Search results for: efficient inventory

Authors: Tlili-Guiassa Yamina

Abstract:

Many natural language expressions are ambiguous, and need to draw on other sources of information to be interpreted. Interpretation of the e word تعاون to be considered as a noun or a verb depends on the presence of contextual cues. To interpret words we need to be able to discriminate between different usages. This paper proposes a hybrid of based- rules and a machine learning method for tagging Arabic words. The particularity of Arabic word that may be composed of stem, plus affixes and clitics, a small number of rules dominate the performance (affixes include inflexional markers for tense, gender and number/ clitics include some prepositions, conjunctions and others). Tagging is closely related to the notion of word class used in syntax. This method is based firstly on rules (that considered the post-position, ending of a word, and patterns), and then the anomaly are corrected by adopting a memory-based learning method (MBL). The memory_based learning is an efficient method to integrate various sources of information, and handling exceptional data in natural language processing tasks. Secondly checking the exceptional cases of rules and more information is made available to the learner for treating those exceptional cases. To evaluate the proposed method a number of experiments has been run, and in order, to improve the importance of the various information in learning.

Keywords: Arabic language, Based-rules, exceptions, Memorybased learning, Tagging.

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Authors: Abdul Salim Amin

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This paper focuses on how judiciaries in post-conflict societies can gain legitimacy through reformation. Legitimacy plays a pivotal role in shaping people’s behavior to submit to the law and verifies the rightfulness of an organ for taking binding decisions. Among various dynamics, judicial independence, access to justice and behavioral changes of the judicial officials broadly contribute to legitimation of judiciary in general, and the courts in particular. Increasing independence of judiciary through reform limits, inter alia, government interference in judicial issues and protects basic rights of the citizens. Judicial independence does not only matter in institutional terms, individual independence also influences the impartiality and integrity of judges, which can be increased through education and better administration of justice. Finally, access to justice as an intertwined concept both at the legal and moral spectrum of judicial reform avails justice to the citizens and increases the level of public trust and confidence. Efficient legal decisions on fostering such elements through holistic reform create a rule of law atmosphere. Citizens neither accept an illegitimate judiciary nor do they trust its decisions. Lack of such tolerance and confidence deters the rule of law and thus, undermines the democratic development of a society.

Keywords: Legitimacy, judicial reform, judicial independence, access to justice, legal training, informal justice, rule of law.

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Authors: Mohammad Reza Tabatabaei, Mohammad Bagher Haddadi, Mojtaba Saeedimoghadam, Ali Vaseghi Ardekani

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Economic Dispatch (ED) is one of the most challenging problems of power system since it is difficult to determine the optimum generation scheduling to meet the particular load demand with the minimum fuel costs while all constraints are satisfied. The objective of the Economic Dispatch Problems (EDPs) of electric power generation is to schedule the committed generating units outputs so as to meet the required load demand at minimum operating cost while satisfying all units and system equality and inequality constraints. In this paper, an efficient and practical steady-state genetic algorithm (SSGAs) has been proposed for solving the economic dispatch problem. The objective is to minimize the total generation fuel cost and keep the power flows within the security limits. To achieve that, the present work is developed to determine the optimal location and size of capacitors in transmission power system where, the Participation Factor Algorithm and the Steady State Genetic Algorithm are proposed to select the best locations for the capacitors and determine the optimal size for them.

Keywords: Economic Dispatch, Lagrange, Capacitors Placement, Losses Reduction, Genetic Algorithm.

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Authors: H. Higashiyama, M. Sappakittipakorn, M. Mizukoshi, O. Takahashi

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Ceramic Waste Aggregates (CWAs) were made from electric porcelain insulator wastes supplied from an electric power company, which were crushed and ground to fine aggregate sizes. In this study, to develop the CWA mortar as an eco–efficient, ground granulated blast–furnace slag (GGBS) as a Supplementary Cementitious Material (SCM) was incorporated. The water–to–binder ratio (W/B) of the CWA mortars was varied at 0.4, 0.5, and 0.6. The cement of the CWA mortar was replaced by GGBS at 20 and 40% by volume (at about 18 and 37% by weight). Mechanical properties of compressive and splitting tensile strengths, and elastic modulus were evaluated at the age of 7, 28, and 91 days. Moreover, the chloride ingress test was carried out on the CWA mortars in a 5.0% NaCl solution for 48 weeks. The chloride diffusion was assessed by using an electron probe microanalysis (EPMA). To consider the relation of the apparent chloride diffusion coefficient and the pore size, the pore size distribution test was also performed using a mercury intrusion porosimetry at the same time with the EPMA. The compressive strength of the CWA mortars with the GGBS was higher than that without the GGBS at the age of 28 and 91 days. The resistance to the chloride ingress of the CWA mortar was effective in proportion to the GGBS replacement level.

Keywords: Ceramic waste aggregate, Chloride diffusion, GGBS, Pore size distribution.

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Authors: Ashraf M. A. Ahmad

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Delivering streaming video over wireless is an important component of many interactive multimedia applications running on personal wireless handset devices. Such personal devices have to be inexpensive, compact, and lightweight. But wireless channels have a high channel bit error rate and limited bandwidth. Delay variation of packets due to network congestion and the high bit error rate greatly degrades the quality of video at the handheld device. Therefore, mobile access to multimedia contents requires video transcoding functionality at the edge of the mobile network for interworking with heterogeneous networks and services. Therefore, to guarantee quality of service (QoS) delivered to the mobile user, a robust and efficient transcoding scheme should be deployed in mobile multimedia transporting network. Hence, this paper examines the challenges and limitations that the video transcoding schemes in mobile multimedia transporting network face. Then handheld resources, network conditions and content based mobile and wireless video transcoding is proposed to provide high QoS applications. Exceptional performance is demonstrated in the experiment results. These experiments were designed to verify and prove the robustness of the proposed approach. Extensive experiments have been conducted, and the results of various video clips with different bit rate and frame rate have been provided.

Keywords: Content, Object detection, Transcoding, Texture, Temporal, Video.

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Authors: J. Barilla, M. Lokajíček, H. Pisaková, P. Simr

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The final biological effect of ionizing particles may be influenced strongly by some chemical substances present in cells mainly in the case of low-LET radiation. The influence of oxygen may by particularly important because oxygen is always present in living cells. The corresponding processes are then running mainly in the chemical stage of radiobiological mechanism.

The radical clusters formed by densely ionizing ends of primary or secondary charged particles are mainly responsible for final biological effect. The damage effect depends then on radical concentration at a time when the cluster meets a DNA molecule. It may be strongly influenced by oxygen present in a cell as oxygen may act in different directions: at small concentration of it the interaction with hydrogen radicals prevails while at higher concentrations additional efficient oxygen radicals may be formed.

The basic radical concentration in individual clusters diminishes, which is influenced by two parallel processes: chemical reactions and diffusion of corresponding clusters. The given simultaneous evolution may be modeled and analyzed well with the help of Continuous Petri nets. The influence of other substances present in cells during irradiation may be studied, too. Some results concerning the impact of oxygen content will be presented.

Keywords: DSB formation, chemical stage, Petri nets, radiobiological mechanism.

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Authors: Mohammad Reza Farzami Pour

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Determination of genetic variation is useful for plant breeding and hence production of more efficient plant species under different conditions, like drought stress. In this study a sample of 28 recombinant inbred lines (RILs) of wheat developed from the cross of Norstar and Zagross varieties, together with their parents, were evaluated for two years (2010-2012) under normal and water stress conditions using split plot design with three replications. Main plots included two irrigation treatments of 70 and 140 mm evaporation from Class A pan and sub-plots consisted of 30 genotypes. The effect of genotypes and interaction of genotypes with years and water regimes were significant for all characters. Significant genotypic effect implies the existence of genetic variation among the lines under study. Heritability estimates were high for 1000 grain weight (0.87). Biomass and grain yield showed the lowest heritability values (0.42 and 0.50, respectively). Highest genotypic and phenotypic coefficients of variation (GCV and PCV) belonged to harvest index. Moderate genetic advance for most of the traits suggested the feasibility of selection among the RILs under investigation. Some RILs were higher yielding than either parent at both environments.

Keywords: Wheat, genetic gain, heritability, recombinant inbred lines.

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Authors: Rudy Djamaluddin, Yasser Bachtiar, Rita Irmawati, Abd. Madjid Akkas, Rusdi Usman Latief

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The aesthetic qualities and the versatility of reinforced concrete have made it a popular choice for many architects and structural engineers. Therefore, the exploration of natural materials such as gravels and sands as well as lime-stone for cement production is increasing to produce a concrete material. The exploration must affect to the environment. Therefore, the using of the concrete materials should be as efficient as possible. According to its natural behavior of the concrete material, it is strong in compression and weak in tension. Therefore the contribution of the tensile stresses of the concrete to the flexural capacity of the beams is neglected. However, removing of concrete on tension zone affects to the decreasing of flexural capacity. Introduce the strut action of truss structures may an alternative to solve the decreasing of flexural capacity. A series of specimens were prepared to clarify the effect of the truss structures in the concrete beams without concrete on the tension zone. Results indicated that the truss system is necessary for the external reinforced concrete beams. The truss system of concrete beam without concrete on tension zone (BR) could develop almost same capacity to the normal beam (BN). It can be observed also that specimens BR has lower number of cracks than specimen BN. This may be caused by the fact that there was no bonding effect on the tensile reinforcement on specimen BR to distribute the cracks.

Keywords: External Reinforcement, Truss, Concrete Beams.

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Authors: Qian Liu, Steve Furber

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To explore how the brain may recognise objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor (DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network (SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modelled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study’s largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognise the postures with an accuracy of around 86.4% - only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much improved cost to performance trade-off in its approach.

Keywords: Spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system.

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Authors: Zhanna Mingaleva, Irina Mirskikh

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Innovational development of regions in Russia is generally faced with the essential influence from federal and local authorities. The organization of effective mechanism of innovation development (and self-development) is impossible without establishment of defined institutional conditions in the analyzed field. Creative utilization of scientific concepts and information should merge, giving rise to continuing innovation and advanced production. The paper presents an analysis of institutional conditions in the field of creation and development of innovation activity infrastructure and transferring of knowledge and skills between different economic agents in Russia. Knowledge is mainly privately owned, developed through R&D investments and incorporated into technology or a product. Innovation infrastructure is a strong concentration mechanism of advanced facilities, which are mainly located inside large agglomerations or city-regions in order to benefit from scale effects in both input markets (human capital, private financial capital) and output markets (higher education services, research services). The empirical results of the paper show that in the presence of more efficient innovation and knowledge transfer and transcoding system and of a more open attitude of economic agents towards innovation, the innovation and knowledge capacity of regional economy is much higher.

Keywords: knowledge economy, innovational development, transfer of knowledge, institutional preconditions, innovation andknowledge capacity.

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Authors: Belkacem Selma, Boumediene Selma, Samira Chouraqui, Hanifi Missoum, Tourkia Guerzou

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. Earthquake prediction to prevent the loss of human lives and even property damage is an important factor; that, is why it is crucial to develop techniques for predicting this natural disaster. This study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 104 J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines have been analyzed. The results obtained show that the ANN is able to predict earthquake parameters with  high accuracy; the classification accuracy through neural networks is more than 94%, and the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: Earthquake prediction, artificial intelligence, AI, Artificial Neural Network, ANN, seismic bumps.

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Authors: Jae Chul Cha, Sandeep K. Gupta

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The demand for higher performance graphics continues to grow because of the incessant desire towards realism. And, rapid advances in fabrication technology have enabled us to build several processor cores on a single die. Hence, it is important to develop single chip parallel architectures for such data-intensive applications. In this paper, we propose an efficient PIM architectures tailored for computer graphics which requires a large number of memory accesses. We then address the two important tasks necessary for maximally exploiting the parallelism provided by the architecture, namely, partitioning and placement of graphic data, which affect respectively load balances and communication costs. Under the constraints of uniform partitioning, we develop approaches for optimal partitioning and placement, which significantly reduce search space. We also present heuristics for identifying near-optimal placement, since the search space for placement is impractically large despite our optimization. We then demonstrate the effectiveness of our partitioning and placement approaches via analysis of example scenes; simulation results show considerable search space reductions, and our heuristics for placement performs close to optimal – the average ratio of communication overheads between our heuristics and the optimal was 1.05. Our uniform partitioning showed average load-balance ratio of 1.47 for geometry processing and 1.44 for rasterization, which is reasonable.

Keywords: Data Partitioning and Placement, Graphics, PIM, Search Space Reduction.

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Authors: Jehad Al Dallal

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Program slicing is the task of finding all statements in a program that directly or indirectly influence the value of a variable occurrence. The set of statements that can affect the value of a variable at some point in a program is called a program slice. In several software engineering applications, such as program debugging and measuring program cohesion and parallelism, several slices are computed at different program points. In this paper, algorithms are introduced to compute all backward and forward static slices of a computer program by traversing the program representation graph once. The program representation graph used in this paper is called Program Dependence Graph (PDG). We have conducted an experimental comparison study using 25 software modules to show the effectiveness of the introduced algorithm for computing all backward static slices over single-point slicing approaches in computing the parallelism and functional cohesion of program modules. The effectiveness of the algorithm is measured in terms of time execution and number of traversed PDG edges. The comparison study results indicate that using the introduced algorithm considerably saves the slicing time and effort required to measure module parallelism and functional cohesion.

Keywords: Backward slicing, cohesion measure, forward slicing, parallelism measure, program dependence graph, program slicing, static slicing.

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Authors: Rajine Swetha R, B. Shekar Babu, Sumithra Devi K.A

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Electronic Systems are the core of everyday lives. They form an integral part in financial networks, mass transit, telephone systems, power plants and personal computers. Electronic systems are increasingly based on complex VLSI (Very Large Scale Integration) integrated circuits. Initial electronic design automation is concerned with the design and production of VLSI systems. The next important step in creating a VLSI circuit is Physical Design. The input to the physical design is a logical representation of the system under design. The output of this step is the layout of a physical package that optimally or near optimally realizes the logical representation. Physical design problems are combinatorial in nature and of large problem sizes. Darwin observed that, as variations are introduced into a population with each new generation, the less-fit individuals tend to extinct in the competition of basic necessities. This survival of fittest principle leads to evolution in species. The objective of the Genetic Algorithms (GA) is to find an optimal solution to a problem .Since GA-s are heuristic procedures that can function as optimizers, they are not guaranteed to find the optimum, but are able to find acceptable solutions for a wide range of problems. This survey paper aims at a study on Efficient Algorithms for VLSI Physical design and observes the common traits of the superior contributions.

Keywords: Genetic Algorithms, Physical Design, VLSI.

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Authors: V. Balanica, W. I. D. Rae, M. Caramihai, S. Acho, C. P. Herbst

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Mammographic images and data analysis to facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file formats and relate these to other patient information. This would optimize the use of the data as both primary reporting and enhanced information extraction of research data could be performed from the single dataset. One desired improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically available in the images. The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research purposes. An interface was developed for accessing, adding, updating, modifying and extracting data from the common database, enhancing the future possible application of the data in CAD processing. Technically, future developments envisaged include the creation of an advanced search function to selects image files based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a user friendly configuration utility for importing of the required fields from the DICOM files must be done.

Keywords: Database Integration, Mammogram Classification, Tumour Classification, Computer Aided Diagnosis.

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Authors: M. S. Manikandan, K. V. Nithish Kumar, M. Krishnamoorthi, V. Ganesh

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The Automobile Braking System has a crucial role for safety of the passenger and riding quality of the vehicle. The braking force mainly depends on normal reaction on the wheel and the co-efficient of friction between the tire and the road surface. Whenever a vehicle is loaded, the normal reaction on the rear wheel is increased. Thus the amount of braking force required to halt the vehicle with minimum stopping distance, is based on the pillion load on the vehicle. In this work, in order to vary the braking force in two wheelers, the mechanical leverage which operates the master cylinder is varied based on the pillion load. Thus the amount of braking force developed between ground and tire is varied. This optimum braking force on the disc brake helps in attaining the minimum vehicle stopping distance. In addition to that, it also helps in preventing sliding. Thus the system results in reducing the stopping distance of the two wheelers and providing a better braking efficiency than the conventional braking system.

Keywords: Braking force, Master cylinder, Mechanical leverage, Minimum stopping distance.

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Authors: Dana M. Ragab, Jasim A. Ghaeb

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The three-phase power system suffers from different challenging problems, e.g. voltage unbalance conditions at the load side. The voltage unbalance usually degrades the power quality of the electric power system. Several techniques can be considered for load balancing including load reconfiguration, static synchronous compensator and static reactive power compensator. In this work an efficient neural network is designed to control the unbalanced condition in the Aqaba-Qatrana-South Amman (AQSA) electric power system. It is designed for highly enhanced response time of the reactive compensator for voltage balancing. The neural network is developed to determine the appropriate set of firing angles required for the thyristor-controlled reactor to balance the three load voltages accurately and quickly. The parameters of AQSA power system are considered in the laboratory model, and several test cases have been conducted to test and validate the proposed technique capabilities. The results have shown a high performance of the proposed Neural Network Control (NNC) technique for correcting the voltage unbalance conditions at three-phase load based on accuracy and response time.

Keywords: Three-phase power system, reactive power control, voltage unbalance factor, neural network, power quality.

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Authors: Musthafah b. Mohd.Tahir, Noboru Yamada, Tetsuya Hoshino

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This paper describes the experimental efficiency of a compact organic Rankine cycle (ORC) system with a compact rotary-vane-type expander. The compact ORC system can be used for power generation from low-temperature heat sources such as waste heat from various small-scale heat engines, fuel cells, electric devices, and solar thermal energy. The purpose of this study is to develop an ORC system with a low power output of less than 1 kW with a hot temperature source ranging from 60°C to 100°C and a cold temperature source ranging from 10°C to 30°C. The power output of the system is rather less due to limited heat efficiency. Therefore, the system should have an economically optimal efficiency. In order to realize such a system, an efficient and low-cost expander is indispensable. An experimental ORC system was developed using the rotary-vane-type expander which is one of possible candidates of the expander. The experimental results revealed the expander performance for various rotation speeds, expander efficiencies, and thermal efficiencies. Approximately 30 W of expander power output with 48% expander efficiency and 4% thermal efficiency with a temperature difference between the hot and cold sources of 80°C was achieved.

Keywords: Organic Rankine cycle, Thermodynamic cycle, Thermal efficiency, Turbine efficiency, Waste heat recovery, Powergeneration, Low temperature heat engine.

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Authors: Su Xiaohan, Jin Chicheng, Liu Yijing, Burra Venkata Durga Kumar

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Energy-aware scheduling in real-time systems aims to minimize energy consumption, but issues related to resource reservation and timing constraints remain challenges. This study focuses on analyzing two scheduling algorithms, Fair-Share Scheduling (FFS) and Priority-Driven Preemptive Scheduling (PDPS), for solving these issues and energy-aware scheduling in real-time systems. Based on research on both algorithms and the processes of solving two problems, it can be found that FFS ensures fair allocation of resources but needs to improve with an imbalanced system load. And PDPS prioritizes tasks based on criticality to meet timing constraints through preemption but relies heavily on task prioritization and may not be energy efficient. Therefore, improvements to both algorithms with energy-aware features will be proposed. Future work should focus on developing hybrid scheduling techniques that minimize energy consumption through intelligent task prioritization, resource allocation, and meeting time constraints.

Keywords: Energy-aware scheduling, fair-share scheduling, priority-driven preemptive scheduling, real-time systems, optimization, resource reservation, timing constraints.

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Authors: Xin Bai, Kresimir Sivoncik, Damla Turgut, Ladislau Bölöni

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Market based models are frequently used in the resource allocation on the computational grid. However, as the size of the grid grows, it becomes difficult for the customer to negotiate directly with all the providers. Middle agents are introduced to mediate between the providers and customers and facilitate the resource allocation process. The most frequently deployed middle agents are the matchmakers and the brokers. The matchmaking agent finds possible candidate providers who can satisfy the requirements of the consumers, after which the customer directly negotiates with the candidates. The broker agents are mediating the negotiation with the providers in real time. In this paper we present a new type of middle agent, the marketmaker. Its operation is based on two parallel operations - through the investment process the marketmaker is acquiring resources and resource reservations in large quantities, while through the resale process it sells them to the customers. The operation of the marketmaker is based on the fact that through its global view of the grid it can perform a more efficient resource allocation than the one possible in one-to-one negotiations between the customers and providers. We present the operation and algorithms governing the operation of the marketmaker agent, contrasting it with the matchmaker and broker agents. Through a series of simulations in the task oriented domain we compare the operation of the three agents types. We find that the use of marketmaker agent leads to a better performance in the allocation of large tasks and a significant reduction of the messaging overhead.

Keywords: grid computing, autonomous agents, market-basedgrid

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Authors: K. T. Sun, Y. H. Tai, H. W. Yang, H. T. Lin

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This paper presented the technique of robot control by event-related potentials (ERPs) of brain waves. Based on the proposed technique, severe physical disabilities can free browse outside world. A specific component of ERPs, N2P3, was found and used to control the movement of robot and the view of camera on the designed brain-computer interface (BCI). Users only required watching the stimuli of attended button on the BCI, the evoked potentials of brain waves of the target button, N2P3, had the greatest amplitude among all control buttons. An experimental scene had been constructed that the robot required walking to a specific position and move the view of camera to see the instruction of the mission, and then completed the task. Twelve volunteers participated in this experiment, and experimental results showed that the correct rate of BCI control achieved 80% and the average of execution time was 353 seconds for completing the mission. Four main contributions included in this research: (1) find an efficient component of ERPs, N2P3, for BCI control, (2) embed robot's viewpoint image into user interface for robot control, (3) design an experimental scene and conduct the experiment, and (4) evaluate the performance of the proposed system for assessing the practicability.

Keywords: Brain-computer interface (BCI), event-related potentials (ERPs), robot control, severe physical disabilities.

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Authors: Marley Rosa Luciano, Rodney Rezende Saldanha

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The race for electrification and the need for innovation to attract customers has led the automotive industry to do something different with vehicles. New emissions control challenges and efficient technological availability are the pillars of creation. The growing demand to upgrade industrial manufacturing systems creates actions that directly impact vehicle production. With this comes the search for new prototyping methods and virtual tools for component testing and validation, and vehicle systems have established themselves. The demand for Electronic Control Units (ECU) is increasing due to the availability of intelligence and safety in today's vehicles, directly affecting their development, performance, and functional testing. In order to keep up with global changes, the automotive industry uses different virtual environments to produce, verify and validate their vehicles and test prototypes used during development. Therefore, in this paper, integration and validation were performed using the Hardware in the Loop (HIL) test platform, focusing on the ECU Body Control Module (BCM). Then, a brief commentary reviews other test medium platforms, such as the Plywood Buck (PWB), and examines the reliability, flexibility, installation time, and cost of the three test platforms, software in the loop (SIL), Model in the loop (MIL), and HIL, to review their benefits, challenges, and issues in use and information to optimize the use of each platform and test medium.

Keywords: Automotive, Electronic Central Unit, xIL, Hardware in the loop.

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Authors: R. Litt, A. Brown

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Aims: We aimed to assess the efficiency of ‘Attend Anywhere’ orthodontic clinics within a district general hospital during COVID- 19. Our secondary aim was to pilot a questionnaire to assess patient satisfaction with virtual orthodontic appointments. Design: The study design is a service evaluation including pilot questionnaire. Methods: The average number of patients seen per virtual clinic and the number of patients failing to attend was compared to face-to-face clinics. The capability of virtual appointments to be successful in preventing the need for a face-to-face appointment was assessed. Patients were invited to complete a telephone pilot questionnaire focusing on patient satisfaction and accessibility. Results: There was a small increase in the number of patients failing to attend virtual appointments, with a third of the patients who did not attend failing to receive the appointment link. 81.9% of virtual clinic appointments were successful and prevented the need for a face-to-face appointment. Overall patients were very satisfied with their virtual orthodontic appointment and the majority required no assistance to access the service. Conclusions: The use of ‘Attend Anywhere’ clinics in orthodontics offers patients and clinicians an effective and efficient alternative to face-to-face appointments that patients on average find easy to use and completely satisfactory.

Keywords: Clinics, COVID-19, orthodontics, patient satisfaction, virtual.

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Authors: Rafic Ayoubi, Jean-Pierre Dubois, Rania Minkara

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In this paper, we study FPGA implementation of a novel supra-optimal receiver diversity combining technique, generalized maximal ratio combining (GMRC), for wireless transmission over fading channels in SIMO systems. Prior published results using ML-detected GMRC diversity signal driven by BPSK showed superior bit error rate performance to the widely used MRC combining scheme in an imperfect channel estimation (ICE) environment. Under perfect channel estimation conditions, the performance of GMRC and MRC were identical. The main drawback of the GMRC study was that it was theoretical, thus successful FPGA implementation of it using pipeline techniques is needed as a wireless communication test-bed for practical real-life situations. Simulation results showed that the hardware implementation was efficient both in terms of speed and area. Since diversity combining is especially effective in small femto- and picocells, internet-associated wireless peripheral systems are to benefit most from GMRC. As a result, many spinoff applications can be made to the hardware of IP-based 4th generation networks.

Keywords: Femto-internet cells, field-programmable gate array, generalized maximal-ratio combining, Lyapunov fractal dimension, pipelining technique, wireless SIMO channels.

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Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: Structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures.

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Authors: Komeil Valipourian

Abstract:

Urban advances and the growing need for developing infrastructures has increased the importance of deep excavations. In this study, after the introducing probability analysis as an important issue, an attempt has been made to apply it for the deep excavation project of Bangkok’s Metro as a case study. For this, the numerical probability model has been developed based on the Finite Difference Method and Monte Carlo sampling approach. The results indicate that disregarding the issue of probability in this project will result in an inappropriate design of the retaining structure. Therefore, probabilistic redesign of the support is proposed and carried out as one of the applications of probability analysis. A 50% reduction in the flexural strength of the structure increases the failure probability just by 8% in the allowable range and helps improve economic conditions, while maintaining mechanical efficiency. With regard to the lack of efficient design in most deep excavations, by considering geometrical and geotechnical variability, an attempt was made to develop an optimum practical design standard for deep excavations based on failure probability. On this basis, a practical relationship is presented for estimating the maximum allowable horizontal displacement, which can help improve design conditions without developing the probability analysis.

Keywords: Numerical probability modeling, deep excavation, allowable maximum displacement, finite difference method, FDM.

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Authors: Aicha Majda, Abdelhamid El Hassani

Abstract:

Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: Graph cuts, lung CT scan, lung parenchyma segmentation, patch based similarity metric.

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Authors: Jeni A. Popescu, Ionut Porumbel, Valeriu A. Vilag, Cleopatra F. Cuciumita

Abstract:

The paper presents a thermodynamic cycle analysis for three turboshaft engines. The first cycle is a Brayton cycle, describing the evolution of a classical turboshaft, based on the Klimov TV2 engine. The other four cycles aim at approaching an Ericsson cycle, by replacing the Brayton cycle adiabatic expansion in the turbine by quasi-isothermal expansion. The maximum quasi- Ericsson cycles temperature is set to a lower value than the maximum Brayton cycle temperature, equal to the Brayton cycle power turbine inlet temperature, in order to decrease the engine NOx emissions. Also, the power/expansion ratio distribution over the stages of the gas generator turbine is maintained the same. In two of the considered quasi-Ericsson cycles, the efficiencies of the gas generator turbine, as well as the power/expansion ratio distribution over the stages of the gas generator turbine are maintained the same as for the reference case, while for the other two cases, the efficiencies are increased in order to obtain the same shaft power as in the reference case. For the two cases respecting the first condition, both the shaft power and the thermodynamic efficiency of the engine decrease, while for the other two, the power and efficiency are maintained, as a result of assuming new, more efficient gas generator turbines.

Keywords: Combustion, Ericsson, thermodynamic analysis, turbine.

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Authors: Cheng Shen, LaiHong Shen

Abstract:

Ammonia is an important carrier of hydrogen energy, with the characteristics of high hydrogen content density and no carbon dioxide emission. Safe and efficient ammonia capture for ammonia synthesis from biomass is an important way to alleviate the energy crisis and solve the energy problem. Metal chloride has a chemical adsorption effect on ammonia and can be desorbed at high temperatures to obtain high-concentration ammonia after combining with ammonia, which has a good development prospect in ammonia capture and separation technology. In this paper, the ammonia adsorption properties of CuCl2 were measured, and the composite adsorbents were prepared by using silicon and multi-walled carbon nanotubes, respectively to support CuCl2, and the ammonia adsorption properties of the composite adsorbents were studied. The study found that the ammonia adsorption capacity of the three adsorbents decreased with the increase in temperature, so metal chlorides were more suitable for the low-temperature adsorption of ammonia. Silicon and multi-walled carbon nanotubes have an enhanced effect on the ammonia adsorption of CuCl2. The reason is that the porous material itself has a physical adsorption effect on ammonia, and silicon can play the role of skeleton support in cupric chloride particles, which enhances the pore structure of the adsorbent, thereby alleviating sintering.

Keywords: Ammonia, adsorption properties, metal chloride, MWCNTs, silicon.

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Authors: S. R. M. Kutty, S. N. I. Ngatenah, M. H. Isa, A. Malakahmad

Abstract:

Water hyacinth has been used in aquatic systems for wastewater purification in many years worldwide. The role of water hyacinth (Eichhornia crassipes) species in polishing nitrate and phosphorus concentration from municipal wastewater treatment plant effluent by phytoremediation method was evaluated. The objective of this project is to determine the removal efficiency of water hyacinth in polishing nitrate and phosphorus, as well as chemical oxygen demand (COD) and ammonia. Water hyacinth is considered as the most efficient aquatic plant used in removing vast range of pollutants such as organic matters, nutrients and heavy metals. Water hyacinth, also referred as macrophytes, were cultivated in the treatment house in a reactor tank of approximately 90(L) x 40(W) x 25(H) in dimension and built with three compartments. Three water hyacinths were placed in each compartments and water sample in each compartment were collected in every two days. The plant observation was conducted by weight measurement, plant uptake and new young shoot development. Water hyacinth effectively removed approximately 49% of COD, 81% of ammonia, 67% of phosphorus and 92% of nitrate. It also showed significant growth rate at starting from day 6 with 0.33 shoot/day and they kept developing up to 0.38 shoot/day at the end of day 24. From the studies conducted, it was proved that water hyacinth is capable of polishing the effluent of municipal wastewater which contains undesirable amount of nitrate and phosphorus concentration.

Keywords: water hyacinth, phytoremediation, nutrient removal, Eichhornia crassipes

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