Search results for: back propagation neural network BP ANN
Commenced in January 2007
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Edition: International
Paper Count: 7204

Search results for: back propagation neural network BP ANN

2734 Matlab Method for Exclusive-or Nodes in Fuzzy GERT Networks

Authors: Roland Lachmayer, Mahtab Afsari

Abstract:

Research is the cornerstone for advancement of human communities. So that it is one of the indexes for evaluating advancement of countries. Research projects are usually cost and time-consuming and do not end in result in short term. Project scheduling is one of the integral parts of project management. The present article offers a new method by using C# and Matlab software to solve Fuzzy GERT networks for Exclusive-OR kind of nodes to schedule the network. In this article we concentrate on flowcharts that we used in Matlab to show how we apply Matlab to schedule Exclusive-OR nodes.

Keywords: research projects, fuzzy GERT, fuzzy CPM, CPM, α-cuts, scheduling

Procedia PDF Downloads 392
2733 A Study of Predicting Judgments on Causes of Online Privacy Invasions: Based on U.S Judicial Cases

Authors: Minjung Park, Sangmi Chai, Myoung Jun Lee

Abstract:

Since there are growing concerns on online privacy, enterprises could involve various personal privacy infringements cases resulting legal causations. For companies that are involving online business, it is important for them to pay extra attentions to protect users’ privacy. If firms can aware consequences from possible online privacy invasion cases, they can more actively prevent future online privacy infringements. This study attempts to predict the probability of ruling types caused by various invasion cases under U.S Personal Privacy Act. More specifically, this research explores online privacy invasion cases which was sentenced guilty to identify types of criminal punishments such as penalty, imprisonment, probation as well as compensation in civil cases. Based on the 853 U.S judicial cases ranged from January, 2000 to May, 2016, which related on data privacy, this research examines the relationship between personal information infringements cases and adjudications. Upon analysis results of 41,724 words extracted from 853 regal cases, this study examined online users’ privacy invasion cases to predict the probability of conviction for a firm as an offender in both of criminal and civil law. This research specifically examines that a cause of privacy infringements and a judgment type, whether it leads a civil or criminal liability, from U.S court. This study applies network text analysis (NTA) for data analysis, which is regarded as a useful method to discover embedded social trends within texts. According to our research results, certain online privacy infringement cases caused by online spamming and adware have a high possibility that firms are liable in the case. Our research results provide meaningful insights to academia as well as industry. First, our study is providing a new insight by applying Big Data analytics to legal cases so that it can predict the cause of invasions and legal consequences. Since there are few researches applying big data analytics in the domain of law, specifically in online privacy, this study suggests new area that future studies can explore. Secondly, this study reflects social influences, such as a development of privacy invasion technologies and changes of users’ level of awareness of online privacy on judicial cases analysis by adopting NTA method. Our research results indicate that firms need to improve technical and managerial systems to protect users’ online privacy to avoid negative legal consequences.

Keywords: network text analysis, online privacy invasions, personal information infringements, predicting judgements

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2732 The Concepts of Ibn Taymiyyah in Halal and Haram and Their Relevance to Contemporary Issues

Authors: Muhammad Fakhrul Arrazi

Abstract:

Ibn Taymiyyah is a great figure in Islam. His works have become the reference for many Muslims in implementing the fiqh of Ibadah and Muamalat. This article reviews the concepts that Ibn Taymiyyah has initiated in Halal and Haram, long before the books on Halal and Haram are written by contemporary scholars. There are at least four concepts of Halal and Haram ever spawned by Ibn Taymiyyah. First, the belief of a jurist (Faqih) in a matter that is Haram does not necessarily make the matter Haram. Haram arises from the Quran, Sunnah, Ijma’ and Qiyas as the tarjih. Due to the different opinions among the ulama, we should revisit this concept. Second, if a Muslim involves in a transaction (Muamalat), believes it permissible and gets money from such transaction, then it is legal for other Muslims to transact with the property of this Muslim brother, even if he does not believe that the transactions made by his Muslims brother are permissible. Third, Haram is divided into two; first is Haram because of the nature of an object, such as carrion, blood, and pork. If it is mixed with water or food and alters their taste, color, and smell, the food and water become Haram. Second is Haram because of the way it is obtained such as a stolen item and a broken aqad. If it is mixed with the halal property, the property does not automatically become Haram. Fourth, a treasure whose owners cannot be traced back then it is used for the benefit of the ummah. This study used the secondary data from the classics books by Ibn Taymiyyah, particularly those entailing his views on Halal and Haram. The data were then analyzed by using thematic and comparative approach. It is found that most of the concepts proposed by Ibn Taymiyyah in Halal and Haram correspond the majority’s views in the schools. However, some of his concepts are also in contrary to other scholars. His concepts will benefit the ummah, should it be applied to the contemporary issues.

Keywords: fiqh Muamalat, halal, haram, Ibn Taymiyyah

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2731 Central African Republic Government Recruitment Agency Based on Identity Management and Public Key Encryption

Authors: Koyangbo Guere Monguia Michel Alex Emmanuel

Abstract:

In e-government and especially recruitment, many researches have been conducted to build a trustworthy and reliable online or application system capable to process users or job applicant files. In this research (Government Recruitment Agency), cloud computing, identity management and public key encryption have been used to management domains, access control authorization mechanism and to secure data exchange between entities for reliable procedure of processing files.

Keywords: cloud computing network, identity management systems, public key encryption, access control and authorization

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2730 High Culture or Low Culture: The Propagation and Popularization of the Classic of Poetry in Modern China

Authors: Fang Tang

Abstract:

A major Confucian masterpiece and the earliest-known poetry anthology (composed approximately 1046-771 BCE), The Classic of Poetry, reflects different cultures in ancient China. It is regarded as a Chinese classic and one of the world’s most significant written works, an essential part of our global cultural heritage. This paper explores how the ancient Chinese classic became transformed into part of popular culture, found in folk songs circulated in Fangxian county, a mountainous location in Hubei province in central mainland China. It is the hometown of one of the most well-known authors of The Classic of Poetry, whose name is Yin Jifu. Local villagers process, refine, and recreate these poems into popular folk songs, which have been handed down from generation to generation. The folk songs based on The Classic of Poetry vividly reflect local customs, life styles, and various cultural activities. After thousands of years of singing these traditional songs, the region has become an important area to maintain part of Chinese cultural heritages; here, the original high culture is converted into a popular culture that is absorbed into people’s daily life. Based on a year’s field research and many interviews with local singers, this paper explores the ways in which locals have transformed the contents of The Classic of Poetry. It examines how today these popular folk songs become part of much-treasured culture heritage, illustrating the transformation of traditional high culture into popular culture. The paper argues that the modern adaptations of the traditional poems of The Classic of Poetry combine both oral and written cultural heritage and reflects the interaction between ancient Chinese official literature and folk literature. The paper also explores the reasons why the folk songs of The Classic of Poetry are so popular in the area, including the influences of its author Yin Jifu, the impact of ancient diasporic culture from the political centre to remote rural areas, and the interactions of local cultures (famous as Chu culture) and Chinese mainstream cultural policies.

Keywords: high/low culture, The Classic of Poetry, the functions of media, cultural policy

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2729 An Application of Meta-Modeling Methods for Surrogating Lateral Dynamics Simulation in Layout-Optimization for Electric Drivetrains

Authors: Christian Angerer, Markus Lienkamp

Abstract:

Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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2728 The Role of Development in Settling Migration Crisis: The Preventive Approach of the European Union in Relations with Sub-Saharan African States

Authors: Artsiom Zinchanka

Abstract:

The world faces now one of the largest migration crisis and the European Union meets challenges in accepting the flow of migrants that could not be handled finally at this step. This crisis is complicated with many factors, such as military conflict in the Middle East; absence of the appropriate conditions in the refugees’ camps; but also with the complicity of the migration flow consisting of the Sub-Saharan migrants. This type of migrants leave their homelands for many reasons including poverty, not appropriate level of social and economic conditions, absence of infrastructure and access to the education and medical care. In practice, when the restrictive approach directed to limit the flow of illicit migration and to send illicit migrants back to their homelands is not always working, the approach directed to the root causes of the migration crisis can be more effective in settling the crisis. The Cotonou Agreement and the following treaties concluded between the European Union, and Sub-Saharan states show that the European Union considers the development of human rights and appropriate social and economic conditions in the Sub-Saharan states as one of the most important factors addressing the migration crisis. The preventive approach as the efforts of the European Union to develop appropriate social and economic conditions in Sub-Saharan states is considered in this article, as well as its evolution and current condition. This article also considers pros and cons of this approach and the obstacles that this approach faces. The research methods include review of literature and documents, analytical and descriptive methods.

Keywords: migration crisis, preventive approach, Sub-Saharan States, the European Union

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2727 Injury Prevention among Construction Workers: A Case Study on Iranian Steel Bar Bending Workers

Authors: S. Behnam Asl, H. Sadeghi Naeini, L. Sadat Ensaniat, R. Khorshidian, S. Alipour, S. Behnam Asl

Abstract:

Nowadays, the construction industry is growing, especially among developing countries. Iran also has a critical role in these industries in terms of workers disorders. Work-related musculoskeletal disorders (WMSDs) account for 7% of the whole diseases in the society, which makes some limitations. One of the main factors which causes WMSDs is awkward posture. Steel bar bending is considered as one of the prominent performance among construction workers. In this case study, we aimed to find the major tasks of bar benders and the most important risk factors related to it. This study was carried out among twenty workers (18-45 years) as our volunteer samples in some construction sites with less than 6 floors in two regions of Tehran municipality. The data was gathered through in depth observation, interview and questionnaire. Also postural analysis was done by OWAS method. In another part of study we used NMQ for gathering some data about psychosocial effects of work related disorders. Our findings show that 64% of workers were not aware of work risks, about 59% of workers had troubles in their wrists, hands, especially workers who worked in steel bar bending. In 46% cases lower back pain was in prevalence. Considering gathered data and results, awkward postures and long term tasks and their duration are known as the main risk factors of WMSDs among construction workers, meaning that work-rest schedule and tools design should be reconsidered to make an ergonomic condition for the mentioned workers.

Keywords: bar benders, construction workers, musculoskeletal disorders (WMSDs), OWAS method

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2726 Capacity Optimization in Cooperative Cognitive Radio Networks

Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

Abstract:

Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: cooperative networks, normalized capacity, sensing time

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2725 The Tourism in the Regional Development of South Caucasus

Authors: Giorgi Sulashvili, Vladimer Kekenadze, Olga Khutsishvili, Bela Khotenashvili, Tsiuri Phkhakadze, Besarion Tsikhelashvili

Abstract:

The article dealt with the South Caucasus is a complex economic policy, which consists of strands: The process of deepening economic integration in the South Caucasus region; deepening economic integration with the EU in the framework of "Neighbourhood policy with Europe" and in line with the Maastricht criteria; the development of bilateral trade and economic relations with many countries of the world community; the development of sufficient conditions for the integration of the South Caucasus region in the world to enter the market. According to the author, to determine the place of Georgia in the regional policy of the South Caucasus, it is necessary to consider two views about Georgia: The first is the view of Georgia, as a part of global economic and political processes and the second look at Georgia, as a country located in the geo-economic and geopolitical space of the South Caucasus. Such approaches reveal the place of Georgia in two dimensions; in the global and regional economies. In the countries of South Caucasus, the tourism has been developing fast and has a great social and economic importance. Tourism influences deeply on the social and economic growth of the regions of the country. Tourism development formulates thousand new jobs, fixes the positions of small and middle businesses, ensures the development of the education and culture of the population. In the countries of South Caucasus, the Tourist Industry can be specified as the intersectoral complex, which consists of travel transport and it’s technical service network, tourist enterprises which are specialized in various types, wide network services. Tourists have a chance to enjoy all of these services. At the transitional stage of shifting to the market economy, tourism is among the priorities in the development of the national economy of our country. It is true that the Georgian tourism faces a range of problems at present, but its recognition and the necessity for its development may be considered as a fact. Besides, we would underline that the revitalization of the Georgian tourism is not only the question of time. This area can bring a lot of benefits as to private firms, as to specific countries. It also has many negative effects were conducted fundamental research and studies to consider both, positive and negative impacts of tourism. In the future such decisions will be taken that will bring, the maximum benefit at minimum cost, in order for tourism to take its place in Georgia it is necessary to understand the role of the tourism sector in the economic structure.

Keywords: transitional stage, national economy, Georgian tourism, positive and negative impacts

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2724 Fault Diagnosis in Confined Systems

Authors: Nesrine Berber, Hafid Haffaf, Abdel Madjid Meghabar

Abstract:

In the last decade, technology has continued to grow and has changed the structure of our society. Today, new technologies including the information and communication (ICT) play a main role which importance continues to grow, now it's become indispensable to the economic, social and cultural. Thus, ICT technology has proven to be as a promising intervention in the area of road transport. The supervision model of class of train of intelligent and autonomous vehicles leads us to give some defintions about IAV and the different technologies used for communication between them. Our aim in this work is to present an hypergraph modeling a class of train of Intelligent and Autonomous Vehicles (IAV).

Keywords: intelligent transportation system, intelligent autonomous vehicles, Ad Hoc network, wireless technologies, hypergraph modeling, supervision

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2723 Analysis of the Internationalisation of Spanish Enterprises in Colombia through Cooperation Agreements

Authors: Sandoval H. Leyla Angélica, Casani Fernando

Abstract:

The objective of this study is to analyse how enterprises in developed countries use cooperation agreements to expand into developing countries. Starting from the literature review, seven theoretical prepositions were derived. The qualitative methodology used includes case study, through interviews conducted with eight enterprises from Spain and Colombia. Results show that the cooperation agreements have provided a quick and solid connection that facilitates internationalization, bearing in mind aspects such as: strategic factors, partners, network, technology, experience, communication methods, social benefit and the connection between these aspects and allied enterprises.

Keywords: internationalisation, firms, cooperation agreement, case study, Spain, Colombia

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2722 Health Hazards in SME Garment Industries in India

Authors: Pranab Kumar Goswami

Abstract:

According to WHO, over 1000 million people worldwide are employed in small-scale industries. The ‘garment’ industry’ is one such industry in developing countries. These garment SMEs are mostly run by private establishments in the unorganized sector to avoid legal obligations of OSH provisions. The OSH standards are very poor and even basic health and safety provisions are not provided in such units. The study has been conducted in India among workers employed in the ‘garment’ industry with the objectives to analyze the types and extent of occupational health hazards of the garment workers and to assess the relationship of sociodemographic and occupational factors with various health hazards. The survey method, the tabular method followed by applying simple statistical technique, has been taken into account to analyze the data collected from three SME garment industries in Delhi (India-Asia). The study was conducted in Delhi from August-2019 to October-2020. A random sampling of 70 workers from three factories has been chosen for this study. The study shows that most of the workers were males (82%) and were in the 18-50 age group (78%), with none below 18 years of age. It was found that 26% of the workers were illiterate and most of them belonged to poor socioeconomic status. The study revealed that the nature of the hazards in garment industries in India is mostly physical and mechanical. We found that musculoskeletal problems (54%) were the commonest health problem. The body areas commonly affected were neck, low back, hand, wrist, finger, and shoulder. If garment workers’ health is affected by occupational hazards, it will impact on national health and economic growth of developing countries. Health is a joint responsibility of both government and employing authority.

Keywords: garment, MSD, health hazard, social factor

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2721 On the convergence of the Mixed Integer Randomized Pattern Search Algorithm

Authors: Ebert Brea

Abstract:

We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.

Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain

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2720 Valence Effects on Episodic Memory Retrieval Following Exposure to Arousing Stimuli in Young and Old Adults

Authors: Marianna Constantinou, Hana Burianova, Ala Yankouskaya

Abstract:

Episodic memory retrieval benefits from arousal, with better performance linked to arousing to-be-remembered information. However, the enduring impact of arousal on subsequent memory processes, particularly for non-arousing stimuli, remains unclear. This functional Magnetic Resonance Imaging (fMRI) study examined the effects of arousal on episodic memory processes in young and old adults, focusing on memory of neutral information following arousal exposure. Neural activity was assessed at three distinct timepoints: during exposure to arousing and non-arousing stimuli, memory consolidation (with or without arousing stimulus exposure), and during memory retrieval (with or without arousing stimulus exposure). Behavioural results show that across both age groups, participants performed worse when retrieving episodic memories about a video preceded by a highly arousing negative image. Our fMRI findings reveal three key findings: i) the extension of the influence of negative arousal beyond encoding; ii) the presence of this influence in both young and old adults; iii) and the differential treatment of positive arousal between these age groups. Our findings emphasise valence-specific effects on memory processes and support the enduring impact of negative arousal. We further propose an age-related alteration in the old adult brain in differentiating between positive and negative arousal.

Keywords: episodic memory, ageing, fmri, arousal, valence

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2719 The Analysis of Split Graphs in Social Networks Based on the k-Cardinality Assignment Problem

Authors: Ivan Belik

Abstract:

In terms of social networks split graphs correspond to the variety of interpersonal and intergroup relations. In this paper we analyse the interaction between the cliques (socially strong and trusty groups) and the independent sets (fragmented and non-connected groups of people) as the basic components of any split graph. Based on the Semi-Lagrangean relaxation for the k-cardinality assignment problem we show the way of how to minimize the socially risky interactions between the cliques and the independent sets within the social network.

Keywords: cliques, independent sets, k-cardinality assignment, social networks, split graphs

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2718 Reconstructing the Trace of Mesozoic Subduction and Its Implication on Stratigraphy Correlation between Deep Marine Sediment and Granite: Case Study of Garba Complex, South Sumatera

Authors: Fadlan Atmaja Nursiwan, Ugi Kurnia Gusti

Abstract:

Garba Hill, located in Tekana Village, South Sumatera Province is comprised to South Sumatra Basin and classified as back arc basin. This area is entered as an active margin of Sundaland which experiences subduction several times since Mesozoic to recent time. The traces of Mesozoic subduction in the southern part of Sumatra island are exposed in Garba Hill area. The aim of this investigation is to study the tectonic changes in the first phase in Mesozoic era at the active margin of Sundaland which causes the rocks assemblage in Garba hill consist of continental and oceanic plate rocks which the correlation between those rocks show indistinct relation. This investigation is conducted by field observation in Tekana village and Lubar Village, Muara Dua, South Sumatra along with laboratory analysis included fossil and geochemistry analysis of radiolarian chert, petrography analysis of granite and basalt, and structural modelling. Fossil and geochemistry analysis of radiolarian chert and geochemistry of granite rocks shown the relation between the two rocks and Mesozoic subduction of Woyla terrane on western margin of Sundaland. Petrography analysis from granite and basalt depict the tectonic affinity of rocks. Moreover, structural analysis showed the changes of lineation direction from N-S to WNW-ESE.

Keywords: granite, mesozoic, radiolarian, subduction traces

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2717 Valorization of Waste Reverse Osmosis Desalination Brine and Crystallization Sequence Approach for Kainite Recovery

Authors: Ayoub Bouazza, Ali Faddouli, Said Amal, Rachid Benhida, Khaoula Khaless

Abstract:

Brine waste generated from reverse osmosis (RO) desalination plants contains various valuable compounds, mainly salts, trace elements, and organic matter. These wastes are up to two times saltier than standard seawater. Therefore, there is a strong economic interest in recovering these salts. The current practice in desalination plants is to reject the brine back to the sea, which affects the marine ecosystem and the environment. Our study aims to bring forth a reliable management solution for the valorisation of waste brines. Natural evaporation, isothermal evaporation at 25°C and 50°C, and evaporation using continuous heating were used to crystallize valuable salts from a reverse osmosis desalination plant brine located on the Moroccan Atlantic coast. The crystallization sequence of the brine was studied in comparison with standard seawater. The X-Ray Diffraction (XRD) of the precipitated solid phases showed similar results, where halite was the main solid phase precipitated from both the brine and seawater. However, Jänecke diagram prediction, along with FREZCHEM simulations, showed that Kainite should crystallize before Epsomite and Carnallite. As the absence of kainite formation in many experiments in the literature has been related to the metastability of kainite and the critical relative humidity conditions, and the precipitation of K–Mg salts is very sensitive to climatic conditions. An evaporation process is proposed as a solution to achieve the predicted crystallization path and to affirm the recovery of Kainite.

Keywords: salts crystallization, reverse osmosis, solar evaporation, frezchem, ZLD

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2716 An Intelligent Scheme Switching for MIMO Systems Using Fuzzy Logic Technique

Authors: Robert O. Abolade, Olumide O. Ajayi, Zacheaus K. Adeyemo, Solomon A. Adeniran

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Link adaptation is an important strategy for achieving robust wireless multimedia communications based on quality of service (QoS) demand. Scheme switching in multiple-input multiple-output (MIMO) systems is an aspect of link adaptation, and it involves selecting among different MIMO transmission schemes or modes so as to adapt to the varying radio channel conditions for the purpose of achieving QoS delivery. However, finding the most appropriate switching method in MIMO links is still a challenge as existing methods are either computationally complex or not always accurate. This paper presents an intelligent switching method for the MIMO system consisting of two schemes - transmit diversity (TD) and spatial multiplexing (SM) - using fuzzy logic technique. In this method, two channel quality indicators (CQI) namely average received signal-to-noise ratio (RSNR) and received signal strength indicator (RSSI) are measured and are passed as inputs to the fuzzy logic system which then gives a decision – an inference. The switching decision of the fuzzy logic system is fed back to the transmitter to switch between the TD and SM schemes. Simulation results show that the proposed fuzzy logic – based switching technique outperforms conventional static switching technique in terms of bit error rate and spectral efficiency.

Keywords: channel quality indicator, fuzzy logic, link adaptation, MIMO, spatial multiplexing, transmit diversity

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2715 Performance Comparison of Outlier Detection Techniques Based Classification in Wireless Sensor Networks

Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

Abstract:

Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

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2714 Large Eddy Simulations for Flow Blurring Twin-Fluid Atomization Concept Using Volume of Fluid Method

Authors: Raju Murugan, Pankaj S. Kolhe

Abstract:

The present study is mainly focusing on the numerical simulation of Flow Blurring (FB) twin fluid injection concept was proposed by Ganan-Calvo, which involves back flow atomization based on global bifurcation of liquid and gas streams, thus creating two-phase flow near the injector exit. The interesting feature of FB injector spray is an insignificant effect of variation in atomizing air to liquid ratio (ALR) on a spray cone angle. Besides, FB injectors produce a nearly uniform spatial distribution of mean droplet diameter and are least susceptible to variation in thermo-physical properties of fuels, making it a perfect candidate for fuel flexible combustor development. The FB injector working principle has been realized through experimental flow visualization techniques only. The present study explores potential of ANSYS Fluent based Large Eddy Simulation(LES) with volume of fluid (VOF) method to investigate two-phase flow just upstream of injector dump plane and spray quality immediate downstream of injector dump plane. Note that, water and air represent liquid and gas phase in all simulations and ALR is varied by changing the air mass flow rate alone. Preliminary results capture two phase flow just upstream of injector dump plane and qualitative agreement is observed with the available experimental literature.

Keywords: flow blurring twin fluid atomization, large eddy simulation, volume of fluid, air to liquid ratio

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2713 Pre-Shared Key Distribution Algorithms' Attacks for Body Area Networks: A Survey

Authors: Priti Kumari, Tricha Anjali

Abstract:

Body Area Networks (BANs) have emerged as the most promising technology for pervasive health care applications. Since they facilitate communication of very sensitive health data, information leakage in such networks can put human life at risk, and hence security inside BANs is a critical issue. Safe distribution and periodic refreshment of cryptographic keys are needed to ensure the highest level of security. In this paper, we focus on the key distribution techniques and how they are categorized for BAN. The state-of-art pre-shared key distribution algorithms are surveyed. Possible attacks on algorithms are demonstrated with examples.

Keywords: attacks, body area network, key distribution, key refreshment, pre-shared keys

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2712 Status Report of the Express Delivery Industry in China

Authors: Ying Bo Xie, Hisa Yuki Kurokawa

Abstract:

Due to the fast development, China's express delivery industry has involved in a dilemma that the service quality are keeping decreasing while the construction rate of delivery network cannot meet the customers’ demand. In order to get out of this dilemma and enjoy a succession development rate, it is necessary to understand the current situation of China's express delivery industry. Firstly, the evolution of China's express delivery industry was systematical presented. Secondly, according to the number of companies and the amount of parcels they has dealt each year, the merits and faults of tow kind of operating pattern was analyzed. Finally, based on the characteristics of these express companies, the problems of China's express delivery industry was divided into several types and the countermeasures were given out respectively.

Keywords: China, express delivery industry, status, problem

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2711 About the Case Portfolio Management Algorithms and Their Applications

Authors: M. Chumburidze, N. Salia, T. Namchevadze

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This work deal with case processing problems in business. The task of strategic credit requirements management of cases portfolio is discussed. The information model of credit requirements in a binary tree diagram is considered. The algorithms to solve issues of prioritizing clusters of cases in business have been investigated. An implementation of priority queues to support case management operations has been presented. The corresponding pseudo codes for the programming application have been constructed. The tools applied in this development are based on binary tree ordering algorithms, optimization theory, and business management methods.

Keywords: credit network, case portfolio, binary tree, priority queue, stack

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2710 Assessing the Influence of Station Density on Geostatistical Prediction of Groundwater Levels in a Semi-arid Watershed of Karnataka

Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

Abstract:

The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

Procedia PDF Downloads 53
2709 Four-Electron Auger Process for Hollow Ions

Authors: Shahin A. Abdel-Naby, James P. Colgan, Michael S. Pindzola

Abstract:

A time-dependent close-coupling method is developed to calculate a total, double and triple autoionization rates for hollow atomic ions of four-electron systems. This work was motivated by recent observations of the four-electron Auger process in near K-edge photoionization of C+ ions. The time-dependent close-coupled equations are solved using lattice techniques to obtain a discrete representation of radial wave functions and all operators on a four-dimensional grid with uniform spacing. Initial excited states are obtained by relaxation of the Schrodinger equation in imaginary time using a Schmidt orthogonalization method involving interior subshells. The radial wave function grids are partitioned over the cores on a massively parallel computer, which is essential due to the large memory requirements needed to store the coupled-wave functions and the long run times needed to reach the convergence of the ionization process. Total, double, and triple autoionization rates are obtained by the propagation of the time-dependent close-coupled equations in real-time using integration over bound and continuum single-particle states. These states are generated by matrix diagonalization of one-electron Hamiltonians. The total autoionization rates for each L excited state is found to be slightly above the single autoionization rate for the excited configuration using configuration-average distorted-wave theory. As expected, we find the double and triple autoionization rates to be much smaller than the total autoionization rates. Future work can be extended to study electron-impact triple ionization of atoms or ions. The work was supported in part by grants from the American University of Sharjah and the US Department of Energy. Computational work was carried out at the National Energy Research Scientific Computing Center (NERSC) in Berkeley, California, USA.

Keywords: hollow atoms, autoionization, auger rates, time-dependent close-coupling method

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2708 Optoelectronic Hardware Architecture for Recurrent Learning Algorithm in Image Processing

Authors: Abdullah Bal, Sevdenur Bal

Abstract:

This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.

Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware

Procedia PDF Downloads 505
2707 Concept of Automation in Management of Electric Power Systems

Authors: Richard Joseph, Nerey Mvungi

Abstract:

An electric power system includes a generating, a transmission, a distribution and consumers subsystems. An electrical power network in Tanzania keeps growing larger by the day and become more complex so that, most utilities have long wished for real-time monitoring and remote control of electrical power system elements such as substations, intelligent devices, power lines, capacitor banks, feeder switches, fault analyzers and other physical facilities. In this paper, the concept of automation of management of power systems from generation level to end user levels was determined by using Power System Simulator for Engineering (PSS/E) version 30.3.2.

Keywords: automation, distribution subsystem, generating subsystem, PSS/E, TANESCO, transmission subsystem

Procedia PDF Downloads 669
2706 Cloud-Based Mobile-to-Mobile Computation Offloading

Authors: Ebrahim Alrashed, Yousef Rafique

Abstract:

Mobile devices have drastically changed the way we do things on the move. They are being extremely relied on to perform tasks that are analogous to desktop computer capability. There has been a rapid increase of computational power on these devices; however, battery technology is still the bottleneck of evolution. The primary modern approach day approach to tackle this issue is offloading computation to the cloud, proving to be latency expensive and requiring high network bandwidth. In this paper, we explore efforts to perform barter-based mobile-to-mobile offloading. We present define a protocol and present an architecture to facilitate the development of such a system. We further highlight the deployment and security challenges.

Keywords: computational offloading, power conservation, cloud, sandboxing

Procedia PDF Downloads 384
2705 Optimization for Autonomous Robotic Construction by Visual Guidance through Machine Learning

Authors: Yangzhi Li

Abstract:

Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 84