Search results for: fifth-generation district heating network

Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: P. Prasanna Murali Krishna, M. V. Subramanyam, K. Satya Prasad

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File sharing in networks are generally achieved using Peer-to-Peer (P2P) applications. Structured P2P approaches are widely used in adhoc networks due to its distributed and scalability features. Efficient mechanisms are required to handle the huge amount of data distributed to all peers. The intrinsic characteristics of P2P system makes for easier content distribution when compared to client-server architecture. All the nodes in a P2P network act as both client and server, thus, distributing data takes lesser time when compared to the client-server method. CHORD protocol is a resource routing based where nodes and data items are structured into a 1- dimensional ring. The structured lookup algorithm of Chord is advantageous for distributed P2P networking applications. Though, structured approach improves lookup performance in a high bandwidth wired network it could contribute to unnecessary overhead in overlay networks leading to degradation of network performance. In this paper, the performance of existing CHORD protocol on Wireless Mesh Network (WMN) when nodes are static and dynamic is investigated.

Keywords: wireless mesh network (WMN), structured P2P networks, peer to peer resource sharing, CHORD Protocol, DHT

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Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Sheng Fu, Yinbo Gao, Hao Lin

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In the current mine air compressors monitoring system, there are some difficulties in the installation and maintenance because of the wired connection. To solve the problem, this paper introduces a new air compressors monitoring system based on ZigBee in which the monitoring parameters are transmitted wirelessly. The collecting devices are designed to form a cluster network to collect vibration, temperature, and pressure of air cylinders and other parameters. All these devices are battery-powered. Besides, the monitoring software in PC is developed using MFC. Experiments show that the designed wireless sensor network works well in the site environmental condition and the system is very convenient to be installed since the wireless connection. This monitoring system will have a wide application prospect in the upgrade of the old monitoring system of the air compressors.

Keywords: condition monitoring, wireless sensor network, air compressor, zigbee, data collecting

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Authors: Ali Mohammad Mobaser Azad, Alireza Akhlaghinia

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Blockchain is changing our world and launching a new generation of decentralized networks. Meanwhile, Blockchain-based networks like Ethereum have been created and they will facilitate these processes using tools like smart contracts. The Ethereum has fundamental structures, each of which affects the activity of the nodes. Our purpose in this paper is to review similar research and examine various components to demonstrate the performance of the Ethereum network and to do this, and we used the data published by the Ethereum Foundation in different time spots to examine the number of changes that determine the status of network performance. This will help other researchers understand better Ethereum in different situations.

Keywords: blockchain, ethereum, smart contract, decentralization consensus algorithm

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Authors: Nurhayati Abdullah, Fauziah Sulaiman, Muhamad Azman Miskam, Rahmad Mohd Taib

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Banana pseudo-stem and fruit-bunch-stem are agricultural residues that can be used for conversion to bio-char, bio-oil, and gases by using thermochemical process. The aim of this work is to characterize banana pseudo-stem and banana fruit-bunch-stem through proximate analysis, elemental analysis, chemical analysis, thermo-gravimetric analysis, and heating calorific value. The ash contents of the banana pseudo-stem and banana fruit-bunch-stem are 11.0 mf wt.% and 20.6 mf wt.%; while the carbon content of banana pseudo-stem and fruit-bunch-stem are 37.9 mf wt.% and 35.58 mf wt.% respectively. The molecular formulas for banana stem and banana fruit-bunch-stem are C24H33NO26 and C19H29NO33 respectively. The measured higher heating values of banana pseudo-stem and banana fruit-bunch-stem are 15.5MJ/kg and 12.7 MJ/kg respectively. By chemical analysis, the lignin, cellulose, and hemicellulose contents in the samples will also be presented. The feasibility of the banana wastes to be a feedstock for thermochemical process in comparison with other biomass will be discussed in this paper.

Keywords: banana waste, biomass, renewable energy, thermo-chemical characteristics

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Authors: Hanlin Liu, Hua Li, Yintan AI

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Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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Authors: Rania Alshikhe, Vinita Jindal

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Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

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Authors: Worakrit Worananthakij, Kamonchanok Doungtadum, Nattagan Mingkwan, Supatsorn Chupong

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Natural products from herb have been used in different aspects of life as a result of their various biological activities. Generally, plant growth and production of secondary compounds largely depend on environmental conditions. To better understand this correlation, study on biological activity and soil parameter is necessary. This research aims to study the soil parameters which affect the efficiency of the antioxidant activity of essential oils extracted from the Zingiber zerumbet in three areas of Thailand, including Min Buri district, Bangkok province; Muang district, Chiang Mai province and Kaeng Sanam Nang district, Nakhon Ratchasima province. The soil samples in each area were collected and analyzed in the laboratory. The essential oil of Z. zerumbet in each province was extracted and tested for antioxidant activity by hydrodistillation method and DPPH (2,2-diphenyl-1-picrylhydrazyl radical) assay, respectively. The results showed that, the soil parameters such as pH, nitrogen, potassium and phosphorus elements and exchange of cations of soil specimen from Nakhon Ratchasima province were the highest (P<0.05) (6.10 ±0.03, 0.15 ± 0.04 percent of total nitrogen, 16.67 ± 0.46 mg/L, 3.35 ± 0.65 mg/kg and 12.87 ± 0.11 cmol/kg, respectively). In addition, IC50 (Inhibition Concentrtion of antioxidant at 50%) of Z. zerumbet essential oil collected from Nakhon Ratchasima showed the highest value (P<0.05) (1,400 µg/mL). In conclusion, the soil parameters are once important factor for the efficiency of essential oils extract from Z. zerumbet.

Keywords: antioxidant, essential oil, herb, soil parameter, Zingiber zerumbet

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Authors: Huy Q. Tran, Jungwon Huh, Kiseok Kwak, Choonghyun Kang

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Infrared thermography (IRT) technique has been proven to be a good method for nondestructive evaluation of concrete material. In the building, a broad range of applications has been used such as subsurface defect inspection, energy loss, and moisture detection. The purpose of this research is to consider the qualitative and quantitative performance of reinforced concrete deteriorations using active infrared thermography technique. An experiment of three different heating regimes was conducted on a concrete slab in the laboratory. The thermal characteristics of the IRT method, i.e., absolute contrast and observation time, are investigated. A linear relationship between the observation time and the real depth was established with a well linear regression R-squared of 0.931. The results showed that the absolute contrast above defective area increases with the rise of the size of delamination and the heating time. In addition, the depth of delamination can be predicted by using the proposal relationship of this study.

Keywords: concrete building, infrared thermography, nondestructive evaluation, subsurface delamination

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Authors: Zhao Haoyue

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Due to the combined effects of climate change, urban expansion, and population growth, various environmental issues, such as urban heat islands and pollution, arise. Therefore, reliable information on urban environmental climate is needed to address and mitigate the negative effects. The emergence of urban climate maps provides a practical basis for urban climate regulation and improvement. This article takes Shapingba District, Chongqing City, as an example to study the construction method of urban thermal environment climate maps based on GIS spatial analysis technology. The thermal load, ventilation potential analysis map, and thermal environment comprehensive analysis map were obtained. Based on the classification criteria obtained from the climate map, corresponding protection and planning mitigation measures have been proposed.

Keywords: urban climate, GIS, heat island analysis, urban thermal environment

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Authors: Yogi Sirodz Gaos, Irvan Wiradinata

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In the 500 kW Organic Rankine Cycle (ORC) power plant in Indonesia, an AFT (according to the Tubular Exchanger Manufacturers Association – TEMA) type shell and tube heat exchanger device is used as a pre-heating system for the ORC’s hot water circulation system. The pre-heating source is a waste heat recovery of the brine water, which is tapped from a geothermal power plant. The brine water itself has 5 MWₜₕ capacities, with average temperature of 170ᵒC, and 7 barg working pressure. The aim of this research is to examine the performance of the heat exchanger in the ORC system in a 500 kW ORC power plant. The data for this research were collected during the commissioning on the middle of December 2016. During the commissioning, the inlet temperature and working pressure of the brine water to the shell and tube type heat exchanger was 149ᵒC, and 4.4 barg respectively. Furthermore, the ΔT for the hot water circulation of the ORC system to the heat exchanger was 27ᵒC, with the inlet temperature of 140ᵒC. The pressure in the hot circulation system was dropped slightly from 7.4ᵒC to 7.1ᵒC. The flow rate of the hot water circulation was 80.5 m³/h. The presentation and discussion of a case study on the performance of the heat exchanger on the 500 kW ORC system is presented as follows: (1) the heat exchange duty is 2,572 kW; (2) log mean temperature of the heat exchanger is 13.2ᵒC; (3) the actual overall thermal conductivity is 1,020.6 W/m².K (4) the required overall thermal conductivity is 316.76 W/m².K; and (5) the over design for this heat exchange performance is 222.2%. An analysis of the heat exchanger detailed engineering design (DED) is briefly discussed. To sum up, this research concludes that the shell and tube heat exchangers technology demonstrated a good performance as pre-heating system for the ORC’s hot water circulation system. Further research need to be conducted to examine the performance of heat exchanger system on the ORC’s hot water circulation system.

Keywords: shell and tube, heat exchanger, organic Rankine cycle, performance, commissioning

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Authors: Jenin Zidan

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This research paper investigates how planning, urban design, and architectural decisions affect the long-term environmental sustainability of residential buildings. The study, which focuses on the Al-Malaz District in Riyadh, Saudi Arabia, looks into how strategic planning, innovative urban design, and sustainable architectural practices might help mitigate environmental concerns and promote sustainable development in rapidly growing cities. This study attempts to shed light on the interplay of urban planning, design, and architecture in constructing sustainable residential environments by conducting a thorough examination of case studies and empirical data.

Keywords: urban planning, sustainable architecture, urban environmental challenge, residential buildings, villa house type

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Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

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The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

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Authors: Mohammed A. Elhaj, Jamal S. Yassin

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Owing to the lack of synchronization between the solar energy availability and the heat demands in a specific application, the energy storing sub-system is necessary to maintain the continuity of thermal process. The present work is dealing with an active solar heating storing system in which an air solar collector is connected to storing unit where this energy is distributed and provided to the heated space in a controlled manner. The solar collector is a box type absorber where the air flows between a number of vanes attached between the collector absorber and the bottom plate. This design can improve the efficiency due to increasing the heat transfer area exposed to the flowing air, as well as the heat conduction through the metal vanes from the top absorbing surface. The storing unit is a packed bed type where the air is coming from the air collector and circulated through the bed in order to add/remove the energy through the charging / discharging processes, respectively. The major advantage of the packed bed storage is its high degree of thermal stratification. Numerical solution of the packed bed energy storage is considered through dividing the bed into a number of equal segments for the bed particles and solved the energy equation for each segment depending on the neighbor ones. The studied design and performance parameters in the developed simulation model including, particle size, void fraction, etc. The final results showed that the collector efficiency was fluctuated between 55%-61% in winter season (January) under the climatic conditions of Misurata in Libya. Maximum temperature of 52ºC is attained at the top of the bed while the lower one is 25ºC at the end of the charging process of hot air into the bed. This distribution can satisfy the required load for the most house heating in Libya.

Keywords: solar energy, thermal process, performance, collector, packed bed, numerical analysis, simulation

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez, Mehdi Mrad

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We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defender-based-network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k > 1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: defense/attack strategies, large scale, networks, partitioning a network

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Authors: Vishal H. Shukla, Sanjay B. Deshmukh

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Traffic engineering, at its center, is the ability of moving traffic approximately so that traffic from a congested link is moved onto the unused capacity on another link. Traffic Engineering ensures the best possible use of the resources. Now to support traffic engineering in the today’s network, Multiprotocol Label Switching (MPLS) is being used which is very helpful for reliable packets delivery in an ongoing internet services. Here a topology is been implemented on GNS3 to focus on the analysis of the communication take place from one site to other through the ISP. The comparison is made between the IP network & MPLS network based on Bandwidth & Jitter which are one of the performance parameters using JPERF simulator.

Keywords: GNS3, JPERF, MPLS, traffic engineering, VMware

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Authors: Afaneen Anwer, Samara M. Kamil

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Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

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Authors: Boukari Nassim

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This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

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Authors: Arfan Riasat, M. Iqbal Zafar, Gulfam Riasat

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Pakistani women actively participate in livestock management activities, along with their normal domestic chores. The study was designed to measure the position and contribution of rural women, their constraints in livestock management activities and mainly how the rural women contribute for development in the district Faisalabad. It was envisioned that women participation in livestock activities have rarely been investigated. A multistage random sampling technique was used to collect the data from Tehsil Summandry of the district selected at random. Two union councils were taken by using simple random sampling technique. Four Chak (village) from each union council were selected at random and fifteen woman were further selected randomly from each selected chak. The results show that a vast majority of women were illiterate, having annual family income of one to two lac. They are living in joint family system. Their main occupation is agriculture and they spend long hours in whole livestock related activities to support their families. A large proportion of the respondents reported that they had to face problems and constraints in livestock activities in the context of decision making, medication, awareness, training along with social and economic issues. Analysis indicated that education level of women, income of household, age were significantly associated with level of participation. Women participation in livestock activities increased production and they were involved in income generating activities for better economic conditions of their families.

Keywords: women, participation, livestock, management, rural development

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Authors: Zeta Dooly, Aidan Duane

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The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

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Authors: Umut Tuğlu Karslı

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While, port function had a major role during the antiquity and medieval times, it has started to lose its significance in 19th century. In many port cities, while heavy industrial functions and ports have been moved out of the former port districts, the resulting derelict spaces have been transformed to new waterfront quarters to accommodate commercial, tourism, cultural, residential and public uses. Primary aim of these operations is to revitalize abandoned spaces of historical potential and re-establish a relationship between the city and the coast. Karakoy Port, field of this study, located in the Bosphorus, was surrounded by the city centre in time due to the transformation of urban functions, and as a result it has lost its former significance. While Karakoy has 24 hours lively residential and commercial uses in old times; in early 1980s, became a district of mechanical, plumbing and electronic parts suppliers during the day and a place for homeless at night. Today, activities for revitalization of this region continue in two forms and scales. First of these activities is the "planned transformation projects," which also includes the most important one “Galataport project”, and the second one is "spontaneous transformation," which consists of individual interventions. Galataport project that based on the idea of arranging the area specifically for tourists was prepared in 2005 and became a topic of tremendous public debate. On the other hand, the "spontaneous transformation" that is observed in the Karakoy District starts in 2004 with the foundation of “Istanbul Modern Museum”. Istanbul Modern, the first contemporary arts museum of the city, allowed the cultural integration of old naval warehouses of the port to the daily life. Following this adaptive reuse intervention, the district started to accommodate numerous art galleries, studios, café-workshops and design stores. In this context, this paper briefly examines revitalization studies in obsolete port regions, analyzes the planned and ongoing socio-spatial transformations in the specific case of Karakoy under the subjects of "planned transformation projects" and "spontaneous transformation", and realizes a critical review of the sustainability of the proposals on how to reinstate the district in the active life of Istanbul.

Keywords: port cities, socio-spatial transformation, urban regeneration, urban revitalization

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Authors: Wanida Suwunniponth

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The purpose of this research was to investigate the relationship between the factors of using online social network for tourism destination in case of Bangkok area in Thailand, by extending the use of technology acceptance model (TAM). This study employed by quantitative research and the target population were entrepreneurs and local people in Bangkok who use social network-Facebook concerning tourist destinations in Bangkok. Questionnaire was used to collect data from 300 purposive samples. The multiple regression analysis and path analysis were used to analyze data. The results revealed that most people who used Facebook for promoting tourism destinations in Bangkok perceived ease of use, perceived usefulness, perceived trust in using Facebook and influenced by social normative as well as having positive attitude towards using this application. Addition, the hypothesis results indicate that acceptance of online social network-Facebook was related to the positive attitude towards using of Facebook and related to their intention to use this application for tourism.

Keywords: Facebook, online social network, technology acceptance model, tourism destination

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Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

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This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

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Authors: A. Hakimiyan, H. Namazi

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Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

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Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

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Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Dessy Pinem, Rahmadian Sembiring, Adanil Bushra

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Medan Belawan is one of the subdistricts of 21 districts in Medan. Medan Belawan Sub-district is directly adjacent to the Malacca Strait in the North. Due to its direct border with the Malacca Strait, the problem in this sub-district, which has continued for many years, is a flood of rob. In 2015, rob floods inundated Sicanang urban village, Belawan I urban village, Belawan Bahagia urban village and Bagan Deli village. The extent of inundation in the flood of rob that occurred in September 2015 reached 540, 938 ha. Rob flood is a phenomenon where the sea water is overflowing into the mainland. Rob floods can also be interpreted as a puddle of water on the coastal land that occurs when the tidal waters. So this phenomenon will inundate parts of the coastal plain or lower place of high tide sea level. Rob flood is a daily disaster faced by the residents in the district of Medan Belawan. Rob floods can happen every month and last for a week. The flood is not only the residents' houses, the flood also soaked the main road to Belawan Port reaching 50 cm. To deal with the problems caused by the flood and to prepare coastal communities to face the character of coastal areas, it is necessary to know the vulnerability of the people who are always the victims of the rob flood. Are the people of Medan Belawan sub-district, especially in the flood-affected villages, able to cope with the consequences of the floods? To answer this question, it is necessary to assess the vulnerability of the Belawan District community in the face of the flood disaster. This research is descriptive, qualitative and quantitative. Data were collected by observation, interview and questionnaires in 4 urban villages often affected by rob flood. The vulnerabilities measured are physical, economic, social, environmental, organizational and motivational vulnerabilities. For vulnerability in the physical field, the data collected is the distance of the building, floor area ratio, drainage, and building materials. For economic vulnerability, data collected are income, employment, building ownership, and insurance ownership. For the vulnerability in the social field, the data collected is education, number of family members, children, the elderly, gender, training for disasters, and how to dispose of waste. For the vulnerability in the field of organizational data collected is the existence of organizations that advocate for the victims, their policies and laws governing the handling of tidal flooding. The motivational vulnerability is seen from the information center or question and answer about the rob flood, and the existence of an evacuation plan or path to avoid disaster or reduce the victim. The results of this study indicate that most people in Medan Belawan sub-district have a high-level vulnerability in physical, economic, social, environmental, organizational and motivational fields. They have no access to economic empowerment, no insurance, no motivation to solve problems and only hope to the government, not to have organizations that support and defend them, and have physical buildings that are easily destroyed by rob floods.

Keywords: disaster, rob flood, Medan Belawan, vulnerability

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

Abstract:

Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Viktória Sugár, Attila Talamon, András Horkai, Michihiro Kita

Abstract:

The dense urban fabric of the Budapest 7th district is known as the former Jewish Quarter. The majority of the historical building stock contains multi-story tenement houses with courtyards, built around the end of the 19^th century. Various rehabilitation and urban planning attempt occurred until today, mostly left unfinished. Present paper collects the past rehabilitation plans, actions and their effect which took place in the former Jewish District of Budapest. The authors aim to assess the boundaries of a complex building stock rehabilitation, by taking into account the monument protection guidelines. As a main focus of the research, structural as well as energetic rehabilitation possibilities are analyzed in case of each building by using Geographic Information System (GIS) methods.

Keywords: geographic information system, Hungary, Jewish Quarter, monument, protection, rehabilitation

Procedia PDF Downloads 249