Search results for: dispersed region growing algorithm (DRGA)
10832 Is Electricity Consumption Stationary in Turkey?
Authors: Eyup Dogan
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The number of research articles analyzing the integration properties of energy variables has rapidly increased in the energy literature for about a decade. The stochastic behaviors of energy variables are worth knowing due to several reasons. For instance, national policies to conserve or promote energy consumption, which should be taken as shocks to energy consumption, will have transitory effects in energy consumption if energy consumption is found to be stationary in one country. Furthermore, it is also important to know the order of integration to employ an appropriate econometric model. Despite being an important subject for applied energy (economics) and having a huge volume of studies, several known limitations still exist with the existing literature. For example, many of the studies use aggregate energy consumption and national level data. In addition, a huge part of the literature is either multi-country studies or solely focusing on the U.S. This is the first study in the literature that considers a form of energy consumption by sectors at sub-national level. This research study aims at investigating unit root properties of electricity consumption for 12 regions of Turkey by four sectors in addition to total electricity consumption for the purpose of filling the mentioned limits in the literature. In this regard, we analyze stationarity properties of 60 cases . Because the use of multiple unit root tests make the results robust and consistent, we apply Dickey-Fuller unit root test based on Generalized Least Squares regression (DFGLS), Phillips-Perron unit root test (PP) and Zivot-Andrews unit root test with one endogenous structural break (ZA). The main finding of this study is that electricity consumption is trend stationary in 7 cases according to DFGLS and PP, whereas it is stationary process in 12 cases when we take into account the structural change by applying ZA. Thus, shocks to electricity consumption have transitory effects in those cases; namely, agriculture in region 1, region 4 and region 7, industrial in region 5, region 8, region 9, region 10 and region 11, business in region 4, region 7 and region 9, total electricity consumption in region 11. Regarding policy implications, policies to decrease or stimulate the use of electricity have a long-run impact on electricity consumption in 80% of cases in Turkey given that 48 cases are non-stationary process. On the other hand, the past behavior of electricity consumption can be used to predict the future behavior of that in 12 cases only.Keywords: unit root, electricity consumption, sectoral data, subnational data
Procedia PDF Downloads 40210831 Exploring Fertility Dynamics in the MENA Region: Distribution, Determinants, and Temporal Trends
Authors: Dena Alhaloul
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The Middle East and North Africa (MENA) region is characterized by diverse cultures, economies, and social structures. Fertility rates in MENA have seen significant changes over time, with variations among countries and subregions. Understanding fertility patterns in this region is essential due to its impact on demographic dynamics, healthcare, labor markets, and social policies. Rising or declining fertility rates have far-reaching consequences for the region's socioeconomic development. The main thrust of this study is to comprehensively examine fertility rates in the Middle East and North Africa (MENA) region. It aims to understand the distribution, determinants, and temporal trends of fertility rates in MENA countries. The study seeks to provide insights into the factors influencing fertility decisions, assess how fertility rates have evolved over time, and potentially develop statistical models to characterize these trends. As for the methodology of the study, the study uses descriptive statistics to summarize and visualize fertility rate data. It also uses regression analyses to identify determinants of fertility rates as well as statistical modeling to characterize temporal trends in fertility rates. The conclusion of this study The research will contribute to a deeper understanding of fertility dynamics in the MENA region, shedding light on the distribution of fertility rates, their determinants, and historical trends.Keywords: fertility, distribution, modeling, regression
Procedia PDF Downloads 6410830 A Kinetic Study of Radical Polymerisation of Acrylic Monomers in the Presence of the Liquid Crystal and the Electro-Optical Properties of These Mixtures
Authors: A. Bouriche, D. Merah, T. Bouchaour, L. Alachaher-Bedjaoui, U. Maschke
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Intensive research continues in the field of liquid crystals (LCs) for their potential use in modern display applications. Nematic LCs has been most commonly used due to the large birefringence and their sensitivity to even weak perturbation forces induced by electric, magnetic and optical fields. Polymer dispersed liquid crystals (PDLCs), composed of micron-sized nematic LC droplets dispersed in a polymer matrix is an important class of materials for applications in different domains of technology involving large area display devices, optical switches, phase modulators, variable attenuators, polarisers, flexible displays and smart windows. In this study the composites are prepared from mixtures of mono functional acrylic monomers, (Butylacrylate (ABu), 2-Ethylhexylacrylate (2-EHA), 2-Hydroxyethyl methacrylate (HEMA) and hydroxybutylmethacrylate (HBMA)) and two liquid crystals: (4-cyano-4'-n-pentyl-biphenyl) (5CB) and E7 which is an eutectic mixtures of four cyanoparaphenylenes. These mixtures are prepared adding the Darocur 1173 as photoinitiator, the 1.6-hexanediol diacrylate (HDDA) as cross-linker agent, and finally they are exposed to UV irradiation. The kinetic polymerization of monomer/LC mixture were investigated with the Fourier Transform Infra Red spectroscopy (FTIR). The electro-optical properties of the PDLC films were determined by measuring the voltage dependence on the transmitted light.Keywords: acrylic monomers, films PDLC, liquid crystal, polymerisation
Procedia PDF Downloads 29010829 Comparative Analysis of Two Different Ant Colony Optimization Algorithm for Solving Travelling Salesman Problem
Authors: Sourabh Joshi, Tarun Sharma, Anurag Sharma
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Ant Colony Optimization is heuristic Algorithm which has been proven a successful technique applied on number of combinatorial optimization problems. Two variants of Ant Colony Optimization algorithm named Ant System and Max-Min Ant System are implemented in MATLAB to solve travelling Salesman Problem and the results are compared. In, this paper both systems are analyzed by solving the some Travelling Salesman Problem and depict which system solve the problem better in term of cost and time.Keywords: Ant Colony Optimization, Travelling Salesman Problem, Ant System, Max-Min Ant System
Procedia PDF Downloads 47010828 Identification of the Parameters of a AC Servomotor Using Genetic Algorithm
Authors: J. G. Batista, K. N. Sousa, ¬J. L. Nunes, R. L. S. Sousa, G. A. P. Thé
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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measured and/or expected values.Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control
Procedia PDF Downloads 45910827 An Efficient Algorithm for Global Alignment of Protein-Protein Interaction Networks
Authors: Duc Dong Do, Ngoc Ha Tran, Thanh Hai Dang, Cao Cuong Dang, Xuan Huan Hoang
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Global aligning two protein-protein interaction networks is an essentially important task in bioinformatics/computational biology field of study. It is a challenging and widely studied research topic in recent years. Accurately aligned networks allow us to identify functional modules of proteins and/ororthologous proteins from which unknown functions of a protein can be inferred. We here introduce a novel efficient heuristic global network alignment algorithm called FASTAn, including two phases: the first to construct an initial alignment and the second to improve such alignment by exerting a local optimization repeated procedure. The experimental results demonstrated that FASTAn outperformed the state-of-the-art global network alignment algorithm namely SPINAL in terms of both commonly used objective scores and the run-time.Keywords: FASTAn, Heuristic algorithm, biological network alignment, protein-protein interaction networks
Procedia PDF Downloads 59410826 On the convergence of the Mixed Integer Randomized Pattern Search Algorithm
Authors: Ebert Brea
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We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain
Procedia PDF Downloads 45910825 Managing IT Departments in Higher Education Institutes: Coping with the Exponentially Growing Needs and Expectations
Authors: Balqees A. Al-Thuhli, Ali H. Al-Badi, Khamis Al-Gharbi
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Information technology is changing rapidly and the users’ expectations are also growing. Dealing with these changes in information technology, while satisfying the users’ needs and expectations is a big challenge. IT managers need to explore new mechanisms/strategies to enable them to cope with such challenges. The objectives of this research are to identify the significant challenges that might face IT managers in higher education institutes in the face of the high and ever growing customer expectations and to propose possible solutions to cope with such high-speed changes in information technology. To achieve these objectives, interviews with the IT professionals from different higher education institutes in Oman were conducted. In addition, documentation (printed and online) related to these institutions were studied and an intensive literature review of published work was examined. The findings of this research are expected to give a better understanding of the challenges that might face the IT managers at higher education institutes. This acquired understanding is expected to highlight the importance of being adaptable and fast in keeping up with the ever-growing technological changes. Moreover, adopting different tools and technologies could assist IT managers in developing their organisations’ IT policies and strategies.Keywords: information technology, rapid change, CIO roles, challenges, IT managers, coping mechanisms, users' expectations
Procedia PDF Downloads 25410824 Arithmetic Operations Based on Double Base Number Systems
Authors: K. Sanjayani, C. Saraswathy, S. Sreenivasan, S. Sudhahar, D. Suganya, K. S. Neelukumari, N. Vijayarangan
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Double Base Number System (DBNS) is an imminent system of representing a number using two bases namely 2 and 3, which has its application in Elliptic Curve Cryptography (ECC) and Digital Signature Algorithm (DSA).The previous binary method representation included only base 2. DBNS uses an approximation algorithm namely, Greedy Algorithm. By using this algorithm, the number of digits required to represent a larger number is less when compared to the standard binary method that uses base 2 algorithms. Hence, the computational speed is increased and time being reduced. The standard binary method uses binary digits 0 and 1 to represent a number whereas the DBNS method uses binary digit 1 alone to represent any number (canonical form). The greedy algorithm uses two ways to represent the number, one is by using only the positive summands and the other is by using both positive and negative summands. In this paper, arithmetic operations are used for elliptic curve cryptography. Elliptic curve discrete logarithm problem is the foundation for most of the day to day elliptic curve cryptography. This appears to be a momentous hard slog compared to digital logarithm problem. In elliptic curve digital signature algorithm, the key generation requires 160 bit of data by usage of standard binary representation. Whereas, the number of bits required generating the key can be reduced with the help of double base number representation. In this paper, a new technique is proposed to generate key during encryption and extraction of key in decryption.Keywords: cryptography, double base number system, elliptic curve cryptography, elliptic curve digital signature algorithm
Procedia PDF Downloads 39110823 The Security Challenges of Urbanization and Environmental Degradation in the Niger-Delta Area of Nigeria
Authors: Gloria Ogungbade, Ogaba Oche, Moses Duruji, Chris Ehiobuche, Lady Ajayi
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Human’s continued sustenance on earth and the quality of living are heavily dependent on the environment. The major components of the environment being air, water and land are the supporting pillars of the human existence, which they depend on directly or indirectly for survival and well-being. Unfortunately, due to some of the human activities on the environment, there seems to be a war between humans and the environment, which is evident in his over-exploitation and inadequate management of the basic components of the environment. Since the discovery of crude oil in the Niger Delta, the region has experienced various forms of degradation caused by pollution from oil spillage, gas flaring and other forms of environmental pollution, as a result of reckless way and manner with which oil is being exploited by the International Oil Corporations (IOCs) operating within the region. The Nigerian government on the other, not having strong regulations guiding the activities of the operations of these IOCs, has done almost nothing to curtail the activities of these IOCs because of the revenue generated the IOCs, as such the region is deprived of the basic social amenities and infrastructures. The degree of environmental pollution suffered within the region affects their major sources of livelihood – being fishing and farming, and has also left the region in poverty, which has led to a large number of people migrating to the urban areas to escape poverty. This paper investigates how environment degradation impact urbanization and security in the region.Keywords: environmental degradation, environmental pollution, gas flaring, oil spillage, urbanization
Procedia PDF Downloads 27410822 Spinach Lipid Extract as an Alternative Flow Aid for Fat Suspensions
Authors: Nizaha Juhaida Mohamad, David Gray, Bettina Wolf
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Chocolate is a material composite with a high fraction of solid particles dispersed in a fat phase largely composed of cocoa butter. Viscosity properties of chocolate can be manipulated by the amount of fat - increased levels of fat lead to lower viscosity. However, a high content of cocoa butter can increase the cost of the chocolate and instead surfactants are used to manipulate viscosity behaviour. Most commonly, lecithin and polyglycerol polyricinoleate (PGPR) are used. Lecithin is a natural lipid emulsifier which is based on phospholipids while PGPR is a chemically produced emulsifier which based on the long continuous chain of ricinoleic acid. Lecithin and PGPR act to lower the viscosity and yield stress, respectively. Recently, natural lipid emulsifiers based on galactolipid as the functional ingredient have become of interest. Spinach lipid is found to have a high amount of galactolipid, specifically MGDG and DGDG. The aim of this research is to explore the influence of spinach lipid in comparison with PGPR and lecithin on the rheological properties of sugar/oil suspensions which serve as chocolate model system. For that purpose, icing sugar was dispersed from 40%, 45% and 50% (w/w) in oil which has spinach lipid at concentrations from 0.1 – 0.7% (w/w). Based on viscosity at 40 s-1 and yield value reported as shear stress measured at 5 s-1, it was found that spinach lipid shows viscosity reducing and yield stress lowering effects comparable to lecithin and PGPR, respectively. This characteristic of spinach lipid demonstrates great potential for it to act as single natural lipid emulsifier in chocolate.Keywords: chocolate viscosity, lecithin, polyglycerol polyricinoleate (PGPR), spinach lipid
Procedia PDF Downloads 23910821 Improved Artificial Bee Colony Algorithm for Non-Convex Economic Power Dispatch Problem
Authors: Badr M. Alshammari, T. Guesmi
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This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones
Procedia PDF Downloads 24910820 An Application of Integrated Multi-Objective Particles Swarm Optimization and Genetic Algorithm Metaheuristic through Fuzzy Logic for Optimization of Vehicle Routing Problems in Sugar Industry
Authors: Mukhtiar Singh, Sumeet Nagar
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Vehicle routing problem (VRP) is a combinatorial optimization and nonlinear programming problem aiming to optimize decisions regarding given set of routes for a fleet of vehicles in order to provide cost-effective and efficient delivery of both services and goods to the intended customers. This paper proposes the application of integrated particle swarm optimization (PSO) and genetic optimization algorithm (GA) to address the Vehicle routing problem in sugarcane industry in India. Suger industry is very prominent agro-based industry in India due to its impacts on rural livelihood and estimated to be employing around 5 lakhs workers directly in sugar mills. Due to various inadequacies, inefficiencies and inappropriateness associated with the current vehicle routing model it costs huge money loss to the industry which needs to be addressed in proper context. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to improve its flexibility and manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the hybrid approach to an example of VRP and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of hybrid algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.Keywords: fuzzy logic, genetic algorithm, particle swarm optimization, vehicle routing problem
Procedia PDF Downloads 38810819 Evaulation of Food Safety Management in Central Elementary School Canteens in Tuguegarao City, Philippines
Authors: Lea B. Milan
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This descriptive study evaluated the existing Food Safety Management in Central Elementary School Canteens of Region 3. It made used of survey questionnaires, interview guide questions and validated knowledge test on food for data gathering. Results of the study revealed that school principals and canteen managers shared responsibilities in food safety management of school canteen. It also showed that the schools applied different methods of communication, monitoring and evaluation of food safety management. The study further revealed that implementation of monitoring and evaluation of food safety compliance are not being practiced in all elementary schools in the region. The study also showed that school canteens in the Region 3 do not have the thermometers and timers to use to conduct proper monitoring of foods during storage, preparation and serving. It was also found out from the study that canteen personnel lacks the basic knowledge and trainings on food safety. Potential source of physical, chemical and biological hazards that could contaminate foods were also found present in the canteen facilities of the elementary schools in the region. Moreover, evaluation showed that the existing implementation of food safety management in the Central Elementary School Canteens of Region 3 were below the expected level and the need to strengthen the appreciation and advocacy on food safety management in school canteens of Region 3 is still wanting.Keywords: food safety management, food safety school catering, food safety, school food safety management
Procedia PDF Downloads 36810818 Multitemporal Satellite Images for Agriculture Change Detection in Al Jouf Region, Saudi Arabia
Authors: Ali A. Aldosari
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Change detection of Earth surface features is extremely important for better understanding of our environment in order to promote better decision making. Al-Jawf is remarkable for its abundant agricultural water where there is fertile agricultural land due largely to underground water. As result, this region has large areas of cultivation of dates, olives and fruits trees as well as other agricultural products such as Alfa Alfa and wheat. However this agricultural area was declined due to the reduction of government supports in the last decade. This reduction was not officially recorded or measured in this region at large scale or governorate level. Remote sensing data are primary sources extensively used for change detection in agriculture applications. This study is applied the technology of GIS and used the Normalized Difference Vegetation Index (NDVI) which can be used to measure and analyze the spatial and temporal changes in the agriculture areas in the Aljouf region.Keywords: spatial analysis, geographical information system, change detection
Procedia PDF Downloads 39410817 Predictive Analysis for Big Data: Extension of Classification and Regression Trees Algorithm
Authors: Ameur Abdelkader, Abed Bouarfa Hafida
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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm
Procedia PDF Downloads 13410816 On the Influence of the Metric Space in the Critical Behavior of Magnetic Temperature
Authors: J. C. Riaño-Rojas, J. D. Alzate-Cardona, E. Restrepo-Parra
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In this work, a study of generic magnetic nanoparticles varying the metric space is presented. As the metric space is changed, the nanoparticle form and the inner product are also varied, since the energetic scale is not conserved. This study is carried out using Monte Carlo simulations combined with the Wolff embedding and Metropolis algorithms. The Metropolis algorithm is used at high temperature regions to reach the equilibrium quickly. The Wolff embedding algorithm is used at low and critical temperature regions in order to reduce the critical slowing down phenomenon. The ions number is kept constant for the different forms and the critical temperatures using finite size scaling are found. We observed that critical temperatures don't exhibit significant changes when the metric space was varied. Additionally, the effective dimension according the metric space was determined. A study of static behavior for reaching the static critical exponents was developed. The objective of this work is to observe the behavior of the thermodynamic quantities as energy, magnetization, specific heat, susceptibility and Binder's cumulants at the critical region, in order to demonstrate if the magnetic nanoparticles describe their magnetic interactions in the Euclidean space or if there is any correspondence in other metric spaces.Keywords: nanoparticles, metric, Monte Carlo, critical behaviour
Procedia PDF Downloads 50610815 Collocation Method Using Quartic B-Splines for Solving the Modified RLW Equation
Authors: A. A. Soliman
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The Modified Regularized Long Wave (MRLW) equation is solved numerically by giving a new algorithm based on collocation method using quartic B-splines at the mid-knot points as element shape. Also, we use the fourth Runge-Kutta method for solving the system of first order ordinary differential equations instead of finite difference method. Our test problems, including the migration and interaction of solitary waves, are used to validate the algorithm which is found to be accurate and efficient. The three invariants of the motion are evaluated to determine the conservation properties of the algorithm. The temporal evaluation of a Maxwellian initial pulse is then studied.Keywords: collocation method, MRLW equation, Quartic B-splines, solitons
Procedia PDF Downloads 29610814 Influence of Parameters of Modeling and Data Distribution for Optimal Condition on Locally Weighted Projection Regression Method
Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri
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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method
Procedia PDF Downloads 49210813 A Hybrid Distributed Algorithm for Solving Job Shop Scheduling Problem
Authors: Aydin Teymourifar, Gurkan Ozturk
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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network
Procedia PDF Downloads 37710812 Robust Data Image Watermarking for Data Security
Authors: Harsh Vikram Singh, Ankur Rai, Anand Mohan
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In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image.Keywords: data hiding, watermarking, DCT, chaotic sequence, arnold transforms
Procedia PDF Downloads 50110811 Wait-Optimized Scheduler Algorithm for Efficient Process Scheduling in Computer Systems
Authors: Md Habibur Rahman, Jaeho Kim
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Efficient process scheduling is a crucial factor in ensuring optimal system performance and resource utilization in computer systems. While various algorithms have been proposed over the years, there are still limitations to their effectiveness. This paper introduces a new Wait-Optimized Scheduler (WOS) algorithm that aims to minimize process waiting time by dividing them into two layers and considering both process time and waiting time. The WOS algorithm is non-preemptive and prioritizes processes with the shortest WOS. In the first layer, each process runs for a predetermined duration, and any unfinished process is subsequently moved to the second layer, resulting in a decrease in response time. Whenever the first layer is free or the number of processes in the second layer is twice that of the first layer, the algorithm sorts all the processes in the second layer based on their remaining time minus waiting time and sends one process to the first layer to run. This ensures that all processes eventually run, optimizing waiting time. To evaluate the performance of the WOS algorithm, we conducted experiments comparing its performance with traditional scheduling algorithms such as First-Come-First-Serve (FCFS) and Shortest-Job-First (SJF). The results showed that the WOS algorithm outperformed the traditional algorithms in reducing the waiting time of processes, particularly in scenarios with a large number of short tasks with long wait times. Our study highlights the effectiveness of the WOS algorithm in improving process scheduling efficiency in computer systems. By reducing process waiting time, the WOS algorithm can improve system performance and resource utilization. The findings of this study provide valuable insights for researchers and practitioners in developing and implementing efficient process scheduling algorithms.Keywords: process scheduling, wait-optimized scheduler, response time, non-preemptive, waiting time, traditional scheduling algorithms, first-come-first-serve, shortest-job-first, system performance, resource utilization
Procedia PDF Downloads 8110810 Comparison of ANFIS Update Methods Using Genetic Algorithm, Particle Swarm Optimization, and Artificial Bee Colony
Authors: Michael R. Phangtriastu, Herriyandi Herriyandi, Diaz D. Santika
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This paper presents a comparison of the implementation of metaheuristic algorithms to train the antecedent parameters and consequence parameters in the adaptive network-based fuzzy inference system (ANFIS). The algorithms compared are genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC). The objective of this paper is to benchmark well-known metaheuristic algorithms. The algorithms are applied to several data set with different nature. The combinations of the algorithms' parameters are tested. In all algorithms, a different number of populations are tested. In PSO, combinations of velocity are tested. In ABC, a different number of limit abandonment are tested. Experiments find out that ABC is more reliable than other algorithms, ABC manages to get better mean square error (MSE) than other algorithms in all data set.Keywords: ANFIS, artificial bee colony, genetic algorithm, metaheuristic algorithm, particle swarm optimization
Procedia PDF Downloads 34210809 An Efficient Strategy for Relay Selection in Multi-Hop Communication
Authors: Jung-In Baik, Seung-Jun Yu, Young-Min Ko, Hyoung-Kyu Song
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This paper proposes an efficient relaying algorithm to obtain diversity for improving the reliability of a signal. The algorithm achieves time or space diversity gain by multiple versions of the same signal through two routes. Relays are separated between a source and destination. The routes between the source and destination are set adaptive in order to deal with different channels and noises. The routes consist of one or more relays and the source transmits its signal to the destination through the routes. The signals from the relays are combined and detected at the destination. The proposed algorithm provides a better performance than the conventional algorithms in bit error rate (BER).Keywords: multi-hop, OFDM, relay, relaying selection
Procedia PDF Downloads 43910808 Groundwater Quality in the Rhiss-Nekor Plain, Morocco: Impacts of Human Activities
Authors: Ali Ait Boughrous, Said Benyoussef, Hossain El Ouarghi, Moulay Abdelazize Aboulhassan, Samah Aitbnichou, Said Benguamra
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The Rhiss-Nekor aquifer represents a primary water source for the central Rif region. Many operating structures were built for irrigation and drinking water supply. Because of the vulnerability of this aquifer, a thorough knowledge of the environment is needed to evaluate and protect resources. This work aims at the quality assessment of the water table of the plain Ghiss-Nekor and determination of pollution sources in order to establish a map of the web. The plain-Rhiss Nekor, with an area of 100 km2, is located on the Mediterranean coast of Morocco. It has a particular geological structure resulting from the opening of a graben at the end of the Tertiary, which is filled by the accumulation of hundreds of meters of sediment, generating considerable heterogeneity in deposits. This heterogeneity gives various hydrodynamic properties within the aquifer of the plain. The analysis of the water quality of twenty water points, well distributed over the plain, showed high natural salinity linked to the geological nature of the area. This salinity increases in the littoral area by the seawater intrusion phenomenon. This is accentuated by overexploitation of the ground water due to the growing demand. Some wells, located inland, are characterized by organic pollution caused by wastewater seepage from septic tanks and lost wells widespread in the region.Keywords: anthropogenic factors, groundwater quality, marine intrusion, Rhiss-Nekor aquifer
Procedia PDF Downloads 12910807 Investigation of Subsurface Structures within Bosso Local Government for Groundwater Exploration Using Magnetic and Resistivity Data
Authors: Adetona Abbassa, Aliyu Shakirat B.
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The study area is part of Bosso local Government, enclosed within Longitude 6.25’ to 6.31’ and Latitude 9.35’ to 9.45’, an area of 16x8 km², within the basement region of central Nigeria. The region is a host to Nigerian Airforce base 12 (NAF 12quick response) and its staff quarters, the headquarters of Bosso local government, the Independent National Electoral Commission’s two offices, four government secondary schools, six primary schools and Minna international airport. The area suffers an acute shortage of water from November when rains stop to June when rains commence within North Central Nigeria. A way of addressing this problem is a reconnaissance method to delineate possible fractures and fault lines that exists within the region by sampling the Aeromagnetic data and using an appropriate analytical algorithm to delineate these fractures. This is followed by an appropriate ground truthing method that will confirm if the fracture is connected to underground water movement. The first vertical derivative for structural analysis, reveals a set of lineaments labeled AA’, BB’, CC’, DD’, EE’ and FF’ all trending in the Northeast – Southwest directions. AA’ is just below latitude 9.45’ above Maikunkele village, cutting off the upper part of the field, it runs through Kangwo, Nini, Lawo and other communities. BB’ is at Latitude 9.43’ it truncated at about 2Km before Maikunkele and Kuyi. CC’ is around 9.40’ sitting below Maikunkele runs down through Nanaum. DD’ is from Latitude 9.38’; interestingly no community within this region where the fault passes through. A result from the three sites where Vertical Electrical Sounding was carried out reveals three layers comprised of topsoil, intermediate Clay formation and weathered/fractured or fresh basement. The depth to basement map was also produced, depth to the basement from the ground surface with VES A₂, B5, D₂ and E₁ to be relatively deeper with depth values range between 25 to 35 m while the shallower region of the area has a depth range value between 10 to 20 m. Hence, VES A₂, A₅, B₄, B₅, C₂, C₄, D₄, D₅, E₁, E₃, and F₄ are high conductivity zone that are prolific for groundwater potential. The depth range of the aquifer potential zones is between 22.7 m to 50.4 m. The result from site C is quite unique though the 3 layers were detected in the majority of the VES points, the maximum depth to the basement in 90% of the VES points is below 8 km, only three VES points shows considerably viability, which are C₆, E₂ and F₂ with depths of 35.2 m and 38 m respectively but lack of connectivity will be a big challenge of chargeability.Keywords: lithology, aeromagnetic, aquifer, geoelectric, iso-resistivity, basement, vertical electrical sounding(VES)
Procedia PDF Downloads 12910806 An Automated Optimal Robotic Assembly Sequence Planning Using Artificial Bee Colony Algorithm
Authors: Balamurali Gunji, B. B. V. L. Deepak, B. B. Biswal, Amrutha Rout, Golak Bihari Mohanta
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Robots play an important role in the operations like pick and place, assembly, spot welding and much more in manufacturing industries. Out of those, assembly is a very important process in manufacturing, where 20% of manufacturing cost is wholly occupied by the assembly process. To do the assembly task effectively, Assembly Sequences Planning (ASP) is required. ASP is one of the multi-objective non-deterministic optimization problems, achieving the optimal assembly sequence involves huge search space and highly complex in nature. Many researchers have followed different algorithms to solve ASP problem, which they have several limitations like the local optimal solution, huge search space, and execution time is more, complexity in applying the algorithm, etc. By keeping the above limitations in mind, in this paper, a new automated optimal robotic assembly sequence planning using Artificial Bee Colony (ABC) Algorithm is proposed. In this algorithm, automatic extraction of assembly predicates is done using Computer Aided Design (CAD) interface instead of extracting the assembly predicates manually. Due to this, the time of extraction of assembly predicates to obtain the feasible assembly sequence is reduced. The fitness evaluation of the obtained feasible sequence is carried out using ABC algorithm to generate the optimal assembly sequence. The proposed methodology is applied to different industrial products and compared the results with past literature.Keywords: assembly sequence planning, CAD, artificial Bee colony algorithm, assembly predicates
Procedia PDF Downloads 23210805 A New Optimization Algorithm for Operation of a Microgrid
Authors: Sirus Mohammadi, Rohala Moghimi
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The main advantages of microgrids are high energy efficiency through the application of Combined Heat and Power (CHP), high quality and reliability of the delivered electric energy and environmental and economic advantages. This study presents an energy management system (EMS) to optimize the operation of the microgrid (MG). In this paper an Adaptive Modified Firefly Algorithm (AMFA) is presented for optimal operation of a typical MG with renewable energy sources (RESs) accompanied by a back-up Micro-Turbine/Fuel Cell/Battery hybrid power source to level the power mismatch or to store the energy surplus when it’s needed. The problem is formulated as a nonlinear constraint problem to minimize the total operating cost. The management of Energy storage system (ESS), economic load dispatch and operation optimization of distributed generation (DG) are simplified into a single-object optimization problem in the EMS. The proposed algorithm is tested on a typical grid-connected MG including WT/PV/Micro Turbine/Fuel Cell and Energy Storage Devices (ESDs) then its superior performance is compared with those from other evolutionary algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Self Adaptive PSO (FSAPSO), Chaotic Particle PSO (CPSO), Adaptive Modified PSO (AMPSO), and Firefly Algorithm (FA).Keywords: microgrid, operation management, optimization, firefly algorithm (AMFA)
Procedia PDF Downloads 33310804 A Robust Visual Simultaneous Localization and Mapping for Indoor Dynamic Environment
Authors: Xiang Zhang, Daohong Yang, Ziyuan Wu, Lei Li, Wanting Zhou
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Visual Simultaneous Localization and Mapping (VSLAM) uses cameras to collect information in unknown environments to realize simultaneous localization and environment map construction, which has a wide range of applications in autonomous driving, virtual reality and other related fields. At present, the related research achievements about VSLAM can maintain high accuracy in static environment. But in dynamic environment, due to the presence of moving objects in the scene, the movement of these objects will reduce the stability of VSLAM system, resulting in inaccurate localization and mapping, or even failure. In this paper, a robust VSLAM method was proposed to effectively deal with the problem in dynamic environment. We proposed a dynamic region removal scheme based on semantic segmentation neural networks and geometric constraints. Firstly, semantic extraction neural network is used to extract prior active motion region, prior static region and prior passive motion region in the environment. Then, the light weight frame tracking module initializes the transform pose between the previous frame and the current frame on the prior static region. A motion consistency detection module based on multi-view geometry and scene flow is used to divide the environment into static region and dynamic region. Thus, the dynamic object region was successfully eliminated. Finally, only the static region is used for tracking thread. Our research is based on the ORBSLAM3 system, which is one of the most effective VSLAM systems available. We evaluated our method on the TUM RGB-D benchmark and the results demonstrate that the proposed VSLAM method improves the accuracy of the original ORBSLAM3 by 70%˜98.5% under high dynamic environment.Keywords: dynamic scene, dynamic visual SLAM, semantic segmentation, scene flow, VSLAM
Procedia PDF Downloads 10110803 A Fast Parallel and Distributed Type-2 Fuzzy Algorithm Based on Cooperative Mobile Agents Model for High Performance Image Processing
Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah
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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing
Procedia PDF Downloads 416