Search results for: efficient crow search algorithm

Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Jamileh Darsareh, Mohammad Nikafrooz

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Some teachers and e-content producers, based on their experiences, try to produce educational videos using screen recording software. There are many challenges that they may encounter while producing screen-recorded videos. These are in the domains of technical and pedagogical challenges like designing the roadmap, preparing the screen, setting the recording software and recording the screen, editing, etc. This study is a descriptive study and tries to present some procedures for producing acceptable and well-made videos. These procedures are presented in the form of an algorithm for producing screen-recorded video. This algorithm presents the main producing phases, including design, pre-production, production, post-production, and distribution. These phases consist of some steps which are supported by several technical and pedagogical considerations. Following these phases and steps according to the suggested order helps the producers to produce their intended and desired video by saving time and also facing fewer technical problems. It is expected that by using this algorithm, e-content producers and teachers gain better performance in producing educational videos.

Keywords: e-content producing algorithm, screen-recorded videos, screen recording software, technical and pedagogical considerations

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

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Authors: Rimmy Yadav, Avtar Singh

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—Ant Colony Optimization (ACO) is a promising modern approach to the unused combinatorial optimization. Here ACO is applied to finding the shortest during communication link failure. In this paper, the performances of the prim’s and ACO algorithm are made. By comparing the time complexity and program execution time as set of parameters, we demonstrate the pleasant performance of ACO in finding excellent solution to finding shortest path during communication link failure.

Keywords: ant colony optimization, link failure, prim’s algorithm, shortest path

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Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

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Authors: Z. Abdollahi Biron, P. Pisu

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Connected vehicles are one of the promising technologies for future Intelligent Transportation Systems (ITS). A connected vehicle system is essentially a set of vehicles communicating through a network to exchange their information with each other and the infrastructure. Although this interconnection of the vehicles can be potentially beneficial in creating an efficient, sustainable, and green transportation system, a set of safety and reliability challenges come out with this technology. The first challenge arises from the information loss due to unreliable communication network which affects the control/management system of the individual vehicles and the overall system. Such scenario may lead to degraded or even unsafe operation which could be potentially catastrophic. Secondly, faulty sensors and actuators can affect the individual vehicle’s safe operation and in turn will create a potentially unsafe node in the vehicular network. Further, sending that faulty sensor information to other vehicles and failure in actuators may significantly affect the safe operation of the overall vehicular network. Therefore, it is of utmost importance to take these issues into consideration while designing the control/management algorithms of the individual vehicles as a part of connected vehicle system. In this paper, we consider a connected vehicle system under Co-operative Adaptive Cruise Control (CACC) and propose a fault diagnosis scheme that deals with these aforementioned challenges. Specifically, the conventional CACC algorithm is modified by adding a Kalman filter-based estimation algorithm to suppress the effect of lost information under unreliable network. Further, a sliding mode observer-based algorithm is used to improve the sensor reliability under faults. The effectiveness of the overall diagnostic scheme is verified via simulation studies.

Keywords: fault diagnostics, communication network, connected vehicles, packet drop out, platoon

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

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Authors: Nicolas Zufferey

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Ant algorithms are well-known metaheuristics which have been widely used since two decades. In most of the literature, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. Generally, at each generation of an ant algorithm, each ant builds a solution step by step by adding an element to it. Each choice is based on the greedy force (also called the visibility, the short term profit or the heuristic information) and the trail system (central memory which collects historical information of the search process). Usually, all the ants of the population have the same characteristics and behaviors. In contrast in this paper, a new type of ant metaheuristic is proposed, namely SMART (for Solution Methods with Ants Running by Types). It relies on the use of different population of ants, where each population has its own personality.

Keywords: ant algorithms, evolutionary procedures, metaheuristics, optimization, population-based methods

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Authors: David Koren, Vojko Kilar

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The modern energy-efficient houses are often founded on a thermal insulation (TI) layer placed under the building’s RC foundation slab. The purpose of the paper is to identify the potential problems of the buildings founded on TI layer from the seismic point of view. The two main goals of the study were to assess the seismic behavior of such buildings, and to search for the critical structural parameters affecting the response of the superstructure as well as of the extruded polystyrene (XPS) layer. As a test building a multi-storeyed RC frame structure with and without the XPS layer under the foundation slab has been investigated utilizing nonlinear dynamic (time-history) and static (pushover) analyses. The structural response has been investigated with reference to the following performance parameters: i) Building’s lateral roof displacements, ii) Edge compressive and shear strains of the XPS, iii) Horizontal accelerations of the superstructure, iv) Plastic hinge patterns of the superstructure, v) Part of the foundation in compression, and vi) Deformations of the underlying soil and vertical displacements of the foundation slab (i.e. identifying the potential uplift). The results have shown that in the case of higher and stiff structures lying on firm soil the use of XPS under the foundation slab might induce amplified structural peak responses compared to the building models without XPS under the foundation slab. The analysis has revealed that the superstructure as well as the XPS response is substantially affected by the stiffness of the foundation slab.

Keywords: extruded polystyrene (XPS), foundation on thermal insulation, energy-efficient buildings, nonlinear seismic analysis, seismic response, soil–structure interaction

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Authors: N. M. G. Al-Saidi, K. A. Kadhim, N. A. Rajab

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Over the past decades, computer networks and data communication system has been developing fast, so, the necessity to protect a transmitted data is a challenging issue, and data security becomes a serious problem nowadays. A secret sharing scheme is a method which allows a master key to be distributed among a finite set of participants, in such a way that only certain authorized subsets of participants to reconstruct the original master key. To create a secret sharing scheme, many mathematical structures have been used; the most widely used structure is the one that is based on graph theory (graph access structure). Subsequently, many researchers tried to find efficient schemes based on graph access structures. In this paper, we propose a novel efficient construction of a perfect secret sharing scheme for uniform access structure. The dominating set of vertices in a regular graph is used for this construction in the following way; each vertex represents a participant and each minimum independent dominating subset represents a minimal qualified subset. Some relations between dominating set, graph order and regularity are achieved, and can be used to demonstrate the possibility of using dominating set to construct a secret sharing scheme. The information rate that is used as a measure for the efficiency of such systems is calculated to show that the proposed method has some improved values.

Keywords: secret sharing scheme, dominating set, information rate, access structure, rank

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Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

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In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder enveloping surface, and then the detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator.

Keywords: space manipulator, collision detection, self-collision, the real-time collision detection

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Authors: Alaa Sheta

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Economic Load Dispatch (ELD) is one of the vital optimization problems in power system planning. Solving the ELD problems mean finding the best mixture of power unit outputs of all members of the power system network such that the total fuel cost is minimized while sustaining operation requirements limits satisfied across the entire dispatch phases. Many optimization techniques were proposed to solve this problem. A famous one is the Quadratic Programming (QP). QP is a very simple and fast method but it still suffer many problem as gradient methods that might trapped at local minimum solutions and cannot handle complex nonlinear functions. Numbers of metaheuristic algorithms were used to solve this problem such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). In this paper, another meta-heuristic search algorithm named Differential Evolution (DE) is used to solve the ELD problem in power systems planning. The practicality of the proposed DE based algorithm is verified for three and six power generator system test cases. The gained results are compared to existing results based on QP, GAs and PSO. The developed results show that differential evolution is superior in obtaining a combination of power loads that fulfill the problem constraints and minimize the total fuel cost. DE found to be fast in converging to the optimal power generation loads and capable of handling the non-linearity of ELD problem. The proposed DE solution is able to minimize the cost of generated power, minimize the total power loss in the transmission and maximize the reliability of the power provided to the customers.

Keywords: economic load dispatch, power systems, optimization, differential evolution

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Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, multiobjective optimization, ZDT test functions, evolutionary algorithms

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Authors: Rosa L. Figueroa, Christopher A. Flores, Qing Zeng-Treitler

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A regular expression consists of sequence characters which allow describing a text path. Usually, in clinical research, regular expressions are manually created by programmers together with domain experts. Lately, there have been several efforts to investigate how to generate them automatically. This article presents a text classification algorithm based on regexes. The algorithm named REX was designed, and then, implemented as a simplified method to create regexes to classify Spanish text automatically. In order to classify ambiguous cases, such as, when multiple labels are assigned to a testing example, REX includes an information gain method Two sets of data were used to evaluate the algorithm’s effectiveness in clinical text classification tasks. The results indicate that the regular expression based classifier proposed in this work performs statically better regarding accuracy and F-measure than Support Vector Machine and Naïve Bayes for both datasets.

Keywords: information gain, regular expressions, smith-waterman algorithm, text classification

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Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

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In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

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Authors: S. Som-Am, B. Grechuk

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Moser’s worm problem is the unsolved problem in geometry which asks for the minimal area of a convex region on the plane which can cover all curves of unit length, assuming that curves may be rotated and translated to fit inside the region. We study a version of this problem asking for a minimal convex cover for closed unit curves. By combining geometric methods with numerical box’s search algorithm, we show that any such cover should have an area at least 0.0975. This improves the best previous lower bound of 0.096694. In fact, we show that the minimal area of convex hull of circle, equilateral triangle, and rectangle of perimeter 1 is between 0.0975 and 0.09763.

Keywords: Moser’s worm problem, closed arcs, convex cover, minimal-area cover

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Authors: Yan-Ren Chen, Jenn-Kaie Lain

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This paper proposes a novel indoor positioning algorithm based on visible light communications, implemented by light-emitting diode fixtures. In the proposed positioning algorithm, distances between light-emitting diode fixtures and mobile terminal are derived from the assumption of ideal Lambertian optic radiation model, and Trilateration positioning method is proceeded immediately to get the coordinates of mobile terminal. The proposed positioning algorithm directly obtains distance information from the optical signal modeling, and therefore, statistical distribution of received signal strength at different positions in interior space has no need to be pre-established. Numerically, simulation results have shown that the proposed indoor positioning algorithm can provide accurate location coordinates estimation.

Keywords: indoor positioning, received signal strength, trilateration, visible light communications

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Authors: Mei-Yi Wu, Shang-Ming Huang

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The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

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Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

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Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Seong-Jin Cho, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorption coefficient is considered important when designing because noise affects emotion quality of car. It is designed with lots of experiment tunings in the field because it is unreliable to predict it for multi-layer material. In this paper, we present the design of sound absorption for automotive interior material with multiple layers using estimation software of sound absorption coefficient for reverberation chamber. Additionally, we introduce the method for estimation of physical properties required to predict sound absorption coefficient of car interior materials with multiple layers too. It is calculated by inverse algorithm. It is very economical to get information about physical properties without expensive equipment. Correlation test is carried out to ensure reliability for accuracy. The data to be used for the correlation is sound absorption coefficient measured in the reverberation chamber. In this way, it is considered economical and efficient to design automotive interior materials. And design optimization for sound absorption coefficient is also easy to implement when it is designed.

Keywords: sound absorption coefficient, optimization design, inverse algorithm, automotive interior material, multiple layers nonwoven, scaled reverberation chamber, sound impedance tubes

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. Modeling option pricing by Black-School models with jumps guarantees to consider the market movement. However, only numerical methods can solve this model. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, the exponential time differencing (ETD) method is applied for solving partial integrodifferential equations arising in pricing European options under Merton’s and Kou’s jump-diffusion models. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). A partial fraction form of Pad`e schemes is used to overcome the complexity of inverting polynomial of matrices. These two tools guarantee to get efficient and accurate numerical solutions. We construct a parallel and easy to implement a version of the numerical scheme. Numerical experiments are given to show how fast and accurate is our scheme.

Keywords: Integral differential equations, , L-stable methods, pricing European options, Jump–diffusion model

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Authors: Alireza Gholami, Amir H. D. Markazi

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In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.

Keywords: adaptive algorithm, fuzzy systems, membership functions, observer

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Authors: Ajay Kadam, Ramesh Kagalkar

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The proposed research objective is to add to a framework for programmed recognition of sound. In this framework the real errand is to distinguish any information sound stream investigate it & anticipate the likelihood of diverse sounds show up in it. To create and industrially conveyed an adaptable sound web crawler a flexible sound search engine. The calculation is clamor and contortion safe, computationally productive, and hugely adaptable, equipped for rapidly recognizing a short portion of sound stream caught through a phone microphone in the presence of frontal area voices and other predominant commotion, and through voice codec pressure, out of a database of over accessible tracks. The algorithm utilizes a combinatorial hashed time-recurrence group of stars examination of the sound, yielding ordinary properties, for example, transparency, in which numerous tracks combined may each be distinguished.

Keywords: fingerprinting, pure tone, white noise, hash function

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Authors: Jodie Bradshaw, Rebecca Dooley, Habib Kadiri, Holly Bird, Aaliyah Felix-West, Udit Mahalingam, Ella Thomson

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The sharp rise of civil orders has led to an expansion of police powers, particularly in the realm of stop and search activities. The broad scope and objectives of these civil orders –addressing issues as varied as public safety, crime prevention, and counter-terrorism – has led to ‘mission-creep’, whereby orders were being imposed in a wider range of contexts than initially intended. The ever-widening purview of civil orders in practice necessitates proactive measures by law enforcement which often rely heavily on the utilisation of stop and search, leading to an expansion of stop and search practices and the regulation of public space. Civil liberties organisations, criminal justice and legal practitioners, activist groups, and researchers have argued that civil orders dilute and undermine foundational legal principles, pose a threat to our basic rights and freedoms, facilitate dangerous criminal justice net-widening, and disproportionately target young, working-class people of colour. Many of the provisions in these orders are potentially incompatible with the right to liberty and security. The conditions of an order (whether negative restrictions or positive obligations) tend to be extremely easy to breach –and in some cases, almost impossible for the person subject to the order not to breach. When the conditions of an order are breached, the result is criminal punishment – often in the form of imprisonment. This paper argues that civil orders set people up to fail, sending them down a path towards incarceration and the ultimate deprivation of liberty. The proclaimed intentions underpinning these civil orders – to tackle purportedly ‘undesirable’ behaviour (which in and of itself is not a crime) committed by ‘undesirable’ people – paves the way for justifying violent and racially disproportionate policing practices.

Keywords: civil orders, policing, stop and search, crime, civil liberties, criminal punishment, anti-social behaviour

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Authors: Md Habibul Ansary, Chandan Garai, Ranjan Dasgupta

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Utilization of resources is always a great challenge for any allocation problem, particularly when resource availability is dynamic in nature. In this work VM allocation mechanism has been augmented by providing resources in a combined manner. This approach has some inherent advantages in terms of reduction of wait state for the pending jobs of some users and better utilization of unused resources from the service providers’ point of view. Moreover the algorithm takes care of released resources from the finished jobs as soon as those become available. The proposed algorithm has been explained by suitable example to make the work complete.

Keywords: Bid ratio, cloud service, virtualization, VM allocation problem

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Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: inversion, limitations, optimization, resistivity

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Authors: Catherine Thompson, Maryam Jalali, Peter Hills

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The allocation of visual attention is critical when driving and anything that limits attention will have a detrimental impact on safety. Engaging in a secondary task reduces the amount of attention directed to the road because drivers allocate resources towards this task, leaving fewer resources to process driving-relevant information. Yet the dangers associated with a secondary task do not end when the driver returns their attention to the road. Instead, the attentional settings adopted to complete a secondary task may persist to the road, affecting attention, and therefore affecting driver performance. This 'attentional inertia' effect was investigated in the current work. Forty drivers searched for hazards in driving video clips while their eye-movements were recorded. At varying intervals they were instructed to attend to a secondary task displayed on a tablet situated to their left-hand side. The secondary task consisted of three separate computer games that induced horizontal, vertical, and random eye movements. Visual search and hazard detection in the driving clips were compared across the three conditions of the secondary task. Results showed that the layout of information in the secondary task, and therefore the allocation of attention in this task, had an impact on subsequent search in the driving clips. Vertically presented information reduced the wide horizontal spread of search usually associated with accurate driving and had a negative influence on the detection of hazards. The findings show the additional dangers of engaging in a secondary task while driving. The attentional inertia effect has significant implications for semi-autonomous and autonomous vehicles in which drivers have greater opportunity to direct their attention away from the driving task.

Keywords: attention, eye-movements, hazard perception, visual search

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Authors: Nihan Gurel Ulusan

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It is obvious that electrical energy, which is an inseparable part of modern day’s human and also the most important power source of our age, should be generated on a level that will suffice the nation’s requirements. The electrical energy used for a sustainable architectural design should be reduced as much as possible. Designing the buildings as energy efficient systems which aim at reducing the artificial illumination loads has been a current subject of our times as a result of concepts gaining importance like conscious consumption of energy sources, environment-friendly designs and sustainability. Reducing the consumption of electrical energy regarding the artificial lighting carries great significance, especially in the volumes which are used all day long like the educational buildings. Starting out with such an aim in this paper, the educational buildings are explored in terms of energy efficient lighting. Firstly, illumination techniques, illumination systems, light sources, luminaries, illumination controls and 'efficient energy' usage in lighting are mentioned. In addition, natural and artificial lighting systems used in educational buildings and also the spaces building up these kind buildings are examined in terms of energy efficient lighting. Lastly, the illumination properties of the school sample chosen for this study, Kağıthane Anadolu Lisesi, a typical high school in Istanbul, is observed. Suggestions are made in order to improve the system by evaluating the illumination properties of the classes with the survey carried out with the users.

Keywords: educational buildings, energy efficient, illumination techniques, lighting

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

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Authors: Ali Bagherinia

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Efficient task scheduling method can meet users' requirements, and improve the resource utilization, then increase the overall performance of the cloud computing environment. Cloud computing has new features, such as flexibility, virtualization and etc., in this paper we propose a two levels task scheduling method based on load balancing in cloud computing. This task scheduling method meet user's requirements and get high resource utilization, that simulation results in CloudSim simulator prove this.

Keywords: cloud computing, task scheduling, virtualization, SLA

Procedia PDF Downloads 401