Search results for: range migration algorithm

Authors: M. Laura Vazquez Maggio, Lilia Dominguez Villalobos, Jan Luka Frey

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This paper contributes to the understanding of the dynamic and the relational nature of identities formation among skilled middle-class migrants. Following the idea that identities are never singular, multifaceted and have a necessarily processual character, the authors specifically analyze three dimensions of the identity of qualified Mexican migrants in the US and the interplay between them. Drawing on semi-structured interviews with skilled Mexican middle-class migrants in the US, the paper explores how skilled Mexican migrants preserve their ethno-national identity (their ‘Mexicanness’) in reaction to a hostile socio-political reception context in the US. It further shows how these migrants recreate their class identity and show tendencies to distance themselves from what they perceive as lower-class Mexican migrants and the dominant popular Mexican and Latin-American cultural expressions. In a final step, it examines how the lived experience of migration itself impacts the migrants’ identities, their concept of self and feelings/modes of being and belonging.

Keywords: ethno-national identity, middle class identity, middle-class migration, migrants’ identity, skilled migration

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Authors: Kristian Bautista, Ruben A. Idoy

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A bio-inspired metaheuristic algorithm inspired by the theory of collective animal behavior (CAB) was integrated to density-based clustering modeled as multimodal optimization problem. The algorithm was tested on synthetic, Iris, Glass, Pima and Thyroid data sets in order to measure its effectiveness relative to CDE-based Clustering algorithm. Upon preliminary testing, it was found out that one of the parameter settings used was ineffective in performing clustering when applied to the algorithm prompting the researcher to do an investigation. It was revealed that fine tuning distance δ3 that determines the extent to which a given data point will be clustered helped improve the quality of cluster output. Even though the modification of distance δ3 significantly improved the solution quality and cluster output of the algorithm, results suggest that there is no difference between the population mean of the solutions obtained using the original and modified parameter setting for all data sets. This implies that using either the original or modified parameter setting will not have any effect towards obtaining the best global and local animal positions. Results also suggest that CDE-based clustering algorithm is better than CAB-density clustering algorithm for all data sets. Nevertheless, CAB-density clustering algorithm is still a good clustering algorithm because it has correctly identified the number of classes of some data sets more frequently in a thirty trial run with a much smaller standard deviation, a potential in clustering high dimensional data sets. Thus, the researcher recommends further investigation in the post-processing stage of the algorithm.

Keywords: clustering, metaheuristics, collective animal behavior algorithm, density-based clustering, multimodal optimization

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Authors: Fariborz Ahmadi, Reza Tati

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Genetic algorithm is a soft computing method that works on set of solutions. These solutions are called chromosome and the best one is the absolute solution of the problem. The main problem of this algorithm is that after passing through some generations, it may be produced some chromosomes that had been produced in some generations ago that causes reducing the convergence speed. From another respective, most of the genetic algorithms are implemented in software and less works have been done on hardware implementation. Our work implements genetic algorithm in hardware that doesn’t produce chromosome that have been produced in previous generations. In this work, most of genetic operators are implemented without producing iterative chromosomes and genetic diversity is preserved. Genetic diversity causes that not only do not this algorithm converge to local optimum but also reaching to global optimum. Without any doubts, proposed approach is so faster than software implementations. Evaluation results also show the proposed approach is faster than hardware ones.

Keywords: hardware, genetic algorithm, computer science, engineering

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Authors: Anjan Naidu

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In this paper we first discuss the minimum spanning tree, then we use the Kruskal algorithm to obtain minimum spanning tree. Based on Kruskal algorithm we propose Kruskal algorithm to apply an application to find minimum cost applying the concept of spanning tree.

Keywords: Minimum Spanning tree, algorithm, Heuxistic, application, classification of Sub 97K90

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Authors: Karolína Augustovaá

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Turkey’s eastern borders have been at the center of criticism by the European Commission who condemns restrictions against Kurdish civilians as the result of Turkey’s military operations against terrorist organizations (namely PKK). Yet, the Commission has launched economic and political support for numerous military projects along the Iran-Turkey border to fight cross-border crime (namely “illegal” migration) along its external borders. Whilst border externalization has been extensively examined in the EU’s wide neighborhood, its analysis from the ground in conflict zones is emerging. The existing analysis also rarely considers the impact of external border management beyond international migration - on the local context and its people. However, tough externalization policies at borders, where local wars are fought, are fundamental to scrutinize as they invite us to question the effects of EU’s migration management on diverse communities navigating their life along external borders. To fill this research lacunae, this article examines intersections between the local military operations and international (EU-Turkey) migration management at the Turkey’s border with Iran and questions their impact on the everyday struggles of people living at and migrating across the border. To do so, it applies critical feminist and military literature to border studies. Methodologically, the article draws upon ethnographic research in Van (Eastern Turkey), using participant observations and interviews with sixty participants. This article argues that the EU’s externalization policies add to the violence generated by the local militarized conflict and eventually (re-)produce it in the forms of push-backs and physical violence against people who daily cross the border irregularly for their physical/economic survival. By doing so, I suggest that (inter)national fears of terrorism and migration inter-sect, materialize and affect everyday sites of diverse racialized groups living at and moving across external borders, such as international migrants (Afghans) and the local residents (Kurds) at the Turkey-Iran border. This article highlights the need to analyze the local border context in tandem with international migration management in the EU’s wider neighborhood to understand how conflict and violence evolves there.

Keywords: european union border externalization, eastern turkey, migration, conflict, kurdish question

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Authors: Vahid Rashtchi, Ashkan Pirooz

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This paper applies the Imperialist Competitive Algorithm (ICA) to find the optimal place and size of Static Compensator (STATCOM) in power systems. The output of the algorithm is a two dimensional array which indicates the best bus number and STATCOM's optimal size that minimizes all bus voltage deviations from their nominal value. Simulations are performed on IEEE 5, 14, and 30 bus test systems. Also some comparisons have been done between ICA and the famous Particle Swarm Optimization (PSO) algorithm. Results show that how this method can be considered as one of the most precise evolutionary methods for the use of optimum compensator placement in electrical grids.

Keywords: evolutionary computation, imperialist competitive algorithm, power systems compensation, static compensators, voltage profile

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Authors: Ismail Haddad, Djamel Herbadji, Aissa Belmeguenai, Selma Boumerdassi

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in this paper, we provide a novel approach for image encryption that employs the Fibonacci matrix and an enhanced fractional order chaotic map. The enhanced map overcomes the drawbacks of the classical map, especially the limited chaotic range and non-uniform distribution of chaotic sequences, resulting in a larger encryption key space. As a result, this strategy improves the encryption system's security. Our experimental results demonstrate that our proposed algorithm effectively encrypts grayscale images with exceptional efficiency. Furthermore, our technique is resistant to a wide range of potential attacks, including statistical and entropy attacks.

Keywords: image encryption, logistic map, fibonacci matrix, grayscale images

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Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev

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A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference to signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: noise signal, pulse interference, signal power, spectrum width, detection

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Authors: Doga Erisik, Ahmet Karaman, Gulfem Alptekin, Ozlem Durmaz Incel

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Augmented reality (AR) is a type of virtual reality aiming to duplicate real world’s environment on a computer’s video feed. The mobile application, which is built for this project (called SARAS), enables annotating real world point of interests (POIs) that are located near mobile user. In this paper, we aim at introducing a robust and simple algorithm for placing labels in an augmented reality system. The system places labels of the POIs on the mobile device screen whose GPS coordinates are given. The proposed algorithm is compared to an existing one in terms of energy consumption and accuracy. The results show that the proposed algorithm gives better results in energy consumption and accuracy while standing still, and acceptably accurate results when driving. The technique provides benefits to AR browsers with its open access algorithm. Going forward, the algorithm will be improved to more rapidly react to position changes while driving.

Keywords: accurate tagging algorithm, augmented reality, localization, location-based AR

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Authors: Adam Modu Abbas

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Nigeria, due to its location, size and population is very vulnerable to the impact of climate change. Little effort is however made to address most of the problems, despite the fact that sufficient understanding is made on the impact of climate change and problems emanating from it are also always being propagated. Migration, one of the resultant effects of climate change is however given less attention. This paper focuses on the climate change impact and one of resulting effects, migration and its associated problems. Purposive sampling technique was adopted in sampling 250 respondents who were mainly family members of out-migrants from Ngala and Kala-Balge LGAs of North-eastern Borno State, Nigeria. Available literatures were consulted for the types of climate change impacts. The results revealed that, climate change leads to climatic variation over the space with numerous effects on the environment such as intermittent droughts, desertification/deforestation, low water table and establishment of dams across the courses of the main sources of water supply to the Lake Chad. Many people in the study area either migrated to Cameroon’s Darrak, Lake Doi and Mayo Mbund, Lagos, Nigeria, leaving some members of their families at home. More than half of respondents indicated that the heads of the households migrated as a result of poor harvest due to diminishing or fluctuating rains/drought and/or drying of river Surbewel. It is recommended that; inter-basin water transfers should be embarked upon.

Keywords: climate, change, migration, dam, intermittent

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Authors: Deane Roehl, Roberto Quevedo

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Gas migration from pressurized formations is a problem reported in the oil and gas industry. This means increased risks for drilling, production, well integrity, and hydrocarbon escape. Different processes can contribute to the development of pressurized formations, particularly in High-Pressure–High-Temperature (HPHT) gas fields. Over geological time-scales, the different formations of those fields have maintained and/or developed abnormal pressures owing to low permeability and the presence of an impermeable seal. However, if this seal is broken, large volumes of gas could migrate into other less pressurized formations. Three main mechanisms for gas migration have been identified in the literature –molecular diffusion, continuous-phase flow, and continuous-phase flow coupled with mechanical effects. In relation to the latter, gas migration can occur as a consequence of the mechanical effects triggered by reservoir depletion. The compaction of the reservoir can redistribute the in-situ stresses sufficiently to induce deformations that may increase the permeability of rocks and lead to fracture processes or reactivate nearby faults. The understanding of gas flow through discontinuities is still under development. However, some models based on porosity changes and fracture aperture have been developed in order to obtain enhanced permeabilities in numerical simulations. In this work, a simple relationship to integrate fluid flow through rock matrix and discontinuities has been implemented in a fully thermo-hydro-mechanical simulator developed in-house. Numerical simulations of hydrocarbon production in an HPHT field were carried out. Results suggest that rock permeability can be considerably affected by the deformation of the field, creating preferential flow paths for the transport of large volumes of gas.

Keywords: gas migration, pressurized formations, fractured rocks, numerical modeling

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Authors: Aleksander Mendoza

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Glushkov's construction has many interesting properties, and they become even more evident when applied to transducers. This article strives to show the vast range of possible extensions and optimisations for this algorithm. Special flavour of regular expressions is introduced, which can be efficiently converted to e-free functional subsequential weighted finite state transducers. Produced automata are very compact, as they contain only one state for each symbol (from input alphabet) of original expression and only one transition for each range of symbols, no matter how large. Such compactified ranges of transitions allow for efficient binary search lookup during automaton evaluation. All the methods and algorithms presented here were used to implement open-source compiler of regular expressions for multitape transducers.

Keywords: weighted automata, transducers, Glushkov, follow automata, regular expressions

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Authors: Abdelghani Choucha, Lakhdar Chaib, Salem Arif

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This paper treated the problem of power system stability with the aid of Static Synchronous Series Compensator (SSSC) installed in the transmission line of single machine infinite bus (SMIB) power system. A fractional order PID (FOPID) controller has been applied as a robust controller for optimal SSSC design to control the power system characteristics. Additionally, the SSSC based FOPID parameters are smoothly tuned using Invasive Weed Optimization algorithm (IWO). To verify the strength of the proposed controller, SSSC based FOPID controller is validated in a wide range of operating condition and compared with the conventional scheme SSSC-POD controller. The main purpose of the proposed process is greatly enhanced the dynamic states of the tested system. Simulation results clearly prove the superiority and performance of the proposed controller design.

Keywords: SSSC-FOPID, SSSC-POD, SMIB power system, invasive weed optimization algorithm

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Authors: Diogen Babuc

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The question that is a motivation of writing is how many devote themselves to discovering something in the world of science where much is discerned and revealed, but at the same time, much is unknown. Methods: The insightful elements of this algorithm are the ciphering and deciphering algorithms of Playfair, Caesar, and Vigenère. Only a few of their main properties are taken and modified, with the aim of forming a specific functionality of the algorithm called Latin Djokovic. Specifically, a string is entered as input data. A key k is given, with a random value between the values a and b = a+3. The obtained value is stored in a variable with the aim of being constant during the run of the algorithm. In correlation to the given key, the string is divided into several groups of substrings, and each substring has a length of k characters. The next step involves encoding each substring from the list of existing substrings. Encoding is performed using the basis of Caesar algorithm, i.e., shifting with k characters. However, that k is incremented by 1 when moving to the next substring in that list. When the value of k becomes greater than b+1, it’ll return to its initial value. The algorithm is executed, following the same procedure, until the last substring in the list is traversed. Results: Using this polyalphabetic method, ciphering and deciphering of strings are achieved. The algorithm also works for a 100-character string. The x character isn’t used when the number of characters in a substring is incompatible with the expected length. The algorithm is simple to implement, but it’s questionable if it works better than the other methods from the point of view of execution time and storage space.

Keywords: ciphering, deciphering, authentic, algorithm, polyalphabetic cipher, random key, methods comparison

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Authors: Zeyu Zhang, Guisheng Yin, Ziying Zhang, Liguo Zhang

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This paper mainly studies the path planning method based on ant colony optimization (ACO), and proposes heuristic integration ant colony optimization (HIACO). This paper not only analyzes and optimizes the principle, but also simulates and analyzes the parameters related to the application of HIACO in path planning. Compared with the original algorithm, the improved algorithm optimizes probability formula, tabu table mechanism and updating mechanism, and introduces more reasonable heuristic factors. The optimized HIACO not only draws on the excellent ideas of the original algorithm, but also solves the problems of premature convergence, convergence to the sub optimal solution and improper exploration to some extent. HIACO can be used to achieve better simulation results and achieve the desired optimization. Combined with the probability formula and update formula, several parameters of HIACO are tested. This paper proves the principle of the HIACO and gives the best parameter range in the research of path planning.

Keywords: ant colony optimization, heuristic integration, path planning, probability formula

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Authors: Evangelia-Matroni Tomara

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This thesis answers the question whether the media representations and reporting in 2015-2016 - especially, after the image of the drowned three-year-old Syrian boy in the Mediterranean Sea which made global headlines in the beginning of September 2015 -, the European Commission regulatory sources material and related reporting, have the power to challenge the conceptualization of humanitarianism or even redefine it. The theoretical foundations of the thesis are based on humanitarianism and its core definitions, the power of media representations and the relative portrayal of migrants, refugees and/or asylum seekers, as well as the dominant migration discourse and EU migration governance. Using content analysis for the media portrayal of migrants (436 newspaper articles) and qualitative content analysis for the European Commission Communication documents from May 2015 until June 2016 that required various depths of interpretation, this thesis allowed us to revise the concept of humanitarianism, realizing that the current crisis may seem to be a turning point for Europe but is not enough to overcome the past hostile media discourses and suppress the historical perspective of security and control-oriented EU migration policies. In particular, the crisis helped to shift the intensity of hostility and the persistence in the state-centric, border-oriented securitization in Europe into a narration of victimization rather than threat where mercy and charity dynamics are dominated and into operational mechanisms, noting the emergency of immediate management of the massive migrations flows, respectively. Although, the understanding of a rights-based response to the ongoing migration crisis, is being followed discursively in both political and media stage, the nexus described, points out that the binary between ‘us’ and ‘them’ still exists, with only difference that the ‘invaders’ are now ‘pathetic’ but still ‘invaders’. In this context, the migration crisis challenges the concept of humanitarianism because rights dignify migrants as individuals only in a discursive or secondary level while the humanitarian work is mostly related with the geopolitical and economic interests of the ‘savior’ states.

Keywords: European Union politics, humanitarianism, immigration, media representation, policy-making, refugees, security studies

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Authors: Mohamed Mahmoud

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This paper has developed an effect-cause analysis technique for fault diagnosis in digital circuits. The main algorithm of our technique is based on the Enhanced Deduction Algorithm, which processes the real response of the CUT to the applied test T to deduce the values of the internal lines. An experimental version of the algorithm has been implemented in C++. The code takes about 7592 lines. The internal values are determined based on the logic values under the permanent stuck-fault model. Using a backtracking strategy guarantees that the actual values are covered by at least one solution, or no solution is found.

Keywords: enhanced deduction algorithm, backtracking strategy, automatic test equipment, verfication

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Authors: Farha Lakhani, Michael J. Pont

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There are two main architectures used to develop software for modern embedded systems: these can be labelled as “event-triggered” (ET) and “time-triggered” (TT). The research presented in this paper is concerned with the issues involved in migration between these two architectures. Although TT architectures are widely used in safety-critical applications they are less familiar to developers of mainstream embedded systems. The research presented in this paper began from the premise that–for a broad class of systems that have been implemented using an ET architecture–migration to a TT architecture would improve reliability. It may be tempting to assume that conversion between ET and TT designs will simply involve converting all event-handling software routines into periodic activities. However, the required changes to the software architecture are, in many cases rather more profound. The main contribution of the work presented in this paper is to identify ways in which the significant effort involved in migrating between existing ET architectures and “equivalent” (and effective) TT architectures could be reduced. The research described in this paper has taken an innovative step in this regard by introducing the use of ‘Design patterns’ for this purpose for the first time.

Keywords: embedded applications, software architectures, reliability, pattern

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Authors: Yiding Qu, Svetlana V. Komarova

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Chemokines acting through their cognate chemokine receptors guide the directional migration of the cell along the chemokine gradient. Several chemokine receptors were recently identified as non-signaling (decoy), based on their ability to bind the chemokine but produce no measurable signal in the cell. The function of these decoy receptors is not well understood. We examined the expression of a decoy receptor CCRL1 and a signaling receptor that binds to the same ligands, CCR7, in prostate cancer using publically available microarray data (www.oncomine.org). The expression of both CCRL1 and CCR7 increased in an approximately half of prostate carcinoma samples and the majority of metastatic cancer samples compared to normal prostate. Moreover, the expression of CCRL1 positively correlated with the expression of CCR7. These data suggest that CCR7 and CCRL1 can be used as clinical markers for the early detection of transformation from carcinoma to metastatic cancer. In addition, these data support our hypothesis that the non-signaling chemokine receptors actively stimulate cell migration.

Keywords: bioinformatics, cell migration, decoy receptor, meta-analysis, prostate cancer

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Authors: Yanhua Zhao, Chenli Rao, Dongdong Li, Chuanmin Tao

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The Chinese Centers for Disease Control and Prevention (CCDC) issued a new laboratory-based algorithm for HIV diagnosis on April 2016, which initially screens with a combination HIV-1/HIV-2 antigen/antibody fourth-generation immunoassay (IA) followed, when reactive, an HIV-1/HIV-2 undifferentiated antibody IA in duplicate. Reactive specimens with concordant results undergo supplemental tests with western blots, or HIV-1 nucleic acid tests (NATs) and non-reactive specimens with discordant results receive HIV-1 NATs or p24 antigen tests or 2-4 weeks follow-up tests. However, little data evaluating the application of the new algorithm have been reported to date. The study was to evaluate the performance of new laboratory-based HIV diagnostic algorithm in an inpatient population of Southwest China over the initial 6 months by compared with the old algorithm. Plasma specimens collected from inpatients from May 1, 2016, to October 31, 2016, are submitted to the laboratory for screening HIV infection performed by both the new HIV testing algorithm and the old version. The sensitivity and specificity of the algorithms and the difference of the categorized numbers of plasmas were calculated. Under the new algorithm for HIV diagnosis, 170 of the total 52 749 plasma specimens were confirmed as positively HIV-infected (0.32%). The sensitivity and specificity of the new algorithm were 100% (170/170) and 100% (52 579/52 579), respectively; while 167 HIV-1 positive specimens were identified by the old algorithm with sensitivity 98.24% (167/170) and 100% (52 579/52 579), respectively. Three acute HIV-1 infections (AHIs) and two early HIV-1 infections (EHIs) were identified by the new algorithm; the former was missed by old procedure. Compared with the old version, the new algorithm produced fewer WB-indeterminate results (2 vs. 16, p = 0.001), which led to fewer follow-up tests. Therefore, the new HIV testing algorithm is more sensitive for detecting acute HIV-1 infections with maintaining the ability to verify the established HIV-1 infections and can dramatically decrease the greater number of WB-indeterminate specimens.

Keywords: algorithm, diagnosis, HIV, laboratory

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Authors: Doru Anastasiu Popescu, Dan Rădulescu

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In this paper, we determine the similarity of two HTML web applications. We are going to use a genetic algorithm in order to determine the most significant web pages of each application (we are not going to use every web page of a site). Using these significant web pages, we will find the similarity value between the two applications. The algorithm is going to be efficient because we are going to use a reduced number of web pages for comparisons but it will return an approximate value of the similarity. The binary trees are used to keep the tags from the significant pages. The algorithm was implemented in Java language.

Keywords: Tag, HTML, web page, genetic algorithm, similarity value, binary tree

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Authors: Engy Adel Mohamed, Yasser Gamal-Eldin Hegazy

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This paper presents a firefly based algorithm for optimal sizing and allocation of distributed generators for profit maximization. Distributed generators in the proposed algorithm are of photovoltaic and combined heat and power technologies. Combined heat and power distributed generators are modeled as voltage controlled nodes while photovoltaic distributed generators are modeled as constant power nodes. The proposed algorithm is implemented in MATLAB environment and tested the unbalanced IEEE 37-node feeder. The results show the effectiveness of the proposed algorithm in optimal selection of distributed generators size and site in order to maximize the total system profit.

Keywords: distributed generators, firefly algorithm, IEEE 37-node feeder, profit maximization

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Authors: Selcuk Aslan, Dervis Karaboga, Celal Ozturk

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Artificial Bee Colony (ABC) algorithm is one of the most successful swarm intelligence based metaheuristics. It has been applied to a number of constrained or unconstrained numerical and combinatorial optimization problems. In this paper, we presented a parallelized version of ABC algorithm by adapting employed and onlooker bee phases to the Compute Unified Device Architecture (CUDA) platform which is a graphical processing unit (GPU) programming environment by NVIDIA. The execution speed and obtained results of the proposed approach and sequential version of ABC algorithm are compared on functions that are typically used as benchmarks for optimization algorithms. Tests on standard benchmark functions with different colony size and number of parameters showed that proposed parallelization approach for ABC algorithm decreases the execution time consumed by the employed and onlooker bee phases in total and achieved similar or better quality of the results compared to the standard sequential implementation of the ABC algorithm.

Keywords: Artificial Bee Colony algorithm, GPU computing, swarm intelligence, parallelization

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Authors: Vidya Yadav

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Migration is the demographic process that links rural to urban areas, generating or spurring the growth of cities. Evidence shows the role of the city as a production processes. It looks the city as a power of centre, and a centre of change. It has been observed that not only the professionals want to settle down in an urban area but rural labourers are also coming to cities for employment. These are the people who are compelled to migrate to metropolises because of lack of employment opportunities in their place of residence. However, the cities also fail to provide adequate employment because of limited job opportunity creation and capital-intensive industrialization. So these masses of incoming migrants are force to take up whatever employment absorption is available to them particularly in urban informal activities. Ultimately with this informal job they are compelled to stay in the slum areas, which is another form of deprived housing colonies. The paper seeks to examine the evidences of poverty induced migration from rural to urban areas (particularly in urban agglomeration). The present paper utilizes an abundant rich source of census migration data (D-Series) of 1991-2001. Result shows that Mumbai remain as the most attractive place to migrate. The migrants are mainly from the major states like Uttar Pradesh, Bihar, West Bengal, Jharkhand, Odisha, and Rajasthan. Male dominated migration is related mostly for employment and females due to marriages. The picture of occupational absorption of migrants who moved for employment, cross classified with educational status. Result shows that illiterate males are primarily engaged in low grade production processing work. Illiterate’s females engaged in service sectors; but these are actually very low grade services in urban informal sectors in India like maid servants, domestic help, hawkers, vendors or vegetables sellers. Among the higher educational level, a small percentage of males and females got absorbed in professional or clerical work but the percentage has been increased in the period 1991-2001.

Keywords: informal, job, migration, urban

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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The human immunodeficiency virus (HIV) that causes acquired immune deficiency syndrome (AIDS) remains a global cause of morbidity and mortality. It has caused panic since its emergence. Relationships between migration and HIV/AIDS have become complex. In the absence of prospectively designed studies, dynamic mathematical models that take into account the migration movement which will give very useful information. We have explored the utility of mathematical models in understanding transmission dynamics of HIV and AIDS and in assessing the magnitude of how migration has impact on the disease. The model was calibrated to HIV and AIDS incidence data from Malaysia Ministry of Health from the period of 1986 to 2011 using Bayesian analysis with combination of Markov chain Monte Carlo method (MCMC) approach to estimate the model parameters. From the estimated parameters, the estimated basic reproduction number was 22.5812. The rate at which the susceptible individual moved to HIV compartment has the highest sensitivity value which is more significant as compared to the remaining parameters. Thus, the disease becomes unstable. This is a big concern and not good indicator from the public health point of view since the aim is to stabilize the epidemic at the disease-free equilibrium. However, these results suggest that the government as a policy maker should make further efforts to curb illegal activities performed by migrants. It is shown that our models reflect considerably the dynamic behavior of the HIV/AIDS epidemic in Malaysia and eventually could be used strategically for other countries.

Keywords: epidemic model, reproduction number, HIV, MCMC, parameter estimation

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Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

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Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

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Authors: Qiang Zhang, Chun Yuan

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Since the PU (Prediction Unit) decision process is the most time consuming part of the emerging HEVC (High Efficient Video Coding) standardin intra and inter frame coding, this paper proposes the fast PU decision algorithm and speed up the algorithm using CUDA (Compute Unified Device Architecture). In intra frame coding, the fast PU decision algorithm uses the texture features to skip intra-frame prediction or terminal the intra-frame prediction for smaller PU size. In inter frame coding of HEVC, the fast PU decision algorithm takes use of the similarity of its own two Nx2N size PU's motion vectors and the hierarchical structure of CU (Coding Unit) partition to skip some modes of PU partition, so as to reduce the motion estimation times. The accelerate algorithm using CUDA is based on the fast PU decision algorithm which uses the GPU to make the motion search and the gradient computation could be parallel computed. The proposed algorithm achieves up to 57% time saving compared to the HM 10.0 with little rate-distortion losses (0.043dB drop and 1.82% bitrate increase on average).

Keywords: HEVC, PU decision, inter prediction, intra prediction, CUDA, parallel

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Authors: Mengjun Yang, Zhulin Zong, Jie Gao

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In this paper, a new and robust algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework. Traditional CS based methods have to assume that unknown scatters exactly lie on the pre-divided grids; otherwise, their reconstruction performance dropped significantly. In this processing algorithm, several basis shifts are utilized to achieve the same effect as grid refinement does. The detailed implementation of the basis shift algorithm is presented in this paper. From the simulation we can see that using the basis shift algorithm, imaging precision can be improved. The effectiveness and feasibility of the proposed method are investigated by the simulation results.

Keywords: ISAR imaging, sparse reconstruction, off-grid, basis shift

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Authors: G. Obrentri, C. Whajah, E. Yeboah Acheampong

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Professional status for African male players guarantees them socioeconomic benefits that may not necessarily be the case for female footballers. The study’s rationale is to understand how female footballers achieve professional status abroad. That contributes to analyzing how female players from Africa especially, Ghana, manage their professional status to improve their family’s social welfare and the community. Relying on football migration and feminization, we identify their migration process and its relevance to their social mobility in society. Analysis through interviews with some female footballers revealed the importance of playing professional abroad that goes to increase their social status and national identity. Findings show that some female footballers with secondary education achieved career empowerment and social independence via their profession. Thus becoming medical doctors and nurses, sports administrators, football coaches and welfare officers for clubs. These achievements of the female footballers can provide useful information and lessons for young female African players aspiring to play professionally abroad.

Keywords: empowerment, female footballers, football migration, professional status, social independence

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: distributed control, game theory, multi-agent learning, reinforcement learning

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