Search results for: evolutionary cultural algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7494

Search results for: evolutionary cultural algorithm

7044 A Study on the Cultural Landscape of the Living Environment of Hoklo-Hakka: Case Study of Dacun

Authors: Meng-Li Lin, Shang-Hsuan Chiu

Abstract:

Taiwan is a country of diverse ethnic groups, the historical background of each ethnic group is different, and the conflict between them influence on each other, result in Taiwan's multi-culture. The Changhua County in Taiwan is the largest county of Hoklo-Hakka. Hakka people get along with Hoklo people for a long time. There are integration and conflict during that time and makes Hakka people gradually assimilated Hoklo-Hakka people. Today in Changhua Plain area, many Hoklo-Hakka people do not speak Hakka language. Therefore, it has been difficult to find information of Hakka from the Hakka language in the group of Hoklo-Hakka. But in the living space or culture to find relevant historical traces of life could be confirmed in Hakka Culture. In this paper, through the investigation of descent, life field, religion, language and other investigations of the Dacun, Changhua County residents to carry out the analysis of the process of assimilating Hoklo in living cultural landscape. First is through the local literature, the elderly and other oral history stories, to investigate the changes in Dacun field historical. Second, the comparison of collected traditional Hakka culture and the living cultural landscape of Hoklo-Haka are done to explore the differences between the living cultural landscape and the traditional Hakka culture. After analysis Hoklo-Hakka living cultural landscape, the significant differences, we proposed preservation strategy to provide recommendations to save the cultural life of Hoklo-Hakka landscape in future. Changhua Dacun traditional Hakka landscape is disappearing, in this study, we explore and investigate the data of Changhua Dacun Hoklo-Hakka living cultural landscape to analyze and to provide strategic advice to save. Here we have three study purposes. 1. Discuss the Hoklo-Hakka living cultural landscape of Changhua Dacun. 2. Investigate and record the Hoklo-Hakka living cultural landscape. 3. Propose a reserve strategy of the Hoklo-Hakka living cultural landscape in future.

Keywords: Hoklo-Hakka, Dacun, save policy, life Culture

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7043 Adaptive Multipath Mitigation Acquisition Approach for Global Positioning System Software Receivers

Authors: Animut Meseret Simachew

Abstract:

Parallel Code Phase Search Acquisition (PCSA) Algorithm has been considered as a promising method in GPS software receivers for detection and estimation of the accurate correlation peak between the received Global Positioning System (GPS) signal and locally generated replicas. GPS signal acquisition in highly dense multipath environments is the main research challenge. In this work, we proposed a robust variable step-size (RVSS) PCSA algorithm based on fast frequency transform (FFT) filtering technique to mitigate short time delay multipath signals. Simulation results reveal the effectiveness of the proposed algorithm over the conventional PCSA algorithm. The proposed RVSS-PCSA algorithm equalizes the received carrier wiped-off signal with locally generated C/A code.

Keywords: adaptive PCSA, detection and estimation, GPS signal acquisition, GPS software receiver

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7042 Test Suite Optimization Using an Effective Meta-Heuristic BAT Algorithm

Authors: Anuradha Chug, Sunali Gandhi

Abstract:

Regression Testing is a very expensive and time-consuming process carried out to ensure the validity of modified software. Due to the availability of insufficient resources to re-execute all the test cases in time constrained environment, efforts are going on to generate test data automatically without human efforts. Many search based techniques have been proposed to generate efficient, effective as well as optimized test data, so that the overall cost of the software testing can be minimized. The generated test data should be able to uncover all potential lapses that exist in the software or product. Inspired from the natural behavior of bat for searching her food sources, current study employed a meta-heuristic, search-based bat algorithm for optimizing the test data on the basis certain parameters without compromising their effectiveness. Mathematical functions are also applied that can effectively filter out the redundant test data. As many as 50 Java programs are used to check the effectiveness of proposed test data generation and it has been found that 86% saving in testing efforts can be achieved using bat algorithm while covering 100% of the software code for testing. Bat algorithm was found to be more efficient in terms of simplicity and flexibility when the results were compared with another nature inspired algorithms such as Firefly Algorithm (FA), Hill Climbing Algorithm (HC) and Ant Colony Optimization (ACO). The output of this study would be useful to testers as they can achieve 100% path coverage for testing with minimum number of test cases.

Keywords: regression testing, test case selection, test case prioritization, genetic algorithm, bat algorithm

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7041 A Novel Approach of Secret Communication Using Douglas-Peucker Algorithm

Authors: R. Kiruthika, A. Kannan

Abstract:

Steganography is the problem of hiding secret messages in 'innocent – looking' public communication so that the presence of the secret message cannot be detected. This paper introduces a steganographic security in terms of computational in-distinguishability from a channel of probability distributions on cover messages. This method first splits the cover image into two separate blocks using Douglas – Peucker algorithm. The text message and the image will be hided in the Least Significant Bit (LSB) of the cover image.

Keywords: steganography, lsb, embedding, Douglas-Peucker algorithm

Procedia PDF Downloads 332
7040 A Novel Probablistic Strategy for Modeling Photovoltaic Based Distributed Generators

Authors: Engy A. Mohamed, Y. G. Hegazy

Abstract:

This paper presents a novel algorithm for modeling photovoltaic based distributed generators for the purpose of optimal planning of distribution networks. The proposed algorithm utilizes sequential Monte Carlo method in order to accurately consider the stochastic nature of photovoltaic based distributed generators. The proposed algorithm is implemented in MATLAB environment and the results obtained are presented and discussed.

Keywords: comulative distribution function, distributed generation, Monte Carlo

Procedia PDF Downloads 556
7039 Orthogonal Regression for Nonparametric Estimation of Errors-In-Variables Models

Authors: Anastasiia Yu. Timofeeva

Abstract:

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression

Procedia PDF Downloads 385
7038 Discipline-Specific Culture: A Purpose-Based Investigation

Authors: Sihem Benaouda

Abstract:

English is gaining an international identity as it affects every academic and professional field in the world. Without increasing their cultural understanding, it would obviously be difficult to completely educate learners for communication in a globalised environment. The concept of culture is intricate and needs to be elucidated, especially in an English language teaching (ELT) context. The study focuses on the investigation of the cultural studies integrated into the different types of English for specific purposes (ESP) materials, as opposed to English for general purposes (EGP) textbooks. A qualitative methodology based on a triangulation of techniques was conducted through materials analysis of five textbooks in both advanced EGP and three types of ESP. In addition to a semi-structured interview conducted with Algerian ESP practitioners, data analysis results revealed that culture in ESP textbooks is not overtly isolated into chapters and that cultural studies are predominantly present in business and economics materials, namely English for hotel and catering staff, tourism, and flight attendants. However, implicit cultural instruction is signalled in the social sciences and is negligible in science and technology sources. In terms of content, cultural studies in EGP are more related to generic topics, whereas, in some ESP materials, the topics are rather oriented to the specific field they belong to. Furthermore, the respondents’ answers showed an unawareness of the importance of culture in ESP teaching, besides some disregard for culture teaching per se in ESP contexts.

Keywords: ESP, EGP, cultural studies, textbooks, teaching, materials

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7037 LiDAR Based Real Time Multiple Vehicle Detection and Tracking

Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

Abstract:

Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: lidar, segmentation, clustering, tracking

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7036 Chinese Doctoral Students in Canada: The Influence of Financial Status and Cultural Cognition on Academic Performance

Authors: Xuefan Li

Abstract:

Parts of Chinese doctoral students in Canada are facing significant academic pressure. The factors contributing to such pressure are diverse, including financial conditions and cultural differences. Students from various academic disciplines have been interviewed to investigate the factors that Chinese students consider when selecting Canada as a destination for doctoral studies, as well as to identify the challenges they face during their academic pursuits and the associated factors influencing their performance. The findings indicate that their motivations to pursue doctoral study in Canada are concluded as both push and pull factors. Financial conditions and cultural differences are critical factors affecting academic performance, with disciplinary variations in the degree of influence observed.

Keywords: Chinese doctoral students, financial status, cultural cognition, academic performance

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7035 Traditional Management Systems and the Conservation of Cultural and Natural Heritage: Multiple Case Studies in Zimbabwe

Authors: Nyasha Agnes Gurira, Petronella Katekwe

Abstract:

Traditional management systems (TMS) are a vital source of knowledge for conserving cultural and natural heritage. TMS’s are renowned for their ability to preserve both tangible and intangible manifestations of heritage. They are a construct of the intricate relationship that exists between heritage and host communities, where communities are recognized as owners of heritage and so, set up management mechanisms to ensure its adequate conservation. Multiple heritage condition surveys were conducted to assess the effectiveness of using TMS in the conservation of both natural and cultural heritage. Surveys were done at Nharira Hills, Mahwemasimike, Dzimbahwe, Manjowe Rock art sites and Norumedzo forest which are heritage places in Zimbabwe. It assessed the state of conservation of the five case studies and assessed the role that host communities play in the management of these heritage places. It was revealed that TMS’s are effective in the conservation of natural heritage, however in relation to heritage forms with cultural manifestations, there are major disparities. These range from differences in appreciation and perception of value within communities leading to vandalism, over emphasis in the conservation of the intangible element as opposed to the tangible. This leaves the tangible element at risk. Despite these issues, TMS are a reliable knowledge base which enables more holistic conservation approaches for cultural and natural heritage.

Keywords: communities, cultural intangible, tangible heritage, traditional management systems, natural

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7034 Vision Based People Tracking System

Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

Abstract:

In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: camshift algorithm, computer vision, Kalman filter, object tracking

Procedia PDF Downloads 422
7033 Architects Lens on Afrocentric Cultural Approach to Housing

Authors: Aisha Abdulkarim Aliyu, Alice Sabrina Ismail, Fadhlina Binti Ahmad

Abstract:

The study's main goal is to improve Afrocentric cultural approaches in Nigerian residential environments (Kano) in terms of physical, aesthetical, and socio-cultural factors. Kano's fast-changing residential settings and city image have been subjected to a significant neoliberal restructuring process in recent decades. Architects have evolved in lockstep with the society they serve, first as an art form, then as a science, and finally as a business that designs structures. Design values have always emphasized a certain building style throughout history. Architects and architectural critics have a different perspective on them than the general public. In fact, a popular style among the general public was taken into consideration. When it comes to the current design, this study examines the values and viewpoints of architects on the usage of an Afrocentric cultural approach to housing. The qualitative data analysis of surveys conducted with Kano housing and planning professionals is used to determine the criteria for using an Afrocentric cultural approach in housing development in order to preserve and restore our cultural heritage, as well as to rank these criteria according to their importance. The professional lens on this subject differs insignificantly across Nigeria, although they do vary to some amount based on the sector of the housing industry, according to the study.

Keywords: architects lens, Afrocentric culture, housing, northern Nigeria

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7032 Sub-Pixel Mapping Based on New Mixed Interpolation

Authors: Zeyu Zhou, Xiaojun Bi

Abstract:

Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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7031 Review of Hydrologic Applications of Conceptual Models for Precipitation-Runoff Process

Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

Abstract:

The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

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7030 A Radiomics Approach to Predict the Evolution of Prostate Imaging Reporting and Data System Score 3/5 Prostate Areas in Multiparametric Magnetic Resonance

Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

Abstract:

Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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7029 Curating Pluralistic Futures: Leveling up for Whole-Systems Change

Authors: Daniel Schimmelpfennig

Abstract:

This paper attempts to delineate the idea to curate the leveling up for whole-systems change. Curation is the act fo select, organize, look after, or present information from a professional point of view through expert knowledge. The trans-paradigmatic, trans-contextual, trans-disciplinary, trans-perspective of trans-media futures studies hopes to enable a move from a monochrome intellectual pursuit towards breathing a higher dimensionality. Progressing to the next level to equip actors for whole-systems change is in consideration of the commonly known symptoms of our time as well as in anticipation of future challenges, both a necessity and desirability. Systems of collective intelligence could potentially scale regenerative, adaptive, and anticipatory capacities. How could such a curation then be enacted and implemented, to initiate the process of leveling-up? The suggestion here is to focus on the metasystem transition, the bio-digital fusion, namely, by merging neurosciences, the ontological design of money as our operating system, and our understanding of the billions of years of time-proven permutations in nature, biomimicry, and biological metaphors like symbiogenesis. Evolutionary cybernetics accompanies the process of whole-systems change.

Keywords: bio-digital fusion, evolutionary cybernetics, metasystem transition, symbiogenesis, transmedia futures studies

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7028 Caged in Concrete Jungles: Reasserting Cultural Identity and Environmental Sustainability through Material Choice and Design Expression in Architecture

Authors: Ikenna Michael Onuorah

Abstract:

The relentless march of globalization in architecture has led to a homogenization of built environments, often characterized by an overreliance on imported, resource-intensive materials and a disregard for local cultural contexts. This research posits that such practices pose significant environmental and cultural perils, trapping communities in "caged concrete jungles" devoid of both ecological sustainability and a meaningful connection to their heritage. Through a mixed-method approach encompassing quantitative and qualitative data analysis, the study investigated the impacts of neglecting local materials and cultural expression in architectural design. The research is anticipated to yield significant insights into the multifaceted consequences of neglecting locally available materials and cultural expression in architecture. It creates a compelling case for reasserting local materials and cultural expression in architectural design. Based on the anticipated research findings, the study proposed series of actionable recommendations for architects, policymakers, and communities to promote sustainable and culturally sensitive built environments. This will serve as a wake-up call, urging architects, policymakers, and communities to break free from the confines of "caged concrete jungles" and embrace a more sustainable and culturally sensitive approach to design.

Keywords: sustainability, cultural identity, building materials, sustainable dsigns

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7027 The Psychology of Cross-Cultural Communication: A Socio-Linguistics Perspective

Authors: Tangyie Evani, Edmond Biloa, Emmanuel Nforbi, Lem Lilian Atanga, Kom Beatrice

Abstract:

The dynamics of languages in contact necessitates a close study of how its users negotiate meanings from shared values in the process of cross-cultural communication. A transverse analysis of the situation demonstrates the existence of complex efforts on connecting cultural knowledge to cross-linguistic competencies within a widening range of communicative exchanges. This paper sets to examine the psychology of cross-cultural communication in a multi-linguistic setting like Cameroon where many local and international languages are in close contact. The paper equally analyses the pertinence of existing macro sociological concepts as fundamental knowledge traits in literal and idiomatic cross semantic mapping. From this point, the article presents a path model of connecting sociolinguistics to the increasing adoption of a widening range of communicative genre piloted by the on-going globalisation trends with its high-speed information technology machinery. By applying a cross cultural analysis frame, the paper will be contributing to a better understanding of the fundamental changes in the nature and goals of cross-cultural knowledge in pragmatics of communication and cultural acceptability’s. It emphasises on the point that, in an era of increasing global interchange, a comprehensive inclusive global culture through bridging gaps in cross-cultural communication would have significant potentials to contribute to achieving global social development goals, if inadequacies in language constructs are adjusted to create avenues that intertwine with sociocultural beliefs, ensuring that meaningful and context bound sociolinguistic values are observed within the global arena of communication.

Keywords: cross-cultural communication, customary language, literalisms, primary meaning, subclasses, transubstantiation

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7026 Design an Algorithm for Software Development in CBSE Envrionment Using Feed Forward Neural Network

Authors: Amit Verma, Pardeep Kaur

Abstract:

In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there.

Keywords: component based development, clustering, back propagation algorithm, keyword based retrieval

Procedia PDF Downloads 359
7025 Fostering Involvement of Local Inhabitants in Participatory Governance of Cultural Patrimony in Cameroon

Authors: Asah Nelson Asoh, Wanie Clarkson Mvo

Abstract:

Given the diverse nature of cultural diversity in Cameroon from the forested south to the sudano-sahelian north regions, Cameroon is aptly described as 'Africa in Miniature', which simply means all of Africa in a single country-Cameroon. Cameroon possesses all that can be attractive to the eyes in Africa. Yet, there is a microscopic involvement of the local inhabitants in participatory governance of cultural patrimony for tourism and community-based socio-economic development, which greatly jeopardizes conservation endeavors because the community fails to trust governing authorities. This study delves into the ways through which local inhabitants could be indulged in participatory governance of cultural patrimony for tourism and community-based socio-economic development. The study adopts a qualitative research design and semi-structured interviews with experts in the collection of primary data blended with secondary materials from published sources, including textbooks, scientific journal articles, dissertations, reports, and internet websites. The collected data was presented and analysed using descriptive statistical techniques, photographic illustrations, and through intuition. The study fosters the ways through which local inhabitants could be indulged in participatory governance of cultural patrimony for tourism and community-based socio-economic development. This is to ensure community support for the conservation of tourism cultural patrimony in Cameroon in particular and the world at large.

Keywords: participatory governance, cultural patrimony, tourism, socio-economic development, Cameroon

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7024 Efficiency of Grover’s Search Algorithm Implemented on Open Quantum System in the Presence of Drive-Induced Dissipation

Authors: Nilanjana Chanda, Rangeet Bhattacharyya

Abstract:

Grover’s search algorithm is the fastest possible quantum mechanical algorithm to search a certain element from an unstructured set of data of N items. The algorithm can determine the desired result in only O(√N) steps. It has been demonstrated theoretically and experimentally on two-qubit systems long ago. In this work, we investigate the fidelity of Grover’s search algorithm by implementing it on an open quantum system. In particular, we study with what accuracy one can estimate that the algorithm would deliver the searched state. In reality, every system has some influence on its environment. We include the environmental effects on the system dynamics by using a recently reported fluctuation-regulated quantum master equation (FRQME). We consider that the environment experiences thermal fluctuations, which leave its signature in the second-order term of the master equation through its appearance as a regulator. The FRQME indicates that in addition to the regular relaxation due to system-environment coupling, the applied drive also causes dissipation in the system dynamics. As a result, the fidelity is found to depend on both the drive-induced dissipative terms and the relaxation terms, and we find that there exists a competition between them, leading to an optimum drive amplitude for which the fidelity becomes maximum. For efficient implementation of the search algorithm, precise knowledge of this optimum drive amplitude is essential.

Keywords: dissipation, fidelity, quantum master equation, relaxation, system-environment coupling

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7023 An Improved Cuckoo Search Algorithm for Voltage Stability Enhancement in Power Transmission Networks

Authors: Reza Sirjani, Nobosse Tafem Bolan

Abstract:

Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

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7022 An Analysis on Clustering Based Gene Selection and Classification for Gene Expression Data

Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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7021 Unifying RSV Evolutionary Dynamics and Epidemiology Through Phylodynamic Analyses

Authors: Lydia Tan, Philippe Lemey, Lieselot Houspie, Marco Viveen, Darren Martin, Frank Coenjaerts

Abstract:

Introduction: Human respiratory syncytial virus (hRSV) is the leading cause of severe respiratory tract infections in infants under the age of two. Genomic substitutions and related evolutionary dynamics of hRSV are of great influence on virus transmission behavior. The evolutionary patterns formed are due to a precarious interplay between the host immune response and RSV, thereby selecting the most viable and less immunogenic strains. Studying genomic profiles can teach us which genes and consequent proteins play an important role in RSV survival and transmission dynamics. Study design: In this study, genetic diversity and evolutionary rate analysis were conducted on 36 RSV subgroup B whole genome sequences and 37 subgroup A genome sequences. Clinical RSV isolates were obtained from nasopharyngeal aspirates and swabs of children between 2 weeks and 5 years old of age. These strains, collected during epidemic seasons from 2001 to 2011 in the Netherlands and Belgium by either conventional or 454-sequencing. Sequences were analyzed for genetic diversity, recombination events, synonymous/non-synonymous substitution ratios, epistasis, and translational consequences of mutations were mapped to known 3D protein structures. We used Bayesian statistical inference to estimate the rate of RSV genome evolution and the rate of variability across the genome. Results: The A and B profiles were described in detail and compared to each other. Overall, the majority of the whole RSV genome is highly conserved among all strains. The attachment protein G was the most variable protein and its gene had, similar to the non-coding regions in RSV, more elevated (two-fold) substitution rates than other genes. In addition, the G gene has been identified as the major target for diversifying selection. Overall, less gene and protein variability was found within RSV-B compared to RSV-A and most protein variation between the subgroups was found in the F, G, SH and M2-2 proteins. For the F protein mutations and correlated amino acid changes are largely located in the F2 ligand-binding domain. The small hydrophobic phosphoprotein and nucleoprotein are the most conserved proteins. The evolutionary rates were similar in both subgroups (A: 6.47E-04, B: 7.76E-04 substitution/site/yr), but estimates of the time to the most recent common ancestor were much lower for RSV-B (B: 19, A: 46.8 yrs), indicating that there is more turnover in this subgroup. Conclusion: This study provides a detailed description of whole RSV genome mutations, the effect on translation products and the first estimate of the RSV genome evolution tempo. The immunogenic G protein seems to require high substitution rates in order to select less immunogenic strains and other conserved proteins are most likely essential to preserve RSV viability. The resulting G gene variability makes its protein a less interesting target for RSV intervention methods. The more conserved RSV F protein with less antigenic epitope shedding is, therefore, more suitable for developing therapeutic strategies or vaccines.

Keywords: drug target selection, epidemiology, respiratory syncytial virus, RSV

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7020 Community Based Heritage Tourism in the Old City of Nazareth

Authors: Alon Gelbman, Daniel Laven

Abstract:

The paper focuses on a case study of a small-scale heritage tourism venture that seeks to influence tourism development in Nazareth’s old city. This is an exploratory case study that uses qualitative research methods including extensive participant observation and in-depth interviews with the venture’s senior management group and selected employees. Study findings indicate a model of the relationship between community-based tourism development, heritage, and peace-building in a city that has experienced a wide range of cross-cultural conflicts. This model represents an alternative view to the notion that heritage serves to enhance differences and dissonance between different cultural groups. In contrast, findings from this study suggest that heritage in the form of tourism; can help create shared interests between different communities in settings characterized by cross-cultural conflict. This model represents an alternative view to the notion that heritage serves to enhance differences and dissonance between different cultural groups. In contrast, findings from this study suggest that heritage in the form of tourism; can help create shared interests between different communities in settings characterized by cross-cultural conflict.

Keywords: cultural heritage tourism, tourism and peace, community-based tourism, sustainable tourism, cross-cultural conflict, Nazareth historic city

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7019 Meta-Learning for Hierarchical Classification and Applications in Bioinformatics

Authors: Fabio Fabris, Alex A. Freitas

Abstract:

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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7018 Protection of Cultural Heritage against the Effects of Climate Change Using Autonomous Aerial Systems Combined with Automated Decision Support

Authors: Artur Krukowski, Emmanouela Vogiatzaki

Abstract:

The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.

Keywords: 3D modelling, UAS, cultural heritage, preservation

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7017 Reforming Traditional and Cultural Practices in Nigeria for Enhancement and Sustainable Development in the 21st Century: A Case Study of the Jukun People

Authors: Iliya Ibrahim Gimba

Abstract:

Human beings or groups over the world have a traditional and cultural practices which guide and direct their ways of life. They value and promote these practices not minding the attitude of others towards them. In spite of the place of culture which is an embodiment of these practices in every human society some people still reduce the understanding of culture to idolatry and other archaic and anachronistic arts good perhaps only for the museum. Others consider culture to be just drumming and dancing. Whether a culture is “good” or “bad”, civilized or barbaric, it can be reformed for the betterment of the society. Hence, this paper focuses on reforming traditional and cultural practices in Nigeria for enhancing development in the 21st century using the Jukun people as a case study. Relevant literatures from journals, reports, published books among others will be consulted.

Keywords: Jukun, traditional and cultural practices, sustainable development, human

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7016 Ideological Manipulations and Cultural-Norm Constraints

Authors: Masoud Hassanzade Novin, Bahloul Salmani

Abstract:

Translation cannot be considered as a simple linguistic act. Through the rise of descriptive approach in the late 1970s and 1980s, translation process managed to meet the requirements of social aspects as well as linguistic approaches. To have the translation considered as the cross-cultural communication through which various cultures communicate in ideological and cultural constraints, the contrastive analysis was conducted in this paper to reveal the distortions imposed in the translated texts. The corpus of the study involved the novel 1984 written by George Orwell and its Persian translated texts which were analyzed through the qualitative type of the research based on critical discourse analysis (CDA) and Toury's norms as well as Lefever's concepts of ideology. Results of the study revealed the point that ideology and the cultural constraints were considered as an important stimulus which can control the process of the translation.

Keywords: critical discourse analysis, ideology, norms, translated texts

Procedia PDF Downloads 313
7015 An Exact Algorithm for Location–Transportation Problems in Humanitarian Relief

Authors: Chansiri Singhtaun

Abstract:

This paper proposes a mathematical model and examines the performance of an exact algorithm for a location–transportation problems in humanitarian relief. The model determines the number and location of distribution centers in a relief network, the amount of relief supplies to be stocked at each distribution center and the vehicles to take the supplies to meet the needs of disaster victims under capacity restriction, transportation and budgetary constraints. The computational experiments are conducted on the various sizes of problems that are generated. Branch and bound algorithm is applied for these problems. The results show that this algorithm can solve problem sizes of up to three candidate locations with five demand points and one candidate location with up to twenty demand points without premature termination.

Keywords: disaster response, facility location, humanitarian relief, transportation

Procedia PDF Downloads 428