Search results for: network analysis.

Authors: J. Khorshidi, E. Zare, A.R. Khademi

Abstract:

The reduction of energy consumption through improvements in energy efficiency has become an important goal for all industries, in order to improve the efficiency of the economy, and to reduce the emissions of Co₂ caused by power generation. The objective of this paper is to investigate opportunities to increase process energy efficiency at the distillation unit of Shiraz oil refinery in south of Iran. The main aim of the project is to locate energy savings by use of pinch technology and to assess them. At first all the required data of hot and cold streams in preheating section of distillation unit has been extracted from the available flow sheets and then pinch analysis has been conducted. The present case study is a threshold one which does not need any utilities. After running range, targeting several heat exchanger networks were designed with respect to operating conditions and different ΔT_min. The optimal value of ΔT_min was calculated to be 22.3 °C. Based on this optimal value, there will be 5% reduction in annual total cost of heat exchanger network.

Keywords: Pinch technology, heat exchanger network, operating cost.

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Authors: Mughal Yar M, Israr Ul Haq, Bushra Noman

Abstract:

The stem cells have ability to differentiated themselves through mitotic cell division and various range of specialized cell types. Cellular differentiation is a way by which few specialized cell develops into more specialized.This paper studies the fundamental problem of computational schema for an artificial neural network based on chemical, physical and biological variables of state. By doing this type of study system could be model for a viable propagation of various economically important stem cells differentiation. This paper proposes various differentiation outcomes of artificial neural network into variety of potential specialized cells on implementing MATLAB version 2009. A feed-forward back propagation kind of network was created to input vector (five input elements) with single hidden layer and one output unit in output layer. The efficiency of neural network was done by the assessment of results achieved from this study with that of experimental data input and chosen target data. The propose solution for the efficiency of artificial neural network assessed by the comparatative analysis of “Mean Square Error" at zero epochs. There are different variables of data in order to test the targeted results.

Keywords: Computational shcmin, meiosis, mitosis, neuralnetwork, Stem cell SOM;

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Authors: B. Juhasova, I. Halenar, M. Juhas

Abstract:

The wireless communication is one of the widely used methods of data transfer at the present days. The benefit of this communication method is the partial independence of the infrastructure and the possibility of mobility. In some special applications it is the only way how to connect. This paper presents some problems in the implementation of a sensor network connection for measuring environmental parameters in the area of manufacturing plants.

Keywords: Network, communication, reliability, sensors.

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Authors: Panagiotis Karadimos, Leonidas Anthopoulos

Abstract:

Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: Actual cost and duration, attribute selection, bridge projects, neural networks, predicting models, FANN TOOL, WEKA.

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Authors: Usha Chouhan, K. R. Pardasani

Abstract:

Phylogenies ; The evolutionary histories of groups of species are one of the most widely used tools throughout the life sciences, as well as objects of research with in systematic, evolutionary biology. In every phylogenetic analysis reconstruction produces trees. These trees represent the evolutionary histories of many groups of organisms, bacteria due to horizontal gene transfer and plants due to process of hybridization. The process of gene transfer in bacteria and hybridization in plants lead to reticulate networks, therefore, the methods of constructing trees fail in constructing reticulate networks. In this paper a model has been employed to reconstruct phylogenetic network in honey bee. This network represents reticulate evolution in honey bee. The maximum parsimony approach has been used to obtain this reticulate network.

Keywords: Hybridization, HGT, Reticulate networks, Recombination, Species, Parsimony.

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Authors: F. O. Aron, T. O. Olwal, A. Kurien, M. O. Odhiambo

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A considerable amount of energy is consumed during transmission and reception of messages in a wireless mesh network (WMN). Reducing per-node transmission power would greatly increase the network lifetime via power conservation in addition to increasing the network capacity via better spatial bandwidth reuse. In this work, the problem of topology control in a hybrid WMN of heterogeneous wireless devices with varying maximum transmission ranges is considered. A localized distributed topology control algorithm is presented which calculates the optimal transmission power so that (1) network connectivity is maintained (2) node transmission power is reduced to cover only the nearest neighbours (3) networks lifetime is extended. Simulations and analysis of results are carried out in the NS-2 environment to demonstrate the correctness and effectiveness of the proposed algorithm.

Keywords: Topology Control, Wireless Mesh Networks, Backbone, Energy Efficiency, Localized Algorithm.

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Authors: Siska Soesanti, Norihiro Nakai

Abstract:

Bandung city center can be deemed as economic, social and cultural center. However the city center suffers from deterioration. The retail activities tend to shift outward the city center. Numerous idyllic residences changed into business premises in two villages situated in the north part of the city during 1990s, especially after a new highway and flyover opened. According to space syntax theory, the pattern of spatial integration in the urban grid is a prime determinant of movement patterns in the system. The syntactic analysis results show the flyover has insignificant influence on street network in the city center. However the flyover has been generating a major difference in the new commercial area since it has become relatively as strategic as the city center. Besides street network, local government policy, rapid private motorization and particular condition of each site also played important roles in encouraging the current commercial areas to flourish.

Keywords: City center, commercial area, space syntax, street network.

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Authors: Insung Jung, Gi-Nam Wang

Abstract:

The objective of this paper is to a design of pattern classification model based on the back-propagation (BP) algorithm for decision support system. Standard BP model has done full connection of each node in the layers from input to output layers. Therefore, it takes a lot of computing time and iteration computing for good performance and less accepted error rate when we are doing some pattern generation or training the network. However, this model is using exclusive connection in between hidden layer nodes and output nodes. The advantage of this model is less number of iteration and better performance compare with standard back-propagation model. We simulated some cases of classification data and different setting of network factors (e.g. hidden layer number and nodes, number of classification and iteration). During our simulation, we found that most of simulations cases were satisfied by BP based using exclusive connection network model compared to standard BP. We expect that this algorithm can be available to identification of user face, analysis of data, mapping data in between environment data and information.

Keywords: Neural network, Back-propagation, classification.

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Authors: Ch. Antonopoulos, Th. Kapourniotis, V. Triantafillou

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Optimum communication and performance in Wireless Sensor Networks, constitute multi-facet challenges due to the specific networking characteristics as well as the scarce resource availability. Furthermore, it is becoming increasingly apparent that isolated layer based approaches often do not meet the demands posed by WSNs applications due to omission of critical inter-layer interactions and dependencies. As a counterpart, cross-layer is receiving high interest aiming to exploit these interactions and increase network performance. However, in order to clearly identify existing dependencies, comprehensive performance studies are required evaluating the effect of different critical network parameters on system level performance and behavior.This paper-s main objective is to address the need for multi-parametric performance evaluations considering critical network parameters using a well known network simulator, offering useful and practical conclusions and guidelines. The results reveal strong dependencies among considered parameters which can be utilized by and drive future research efforts, towards designing and implementing highly efficient protocols and architectures.

Keywords: Wireless sensor network, Communication Systems, cross-layer architectures, simulation based performance evaluation

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Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali

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The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several subnetworks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.

Keywords: Wireless sensor networks, routing protocols, ad hoc topology, cluster, sub-network, WSN design requirements.

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Authors: M. Shariati, N. Tahouni, A. Khoshgard, M.H. Panjeshahi

Abstract:

Owing to extensive use of hydrogen in refining or petrochemical units, it is essential to manage hydrogen network in order to make the most efficient utilization of hydrogen. On the other hand, hydrogen is an important byproduct not properly used through petrochemical complexes and mostly sent to the fuel system. A few works have been reported in literature to improve hydrogen network for petrochemical complexes. In this study a comprehensive analysis is carried out on petrochemical units using a modified automated targeting technique which is applied to determine the minimum hydrogen consumption. Having applied the modified targeting method in two petrochemical cases, the results showed a significant reduction in required fresh hydrogen.

Keywords: Automated targeting, Hydrogen network, Petrochemical, Process integration.

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Authors: Wernhuar Tarng, Kun-Jie Huang, Li-Zhong Deng, Kun-Rong Hsie, Mingteh Chen

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In recent years, the research in wireless sensor network has increased steadily, and many studies were focusing on reducing energy consumption of sensor nodes to extend their lifetimes. In this paper, the issue of energy consumption is investigated and two adaptive mechanisms are proposed to extend the network lifetime. This study uses high-energy-first scheme to determine cluster heads for data transmission. Thus, energy consumption in each cluster is balanced and network lifetime can be extended. In addition, this study uses cluster merging and dynamic routing mechanisms to further reduce energy consumption during data transmission. The simulation results show that the proposed method can effectively extend the lifetime of wireless sensor network, and it is suitable for different base station locations.

Keywords: Wireless sensor network, high-energy-first scheme, adaptive mechanisms, network lifetime

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Authors: H. Izadbakhsh, M.Hour Ali, A. Amirkhani, A. Montazeri, M. Saberi

Abstract:

The after–sales activities are nowadays acknowledged as a relevant source of revenue, profit and competitive advantage in most manufacturing industries. Top and middle management, therefore, should focus on the definition of a structured business performance measurement system for the after-sales business. The paper aims at filling this gap, and presents an integrated methodology for the after-sales network performance measurement, and provides an empirical application to automotive case companies and their official service network. This is the first study that presents an integrated multivariate approach for total assessment and improvement of after-sale services.

Keywords: Data Envelopment Analysis (DEA), Principal Component Analysis (PCA), Automotive companies, After-sale services.

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Authors: Kelvin Rozier, Vladimir E. Bondarenko

Abstract:

It is known that an analog Hopfield neural network with time delay can generate the outputs which are similar to the human electroencephalogram. To gain deeper insights into the mechanisms of rhythm generation by the Hopfield neural networks and to study the effects of noise on their activities, we investigated the behaviors of the networks with symmetric and asymmetric interneuron connections. The neural network under the study consists of 10 identical neurons. For symmetric (fully connected) networks all interneuron connections aij = +1; the interneuron connections for asymmetric networks form an upper triangular matrix with non-zero entries aij = +1. The behavior of the network is described by 10 differential equations, which are solved numerically. The results of simulations demonstrate some remarkable properties of a Hopfield neural network, such as linear growth of outputs, dependence of synchronization properties on the connection type, huge amplification of oscillation by the external uniform noise, and the capability of the neural network to transform one type of noise to another.

Keywords: Chaos, Hopfield neural network, noise, synchronization

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Authors: I. Omerhodzic, S. Avdakovic, A. Nuhanovic, K. Dizdarevic

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In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.

Keywords: Epilepsy, EEG, Wavelet transform, Energydistribution, Neural Network, Classification.

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Authors: Dewan Md. Farid, Nouria Harbi, Suman Ahmmed, Md. Zahidur Rahman, Chowdhury Mofizur Rahman

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Network security attacks are the violation of information security policy that received much attention to the computational intelligence society in the last decades. Data mining has become a very useful technique for detecting network intrusions by extracting useful knowledge from large number of network data or logs. Naïve Bayesian classifier is one of the most popular data mining algorithm for classification, which provides an optimal way to predict the class of an unknown example. It has been tested that one set of probability derived from data is not good enough to have good classification rate. In this paper, we proposed a new learning algorithm for mining network logs to detect network intrusions through naïve Bayesian classifier, which first clusters the network logs into several groups based on similarity of logs, and then calculates the prior and conditional probabilities for each group of logs. For classifying a new log, the algorithm checks in which cluster the log belongs and then use that cluster-s probability set to classify the new log. We tested the performance of our proposed algorithm by employing KDD99 benchmark network intrusion detection dataset, and the experimental results proved that it improves detection rates as well as reduces false positives for different types of network intrusions.

Keywords: Clustering, detection rate, false positive, naïveBayesian classifier, network intrusion detection.

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Authors: H. Shayeghi, M. Mahdavi

Abstract:

Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.

Keywords: Adequacy Optimization, Transmission Expansion Planning, DCGA.

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Authors: S. Jadid, S. Jalilzadeh

Abstract:

In this paper, an improved technique for contingency ranking using artificial neural network (ANN) is presented. The proposed approach is based on multi-layer perceptrons trained by backpropagation to contingency analysis. Severity indices in dynamic stability assessment are presented. These indices are based on the concept of coherency and three dot products of the system variables. It is well known that some indices work better than others for a particular power system. This paper along with test results using several different systems, demonstrates that combination of indices with ANN provides better ranking than a single index. The presented results are obtained through the use of power system simulation (PSS/E) and MATLAB 6.5 software.

Keywords: composite indices, transient stability, neural network.

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Authors: Areej Babiker Idris Babiker, Rosdiazli Ibrahim

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Gas chromatography (GC) is the most widely used technique in analytical chemistry. However, GC has high initial cost and requires frequent maintenance. This paper examines the feasibility and potential of using a neural network model as an alternative whenever GC is unvailable. It can also be part of system verification on the performance of GC for preventive maintenance activities. It shows the performance of MultiLayer Perceptron (MLP) with Backpropagation structure. Results demonstrate that neural network model when trained using this structure provides an adequate result and is suitable for this purpose. cm.

Keywords: Analyzer, Levenberg-Marquardt, Gas chromatography, Neural network

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Authors: Masoud Hassanzade Novin, Bahloul Salmani

Abstract:

The process of the translation is not merely the linguistic aspects. It is also considered in the cultural framework of both the source and target text cultures. The translation process and translated texts are confronted the new aspect in 20th century which is considered mostly in the patronage framework and ideological grillwork of the target language. To have these factors scrutinized in the process of the translation both micro-element factors and macro-element factors can be taken into consideration. For the purpose of this study through a qualitative type of research based on critical discourse analysis approach, the case study of the novel “1984” written by George Orwell was chosen as the corpus of the study to have the contrastive analysis by its Persian translated texts. Results of the study revealed some distortions embedded in the target texts which were overshadowed by ideological aspect and patronage network. The outcomes of the manipulated terms were different in various categories which revealed the manipulation aspects in the texts translated.

Keywords: Critical discourse analysis, ideology, translated texts, patronage network.

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Authors: K. Geetha, P. Thangaraj

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Mobile Ad Hoc Networks (MANETs) is a collection of mobile devices forming a communication network without infrastructure. MANET is vulnerable to security threats due to network’s limited security, dynamic topology, scalability and the lack of central management. The Quality of Service (QoS) routing in such networks is limited by network breakage caused by node mobility or nodes energy depletions. The impact of node mobility on trust establishment is considered and its use to propagate trust through a network is investigated in this paper. This work proposes an enhanced Associativity Based Routing (ABR) with Fuzzy based Trust (Fuzzy- ABR) routing protocol for MANET to improve QoS and to mitigate network attacks.

Keywords: Mobile Ad hoc Networks (MANET), Associativity Based Routing (ABR), Fuzzy based Computed Trust.

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Authors: Jolly Shah, S.S.Rattan, B.C.Nakra

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Automatic control of the robotic manipulator involves study of kinematics and dynamics as a major issue. This paper involves the forward and inverse kinematics of 2-DOF robotic manipulator with revolute joints. In this study the Denavit- Hartenberg (D-H) model is used to model robot links and joints. Also forward and inverse kinematics solution has been achieved using Artificial Neural Networks for 2-DOF robotic manipulator. It shows that by using artificial neural network the solution we get is faster, acceptable and has zero error.

Keywords: Artificial Neural Network, Forward Kinematics, Inverse Kinematics, Robotic Manipulator

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Authors: Wann-Ming Wey

Abstract:

In today's popularity and progress of information technology, the big data set and its analysis are no longer a major conundrum. Now, we could not only use the relevant big data to analysis and emulate the possible status of urban development in the near future, but also provide more comprehensive and reasonable policy implementation basis for government units or decision-makers via the analysis and emulation results as mentioned above. In this research, we set Taipei City as the research scope, and use the relevant big data variables (e.g., population, facility utilization and related social policy ratings) and Analytic Network Process (ANP) approach to implement in-depth research and discussion for the possible reduction of land use in primary and secondary schools of Taipei City. In addition to enhance the prosperous urban activities for the urban public facility utilization, the final results of this research could help improve the efficiency of urban land use in the future. Furthermore, the assessment model and research framework established in this research also provide a good reference for schools or other public facilities land use and adaptive reuse strategies in the future.

Keywords: Adaptive reuse, analytic network process, big data, land use strategy.

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Authors: Wipada Chiawchan

Abstract:

This study found that most corporate personnel are using social media to communicate with colleagues to make the process of working more efficient. Complete satisfaction occurred on the use of security within the University’s computer network. The social network usage for communication, collaboration, entertainment and demonstrating concerns accounted for fifty percent of variance to predict interpersonal relationships of corporate personnel. This evaluation on the effectiveness of social networking involved 213 corporate personnel’s. The data was collected by questionnaires. This data was analyzed by using percentage, mean, and standard deviation. The results from the analysis and the effectiveness of using online social networks were derived from the attitude of private users and safety data within the security system. The results showed that the effectiveness on the use of an online social network for corporate personnel of Suan Sunandha Rajabhat University was specifically at a good level, and the overall effects of each aspect was (Ẋ=3.11).

Keywords: Behaviors, Social Media, Social Network.

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Authors: Juha Kettunen

Abstract:

This study analyzes the quality and the size of the strategic network of higher education institutions. The study analyses the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented of the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: Higher education, network, research and development, strategic management.

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Authors: J. Augutis, R. Krikstolaitis, L. Martisauskas

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Recently global concerns for the energy security have steadily been on the increase and are expected to become a major issue over the next few decades. Energy security refers to a resilient energy system. This resilient system would be capable of withstanding threats through a combination of active, direct security measures and passive or more indirect measures such as redundancy, duplication of critical equipment, diversity in fuel, other sources of energy, and reliance on less vulnerable infrastructure. Threats and disruptions (disturbances) to one part of the energy system affect another. The paper presents methodology in theoretical background about energy system as an interconnected network and energy supply disturbances impact to the network. The proposed methodology uses a network flow approach to develop mathematical model of the energy system network as the system of nodes and arcs with energy flowing from node to node along paths in the network.

Keywords: Energy Security, Energy Supply Disturbances, Modeling of Energy System, Network Flow

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Authors: Efendi Zaenudin, Chien-Hung Huang, Ka-Lok Ng

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Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.

Keywords: Biological molecular networks, essential genes, graph theory, network subgraphs.

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Authors: Ekow A. Kwofie, Emmanuel K. Anto, Godfred Mensah

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In this paper, CYME Distribution software has been used to assess the impacts of solar Photovoltaic (PV) distributed generation (DG) plant on the Electricity Company of Ghana (ECG) 33 kV sub-transmission network at different PV penetration levels. As ECG begins to encourage DG PV interconnections within its network, there has been the need to assess the impacts on the sub-transmission losses and voltage contribution. In Tema, a city in Accra - Ghana, ECG has a 33 kV sub-transmission network made up of 20 No. 33 kV buses that was modeled. Three different locations were chosen: The source bus, a bus along the sub-transmission radial network and a bus at the tail end to determine the optimal location for DG PV interconnection. The optimal location was determined based on sub-transmission technical losses and voltage impact. PV capacities at different penetration levels were modeled at each location and simulations performed to determine the optimal PV penetration level. Interconnection at a bus along (or in the middle of) the sub-transmission network offered the highest benefits at an optimal PV penetration level of 80%. At that location, the maximum voltage improvement of 0.789% on the neighboring 33 kV buses and maximum loss reduction of 6.033% over the base case scenario were recorded. Hence, the optimal location for DG PV integration within the 33 kV sub-transmission utility network is at a bus along the sub-transmission radial network.

Keywords: Distributed generation photovoltaic, DG PV, optimal location, penetration level, sub-transmission network.

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

Abstract:

This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: Landslide, limit analysis, ANN, soil properties.

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Authors: Goran Djukanovic, Goran Popovic

Abstract:

A special area in the study of Wireless Sensor Networks (WSNs) is how to move sensor nodes, as it expands the scope of application of wireless sensors and provides new opportunities to improve network performance. On the other side, it opens a set of new problems, especially if complete clusters are mobile. Node mobility can prolong the network lifetime. In such WSN, some nodes are possibly moveable or nomadic (relocated periodically), while others are static. This paper presents an idea of mobile, solar-powered CHs that relocate themselves inside clusters in such a way that the total energy consumption in the network reduces, and the lifetime of the network extends. Positioning of CHs is made in each round based on selfish herd hypothesis, where leader retreats to the center of gravity. Based on this idea, an algorithm, together with its modified version, has been presented and tested in this paper. Simulation results show that both algorithms have benefits in network lifetime, and prolongation of network stability period duration.

Keywords: CH-active algorithm, mobile cluster head, sensors, wireless sensor network.

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