Search results for: Integrated Network Management

Authors: Ilaha Rzayeva, Emin Alasgarov, Orkhan Karim-Zada

Abstract:

This study attempts to consider the linkage between management and computer sciences in order to develop the software named “IntelSymb” as a demo application to prove data analysis of non-energy^* fields’ diversification, which will positively influence on energy dependency mitigation of countries. Afterward, we analyzed 18 years of economic fields of development (5 sectors) of 13 countries by identifying which patterns mostly prevailed and which can be dominant in the near future. To make our analysis solid and plausible, as a future work, we suggest developing a gateway or interface, which will be connected to all available on-line data bases (WB, UN, OECD, U.S. EIA) for countries’ analysis by fields. Sample data consists of energy (TPES and energy import indicators) and non-energy industries’ (Main Science and Technology Indicator, Internet user index, and Sales and Production indicators) statistics from 13 OECD countries over 18 years (1995-2012). Our results show that the diversification of non-energy industries can have a positive effect on energy sector dependency (energy consumption and import dependence on crude oil) deceleration. These results can provide empirical and practical support for energy and non-energy industries diversification’ policies, such as the promoting of Information and Communication Technologies (ICTs), services and innovative technologies efficiency and management, in other OECD and non-OECD member states with similar energy utilization patterns and policies. Industries, including the ICT sector, generate around 4 percent of total GHG, but this is much higher — around 14 percent — if indirect energy use is included. The ICT sector itself (excluding the broadcasting sector) contributes approximately 2 percent of global GHG emissions, at just under 1 gigatonne of carbon dioxide equivalent (GtCO2eq). Ergo, this can be a good example and lesson for countries which are dependent and independent on energy, and mainly emerging oil-based economies, as well as to motivate non-energy industries diversification in order to be ready to energy crisis and to be able to face any economic crisis as well.

Keywords: Energy policy, energy diversification, “IntelSymb” software, renewable energy.

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: Human machine interface, industrial internet of things, internet of things, optical character recognition, video analytic.

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Authors: V. Vassiliou, M. Charalambides, M. Menicou

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Fish-feed is a major cost component of operating expenses for any aquaculture farm. Due to soaring prices of fish-feed ingredients, the need for better feeding schedule management has become imperative. On such factor that influences the utilization rate of fish-feed are sea currents. Up to now, practical monitoring of fishfeed loss due to sea currents is not exercised. This paper gives a description of an economic methodology that aims at quantifying the amount of fish-feed lost due to sea currents and draws on data from a Mediterranean aquaculture farm to formulate the associated model.

Keywords: Aquaculture, economic model, fish-feed loss, sea currents.

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Authors: Yeung C.L., Cheung C.F., Wang W.M., Tsui E.

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Narratives are invaluable assets of human lives. Due to the distinct features of narratives, they are useful for supporting human reasoning processes. However, many useful narratives become residuals in organizations or human minds nowadays. Researchers have contributed effort to investigate and improve narrative generation processes. This paper attempts to contemplate essential components in narratives and explore a computational approach to acquire and extract knowledge to generate narratives. The methodology and significant benefit for decision support are presented.

Keywords: Decision Support, Knowledge Management, Knowledge-based Systems, Narrative Generation

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Authors: Kyomin Lee, Joohee Kim, Sangho Kang

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The commercial nuclear power reactor in South Korea, Kori Unit 1, which was a 587 MWe pressurized water reactor that started operation since 1978, was permanently shut down in June 2017 without an additional operating license extension. The Kori 1 Unit is scheduled to become the nuclear power unit to enter the decommissioning phase. In this study, the preliminary evaluation of the decommissioning wastes for the Kori Unit 1 was performed based on the following series of process: firstly, the plant inventory is investigated based on various documents (i.e., equipment/ component list, construction records, general arrangement drawings). Secondly, the radiological conditions of systems, structures and components (SSCs) are established to estimate the amount of radioactive waste by waste classification. Third, the waste management strategies for Kori Unit 1 including waste packaging are established. Forth, selection of the proper decontamination and dismantling (D&D) technologies is made considering the various factors. Finally, the amount of decommissioning waste by classification for Kori 1 is estimated using the DeCAT program, which was developed by KEPCO-E&C for a decommissioning cost estimation. The preliminary evaluation results have shown that the expected amounts of decommissioning wastes were less than about 2% and 8% of the total wastes generated (i.e., sum of clean wastes and radwastes) before/after waste processing, respectively, and it was found that the majority of contaminated material was carbon or alloy steel and stainless steel. In addition, within the range of availability of information, the results of the evaluation were compared with the results from the various decommissioning experiences data or international/national decommissioning study. The comparison results have shown that the radioactive waste amount from Kori Unit 1 decommissioning were much less than those from the plants decommissioned in U.S. and were comparable to those from the plants in Europe. This result comes from the difference of disposal cost and clearance criteria (i.e., free release level) between U.S. and non-U.S. The preliminary evaluation performed using the methodology established in this study will be useful as a important information in establishing the decommissioning planning for the decommissioning schedule and waste management strategy establishment including the transportation, packaging, handling, and disposal of radioactive wastes.

Keywords: Characterization, classification, decommissioning, decontamination and dismantling, Kori 1, radioactive waste.

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Authors: Kriddikorn Kaewwongsri, Nikom Suvonvorn

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In the deep south of Thailand, checkpoints for people verification are necessary for the security management of risk zones, such as official buildings in the conflict area. In this paper, we propose an automatic checkpoint system that verifies persons using information from ID cards and facial features. The methods for a person’s information abstraction and verification are introduced based on useful information such as ID number and name, extracted from official cards, and facial images from videos. The proposed system shows promising results and has a real impact on the local society.

Keywords: Face comparison, card recognition, OCR, checkpoint system, authentication.

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Authors: Travis Morris

Abstract:

The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.

Keywords: Emotive triggers, environmental security, natural language processing, propaganda analysis.

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: Muhammad Arslan Usman, Muhammad Rehan Usman, Soo Young Shin

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Live video streaming is one of the most widely used service among end users, yet it is a big challenge for the network operators in terms of quality. The only way to provide excellent Quality of Experience (QoE) to the end users is continuous monitoring of live video streaming. For this purpose, there are several objective algorithms available that monitor the quality of the video in a live stream. Subjective tests play a very important role in fine tuning the results of objective algorithms. As human perception is considered to be the most reliable source for assessing the quality of a video stream subjective tests are conducted in order to develop more reliable objective algorithms. Temporal impairments in a live video stream can have a negative impact on the end users. In this paper we have conducted subjective evaluation tests on a set of video sequences containing temporal impairment known as frame freezing. Frame Freezing is considered as a transmission error as well as a hardware error which can result in loss of video frames on the reception side of a transmission system. In our subjective tests, we have performed tests on videos that contain a single freezing event and also for videos that contain multiple freezing events. We have recorded our subjective test results for all the videos in order to give a comparison on the available No Reference (NR) objective algorithms. Finally, we have shown the performance of no reference algorithms used for objective evaluation of videos and suggested the algorithm that works better. The outcome of this study shows the importance of QoE and its effect on human perception. The results for the subjective evaluation can serve the purpose for validating objective algorithms.

Keywords: Objective evaluation, subjective evaluation, quality of experience (QoE), video quality assessment (VQA).

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Authors: Denisa Ferenčíková, Petr Briš

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Customer audits are generally used to ensure customer that supplier is continuously able to meet his requirements while supplying him required products and services. However, customer audits can be considered as a very useful quality control tool for suppliers as well. In our paper, we analyzed the process of customer audits realized in Czech companies from both perspectives: a supplier´s viewpoint and customer´s viewpoint. At the end, we tried to emphasize some areas that should not be omitted during the audit process.

Keywords: Customer Audit, Quality Control, Quality Management, Product Quality, Service Quality, Process Quality.

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Authors: O. J. Olaniran, P. E. D. Love, D. J. Edwards, O. Olatunji, J. Matthews

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Cost overruns are a persistent problem in oil and gas megaprojects. Whilst the extant literature is filled with studies on incidents and causes of cost overruns, underlying theories to explain their emergence in oil and gas megaprojects are few. Yet, a way to contain the syndrome of cost overruns is to understand the bases of ‘how and why’ they occur. Such knowledge will also help to develop pragmatic techniques for better overall management of oil and gas megaprojects. The aim of this paper is to explain the development of cost overruns in hydrocarbon megaprojects through the perspective of chaos theory. The underlying principles of chaos theory and its implications for cost overruns are examined and practical recommendations proposed. In addition, directions for future research in this fertile area provided.

Keywords: Chaos theory, oil and gas, cost overruns, megaprojects.

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Authors: Rebecca Angeles

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This case study features the Kuehne + Nagel PharmaChain solution for ‘cold chain’ pharmaceutical and biologic product shipments with IOT-enabled features for shipment temperature and location tracking. Using the case study method and content analysis, this research project investigates the application of the structurational model of technology theory introduced by Orlikowski in order to interpret the firm’s entry and participation in the IOT-impelled marketplace.

Keywords: Internet of things, IoT, radio frequency identification, supply chain management, business intelligence.

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Authors: Emanuel Teixeira, Anderson Ramos, Marisa Lourenço, Fernando J. Velez, Jon M. Peha

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This article discusses the benefit cost analysis aspects of millimetre wavebands (mmWaves) and Super High Frequency (SHF). The devaluation along the distance of the carrier-to-noise-plus-interference ratio with the coverage distance is assessed by considering two different path loss models, the two-slope urban micro Line-of-Sight (UMiLoS) for the SHF band and the modified Friis propagation model, for frequencies above 24 GHz. The equivalent supported throughput is estimated at the 5.62, 28, 38, 60 and 73 GHz frequency bands and the influence of carrier-to-noise-plus-interference ratio in the radio and network optimization process is explored. Mostly owing to the lessening caused by the behaviour of the two-slope propagation model for SHF band, the supported throughput at this band is higher than at the millimetre wavebands only for the longest cell lengths. The benefit cost analysis of these pico-cellular networks was analysed for regular cellular topologies, by considering the unlicensed spectrum. For shortest distances, we can distinguish an optimal of the revenue in percentage terms for values of the cell length, R ≈ 10 m for the millimeter wavebands and for longest distances an optimal of the revenue can be observed at R ≈ 550 m for the 5.62 GHz. It is possible to observe that, for the 5.62 GHz band, the profit is slightly inferior than for millimetre wavebands, for the shortest Rs, and starts to increase for cell lengths approximately equal to the ratio between the break-point distance and the co-channel reuse factor, achieving a maximum for values of R approximately equal to 550 m.

Keywords: 5G, millimetre wavebands, super high-frequency band, SINR, signal-to-interference-plus-noise ratio, cost benefit analysis.

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Authors: Patrycja J. Haupt

Abstract:

Today we tend to go back to the past to our root relation to nature. Therefore in search of friendly spaces there are elements of natural environment introduced as elements of spatial composition. Though reinvented through the use of the new substance such as greenery, water etc. made possible by state of the art technologies, still, in principal, they remain the same. As a result, sustainable design, based upon the recognized means of composition in addition to the relation of architecture and urbanism vs. nature introduces a new aesthetical values into architectural and urban space.

Keywords: architectural composition, biodiversity, elements of composition, green architecture, sustainable design, urban composition, water management.

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Authors: Frantisek Jezek, Jan Sedlacek

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This paper is concerned with the role strategic management plays in higher education and the methods it entails. Using the University of West Bohemia and the Czech Republic as examples, the paper describes the methods used in furthering strategic objectives within institutions and their different parts (faculties, institutes). The nature of the demands faced by the university dictates the need for a strategic framework which defines the basic objectives and parameters of tertiary education and research in a local, regional and national context. Sharing strategies with a wider range of actors (universities, cities, regions, the practical sphere) is key to laying the foundations for more efficient cooperation.

Keywords: Strategy, strategic plan, university, university environment.

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Authors: Omid Mirmotahari, Yngvar Berg, Mats Hovin

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The problem discussed in this paper involves packing fresh fish fileet of the northern Cod into a standard square container. The fish is first cleaned and split and then collected on a belt ready to be stacked in a container. The aim of our work is to pack the fish into the container with constraints on the amount of overlap allowed for the fileets. The current focus is to design a packing cell that can be real-time and of practical use, while finding the optimal solution to the degree of overlap and minimise the unused space of the container.

Keywords: Facilities Planning and Management, Intelligent Systems, Manufacturing Systems, Operations Research, Production Planning and Control.

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Authors: Denys Lupshenyuk, Jean Adams

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The current paper presents the findings of a research study on learners- barriers and motivators engaged into blended programs in a workplace context. In this study, the participants were randomly assigned to one of four parallel e-learning courses, each of which was delivered using a different learning strategy. Data were collected through web-based and telephone surveys developed by the researchers. The results showed that vague instruction, time management, and insufficient feedback were the top-most barriers to blended learning. The major motivators for blended learning included content relevance, flexibility in time, and the ability to work at own pace.

Keywords: Adult education, barriers, blended learning, motivators, workplace learning.

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Authors: Mohammad H. Abu-Arqoub, Ihab S. Serhed, Waheeb A. Abu-Dawwas, Rashid M. Al-Azzeh

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This paper aims at improving web server performance by establishing a middleware layer between web and database servers, which minimizes the overload on the database server. A middleware system has been developed as a service mainly to improve the performance. This system manages connection accesses in a way that would result in reducing the overload on the database server. In addition to the connection management, this system acts as an object-oriented model for best utilization of operating system resources. A web developer can use this Service Broker to improve web server performance.

Keywords: Database server, Improve performance, Middleware, Web server.

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Authors: Zuzana Crhova, Karel Kolman, Drahomíra Pavelkova

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Knowledge is considered as an important asset which can help organizations to create competitive advantage. The necessity of taking care of these assets is more important in these days – in days of turbulent changes in business environment. Knowledge could facilitate adaption to constant changes. The aim of this paper is to describe how the knowledge sharing can be supported in the manufacturing companies. The methods of case studies and grounded theory were used to present information gained by carrying out semistructured interviews. Results show that knowledge sharing is supported in very similar ways in respondent companies.

Keywords: Case Study, Human Resource Management, Knowledge, Knowledge Sharing.

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Authors: Dimitrios J. Dimitriou

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Considering a worldwide tendency, air transports are growing very fast and many changes have taken place in planning, management and decision making process. Given the complexity of airport operation, the best use of existing capacity is the key driver of efficiency and productivity. This paper deals with the evaluation framework for the ground access at airports, by using a set of mode choice indicators providing key messages towards airport’s ground access performance. The application presents results for a sample of 12 European airports, illustrating recommendations to define policy and improve service for the air transport access chain.

Keywords: Air transport chain, airport ground access, airport access performance, airport policy.

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Authors: E. Neagoe, V. Balanica

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A Smart Building Controller (SBC) is a server software that offers secured access to a pool of building specific resources, executes monitoring tasks and performs automatic administration of a building, thus optimizing the exploitation cost and maximizing comfort. This paper brings to discussion the issues that arise with the secure exploitation of the SBC administered resources and proposes a technical solution to implement a robust secure access system based on roles, individual rights and privileges (special rights).

Keywords: Access authorization, smart building controller, software security, access rights.

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Authors: Danielle Shackley, Yetunde Folajimi

Abstract:

As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

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Authors: Mamidi Ramakrishna Rao

Abstract:

Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: Direct search, DFIG, equivalent circuit parameters, optimization.

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Authors: Sobir T. Navruzov

Abstract:

The problem of complex use of water resources in Central Asia by taking into consideration the sovereignty of the states and increasing demand on use of water for economic aspects are considered. Complex program with appropriate mathematical software intended for calculation of possible variants of using the Amudarya up-stream water resources according to satisfaction of incompatible requirements of the national economics in irrigation and energy generation is proposed.

Keywords: water resources, national economics, irrigation, transboundry, energy generation, optimal solution, program complex, up-stream, down-stream, compensating services.

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Authors: Jeries Khoury

Abstract:

The use of legendary, folkloric and religious symbols is one of the most important phenomena in modern Arabic poetry. Interestingly enough, most of the modern Arabic poetry’s pioneers were so fascinated by the biblical symbols and they managed to use many modern techniques to make these symbols adequate for their personal life from one side and fit to their Islamic beliefs from the other. One of the most famous poets to do so was al-Sayya:b. The way he employed one of these symbols ‘job’, the new features he adds to this character and the link between this character and his personal life will be discussed in this study. Besides, the study will examine the influence of al-Sayya:b on another modern poet Saadi Yusuf, who, following al-Sayya:b, used the character of Job in a special way, by mixing its features with al-Sayya:b’s personal features and in this way creating a new mixed character. A semantic, cultural and comparative analysis of the poems written by al-Sayya:b himself and the other poets who evoked the mixed image of al-Sayya:b-Job, can reveal the changes Arab poets made to the original biblical figure of Job to bring it closer to Islamic culture. The paper will make an intensive use of intertextuality idioms in order to shed light on the network of relations between three kinds of texts (indeed three ‘palimpsests’: 1- biblical- the primary text; 2- poetic- al-Syya:b’s secondary version; 3- re-poetic- Sa’di Yusuf’s tertiary version). The bottom line in this paper is that that al-Sayya:b was directly influenced by the dramatic biblical story of Job more than the brief Quranic version of the story. In fact, the ‘new’ character of Job designed by al-Sayya:b himself differs from the original one in many aspects that we can safely say it is the Sayyabian-Job that cannot be found in the poems of any other poets, unless they are evoking the own tragedy of al-Sayya:b himself, like what Saadi Yusuf did.

Keywords: Arabic poetry, intertextuality, job, meter, modernism, symbolism.

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Authors: Chih-Jian Hu, Chung-Chih Cheng, Hsiao-Yuan Wu., Nien-Tzu Chao

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Increasing user comfort and reducing operation costs have always been primary objectives of lighting control strategies in a building. This paper proposes an architecture of the lighting control system for a daylit office. The system consists of the lighting controller, A/D & D/A converter, dimmable LED lights, and the lighting management software. Verification tests are conducted using the proposed system specialized for the interior lighting of a open-plan office. The results showed the proposed architecture of the lighting system would improve the overall system reliability, lower the system cost, and provide ease of installation and maintenance.

Keywords: control, dimming, LED, lighting.

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Authors: L. Ludovic, R. Daniel, S-E Tbahriti

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Database management systems that integrate user preferences promise better solution for personalization, greater flexibility and higher quality of query responses. This paper presents a tentative work that studies and investigates approaches to express user preferences in queries. We sketch an extend capabilities of SQLf language that uses the fuzzy set theory in order to define the user preferences. For that, two essential points are considered: the first concerns the expression of user preferences in SQLf by so-called fuzzy commensurable predicates set. The second concerns the bipolar way in which these user preferences are expressed on mandatory and/or optional preferences.

Keywords: Flexible query language, relational database, userpreference.

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Authors: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: Internet of Things, IEEE 802.15.4, security cost evaluation, wireless sensor network, energy consumption.

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: Big data, bus headway prediction, machine learning, public transportation.

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Authors: Tero Halme, Juho Kanniainen, Markus Nordberg

Abstract:

According to the existing literature, companies manage analysts’ expectations of their future earnings by issuing pessimistic earnings guidance to meet the expectations. Consequently, one could expect that markets price this pessimistic bias in advance and penalize companies more for lowering the guidance than reward for beating the guidance. In this paper we confirm this empirically. In addition we show that although guidance revisions have a statistically significant relation to stock returns, that is not the case with the actual earnings surprise. Reason for this could be that, after the annual earnings report also information on future earnings power is given at the same time.

Keywords: Management guidance, earnings guidance, pessimistic bias

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