Search results for: network communities and weighted load balancing

Authors: J. B. Frisch, D. Evandiloff, P. Martin, N. Ouizille, F. Pires

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Smart Beta strategies intend to be an asset management revolution with reference to classical cap-weighted indices. Indeed, these strategies allow a better control on portfolios risk factors and an optimized asset allocation by taking into account specific risks or wishes to generate alpha by outperforming indices called 'Beta'. Among many strategies independently used, this paper focuses on four of them: Minimum Variance Portfolio, Equal Risk Contribution Portfolio, Maximum Diversification Portfolio, and Equal-Weighted Portfolio. Their efficiency has been proven under constraints like momentum or market phenomenon, suggesting a reconsideration of cap-weighting.
 To further increase strategy return efficiency, it is proposed here to compare their strengths and weaknesses inside time intervals corresponding to specific identifiable market phases, in order to define adapted strategies depending on pre-specified situations. 
Results are presented as performance curves from different combinations compared to a benchmark. If a combination outperforms the applicable benchmark in well-defined actual market conditions, it will be preferred. It is mainly shown that such investment 'rules', based on both historical data and evolution of Smart Beta strategies, and implemented according to available specific market data, are providing very interesting optimal results with higher return performance and lower risk.
 Such combinations have not been fully exploited yet and justify present approach aimed at identifying relevant elements characterizing them.

Keywords: smart beta, minimum variance portfolio, equal risk contribution portfolio, maximum diversification portfolio, equal weighted portfolio, combinations

Procedia PDF Downloads 340

Authors: Liang Weichien

Abstract:

Without adequate information and mitigation plan for natural disaster, the risk to urban populated areas will increase in the future as populations grow, especially in Taiwan. Taiwan is recognized as the world's high-risk areas, where an average of 5.7 times of floods occur per year should seek to strengthen coherence and consensus in how cities can plan for flood and climate change. Therefore, this study aims at understanding the vulnerability to flooding in Taipei city, Taiwan, by creating indicators and calculating the vulnerability of each study units. The indicators were grouped into sensitivity and adaptive capacity based on the definition of vulnerability of Intergovernmental Panel on Climate Change. The indicators were weighted by using Principal Component Analysis. However, current researches were based on the assumption that the composition and influence of the indicators were the same in different areas. This disregarded spatial correlation that might result in inaccurate explanation on local vulnerability. The study used Geographically Weighted Principal Component Analysis by adding geographic weighting matrix as weighting to get the different main flood impact characteristic in different areas. Cross Validation Method and Akaike Information Criterion were used to decide bandwidth and Gaussian Pattern as the bandwidth weight scheme. The ultimate outcome can be used for the reduction of damage potential by integrating the outputs into local mitigation plan and urban planning.

Keywords: flood vulnerability, geographically weighted principal components analysis, GWPCA, highly urbanized area, spatial correlation

Procedia PDF Downloads 286

Authors: Rei-Heng Cheng, Wen-Pinn Fang

Abstract:

A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

Procedia PDF Downloads 391

Authors: Marcus Smith

Abstract:

DNA profiling has made a valuable contribution to criminal investigations over the past thirty years. Direct matching DNA profiles from a crime scene and suspect, or between a suspect and a database remain of great importance to crimes such as murder, assault, and property theft. As scientific and technological advancement continues, a wide range of new DNA profiling applications has been developed. The application of new techniques involves an interesting balancing act between admitting probative evidence in a criminal trial, evaluating its degree of relevance and validity, and limiting its prejudicial impact. The impact of new DNA profiling applications that have significant implications for law enforcement and the legal system can be evaluated through a review of relevant case law, legislation and the latest empirical evidence from jurisdictions around the world including the United States, United Kingdom, and Australia. There are benefits in further examining the implications of these new developments, including how the criminal law can best be adapted to ensure that new technology is used to enhance criminal investigation and prosecution while ensuring it is applied in a measured way that respects individual rights and maintains principles of fairness enshrined in the legal system.

Keywords: criminal procedure, forensic evidence, DNA profiling, familial searching, phenotyping

Procedia PDF Downloads 132

Authors: Wang Xue, Fan Liwei

Abstract:

The trust and use of social network platforms by users are instrumental factors that contribute to the platform’s sustainable development. Studying the influential factors of the use of social network platforms is beneficial for developing and maintaining a large user base. This study constructed an extended unified theory of acceptance and use of technology (UTAUT2) moderating model with perceived privacy risks to analyze the factors affecting the trust and use of social network platforms. 444 participants completed our 35 surveys, and we verified the survey results by structural equation model. Empirical results reveal the influencing factors that affect the trust and use of social network platforms, and the extended UTAUT2 model with perceived privacy risks increases the applicability of UTAUT2 in social network scenarios. Social networking platforms can increase their use rate by increasing the economics, functionality, entertainment, and privacy security of the platform.

Keywords: perceived privacy risk, social network, trust, use, UTAUT2 model

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Authors: Mandeep Kaur, Fatehgarh Sahib

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The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system.

Keywords: economic load dispatch, genetic algorithm, generating units, multiobjective optimization, weighting method

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Authors: Ali Hamad, Ibrahim Al-Drous, Saleh Al-Jufout

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This paper presents a case study of using STATCOM to enhance the performance of Al-Qatraneh 33-kV transmission line. The location of the STATCOM was identified maintaining minimum voltage drops at the 110 load nodes. The transmission line and the 110 load nodes have been modeled by MATLAB/Simulink. The suggested STATCOM and its location will increase the transmission capability of this transmission line and overcome the overload expected in the year 2020. The annual percentage loading rise has been considered as 14%. A graphical representation of the line voltages and the voltage drops at different load nodes has been illustrated.

Keywords: FACTS, MATLAB, STATCOM, transmission line, voltage drop

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: A. Al-Rifaie, Z. W. Guan, S. W. Jones

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Beam to column connection can be considered as the most important structural part that affects the response of buildings to progressive collapse. However, many studies were conducted to investigate the beam to column connection under accidental loads such as fire, blast and impact load to investigate the connection response. The study is a part of a PhD plan to investigate different types of connections under lateral impact load. The conventional test setups, such as cruciform setup, were designed to apply shear forces and bending moment on the connection, whilst, in the lateral impact case, the connection is subjected to combined tension and moment. Hence, a review is presented to introduce the previous test setup that is used to investigate the connection behaviour. Then, the design and fabrication of the novel test setup is presented. Finally, some trial test results to investigate the efficiency of the proposed setup are discussed. The final results indicate that the setup was efficient in terms of the simplicity and strength.

Keywords: connections, impact load, drop hammer, testing methods

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Authors: Yichao Lv, Minmin Cai, Yanqiang Tao, Xinyuan Zou, Chao Zhang, Xiangping Liu

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Objective: This study aims to explore the network structure of personality traits and mental health and identify key factors for effective intervention strategies. Methods: All participants (N = 6,067; 3,368 females) underwent the Eysenck Personality Scale (EPQ) to measure personality traits and the Symptom Self-rating Scale (SCL-90) to measure psychiatric symptoms. Using the mean value of the SCL-90 total score plus one standard deviation as the cutoff, 854 participants (14.08%; 528 females) were categorized as individuals exhibiting potential psychological symptoms and were included in the follow-up network analysis. The structure and bridge centrality of the network for dimensions of EPQ and SCL-90 were estimated. Results: Between the EPQ and SCL-90, psychoticism (P), extraversion (E), and neuroticism (N) showed the strongest positive correlations with somatization (Som), interpersonal sensitivity (IS), and hostility (Hos), respectively. Extraversion (E), somatization (Som), and anxiety (Anx) were identified as the most important bridge factors influencing the overall network. Conclusions: This study explored the network structure and complex connections between mental health and personality traits from a network perspective, providing potential targets for intervening in adolescent personality traits and mental health.

Keywords: EPQ, SCL-90, Chinese adolescents, network analysis

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Authors: M. Mokhber, J. Hedayati

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From the managerial perspective, it is important to devise an operational plan based on top priorities due to limited resources, diversity of measures and high costs needed to improve safety in infrastructure. Dealing with the high-risk corridors across Iran, this study prioritized the corridors according to statistical data on accidents involving fatalities, injury or damage over three consecutive years. In collaboration with the Iranian Police Department, data were collected and modified. Then, the prioritization criteria were specified based on the expertise opinions and international standards. In this study, the prioritization criteria included accident severity and accident density. Finally, the criteria were standardized and weighted (equal weights) to score each high-risk corridor. The prioritization phase involved the scoring and weighting procedure. The high-risk corridors were divided into twelve groups out of 50. The results of data analysis for a three-year span suggested that the first three groups (150 corridors) along with a quarter of Iranian road network length account for nearly 60% of traffic accidents. In the next step, according to variables including weather conditions particular roads for the purpose of winter safety measures were extracted from the abovementioned categories. According to the results ranking, ‎‏9‏‎ roads with the overall ‎length of about ‎‎‏1000‏‎ Km of high-risk corridors are considered as preferences of ‎safety measures‎.

Keywords: high-risk corridors, HRCs, road safety rating, road scoring, winter safety measures

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Authors: Robert Höttger, Lukas Krawczyk, Burkhard Igel

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This paper introduces novel approaches to partitioning and mapping in terms of model-based embedded multicore system engineering and further discusses benefits, industrial relevance and features in common with existing approaches. In order to assess and evaluate results, both approaches have been applied to a real industrial application as well as to various prototypical demonstrative applications, that have been developed and implemented for different purposes. Evaluations show, that such applications improve significantly according to performance, energy efficiency, meeting timing constraints and covering maintaining issues by using the AMALTHEA platform and the implemented approaches. Further- more, the model-based design provides an open, expandable, platform independent and scalable exchange format between OEMs, suppliers and developers on different levels. Our proposed mechanisms provide meaningful multicore system utilization since load balancing by means of partitioning and mapping is effectively performed with regard to the modeled systems including hardware, software, operating system, scheduling, constraints, configuration and more data.

Keywords: partitioning, mapping, distributed systems, scheduling, embedded multicore systems, model-based, system analysis

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Authors: Mansilla, Juan Camilo

Abstract:

According to many studies, public space in the cities of Global South is constantly morcellated and captured by a multiplicity of actors in a permanent struggle for power. This imposed public space restricts the access to services and political actions to many inhabitants. The author has conducted several focus group sessions using video in a reflective mode with low-income communities in Medellín, Colombia in order to study how people in this city are shift from a physical public space to a hybrid public space shaped by internet. Beyond the fragmented city and the violent urban context manifested by participants, these activities have highlighted how the access to the city is currently going through a dialectic movement between the physical and the digital space. The purpose of this article is to make explicit the link between this hybrid public space and the boundaries of exclusion in the city. Urban marginality is closely related with the idea of access and space. Low-income communities in Medellín assume the digital realm like a “not controlled space” of resistance, where alternative ways of expression like hip hop movement, graffiti, dance, video and virtual communities produce effective changes in the physical realm.

Keywords: access to the city, hybrid public space, low-income communities, Medellín, urban marginality

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Authors: Ebenezer Obaloluwa Olaniyi

Abstract:

In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Bhmika Raiu

Abstract:

The community forestry programme in Nepal officially started in the late 1970s. Since then concerning movement has been evolving to involve local communities in the management and utilization of forests. The policy of the government was originally intended to meet the basic forest products required by the communities through active participation in forest development and management. Later, it was expanded to include the mobilization and empowerment of the members of community forest user groups in the development of their local communities. It was observed that the trend of forest degradation has decreased since the handing over of national forests to local communities, but a number of unintended social anomalies have also cropped up. Such anomalies essentially constitute of the inequity and unfairness in the local and national level and in terms of long-term sustainability of forest resources. This paper provides an overview of various issues of community forestry, especially focusing on the major achievements made in community forestry. It calls for rethinking the community forestry programme in order to face the present day challenges of linking community forestry with livelihood promotion, good governance, and sustainable forest management. It also lays out strategies for reforms in community forestry.

Keywords: community forest, livelihood promotion, challenges, achievements

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Authors: Ji-Hoon Hong, Dong-Hee Kim, Nam-Uk Kim, Tai-Myoung Chung

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Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS.

Keywords: android malware detection, software-defined network, interaction environment, android malware detection, software-defined network, interaction environment

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Authors: Alireza Alesaadi

Abstract:

Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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Authors: Katherine Carl Payne, Moshe Dror

Abstract:

The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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Authors: Eugene Y. C. Wong, Daniel Y. W. Mo, Cosmo T. Y. Ng, Jessica K. Y. Chan, Leith K. Y. Chan, Henry Y. K. Lau

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The real-time planning visualisation, precise allocation and loading optimisation in air cargo load planning operations are increasingly important as more considerations are needed on dangerous cargo loading, locations of lithium batteries, weight declaration and limited aircraft capacity. The planning of the unit load devices (ULD) can often be carried out only in a limited number of hours before flight departure. A dynamic air cargo load planning system is proposed with the optimisation of cargo load plan and visualisation of planning results in virtual reality systems. The system aims to optimise the cargo load planning and visualise the simulated loading planning decision on air cargo terminal operations. Adopting simulation tools, Cave Automatic Virtual Environment (CAVE) and virtual reality technologies, the results of planning with reference to weight and balance, Unit Load Device (ULD) dimensions, gateway, cargo nature and aircraft capacity are optimised and presented. The virtual reality system facilities planning, operations, education and training. Staff in terminals are usually trained in a traditional push-approach demonstration with enormous manual paperwork. With the support of newly customized immersive visualization environment, users can master the complex air cargo load planning techniques in a problem based training with the instant result being immersively visualised. The virtual reality system is developed with three-dimensional (3D) projectors, screens, workstations, truss system, 3D glasses, and demonstration platform and software. The content will be focused on the cargo planning and loading operations in an air cargo terminal. The system can assist decision-making process during cargo load planning in the complex operations of air cargo terminal operations. The processes of cargo loading, cargo build-up, security screening, and system monitoring can be further visualised. Scenarios are designed to support and demonstrate the daily operations of the air cargo terminal, including dangerous goods, pets and animals, and some special cargos.

Keywords: air cargo load planning, optimisation, virtual reality, weight and balance, unit load device

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

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The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Dodi Ikhsanshaleh

Abstract:

When subjected to dynamic load, foundation oscillates in the way that depends on the soil behaviour, the geometry and inertia of the foundation and the dynamic exctation. The practical guideline to analysis block-type foundation excitated by dynamic load from vibrating machine is presented. The analysis use Lumped Mass Parameter Method to express dynamic properties such as stiffness and damping of soil. The numerical examples are performed on design block-type foundation supporting gas turbine compressor which is important equipment package in gas processing plant

Keywords: block foundation, dynamic load, lumped mass parameter

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Authors: Yeo Kyeong Lee, Ji Yeon Kang, Eun Mi Ryu, Hee Sun Kim, Yeong Soo Shin

Abstract:

The objective of this paper is an investigation of the effects of the thickness and axial loading during a fire test on the load-bearing capacity of a fire-damaged normal-strength concrete wall. Two factors are attributed to the temperature distributions in the concrete members and are mainly obtained through numerous experiments. Toward this goal, three wall specimens of different thicknesses are heated for 2 h according to the ISO-standard heating curve, and the temperature distributions through the thicknesses are measured using thermocouples. In addition, two wall specimens are heated for 2 h while simultaneously being subjected to a constant axial loading at their top sections. The test results show that the temperature distribution during the fire test depends on wall thickness and axial load during the fire test. After the fire tests, the specimens are cured for one month, followed by the loading testing. The heated specimens are compared with three unheated specimens to investigate the residual load-bearing capacities. The fire-damaged walls show a minor difference of the load-bearing capacity regarding the axial loading, whereas a significant difference became evident regarding the wall thickness. To validate the experiment results, finite element models are generated for which the material properties that are obtained for the experiment are subject to elevated temperatures, and the analytical results show sound agreements with the experiment results. The analytical method based on validated thought experimental results is applied to generate the fire-damaged walls with 2,800 mm high considering the buckling effect: typical story height of residual buildings in Korea. The models for structural analyses generated to deformation shape after thermal analysis. The load-bearing capacity of the fire-damaged walls with pin supports at both ends does not significantly depend on the wall thickness, the reason for it is restraint of pinned ends. The difference of the load-bearing capacity of fire-damaged walls as axial load during the fire is within approximately 5 %.

Keywords: normal-strength concrete wall, wall thickness, axial-load ratio, slenderness ratio, fire test, residual strength, finite element analysis

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Authors: Irfan Ali, Srikant Gupta, Aquil Ahmed

Abstract:

Every country needs a sustainable development (SD) for its economic growth by forming suitable policies and initiative programs for the development of different sectors of the country. This paper is comprised of modeling and optimization of different sectors of India that form a multi-criterion model. In this paper, we developed a fractional goal programming (FGP) model that helps in providing the efficient allocation of resources simultaneously by achieving the sustainable goals in gross domestic product (GDP), electricity consumption (EC) and greenhouse gasses (GHG) emission by the year 2030. Also, a weighted model of FGP is presented to obtain varying solution according to the priorities set by the policy maker for achieving future goals of GDP growth, EC, and GHG emission. The presented models provide a useful insight to the decision makers for implementing strategies in a different sector.

Keywords: sustainable and economic development, multi-objective fractional programming, fuzzy goal programming, weighted fuzzy goal programming

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Authors: Youn-Hwan Kim, Jae-Won Moon, Hae-Joong Kim

Abstract:

This paper introduces the study on the method of accelerated life test to electrical rotating system. In recent years, as well as efficiency for motors and generators, there is a growing need for research on the life expectancy. It is considered impossible to calculate the acceleration coefficient by increasing the rotational load or temperature load as the acceleration stress in the motor system because the temperature of the copper exceeds the wire thermal class rating. In this paper, the accelerated life test methods of the electrical rotating system are classified according to the application. This paper describes the development of the test procedure for the highly accelerated life test (HALT) of the 100kW permanent magnet synchronous motor (PMSM) of electric vehicle. Finally, it explains how to select acceleration load for vibration, temperature, bearing load, etc. for accelerated life test.

Keywords: acceleration coefficient, electric vehicle motor, HALT, life expectancy, vibration

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Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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Authors: Sopheak Sorn, Kwok Yip Szeto

Abstract:

Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a complex system will perform satisfactorily. When the system is described by a network of N components (nodes) and their L connection (links), the reliability of the system becomes a network design problem that is an NP-hard combinatorial optimization problem. In this paper, we address the network design problem for a random point set’s pattern in two dimensions. We make use of a Voronoi construction with each cell containing exactly one point in the point pattern and compute the reliability of the Voronoi’s dual, i.e. the Delaunay graph. We further investigate the communicability of the Delaunay network. We find that there is a positive correlation and a negative correlation between the homogeneity of a Delaunay's degree distribution with its reliability and its communicability respectively. Based on the correlations, we alter the communicability and the reliability by performing random edge flips, which preserve the number of links and nodes in the network but can increase the communicability in a Delaunay network at the cost of its reliability. This transformation is later used to optimize a Delaunay network with the optimum geometric mean between communicability and reliability. We also discuss the importance of the edge flips in the evolution of real soap froth in two dimensions.

Keywords: Communicability, Delaunay triangulation, Edge Flip, Reliability, Two dimensional network, Voronio

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Authors: Gui Yang Wu, Bo Wang, Xin Wang

Abstract:

Nowadays, 5G service-based interface architecture uses text-based payload like JSON to transfer business data between network functions, which has obvious advantages as internet services but causes unnecessarily larger traffic. In this paper, a new 5G application payload size reduction method is presented to provides the mechanism to negotiate about new capability between network functions when network communication starts up and how 5G application data are reduced according to negotiated information with peer network function. Without losing the advantages of 5G text-based payload, this method demonstrates an excellent result on application payload size reduction and does not increase the usage quota of computing resource. Implementation of this method does not impact any standards or specifications and not change any encoding or decoding functionality too. In a real 5G network, this method will contribute to network efficiency and eventually save considerable computing resources.

Keywords: 5G, JSON, payload size, service-based interface

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Authors: Sushil Kumar, M. Dakshina Murty

Abstract:

Thermal network modelling has proven to be important tool for thermal analysis of electrical machine. This article investigates numerical thermal network model and experimental performance of a large-scale AC motor. Experimental temperatures were measured using RTD in the stator which have been compared with the numerical data. Thermal network modelling fairly predicts the temperature of various components inside the large-scale AC motor. Results of stator winding temperature is compared with experimental results which are in close agreement with accuracy of 6-10%. This method of predicting hot spots within AC motors can be readily used by the motor designers for estimating the thermal hot spots of the machine.

Keywords: AC motor, thermal network, heat transfer, modelling

Procedia PDF Downloads 326