Search results for: smart U-parking planning

Authors: Mohamed Watfa, William Daher, Hisham Al Azar

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The main idea behind in network aggregation is that, rather than sending individual data items from sensors to sinks, multiple data items are aggregated as they are forwarded by the sensor network. Existing sensor network data aggregation techniques assume that the nodes are preprogrammed and send data to a central sink for offline querying and analysis. This approach faces two major drawbacks. First, the system behavior is preprogrammed and cannot be modified on the fly. Second, the increased energy wastage due to the communication overhead will result in decreasing the overall system lifetime. Thus, energy conservation is of prime consideration in sensor network protocols in order to maximize the network-s operational lifetime. In this paper, we give an energy efficient approach to query processing by implementing new optimization techniques applied to in-network aggregation. We first discuss earlier approaches in sensors data management and highlight their disadvantages. We then present our approach “Energy Efficient Indexed Aggregation" (EEIA) and evaluate it through several simulations to prove its efficiency, competence and effectiveness.

Keywords: Sensor Networks, Data Base, Data Fusion, Aggregation, Indexing, Energy Efficiency

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Authors: Tim Klemke, Peter Nyhuis

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In today-s turbulent environment, companies are faced with two principal challenges. On the one hand, it is necessary to produce ever more cost-effectively to remain competitive. On the other hand, factories need to be transformable in order to manage unpredictable changes in the corporate environment. To deal with these different challenges, companies use the philosophy of lean production in the first case, in the second case the philosophy of transformability. To a certain extent these two approaches follow different directions. This can cause conflicts when designing factories. Therefore, the Institute of Production Systems and Logistics (IFA) of the Leibniz University of Hanover has developed a procedure to allow companies to evaluate and design their factories with respect to the requirements of both philosophies.

Keywords: Factory planning, lean production, transformability

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Lèvy flight, situation awareness, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

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In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO₂ and O₃ concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: Distributed sensor system, environmental monitoring, Internet of Things, IoT, Smart Cities.

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Authors: Petr Teply

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Liquidity risk management ranks to key concepts applied in finance. Liquidity is defined as a capacity to obtain funding when needed, while liquidity risk means as a threat to this capacity to generate cash at fair costs. In the paper we present challenges of liquidity risk management resulting from the 2007- 2009 global financial upheaval. We see five main regulatory liquidity risk management issues requiring revision in coming years: liquidity measurement, intra-day and intra-group liquidity management, contingency planning and liquidity buffers, liquidity systems, controls and governance, and finally models testing the viability of business liquidity models.

Keywords: liquidity, risk management, regulation, global crisis

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Authors: Josefina Bengoechea, Alex Bell

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In the metaverse, the characters were avatars working in a 3-dimensional virtual reality. This virtual reality existed beyond reality. The metaverse is a “the post-reality universe”; a perpetual and persistent multiuser environment in which physical reality and digital virtuality are merged. The virtual infrastructure needed to build a metaverse (which is in the process of being created), are: web3 technologies, non-fungible tokens (NFTs), blockchain, smart contracts, and cryptocurrencies. Web3 refers to a new iteration of the actual web2. The actual web2 is dominated by powerful providers like Google, Apple, Amazon, and other corporate tech companies. The vision for web3 is a decentralized, and thus more equitable version of the web. The aim of this paper is, first, to present the Metaverse as a form of reality in which physical reality and digital virtuality combined to provide new experiences to users; second, to discuss the implications for education, specifically for higher education, and how programs will have to be modified so that the skills obtained by graduates match those demanded by the virtual labour market. This paper builds upon a constructivist approach, combining a literature review and research on key publications.

Keywords: Ethics in technology, cross realities, cryptocurrencies, labour market, metaverse, technology in higher education.

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Authors: Kamel Khoualdi, Radia Benghezal

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Research in distributed artificial intelligence and multiagent systems consider how a set of distributed entities can interact and coordinate their actions in order to solve a given problem. In this paper an overview of this concept and its evolution is presented particularly its application in the design of intelligent tutoring systems. An intelligent tutor based on the concept of agent and centered specifically on the design of a pedagogue agent is illustrated. Our work has two goals: the first one concerns the architecture aspect and the design of a tutor using multiagent approach. The second one deals particularly with the design of a part of a tutor system: the pedagogue agent.

Keywords: Intelligent tutoring systems, Multiagent systems, Pedagogue agent, Planning.

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Authors: Mojtaba Ghodsi, Hamidreza Ziaifar, Morteza Mohammadzaheri, Payam Soltani

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This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.

Keywords: Internal damping coefficient, external damping coefficient, Euler-Bernoulli, energy harvester, Galfenol, magnetostrictive, response surface method.

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Authors: Yi-Cheng Huang, Yan-Chen Shin

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This paper proposes method of diagnosing ball screw preload loss through the Hilbert-Huang Transform （HHT） and Multiscale entropy （MSE） process. The proposed method can diagnose ball screw preload loss through vibration signals when the machine tool is in operation. Maximum dynamic preload of 2 %, 4 %, and 6 % ball screws were predesigned, manufactured, and tested experimentally. Signal patterns are discussed and revealed using Empirical Mode Decomposition（EMD）with the Hilbert Spectrum. Different preload features are extracted and discriminated using HHT. The irregularity development of a ball screw with preload loss is determined and abstracted using MSE based on complexity perception. Experiment results show that the proposed method can predict the status of ball screw preload loss. Smart sensing for the health of the ball screw is also possible based on a comparative evaluation of MSE by the signal processing and pattern matching of EMD/HHT. This diagnosis method realizes the purposes of prognostic effectiveness on knowing the preload loss and utilizing convenience.

Keywords: Empirical Mode Decomposition, Hilbert-Huang Transform, Multi-scale Entropy, Preload Loss, Single-nut Ball Screw

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Authors: A. Al-Mazloum, E. Omer, M. F. A. Abdullah

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Recently many cases of missing children between ages 14 and 17 years are reported. Parents always worry about the possibility of kidnapping of their children. This paper proposes an Android based solution to aid parents to track their children in real time. Nowadays, most mobile phones are equipped with location services capabilities allowing us to get the device’s geographic position in real time. The proposed solution takes the advantage of the location services provided by mobile phone since most of kids carry mobile phones. The mobile application use the GPS and SMS services found in Android mobile phones. It allows the parent to get their child’s location on a real time map. The system consists of two sides, child side and parent side. A parent’s device main duty is to send a request location SMS to the child’s device to get the location of the child. On the other hand, the child’s device main responsibility is to reply the GPS position to the parent’s device upon request.

Keywords: Child Tracking System, Global Positioning System (GPS), SMS-based Mobile Application.

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Authors: Seyed Hamidreza Hejazi Dehghani, Neda Khounsari

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Quick growth of electronic commerce in developed countries means that developing nations must change in their commerce strategies fundamentally. Most organizations are aware of the impact of the Internet and e-Commerce on the future of their firm, and thus, they have to focus on organizational factors that have an effect on the deployment of an e-Commerce strategy. In this situation, it is essential to identify organizational factors such as the organizational culture, human resources, size, structure and product/service that impact an e-commerce strategy. Accordingly, this research specifies the effects of organizational factors on applying an e-commerce strategy in the Namakin food industry. The statistical population of this research is 95 managers and employees. Cochran's formula is used for determination of the sample size that is 77 of the statistical population. Also, SPSS and Smart PLS software were utilized for analyzing the collected data. The results of hypothesis testing show that organizational factors have positive and significant effects of applying an e-Commerce strategy. On the other hand, sub-hypothesizes show that effectiveness of the organizational culture and size criteria were rejected and other sub-hypothesis were accepted.

Keywords: Electronic commerce, organizational factors, attitude of managers, organizational readiness.

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Authors: Vahid Rostami, Saeed Ebrahimijam, P.khajehpoor, P.Mirzaei, Mahdi Yousefiazar

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This paper introduces our first efforts of developing a new team for RoboCup Middle Size Competition. In our robots we have applied omni directional based mobile system with omnidirectional vision system and fuzzy control algorithm to navigate robots. The control architecture of MRL middle-size robots is a three layered architecture, Planning, Sequencing, and Executing. It also uses Blackboard system to achieve coordination among agents. Moreover, the architecture should have minimum dependency on low level structure and have a uniform protocol to interact with real robot.

Keywords: Robocup, Soccer robots, Fuzzy controller, Multi agent.

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Authors: Yessengeldy Kuanyshpayev

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Now in some countries of the world the cellular market is on the point of saturation, in others - positive dynamics of development kept on. The reasons for it are also different, but there are united by their general susceptibility to innovation changes, if they are really innovative. If to take as an example the cellular market of Kazakhstan it is defined by the low percent of smart phones at consumers, the low population density, undercapacity of the 3G channel, and absence of universal access to the LTE technology that limits dynamical growth of this branch. These moments are aggravated by failures of starting commercial projects by private companies which prevent to be implemented and widely adopted to a new product among consumers. The object of the research is possible integration of wireless and program technologies at which introduction the idea can regenerate in an innovation. The analysis of existing projects in the market and the possible union of the technologies through a prism of theoretical bases of innovative activity shows that efficiency of the company by development and introduction of innovations is possible only thanks to strict observance of all terms and conditions of the innovative process which main term is profit. Despite that fact that on a global scale the innovativeness issue of companies is very popular, there are no researches about possibility of innovative breaks in the field of wireless access to the Internet in the cellular market of Kazakhstan.

Keywords: Cellular market, commercialization, innovation, the effectiveness of company.

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Authors: C. Tung, P.-L. Tso

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This paper presents a complete procedure for tool path planning and blade machining in 5-axis manufacturing. The actual cutting contact and cutter locations can be determined by lead and tilt angles. The tool path generation is implemented by piecewise curved approximation and chordal deviation detection. An application about drive surface method promotes flexibility of tool control and stability of machine motion. A real manufacturing process is proposed to separate the operation into three regions with five stages and to modify the local tool orientation with an interactive algorithm.

Keywords: 5-axis machining, tool orientation, lead and tilt angles, tool path generation.

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment, deep neural networks.

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Authors: M. Das Gupta, S. Banerjee

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Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.

Keywords: Case based reasoning, Exudates, Retina image, Similarity based retrieval.

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Authors: Christian Meinecke, Bernd Scholz-Reiter

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The integrated problem of production and distribution scheduling is relevant in many industrial applications. Thus, many heuristics to solve this integrated problem have been developed in the last decade. Most of these heuristics use a sequential working principal or a single decomposition and integration approach to separate and solve subproblems. A heuristic using a multi step decomposition and integration approach is presented in this paper and evaluated in a case study. The result show significant improved results compared with sequential scheduling heuristics.

Keywords: Production and outbound distribution, integrated planning, heuristic, decomposition and integration.

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Authors: Chrysoula Karathanasi, Senad Karavdic, Angela Odero, Michèle Baumann

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It is not only the economic determinants that impact on life conditions, but maintaining a good level of life satisfaction (LS) may also be an important challenge currently. In Luxembourg, university students receive financial aid from the government. They are then registered at the Centre for Documentation and Information on Higher Education (CEDIES). Luxembourg is built on migration with almost half its population consisting of foreigners. It is upon this basis that our research aims to analyze the associations with mental health factors (health satisfaction, psychological quality of life, worry), perceived financial situation, career attitudes (adaptability, optimism, knowledge, planning) and LS, for non-Luxembourgish and native postgraduate students. Between 2012 and 2013, postgraduates registered at CEDIES were contacted by post and asked to participate in an online survey with either the option of English or French. The study population comprised of 644 respondents. Our statistical analysis excluded: those born abroad who had Luxembourgish citizenship, or those born in Luxembourg who did not have citizenship. Two groups were formed one consisting 147 non-Luxembourgish and the other 284 natives. A single item measured LS (1=not at all satisfied to 10=very satisfied). Bivariate tests, correlations and multiple linear regression models were used in which only significant relationships (p<0.05) were integrated. Among the two groups no differences were found between LS indicators (7.8/10 non-Luxembourgish; 8.0/10 natives) as both were higher than the European indicator of 7.2/10 (for 25-34 years). In the case of non-Luxembourgish students, they were older than natives (29.3 years vs. 26.3 years) perceived their financial situation as more difficult, and a higher percentage of their parents had an education level higher than a Bachelor's degree (father 59.2% vs 44.6% for natives; mother 51.4% vs 33.7% for natives). In addition, the father’s education was related to the LS of postgraduates and the higher was the score, the greater was the contribution to LS. Whereas for native students, when their scores of health satisfaction and career optimism were higher, their LS’ score was higher. For both groups their LS was linked to mental health-related factors, perception of their financial situation, career optimism, adaptability and planning. The higher the psychological quality of life score was, the greater the LS of postgraduates’ was. Good health and positive attitudes related to the job market enhanced their LS indicator.

Keywords: Career attitudes, fathers’ education level, life satisfaction, mental health.

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Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, Meisam Babaie

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Gas lift optimization is becoming more important now a day in petroleum industry. A proper lift optimization can reduce the operating cost, increase the net present value (NPV) and maximize the recovery from the asset. A widely accepted definition of gas lift optimization is to obtain the maximum output under specified operating conditions. In addition, gas lift, a costly and indispensable means to recover oil from high depth reservoir entails solving the gas lift optimization problems. Gas lift optimization is a continuous process; there are two levels of production optimization. The total field optimization involves optimizing the surface facilities and the injection rate that can be achieved by standard tools softwares. Well level optimization can be achieved by optimizing the well parameters such as point of injection, injection rate, and injection pressure. All these aspects have been investigated and presented in this study by using experimental data and PROSPER simulation program. The results show that the well head pressure has a large influence on the gas lift performance and also proved that smart gas lift valve can be used to improve gas lift performance by controlling gas injection from down hole. Obtaining the optimum gas injection rate is important because excessive gas injection reduces production rate and consequently increases the operation cost.

Keywords: Optimization, production rate, reservoir pressure effect, gas injection rate effect, gas injection pressure.

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Authors: Víctor Martínez del Rey, Kourosh Nasr Esfahani, Amir Masoud Samani Majd

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In this experimental study, the behaviors of Mixed Oxidant solution components (MOS) and sodium hypochlorite (HYPO) as the most commonly applied surface disinfectant were compared through the effectiveness of chlorine disinfection as a function of the contact time and residual chlorine. In this regard, the variation of pH, free available chlorine (FAC) concentration, and electric conductivity (EC) of disinfection solutions in different concentrations were monitored over 48 h contact time. In parallel, the plant stress activated by chlorine-based disinfectants was assessed by comparing MOS and HYPO. The elements of pH and EC in the plant-soil and their environmental impacts, spread by disinfection solutions were analyzed through several concentrations of FAC including 500 mg/L, 1000 mg/L, and 5000 mg/L in irrigated water. All the experiments were carried out at the service station of Sant Cugat, Spain. The outcomes indicated lower pH and higher durability of MOS than HYPO at the same concentration of FAC which resulted in promising stability of FAC within MOS. Furthermore, the pH and EC value of plant-soil irrigated by NaOCl solution were higher than that of MOS solution at the same FAC concentration. On-site generation of MOS as a safe chlorination option might be considered an imaginary future of smart cities.

Keywords: Disinfection, free available chlorine, on-site generation, sodium hypochlorite.

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Authors: Feng Yang, Xuehai Zhou, Dalei Hu

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In this paper, we propose a general mandatory access framework for distributed systems. The framework can be applied into multiple operating systems and can handle multiple stakeholders. Despite considerable advancements in the area of mandatory access control, a certain approach to enforcing mandatory access control can only be applied in a specific operating system. Other than PC market in which windows captures the overwhelming shares, there are a number of popular operating systems in the emerging smart phone environment, i.e. Android, Windows mobile, Symbian, RIM. It should be noted that more and more stakeholders are involved in smartphone software, such as devices owners, service providers and application providers. Our framework includes three parts—local decision layer, the middle layer and the remote decision layer. The middle layer takes charge of managing security contexts, OS API, operations and policy combination. The design of the remote decision layer doesn’t depend on certain operating systems because of the middle layer’s existence. We implement the framework in windows, linux and other popular embedded systems.

Keywords: Mandatory Access Control, Distributed System, General Platform.

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Authors: Rawinun Praserttaweelap, Somyot Kiatwanidvilai

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Obstacle avoidance is the one key for the robot system in unknown environment. The robots should be able to know their position and safety region. This research starts on the path planning which are SLAM and AMCL in ROS system. In addition, the best parameters of the obstacle avoidance function are required. In situation on Hard Disk Drive Manufacturing, the distance between robots and obstacles are very serious due to the manufacturing constraint. The simulations are accomplished by the SLAM and AMCL with adaptive velocity and safety region calculation.

Keywords: Obstacle avoidance, simultaneous localization and mapping, adaptive Monte Carlo localization, KLD sampling.

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Authors: Giovanni Incerti

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The motion planning procedure described in this paper has been developed in order to eliminate or reduce the residual vibrations of electromechanical positioning systems, without augmenting the motion time (usually imposed by production requirements), nor introducing overtime for vibration damping. The proposed technique is based on a suitable choice of the motion law assigned to the servomotor that drives the mechanism. The reference profile is defined by a Bezier curve, whose shape can be easily changed by modifying some numerical parameters. By means of an optimization technique these parameters can be modified without altering the continuity conditions imposed on the displacement and on its time derivatives at the initial and final time instants.

Keywords: Servomechanism, residual vibrations, motion optimization.

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Authors: L. Chaussy, M. Nouvel

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Workload of the system engineers during Integration Validation Verification process of Electronic Warfare Systems (EWS) is growing with complexity of the systems and with the diversity of tested cases (diversity of operational scenario in front of EWS). Even if the use of Digital Twin makes easier conception and development phases in term of planning and test equipment availability, time to analyze tests results is still too long and too complex. The idea to reduce the system engineer’s workload and improve test coverage is to introduce some intelligent and aid-analysis algorithms to improve this step.

Keywords: Analysis tools, automatic testing, digital twin, electronic warfare system.

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Authors: Kho Mei Ye, Hamzah Abdul Rahman

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This paper provides some thoughts about the lack of attentiveness of building commissioning in the construction industry and the lack of handling in project commissioning as an integral part of the project life-cycle. Many have perceived commissioning as the problem solving process of a project, rather than the start up of the equipment, or the handing over of the project to the client. Therefore, there is a lack of proper attention in the planning of commissioning as a vital part of the project life-cycle. This review paper aims to highlight the benefits of building commissioning and to propose the lacking of knowledge gap on building commissioning. Finally, this paper hopes to propose the shift of focus on this matter in future research.

Keywords: building, commissioning, construction, delay

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Authors: Rohan Putatunda, Aryya Gangopadhyay

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Acoustic sensors, if embedded in smart street lights, can help in capturing the activities (car honking, sirens, events, traffic, etc.) in cities. Needless to say, the acoustic data from such scenarios are complex due to multiple audio streams originating from different events, and when decomposed to independent signals, the amount of retrieved data volume is small in quantity which is inadequate to train deep neural networks. So, in this paper, we address the two challenges: a) separating the mixed signals, and b) developing an efficient acoustic classifier under data paucity. So, to address these challenges, we propose an architecture with supervised deep learning, where the initial captured mixed acoustics data are analyzed with Fast Fourier Transformation (FFT), followed by filtering the noise from the signal, and then decomposed to independent signals by fast independent component analysis (Fast ICA). To address the challenge of data paucity, we propose a multi feature-based deep neural network with high performance that is reflected in our experiments when compared to the conventional convolutional neural network (CNN) and multi-layer perceptron (MLP).

Keywords: FFT, ICA, vehicle classification, multi-feature DNN, CNN, MLP.

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Authors: G. Dottavio, M. F. Andrade, F. Renard, V. Cheutet, A.-L. L. S. Vercraene, P. Hoang, S. Briet, R. Dachicourt, Y. Baizet

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An important number of technological equipment and high-skilled workers over long periods of time have to be mobilized during nuclear decommissioning processes. The related operations generate complex flows of waste and high inventory levels, associated to information flows of heterogeneous types. Taking into account that more than 10 decommissioning operations are on-going in France and about 50 are expected toward 2025: A big challenge is addressed today. The management of decommissioning and dismantling of nuclear installations represents an important part of the nuclear-based energy lifecycle, since it has an environmental impact as well as an important influence on the electricity cost and therefore the price for end-users. Bringing new technologies and new solutions into decommissioning methodologies is thus mandatory to improve the quality, cost and delay efficiency of these operations. The purpose of our project is to improve decommissioning management efficiency by developing a decision-support framework dedicated to plan nuclear facility decommissioning operations and to optimize waste evacuation by means of a logistic approach. The target is to create an easy-to-handle tool capable of i) predicting waste flows and proposing the best decommissioning logistics scenario and ii) managing information during all the steps of the process and following the progress: planning, resources, delays, authorizations, saturation zones, waste volume, etc. In this article we present our results from waste nuclear flows simulation during decommissioning process, including discrete-event simulation supported by FLEXSIM 3-D software. This approach was successfully tested and our works confirms its ability to improve this type of industrial process by identifying the critical points of the chain and optimizing it by identifying improvement actions. This type of simulation, executed before the start of the process operations on the basis of a first conception, allow ‘what-if’ process evaluation and help to ensure quality of the process in an uncertain context. The simulation of nuclear waste flows before evacuation from the site will help reducing the cost and duration of the decommissioning process by optimizing the planning and the use of resources, transitional storage and expensive radioactive waste containers. Additional benefits are expected for the governance system of the waste evacuation since it will enable a shared responsibility of the waste flows.

Keywords: Nuclear decommissioning, logistical optimization, decision-support framework, waste management.

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Authors: Zhiyong Li, Zhigang Chen, Chao Fu, Shipeng Zhang

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Load forecasting has always been the essential part of an efficient power system operation and planning. A novel approach based on support vector machines is proposed in this paper for annual power load forecasting. Different kernel functions are selected to construct a combinatorial algorithm. The performance of the new model is evaluated with a real-world dataset, and compared with two neural networks and some traditional forecasting techniques. The results show that the proposed method exhibits superior performance.

Keywords: combinatorial algorithm, data mining, load forecasting, support vector machines

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Authors: Ahmed Amin Mousa, M. Abd El-Salam

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This study discusses a simple solution for the problem of shortage in learning resources for kindergarten teachers. Occasionally, kindergarten teachers cannot access proper resources by usual search methods as libraries or search engines. Furthermore, these methods require a long time and efforts for preparing. The study is expected to facilitate accessing learning resources. Moreover, it suggests a potential direction for using QR code inside the classroom. The present work proposes that QR code can be used for digitizing kindergarten curriculums and accessing various learning resources. It investigates using QR code for saving information related to the concepts which kindergarten teachers use in the current educational situation. The researchers have established a guide for kindergarten teachers based on the Egyptian official curriculum. The guide provides different learning resources for each scientific and mathematical concept in the curriculum, and each learning resource is represented as a QR code image that contains its URL. Therefore, kindergarten teachers can use smartphone applications for reading QR codes and displaying the related learning resources for students immediately. The guide has been provided to a group of 108 teachers for using inside their classrooms. The results showed that the teachers approved the guide, and gave a good response.

Keywords: Kindergarten, child, learning resources, QR code, smart phone, mobile.

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Authors: C. Wan, A. Mita

Abstract:

This paper proposes a novel system for monitoring the health of underground pipelines. Some of these pipelines transport dangerous contents and any damage incurred might have catastrophic consequences. However, most of these damage are unintentional and usually a result of surrounding construction activities. In order to prevent these potential damages, monitoring systems are indispensable. This paper focuses on acoustically recognizing road cutters since they prelude most construction activities in modern cities. Acoustic recognition can be easily achieved by installing a distributed computing sensor network along the pipelines and using smart sensors to “listen" for potential threat; if there is a real threat, raise some form of alarm. For efficient pipeline monitoring, a novel monitoring approach is proposed. Principal Component Analysis (PCA) was studied and applied. Eigenvalues were regarded as the special signature that could characterize a sound sample, and were thus used for the feature vector for sound recognition. The denoising ability of PCA could make it robust to noise interference. One class SVM was used for classifier. On-site experiment results show that the proposed PCA and SVM based acoustic recognition system will be very effective with a low tendency for raising false alarms.

Keywords: One class SVM, pipeline monitoring system, principal component analysis, sound recognition, third party damage.

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