thickness and concrete strength on the bearing capacity of the twin steel plates-composite shear walls. The analysis results indicate that：（1）the initial shear stiffness and ultimate shear-carrying capacity is not significantly affected by the thickness of concrete wall but by the class of concrete,（2）both factors significantly impact the shear distribution of the shear walls in ultimate shear-carrying capacity. The technique of twin steel plates-composite shear walls has been successfully applied in the construction of a 88-meter Huge Statue of Buddha located in Hunan Province, China. The analysis results and engineering experiences showed that the twin steel plates-composite shear walls have great potential for future research and applications.

Keywords: twin steel plates-concrete composite shear wall, huge statue of Buddha, shear capacity, initial lateral stiffness, overturning moment bearing

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Authors: Sirilak Areerachakul

Abstract:

Water quality has initiated serious management efforts in many countries. Artificial Neural Network (ANN) models are developed as forecasting tools in predicting water quality trend based on historical data. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok. Subsequently, this encouraging result could be combined with GIS data improves the classification accuracy significantly.

Keywords: artificial neural network, geographic information system, water quality, computer science

Procedia PDF Downloads 341