Search results for: Multi Objective Optimization

Authors: T. Lantharthong, N. Rugthaicharoencheep

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This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. A method based on Tabu search algorithm, The Tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system with distributed generations and capacitors placement. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.

Keywords: Network reconfiguration, Distributed generation Capacitor placement, Load balancing, Optimization technique

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Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

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This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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Authors: Md F. Mina, Mohammad D.H. Beg, Muhammad R. Islam, Abu K. M. M. Alam A. Nizam, Rosli M. Younus

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In this study, structural, mechanical, thermal and electrical properties of poly (lactic acid) (PLA) nanocomposites with low-loaded (0-1.5 wt%) untreated, heat and nitric acid treated multiwalled carbon nanotubes (MWCNTs) were studied. Among the composites, untreated 0.5 wt % MWCNTs and acid-treated 1.0 wt% MWCNTs reinforced PLA show the tensile strength and modulus values higher than the others. These two samples along with pure PLA exhibit the stable orthorhombic α-form, whilst other samples reveal the less stable orthorhombic β-form, as demonstrated by X-ray diffraction study. Differential scanning calorimetry reveals the evolution of the mentioned different phases by controlled cooling and discloses an enhancement of PLA crystallization by nanotubes incorporation. Thermogravimetric analysis shows that the MWCNTs loaded sample degraded faster than PLA. Surface resistivity of the nanocomposites is found to be dropped drastically by a factor of 1013 with a low loading of MWCNTs (1.5 wt%).

Keywords: Crystallization, multi-walled carbon nanotubes, nanocomposites, Poly (lactic acid).

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Authors: Sohrab Khanmohammadi, Raana Soltani Zarrin

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In this paper, a heuristic method for simultaneous rescue robot path-planning and mission scheduling is introduced based on project management techniques, multi criteria decision making and artificial potential fields path-planning. Groups of injured people are trapped in a disastrous situation. These people are categorized into several groups based on the severity of their situation. A rescue robot, whose ultimate objective is reaching injured groups and providing preliminary aid for them through a path with minimum risk, has to perform certain tasks on its way towards targets before the arrival of rescue team. A decision value is assigned to each target based on the whole degree of satisfaction of the criteria and duties of the robot toward the target and the importance of rescuing each target based on their category and the number of injured people. The resulted decision value defines the strength of the attractive potential field of each target. Dangerous environmental parameters are defined as obstacles whose risk determines the strength of the repulsive potential field of each obstacle. Moreover, negative and positive energies are assigned to the targets and obstacles, which are variable with respects to the factors involved. The simulation results show that the generated path for two cases studies with certain differences in environmental conditions and other risk factors differ considerably.

Keywords: Artificial potential field, GERT, path planning

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Authors: Dae Il Kim, Jungho Moon, Tae Yun Chung

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This paper presents a car parking monitoring system using a wireless sensor network. The presented sensor network has a line-shaped topology and adopts a TDMA-based protocol for allowing multi-hop communications. Sensor nodes are deployed in the ground of an outdoor parking lot in such a way that a sensor node monitors a parking space. Each sensor node detects the availability of the associated parking space and transmits the detection result to a sink node via intermediate sensor nodes existing between the source sensor node and the sink node. We evaluate the feasibility of the presented sensor network and the TDMA-based communication protocol through experiments using 11 sensor nodes deployed in a real parking lot. The result shows that the presented car parking monitoring system is robust to changes in the communication environments and efficient for monitoring parking spaces of outdoor parking lots.

Keywords: Multi-hop communication, parking monitoring system, TDMA, wireless sensor network.

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Authors: GangHeok Kim, SungHoon Seo, JooSeok Song

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Stream Control Transmission Protocol (SCTP) has been proposed to provide reliable transport of real-time communications. Due to its attractive features, such as multi-streaming and multihoming, the SCTP is often expected to be an alternative protocol for TCP and UDP. In the original SCTP standard, the secondary path is mainly regarded as a redundancy. Recently, most of researches have focused on extending the SCTP to enable a host to send its packets to a destination over multiple paths simultaneously. In order to transfer packets concurrently over the multiple paths, the SCTP should be well designed to avoid unnecessary fast retransmission and the mis-estimation of congestion window size through the paths. Therefore, we propose an Enhanced Cooperative ACK SCTP (ECASCTP) to improve the path recovery efficiency of multi-homed host which is under concurrent multiple transfer mode. We evaluated the performance of our proposed scheme using ns-2 simulation in terms of cwnd variation, path recovery time, and goodput. Our scheme provides better performance in lossy and path asymmetric networks.

Keywords: SCTP, Concurrent Multiple Transfer, CooperativeSack, Dynamic ack policy

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

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The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Keywords: Accident analysis, multi-factorial error modeling, risk, systemic methods.

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Authors: Hema C. R., Paulraj M. P., S. Yaacob, A. H. Adom, R. Nagarajan

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Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification

Keywords: Motor Imagery, Brain Machine Interfaces, Neural Networks, Particle Swarm Optimization, EEG signal processing.

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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: Mohammadjavad Mahdavinejad, Hadi Yazdi

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The greatest influence we have from the world is shaped through the visual form, thus light is an inseparable element in human life. The use of daylight in visual perception and environment readability is an important issue for users. With regard to the hazards of greenhouse gas emissions from fossil fuels, and in line with the attitudes on the reduction of energy consumption, the correct use of daylight results in lower levels of energy consumed by artificial lighting, heating and cooling systems. Windows are usually the starting points for analysis and simulations to achieve visual comfort and energy optimization; therefore, attention should be paid to the orientation of buildings to minimize electrical energy and maximize the use of daylight. In this paper, by using the Design Builder Software, the effect of the orientation of an 18m²(3m*6m) room with 3m height in city of Tehran has been investigated considering the design constraint limitations. In these simulations, the dimensions of the building have been changed with one degree and the window is located on the smaller face (3m*3m) of the building with 80% ratio. The results indicate that the orientation of building has a lot to do with energy efficiency to meet high-performance architecture and planning goals and objectives.

Keywords: Daylight, window, orientation, energy consumption, design builder.

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Authors: T. Aboumahboub, R. Brecha, H. B. Shrestha, U. F. Hutfilter, A. Geiges, W. Hare, M. Schaeffer, L. Welder, M. Gidden

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The proposed stringent mitigation targets require an immediate start for a drastic transformation of the whole energy system. The current Australian energy system is mainly centralized and fossil fuel-based in most states with coal and gas-fired plants dominating the total produced electricity over the recent past. On the other hand, the country is characterized by a huge, untapped renewable potential, where wind and solar energy could play a key role in the decarbonization of the Australia’s future energy system. However, integrating high shares of such variable renewable energy sources (VRES) challenges the power system considerably due to their temporal fluctuations and geographical dispersion. This raises the concerns about flexibility gap in the system to ensure the security of supply with increasing shares of such intermittent sources. One main flexibility dimension to facilitate system integration of high shares of VRES is to increase the cross-sectoral integration through coupling of electricity to other energy sectors alongside the decarbonization of the power sector and reinforcement of the transmission grid. This paper applies a multi-sectoral energy system optimization model for Australia. We investigate the cost-optimal configuration of a renewable-based Australian energy system and its transformation pathway in line with the ambitious range of proposed climate change mitigation targets. We particularly analyse the implications of linking the electricity and transport sectors in a prospective, highly renewable Australian energy system.

Keywords: Decarbonization, energy system modeling, sector coupling, variable renewable energies.

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Authors: Lim Chen Kim, Tan Kian Lam, Chan Yi Chee

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This research presents a multi-modal simulation in the reconstruction of the past and the construction of present in digital cultural heritage on mobile platform. In bringing the present life, the virtual environment is generated through a presented scheme for rapid and efficient construction of 360° panoramic view. Then, acoustical heritage model and crowd model are presented and improvised into the 360° panoramic view. For the reconstruction of past life, the crowd is simulated and rendered in an old trading port. However, the keystone of this research is in a virtual walkthrough that shows the virtual present life in 2D and virtual past life in 3D, both in an environment of virtual heritage sites in George Town through mobile device. Firstly, the 2D crowd is modelled and simulated using OpenGL ES 1.1 on mobile platform. The 2D crowd is used to portray the present life in 360° panoramic view of a virtual heritage environment based on the extension of Newtonian Laws. Secondly, the 2D crowd is animated and rendered into 3D with improved variety and incorporated into the virtual past life using Unity3D Game Engine. The behaviours of the 3D models are then simulated based on the enhancement of the classical model of Boid algorithm. Finally, a demonstration system is developed and integrated with the models, techniques and algorithms of this research. The virtual walkthrough is demonstrated to a group of respondents and is evaluated through the user-centred evaluation by navigating around the demonstration system. The results of the evaluation based on the questionnaires have shown that the presented virtual walkthrough has been successfully deployed through a multi-modal simulation and such a virtual walkthrough would be particularly useful in a virtual tour and virtual museum applications.

Keywords: Boid algorithm, crowd simulation, mobile platform, Newtonian laws, virtual heritage.

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Authors: Jungho Choi, Youngwan Cho

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The paper proposes a way of parallel processing of SURF and Optical Flow for moving object recognition and tracking. The object recognition and tracking is one of the most important task in computer vision, however disadvantage are many operations cause processing speed slower so that it can-t do real-time object recognition and tracking. The proposed method uses a typical way of feature extraction SURF and moving object Optical Flow for reduce disadvantage and real-time moving object recognition and tracking, and parallel processing techniques for speed improvement. First analyse that an image from DB and acquired through the camera using SURF for compared to the same object recognition then set ROI (Region of Interest) for tracking movement of feature points using Optical Flow. Secondly, using Multi-Thread is for improved processing speed and recognition by parallel processing. Finally, performance is evaluated and verified efficiency of algorithm throughout the experiment.

Keywords: moving object recognition, moving object tracking, SURF, Optical Flow, Multi-Thread.

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Authors: D. Mondal, A. Chakrabarti, A. Sengupta

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This paper aims to select the optimal location and setting parameters of TCSC (Thyristor Controlled Series Compensator) controller using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to mitigate small signal oscillations in a multimachine power system. Though Power System Stabilizers (PSSs) are prime choice in this issue, installation of FACTS device has been suggested here in order to achieve appreciable damping of system oscillations. However, performance of any FACTS devices highly depends upon its parameters and suitable location in the power network. In this paper PSO as well as GA based techniques are used separately and compared their performances to investigate this problem. The results of small signal stability analysis have been represented employing eigenvalue as well as time domain response in face of two common power system disturbances e.g., varying load and transmission line outage. It has been revealed that the PSO based TCSC controller is more effective than GA based controller even during critical loading condition.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Small Signal Stability, Thyristor Controlled Series Compensator.

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Authors: Stefan M. Goetz, Thomas Weyh, Hans-Georg Herzog

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The triumph of inductive neuro-stimulation since its rediscovery in the 1980s has been quite spectacular. In lots of branches ranging from clinical applications to basic research this system is absolutely indispensable. Nevertheless, the basic knowledge about the processes underlying the stimulation effect is still very rough and rarely refined in a quantitative way. This seems to be not only an inexcusable blank spot in biophysics and for stimulation prediction, but also a fundamental hindrance for technological progress. The already very sophisticated devices have reached a stage where further optimization requires better strategies than provided by simple linear membrane models of integrate-and-fire style. Addressing this problem for the first time, we suggest in the following text a way for virtual quantitative analysis of a stimulation system. Concomitantly, this ansatz seems to provide a route towards a better understanding by using nonlinear signal processing and taking the nerve as a filter that is adapted for neuronal magnetic stimulation. The model is compact and easy to adjust. The whole setup behaved very robustly during all performed tests. Exemplarily a recent innovative stimulator design known as cTMS is analyzed and dimensioned with this approach in the following. The results show hitherto unforeseen potentials.

Keywords: Theory of magnetic stimulation, inversion, optimization, high voltage oscillator, TMS, cTMS.

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Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

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Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: Clusters of Microcalcifications, Ductal Carcinoma in Situ, Least-Square Support Vector Machine, Particle Swarm Optimization.

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Authors: Khairul Nizam Tahar, Anuar Ahmad

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This paper has introduced a slope photogrammetric mapping using unmanned aerial vehicle. There are two units of UAV has been used in this study; namely; fixed wing and multi-rotor. Both UAVs were used to capture images at the study area. A consumer digital camera was mounted vertically at the bottom of UAV and captured the images at an altitude. The objectives of this study are to obtain three dimensional coordinates of slope area and to determine the accuracy of photogrammetric product produced from both UAVs. Several control points and checkpoints were established Real Time Kinematic Global Positioning System (RTK-GPS) in the study area. All acquired images from both UAVs went through all photogrammetric processes such as interior orientation, exterior orientation, aerial triangulation and bundle adjustment using photogrammetric software. Two primary results were produced in this study; namely; digital elevation model and digital orthophoto. Based on results, UAV system can be used to mapping slope area especially for limited budget and time constraints project.

Keywords: Slope mapping, 3D, DEM, UAV, Photogrammetry, image processing.

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Authors: Ghada Elshafei, Abdelazim Negm

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Recently, the green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives in green buildings should be designed to minimize the overall impact of the built environment that effect on ecosystems in general and in particularly human health and natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state- ofart- review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: Green architecture/building, technologies, optimization, strategies, fuzzy techniques and models.

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Authors: Padmanabhan Balasubramanian, C. Ardil

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An effective approach for realizing the binary tree structure, representing a combinational logic functionality with enhanced throughput, is discussed in this paper. The optimization in maximum operating frequency was achieved through delay minimization, which in turn was possible by means of reducing the depth of the binary network. The proposed synthesis methodology has been validated by experimentation with FPGA as the target technology. Though our proposal is technology independent, yet the heuristic enables better optimization in throughput even after technology mapping for such Boolean functionality; whose reduced CNF form is associated with a lesser literal cost than its reduced DNF form at the Boolean equation level. For cases otherwise, our method converges to similar results as that of [12]. The practical results obtained for a variety of case studies demonstrate an improvement in the maximum throughput rate for Spartan IIE (XC2S50E-7FT256) and Spartan 3 (XC3S50-4PQ144) FPGA logic families by 10.49% and 13.68% respectively. With respect to the LUTs and IOBUFs required for physical implementation of the requisite non-regenerative logic functionality, the proposed method enabled savings to the tune of 44.35% and 44.67% respectively, over the existing efficient method available in literature [12].

Keywords: Binary logic tree, FPGA based design, Boolean function, Throughput rate, CNF, DNF.

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Authors: Ion Miciu

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The system is made with main distributed components: First Level: Industrial Computers placed in Control Room (monitors thermal and electrical processes based on the data provided by the second level); Second Level: PLCs which collects data from process and transmits information on the first level; also takes commands from this level which are further, passed to execution elements from third level; Third Level: field elements consisting in 3 categories: data collecting elements; data transfer elements from the third level to the second; execution elements which take commands from the second level PLCs and executes them after which transmits the confirmation of execution to them. The purpose of the automatic functioning is the optimization of the co-generative electrical energy commissioning in the national energy system and the commissioning of thermal energy to the consumers. The integrated system treats the functioning of all the equipments and devices as a whole: Gas Turbine Units (GTU); MT 20kV Medium Voltage Station (MVS); 0,4 kV Low Voltage Station (LVS); Main Hot Water Boilers (MHW); Auxiliary Hot Water Boilers (AHW); Gas Compressor Unit (GCU); Thermal Agent Circulation Pumping Unit (TPU); Water Treating Station (WTS).

Keywords: Automation System, Cogenerative Power Plant, Control, Monitoring, Real Time

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Authors: Mohanad Alhabo, Naveed Nawaz

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The ongoing call or data session must be maintained to ensure a good quality of service. This can be accomplished by performing handover procedure while the user is on the move. However, dense deployment of small cells in 5G networks is a challenging issue due to the extensive number of handovers. In this paper, a neighbour cell list method is proposed to reduce the number of target small cells and hence minimizing the number of handovers. The neighbour cell list is built by omitting cells that could cause an unnecessary handover and/or handover failure because of short time of stay of a user in these cells. A multi-attribute decision making technique, simple additive weighting, is then applied to the optimized neighbour cell list. The performance of the proposed method is analysed and compared with that of the existing methods. Results disclose that our method decreases the candidate small cell list, unnecessary handovers, handover failure and short time of stay cells compared to the competitive method.

Keywords: Handover, HetNets, MADM, small cells.

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Authors: Sundus Ayyaz, Saad Rehman

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In the recent years, a fundamental revolution in the Mobile Phone technology from just being able to provide voice and short message services to becoming the most essential part of our lives by connecting to network and various app stores for downloading software apps of almost every activity related to our life from finding location to banking from getting news updates to downloading HD videos and so on. This progress in Smart Phone industry has modernized and transformed our way of living into a trouble-free world. The smart phone has become our personal computers with the addition of significant features such as multi core processors, multi-tasking, large storage space, bluetooth, WiFi, including large screen and cameras. With this evolution, the rise in the security threats have also been amplified. In Literature, different threats related to smart phones have been highlighted and various precautions and solutions have been proposed to keep the smart phone safe which carries all the private data of a user. In this paper, a survey has been carried out to find out the most secure and the most unsecure smart phone operating system among the most popular smart phones in use today.

Keywords: Smart phone, operating system, security threats, Android, iOS, Balckberry, Windows.

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Authors: Ivana T. Karabegović, Saša S. Stojičević, Dragan T. Veličković, Nada Č. Nikolić, Miodrag L. Lazić

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Optimization of a microwave-assisted extraction of cherry laurel (Prunus laurocerasus) fruit using methanol was studied. The influence of process parameters (microwave power, plant material-to-solvent ratio and the extraction time) on the extraction efficiency were optimized by using response surface methodology. The predicted maximum yield of extractive substances (41.85 g/100 g fresh plant material) was obtained at microwave power of 600 W and plant material to solvent ratio of 0.2 g/cm3 after 26 minutes of extraction, while a mean value of 40.80±0.41 g/100 g fresh plant material was obtained from laboratory experiments. This proves applicability of the model in predicting optimal extraction conditions with minimal laborious and time consuming. The results indicated that all process parameters were effective on the extraction efficiency, while the most important factor was extraction time. In order to rationalize production the optimal economical condition which gave a large total extract yield with minimal energy and solvent consumption was found.

Keywords: Cherry laurel, Extraction, Multiple regression modeling, Microwave.

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Authors: H. Urbancova, J. Urbanec

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Today the intangible assets are the capital of knowledge and are the most important and the most valuable resource for organizations. All employees have knowledge independently of the kind of jobs they do. Knowledge is thus an asset, which influences business operations. The objective of this article is to identify knowledge continuity as an objective of business continuity management. The article has been prepared based on the analysis of secondary sources and the evaluation of primary sources of data by means of a quantitative survey conducted in the Czech Republic. The conclusion of the article is that organizations that apply business continuity management do not focus on the preservation of the knowledge of key employees. Organizations ensure knowledge continuity only intuitively, on a random basis, non-systematically and discontinuously. The non-ensuring of knowledge continuity represents a threat of loss of key knowledge for organizations and can also negatively affect business continuity.

Keywords: Business continuity, knowledge, organizations, survey.

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Authors: John Justo Ambuchi, Zhaohan Zhang, Yujie Feng

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Quick development and usage of nanotechnology have resulted to massive use of various nanoparticles, such as iron oxide nanoparticles (IONPs) and multi-wall carbon nanotubes (MWCNTs). Thus, this study investigated the role of IONPs and MWCNTs in enhancing bioenergy recovery. Results show that IONPs at a concentration of 750 mg/L and MWCNTs at a concentration of 1500 mg/L induced faster substrate utilization and biogas production rates than the control. IONPs exhibited higher carbon oxygen demand (COD) removal efficiency than MWCNTs while on the contrary, MWCNT performance on biogas generation was remarkable than IONPs. Furthermore, scanning electron microscopy (SEM) investigation revealed extracellular polymeric substances (EPS) excretion from AGS had an interaction with nanoparticles. This interaction created a protective barrier to microbial consortia hence reducing their cytotoxicity. Microbial community analyses revealed genus predominance of bacteria of Anaerolineaceae and Longilinea. Their role in biodegradation of the substrate could have highly been boosted by nanoparticles. The archaea predominance of the genus level of Methanosaeta and Methanobacterium enhanced methanation process. The presence of bacteria of genus Geobacter was also reported. Their presence might have significantly contributed to direct interspecies electron transfer in the system. Exposure of AGS to nanoparticles promoted direct interspecies electron transfer among the anaerobic fermenting bacteria and their counterpart methanogens during the anaerobic digestion process. This results provide useful insightful information in understanding the response of microorganisms to IONPs and MWCNTs in the complex natural environment.

Keywords: Anaerobic granular sludge, extracellular polymeric substances, iron oxide nanoparticles, multi-wall carbon nanotubes.

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Authors: Avadhoot Bhosale, Robin Davis P., Pradip Sarkar

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The seismic performance of buildings with irregular distribution of mass, stiffness and strength along the height may be significantly different from that of regular buildings with masonry infill. Masonry infilled reinforced concrete (RC) frames are very common structural forms used for multi-storey building construction. These structures are found to perform better in past earthquakes owing to additional strength, stiffness and energy dissipation in the infill walls. The seismic performance of a building depends on the variation of material, structural and geometrical properties. The sensitivity of these properties affects the seismic response of the building. The main objective of the sensitivity analysis is to found out the most sensitive parameter that affects the response of the building. This paper presents a sensitivity analysis by considering 5% and 95% probability value of random variable in the infills characteristics, trying to obtain a reasonable range of results representing a wide number of possible situations that can be met in practice by using pushover analysis. The results show that the strength-related variation values of concrete and masonry, with the exception of tensile strength of the concrete, have shown a significant effect on the structural performance and that this effect increases with the progress of damage condition for the concrete. The seismic risk assessments of the selected frames are expressed in terms of reliability index.

Keywords: Fragility curve, sensitivity analysis, reliability index, RC frames.

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Authors: Carlos Gonzalez

Abstract:

This paper describes a system to optimize the use of the internet by clients requiring downloading of videos at peak hours. The system consists of a web server belonging to a provider of video contents, a provider of internet communications and a software application running on a client’s computer. The client using the application software will communicate to the video provider a list of the client’s future video demands. The video provider calculates which videos are going to be more in demand for download in the immediate future, and proceeds to request the internet provider the most optimal hours to do the downloading. The times of the downloading will be sent to the application software, which will use the information of pre-established hours negotiated between the video provider and the internet provider to download those videos. The videos will be saved in a special protected section of the user’s hard disk, which will only be accessed by the application software in the client’s computer. When the client is ready to see a video, the application will search the list of current existent videos in the area of the hard disk; if it does exist, it will use this video directly without the need for internet access. We found that the best way to optimize the download traffic of videos is by negotiation between the internet communication provider and the video content provider.

Keywords: Internet optimization, video download, future demands, secure storage.

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Authors: Rui Qiu, Giles Hardy, Dong Qu, Robert Trengove, Manjree Agarwal, YongLin Ren

Abstract:

Phytophthora cinnamomi (P. c) is a plant pathogenic oomycete that is capable of damaging plants in commercial production systems and natural ecosystems worldwide. The most common methods for the detection and diagnosis of P. c infection are expensive, elaborate and time consuming. This study was carried out to examine whether species specific and life cycle specific volatile organic compounds (VOCs) can be absorbed by solid-phase microextraction fibers and detected by gas chromatography that are produced by P. c and another oomycete Pythium dissotocum. A headspace solid-phase microextraction (HS-SPME) together with gas chromatography (GC) method was developed and optimized for the identification of the VOCs released by P. c. The optimized parameters included type of fiber, exposure time, desorption temperature and desorption time. Optimization was achieved with the analytes of P. c+V8A and V8A alone. To perform the HS-SPME, six types of fiber were assayed and compared: 7μm Polydimethylsiloxane (PDMS), 100μm Polydimethylsiloxane (PDMS), 50/30μm Divinylbenzene/CarboxenTM/Polydimethylsiloxane DVB/CAR/PDMS), 65μm Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), 85μm Polyacrylate (PA) fibre and 85μm CarboxenTM/ Polydimethylsiloxane (Carboxen™/PDMS). In a comparison of the efficacy of the fibers, the bipolar fiber DVB/CAR/PDMS had a higher extraction efficiency than the other fibers. An exposure time of 16h with DVB/CAR/PDMS fiber in the sample headspace was enough to reach the maximum extraction efficiency. A desorption time of 3min in the GC injector with the desorption temperature of 250°C was enough for the fiber to desorb the compounds of interest. The chromatograms and morphology study confirmed that the VOCs from P. c+V8A had distinct differences from V8A alone, as did different life cycle stages of P. c and different taxa such as Pythium dissotocum. The study proved that P. c has species and life cycle specific VOCs, which in turn demonstrated the feasibility of this method as means of

Keywords: Gas chromatography, headspace solid-phase microextraction, optimization, volatile compounds.

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Authors: A. Abdalla, A. Kaltayev

Abstract:

The ultimate goal of this article is to develop a robust and accurate numerical method for solving hyperbolic conservation laws in one and two dimensions. A hybrid numerical method, coupling a cheap fourth order total variation diminishing (TVD) scheme [1] for smooth region and a Robust seventh-order weighted non-oscillatory (WENO) scheme [2] near discontinuities, is considered. High order multi-resolution analysis is used to detect the high gradients regions of the numerical solution in order to capture the shocks with the WENO scheme, while the smooth regions are computed with fourth order total variation diminishing (TVD). For time integration, we use the third order TVD Runge-Kutta scheme. The accuracy of the resulting hybrid high order scheme is comparable with these of WENO, but with significant decrease of the CPU cost. Numerical demonstrates that the proposed scheme is comparable to the high order WENO scheme and superior to the fourth order TVD scheme. Our scheme has the added advantage of simplicity and computational efficiency. Numerical tests are presented which show the robustness and effectiveness of the proposed scheme.

Keywords: WENO scheme, TVD schemes, smoothness indicators, multi-resolution.

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Authors: Jonqlan Lin, C. Y. Tasi, K. H. Lin

Abstract:

This paper addresses the issue of the autonomous mobile robot (AMR) navigation task based on the hybrid control modes. The novel hybrid control mode, based on multi-sensors information by using the fuzzy approach, has been presented in this research. The system operates in real time, is robust, enables the robot to operate with imprecise knowledge, and takes into account the physical limitations of the environment in which the robot moves, obtaining satisfactory responses for a large number of different situations. An experiment is simulated and carried out with a pioneer mobile robot. From the experimental results, the effectiveness and usefulness of the proposed AMR obstacle avoidance and navigation scheme are confirmed. The experimental results show the feasibility, and the control system has improved the navigation accuracy. The implementation of the controller is robust, has a low execution time, and allows an easy design and tuning of the fuzzy knowledge base.

Keywords: Autonomous mobile robot, obstacle avoidance, MEMS, hybrid control mode, navigation control.

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