Search results for: image encryption algorithms

Authors: Mawloud Mosbah, Bachir Boucheham

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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN

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Authors: Aticha Kwaengsopha

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The purpose of this research was to study the behaviour and related factors that tourists utilized for making decisions to choose their accommodations at a tourist destination, Bangkontee district, Samut Songkhran Province, Thailand. The independent variables included gender, age, income, occupation, and region, while the three important dependent variables included selection behaviour, factors related selection process, and satisfaction of the accommodation service. A total of 400 Thai and international tourists were interviewed at tourist destination of Bangkontee. A questionnaire was used as the tool for collecting data. Descriptive statistics in this research included percentage, mean, and standard deviation. The findings revealed that the majority of respondents were single, female, and with the age between 23-30 years old. Most of the international tourists were from Asia and planned to stay in Thailand about 1-6 days. In addition, the majority of tourists preferred to travel in small groups of 3 persons. The majority of respondents used internet and word of mouth as the main tool to search for information. The majority of respondents spent most of their budget on food & drink, accommodation, and travelling. Even though the majority of tourists were satisfied with the quality of accommodation, the price range of accommodation, and the image of accommodation and the facilities of the accommodation, they indicated that they were not likely to re-visit Thailand in the near future.

Keywords: behaviour, decision factors, tourists, media engineering

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Authors: K. Berhanu

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Improper land use results in land degradation and decline in agricultural productivity. Hence, in order to get maximum benefits out of land, proper utilization of its resources is inevitable. The present study was aimed at identifying the landcover changes in the study area in the last 25 years and determines the extent and direction of change that has occurred. The study made use of Landsat TM 1986 and 2011 Remote Sensing Satellite Image for analysis to determine the extent and pattern of rangeland change. The results of the landuse/landcover change detection showed that in the last 25 years, 3 major changes were observed, grassland and open shrub-land resource significantly decreased at a rate of 17.1km2/year and 12 km2/year/, respectively. On the other hand in 25 years dense bushland, open bush land, dense shrubland and cultivated land has shown increment in size at a rate of 0.23km2/year,13.5 km2/year, 6.3 km2/year and 0.2 km2/year, respectively within 25 years. The expansion of unpalatable woody species significantly reduced the rangeland size and availability of grasses. The consequence of the decrease in herbaceous biomass production might result in high risk of food insecurity in the area unless proper interventions are made in time.

Keywords: GIS and remote sensing, Dire District, land use/land cover, land sat TM

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Authors: Devadrita Dey Sarkar

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Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.

Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: time history dynamic analysis, basic modal displacement, earthquake-induced demands, shear steel structures

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Authors: Marianna Constantinou, Hana Burianova, Ala Yankouskaya

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Episodic memory retrieval benefits from arousal, with better performance linked to arousing to-be-remembered information. However, the enduring impact of arousal on subsequent memory processes, particularly for non-arousing stimuli, remains unclear. This functional Magnetic Resonance Imaging (fMRI) study examined the effects of arousal on episodic memory processes in young and old adults, focusing on memory of neutral information following arousal exposure. Neural activity was assessed at three distinct timepoints: during exposure to arousing and non-arousing stimuli, memory consolidation (with or without arousing stimulus exposure), and during memory retrieval (with or without arousing stimulus exposure). Behavioural results show that across both age groups, participants performed worse when retrieving episodic memories about a video preceded by a highly arousing negative image. Our fMRI findings reveal three key findings: i) the extension of the influence of negative arousal beyond encoding; ii) the presence of this influence in both young and old adults; iii) and the differential treatment of positive arousal between these age groups. Our findings emphasise valence-specific effects on memory processes and support the enduring impact of negative arousal. We further propose an age-related alteration in the old adult brain in differentiating between positive and negative arousal.

Keywords: episodic memory, ageing, fmri, arousal, valence

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Authors: Silvia Arrate, Waldo Salud, Eloy París

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The wear of cutting tools is one of the most decisive elements when planning tunneling works, programming the maintenance stops and saving the optimum stock of spare parts during the evolution of the excavation. Being able to predict the behavior of cutting tools can give a very competitive advantage in terms of costs and excavation performance, optimized to the needs of the TBM itself. The incredible evolution of data science in recent years gives the option to implement it at the time of analyzing the key and most critical parameters related to machinery with the purpose of knowing how the cutting head is performing in front of the excavated ground. Taking this as a case study, Metro Line 3 of Guadalajara in Mexico will develop the feasibility of using Specific Energy versus data science applied over parameters of Torque, Penetration, and Contact Force, among others, to predict the behavior and status of cutting tools. The results obtained through both techniques are analyzed and verified in the function of the wear and the field situations observed in the excavation in order to determine its effectiveness regarding its predictive capacity. In conclusion, the possibilities and improvements offered by the application of digital tools and the programming of calculation algorithms for the analysis of wear of cutting head elements compared to purely empirical methods allow early detection of possible damage to cutting tools, which is reflected in optimization of excavation performance and a significant improvement in costs and deadlines.

Keywords: cutting tools, data science, prediction, TBM, wear

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: Chiao-Chen Chang, Yang-Chieh Chin

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Social media has created a change in the way the network community is clustered, especially from the location of the community, from the original virtual space to the intertwined network, and thus the communication between people will change from face to face communication to social media-based communication model. However, social media users who have had a fixed engagement may have an intention to switch to another service provider because of the emergence of new forms of social media. For example, some of Facebook or Twitter users switched to Instagram in 2014 because of social media messages or image overloads, and users may seek simpler and instant social media to become their main social networking tool. This study explores the impact of system features overload, information overload, social monitoring concerns, problematic use and privacy concerns as the antecedents on social media fatigue, dissatisfaction, and alternative attractiveness; further influence social media switching. This study also uses the online questionnaire survey method to recover the sample data, and then confirm the factor analysis, path analysis, model fit analysis and mediating analysis with the structural equation model (SEM). Research findings demonstrated that there were significant effects on multiple paths. Based on the research findings, this study puts forward the implications of theory and practice.

Keywords: social media, switching, social media fatigue, alternative attractiveness

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Authors: Amine Rezzoug, Said Abdi, Nadjet Bouhelal, Ismail Daoud

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This paper investigates the application of metallic coatings on high fiber volume fraction carbon/epoxy polymer matrix composites. For the grip of the metallic layer, a method of modifying the surface of the composite by introducing a mixture of copper and steel powder (filler powders) which can reduce the impact of thermal spray particles. The powder was introduced to the surface at the time of the forming. Arc spray was used to project the zinc coating layer. The substrate was grit blasted to avoid poor adherence. The porosity, microstructure, and morphology of layers are characterized by optical microscopy, SEM and image analysis. The samples were studied also in terms of hardness and erosion resistance. This investigation did not reveal any visible evidence damage to the substrates. The hardness of zinc layer was about 25.94 MPa and the porosity was around (∼6.70%). The erosion test showed that the zinc coating improves the resistance to erosion. Based on the results obtained, we can conclude that thermal spraying allows the production of protective coating on PMC. Zinc coating has been identified as a compatible material with the substrate. The filler powders layer protects the substrate from the impact of hot particles and allows avoiding the rupture of brittle carbon fibers.

Keywords: arc spray, coating, composite, erosion

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: Nancy Ibrahim Abdalla, Abdelaziz Karamalla Gaiballa

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Rangelands in semi-arid areas provide a good source for feeding huge numbers of animals and serving environmental, economic and social importance; therefore, these areas are considered economically very important for the pastoral sector in Sudan. This paper investigates the means of differentiating between different rangelands sites according to soil types using principal component analysis to assist in monitoring and assessment purposes. Three rangeland sites were identified in the study area as flat sandy sites, sand dune site, and hard clay site. Principal component analysis (PCA) was used to reduce the number of factors needed to distinguish between rangeland sites and produce a new set of data including the most useful spectral information to run satellite image processing. It was performed using selected types of data (two vegetation indices, topographic data and vegetation surface reflectance within the three bands of MODIS data). Analysis with PCA indicated that there is a relatively high correspondence between vegetation and soil of the total variance in the data set. The results showed that the use of the principal component analysis (PCA) with the selected variables showed a high difference, reflected in the variance and eigenvalues and it can be used for differentiation between different range sites.

Keywords: principal component analysis, PCA, rangeland sites, semi-arid areas, soil types

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Authors: Wei Zhang

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With the rapid development of deep learning, neural network and deep learning algorithms play a significant role in various practical applications. Due to the high accuracy and good performance, Convolutional Neural Networks (CNNs) especially have become a research hot spot in the past few years. However, the size of the networks becomes increasingly large scale due to the demands of the practical applications, which poses a significant challenge to construct a high-performance implementation of deep learning neural networks. Meanwhile, many of these application scenarios also have strict requirements on the performance and low-power consumption of hardware devices. Therefore, it is particularly critical to choose a moderate computing platform for hardware acceleration of CNNs. This article aimed to survey the recent advance in Field Programmable Gate Array (FPGA)-based acceleration of CNNs. Various designs and implementations of the accelerator based on FPGA under different devices and network models are overviewed, and the versions of Graphic Processing Units (GPUs), Application Specific Integrated Circuits (ASICs) and Digital Signal Processors (DSPs) are compared to present our own critical analysis and comments. Finally, we give a discussion on different perspectives of these acceleration and optimization methods on FPGA platforms to further explore the opportunities and challenges for future research. More helpfully, we give a prospect for future development of the FPGA-based accelerator.

Keywords: deep learning, field programmable gate array, FPGA, hardware accelerator, convolutional neural networks, CNN

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Authors: Pariwat Somnuek

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This study focused on tourism logistic services in the border areas of Thailand by an analysis and comparison of the opinions of tourists, villagers, and entrepreneurs of these services. Sample representatives of this study were a total of 600 villagers and 15 entrepreneurs in the three border areas consisting of Chong Anma, Chong Sa-Ngam, and Chong Jom checkpoints. For methodology, survey questionnaires, situation analysis, TOWS matrix, and focus group discussions were used for data collection, as well as descriptive analysis and statistics such as arithmetic means and standard deviations, were employed for data analysis. The findings revealed that business potential was at the medium level and entrepreneurs were satisfied with their turnovers. However, perspectives of transportation and tourism services provided for tourists need to be immediately improved. Recommendations for the potential development included promotion of border tourism destinations and foreign investments into accommodation, restaurants, and transport, as well as the establishment of business networks between Thailand and Cambodia, along with the introduction of new tourism destinations by co-operation between entrepreneurs in both countries. These initiatives may lead to increased visitors, collaboration of security offices, and an improved image of tourism security.

Keywords: business potential, potential development, tourism logistics, services

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Authors: Maria da Conceição Proença

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This case study implements the evaluation of burned areas that suffered successive wildfires in Portugal mainland during the summer of 2017, killing more than 60 people. It’s intended to show that this evaluation can be done with remote sensing data free of charges in a simple laptop, with open-source software, describing the not-so-simple methodology step by step, to make it available for county workers in city halls of the areas attained, where the availability of information is essential for the immediate planning of mitigation measures, such as restoring road access, allocate funds for the recovery of human dwellings and assess further restoration of the ecological system. Wildfires also devastate forest ecosystems having a direct impact on vegetation cover and killing or driving away from the animal population. The economic interest is also attained, as the pinewood burned becomes useless for the noblest applications, so its value decreases, and resin extraction ends for several years. The tools described in this paper enable the location of the areas where took place the annihilation of natural habitats and establish a baseline for major changes in forest ecosystems recovery. Moreover, the result allows the follow up of the surface fuel loading, enabling the targeting and evaluation of restoration measures in a time basis planning.

Keywords: image processing, remote sensing, wildfires, burned areas evaluation, sentinel-2

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Authors: Usman Jilani, Ibad Khurram, Irshad Hussain

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Environmentally sustainable waste management is a challenging task as it involves multiple and diverse economic, environmental, technical and regulatory issues. Municipal Solid Waste Management (MSWM) is more challenging in developing countries like Pakistan due to lack of awareness, technology and human resources, insufficient funding, inefficient collection and transport mechanism resulting in the lack of a comprehensive waste management system. This work presents an overview of current MSWM practices in Peshawar, the provincial capital of Khyber Pakhtunkhwa, Pakistan and proposes a better and sustainable integrated solid waste management system with incineration (Waste to Energy) option. The diverted waste would otherwise generate revenue; minimize land fill requirement and negative impact on the environment. The proposed optimized solution utilizing scientific techniques (like mathematical modeling, optimization algorithms and GIS) as decision support tools enhances the technical & institutional efficiency leading towards a more sustainable waste management system through incorporating: - Improved collection mechanisms through optimized transportation / routing and, - Resource recovery through incineration and selection of most feasible sites for transfer stations, landfills and incineration plant. These proposed methods shift the linear waste management system towards a cyclic system and can also be used as a decision support tool by the WSSP (Water and Sanitation Services Peshawar), agency responsible for the MSWM in Peshawar.

Keywords: municipal solid waste management, incineration, mathematical modeling, optimization, GIS, Peshawar

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Authors: Dong-Hyun Kim, Wan-Ho Chung, Hak-Sung Kim

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In this work, non-destructive evaluation was conducted to measure the sheet resistance of silver nanowire coated film and find a damage of that film using terahertz (THz) wave. Pulse type THz instrument was used, and the measurement was performed under transmission and pitch-catch reflection modes with 30 degree of incidence angle. In the transmission mode, the intensity of the THz wave was gradually increased as the conductivity decreased. Meanwhile, the intensity of THz wave was decreased as the conductivity decreased in the pitch-catch reflection mode. To confirm the conductivity of the film, sheet resistance was measured by 4-point probe station. Interaction formula was drawn from a relation between the intensity and the sheet resistance. Through substituting sheet resistance to the formula and comparing the resultant value with measured maximum THz wave intensity, measurement of sheet resistance using THz wave was more suitable than that using 4-point probe station. In addition, the damage on the silver nanowire coated film was detected by applying the THz image system. Therefore, the reliability of the entire film can be also be ensured. In conclusion, real-time monitoring using the THz wave can be applied in the transparent electrodes with detecting the damaged area as well as measuring the sheet resistance.

Keywords: terahertz wave, sheet resistance, non-destructive evaluation, silver nanowire

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Authors: Rosy Joseph

Abstract:

From an algebraic point of view, Semirings provide the most natural generalization of group theory and ring theory. In the absence of additive inverse in a semiring, one had to impose a weaker condition on the semiring, i.e., the additive cancellative law to study interesting structural properties. In many practical situations, fuzzy numbers are used to model imprecise observations derived from uncertain measurements or linguistic assessments. In this connection, a special class of fuzzy numbers whose shape is symmetric with respect to a vertical line called the symmetric fuzzy numbers i.e., for α ∈ (0, 1] the α − cuts will have a constant mid-point and the upper end of the interval will be a non-increasing function of α, the lower end will be the image of this function, is suitable. Based on this description, arithmetic operations and a ranking technique to order the symmetric fuzzy numbers were dealt with in detail. Wherein it was observed that the structure of the class of symmetric fuzzy numbers forms a commutative semigroup with cancellative property. Also, it forms a multiplicative monoid satisfying sub-distributive property.In this paper, we introduce the algebraic structure, sub-distributive semiring and discuss its various properties viz., ideals and prime ideals of sub-distributive semiring, sub-distributive ring of difference etc. in detail. Symmetric fuzzy numbers are visualized as an illustration.

Keywords: semirings, subdistributive ring of difference, subdistributive semiring, symmetric fuzzy numbers

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Authors: Arezou Hajhashemi, Karim Asgari, Masoud Etemadifar, Maryam Keyvani, Ali Hekmatnia

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Multiple Sclerosis (MS) is one of the most prevalent demyelinating diseases in CNS. As in other chronic cerebral diseases, impairment in cognitive functioning and in memory is popular. Because of the inflammatory and demyelinating nature of the disease, the localization of plaques in different parts of the Prefrontal and Limbic System, may lead to memorial symptoms. This investigation was intended to study relationship between frequency of plaques and memorial symptoms arising from dysfunction limbic system and prefrontal of patients with MS. The sample was selected randomly from patients with MS with memory problem, who have been referred to Isfahan Multiple Sclerosis Society. Brain System Test and Memory Test was administered to the sample, and their MRI's were analyzed by specialist in order to indentify two different parts of plaques. The data was analyzed by SPSS. The results showed that there were significant relationship between MS plaques and prefrontal's dysfunction and memorial symptom related to prefrontal area; however, there were no significant relationship between MS plaques and limbic system's dysfunction and memorial symptoms related to limbic system area. The results of this study suggest that memorial symptoms due to injury regions of the brain have the most significant relationship to prefrontal. Better judgment about these results needs more studies in future.

Keywords: multiple sclerosis, magnetic image, brain injury, behavior disorder

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Authors: Muhammad Shahzad Iqbal, Zobia Sarwar, Salah-ud-Din

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Tomato spotted wilt virus (TSWV) belongs to the genus Tospoviruses (family Bunyaviridae). It is one of the most devastating pathogens of tomato (Solanum Lycopersicum) and heavily damages the crop yield each year around the globe. In this study, we retrieved 329 mature miRNA sequences from two microRNA databases (miRBase and miRSoldb) and checked the putative target sites in the downloaded-genome sequence of TSWV. A consensus of three miRNA target prediction tools (RNA22, miRanda and psRNATarget) was used to screen the false-positive microRNAs targeting sites in the TSWV genome. These tools calculated different target sites by calculating minimum free energy (mfe), site-complementarity, minimum folding energy and other microRNA-mRNA binding factors. R language was used to plot the predicted target-site data. All the genes having possible target sites for different miRNAs were screened by building a consensus table. Out of these 329 mature miRNAs predicted by three algorithms, only eight miRNAs met all the criteria/threshold specifications. MC-Fold and MC-Sym were used to predict three-dimensional structures of miRNAs and further analyzed in USCF chimera to visualize the structural and conformational changes before and after microRNA-mRNA interactions. The results of the current study show that the predicted eight miRNAs could further be evaluated by in vitro experiments to develop TSWV-resistant transgenic tomato plants in the future.

Keywords: tomato spotted wild virus (TSWV), Solanum lycopersicum, plant virus, miRNAs, microRNA target prediction, mRNA

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Authors: H. W. Meerveld, R. H. A. Lindelauf

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In contemporary warfare, data science is crucial for the military in achieving information superiority. Yet, to the authors’ knowledge, no extensive literature survey on data science in military decision-making has been conducted so far. In this study, 156 peer-reviewed articles were analysed through an integrative, semi-systematic literature review to gain an overview of the topic. The study examined to what extent literature is focussed on the opportunities or risks of data science in military decision-making, differentiated per level of war (i.e. strategic, operational, and tactical level). A relatively large focus on the risks of data science was observed in social science literature, implying that political and military policymakers are disproportionally influenced by a pessimistic view on the application of data science in the military domain. The perceived risks of data science are, however, hardly addressed in formal science literature. This means that the concerns on the military application of data science are not addressed to the audience that can actually develop and enhance data science models and algorithms. Cross-disciplinary research on both the opportunities and risks of military data science can address the observed research gaps. Considering the levels of war, relatively low attention for the operational level compared to the other two levels was observed, suggesting a research gap with reference to military operational data science. Opportunities for military data science mostly arise at the tactical level. On the contrary, studies examining strategic issues mostly emphasise the risks of military data science. Consequently, domain-specific requirements for military strategic data science applications are hardly expressed. Lacking such applications may ultimately lead to a suboptimal strategic decision in today’s warfare.

Keywords: data science, decision-making, information superiority, literature review, military

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Authors: Warsa Melles

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This study examines the way second-generation Eritrean immigrants living in the French-speaking part of Switzerland behave linguistically and culturally. The aim of this research is to demonstrate how the participants deal with their bilingualism (Tigrinya and French). More precisely, how does their language use correlates with their socio-cultural attitudes and how do these aspects (re)construct their identity? Data for this research was collected via, questionnaires and semi-structured interviews. Participants were asked to answer questions regarding their linguistic habits, their perception on being bilingual and their cultural identity. The major findings demonstrate that generation 2 relates more with the host country’s language since French is used as the main language in their daily interactions. On the other hand, due to the fact that they have never lived in Eritrea yet were raised by Eritrean born parents in a foreign country, it is more difficult for them to unanimously identify with just one culture. In that sense, intergenerational transmission plays a major role in the perception of identity. All the participants have at least a basic knowledge of Tigrinya, but the use of languages varies according to the purpose. Proficiency in the native language and sense of belonging can be correlated with the frequency of visits to Eritrea. In conclusion, the question of identity in the second-generation Eritrean community cannot be given a categorical and clear-cut answer instead, the new-self image that this social group aims to build is shaped by different factors that are essential to take into consideration.

Keywords: biculturalism, identity, language, migration

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Authors: Vijaya K. Srivastava, Davide Spinello

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This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: constrained integer problems, enumerative search algorithm, Heuristic algorithm, Tunneling algorithm

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Authors: Youssef Mazloum, Haytham Sayah, Maroun Nemer

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The penetration of renewable energy sources into the electric grid is significantly increasing. However, the intermittence of these sources breaks the balance between supply and demand for electricity. Hence, the importance of the energy storage technologies, they permit restoring the balance and reducing the drawbacks of intermittence of the renewable energies. This paper discusses the modeling and the cost-effectiveness of an isobaric adiabatic compressed air energy storage (IA-CAES) system. The proposed system is a combination among a compressed air energy storage (CAES) system with pumped hydro storage system and thermal energy storage system. The aim of this combination is to overcome the disadvantages of the conventional CAES system such as the losses due to the storage pressure variation, the loss of the compression heat and the use of fossil fuel sources. A steady state model is developed to perform an energy and exergy analyses of the IA-CAES system and calculate the distribution of the exergy losses in the latter system. A sensitivity analysis is also carried out to estimate the effects of some key parameters on the system’s efficiency, such as the pinch of the heat exchangers, the isentropic efficiency of the rotating machinery and the pressure losses. The conducted sensitivity analysis is a local analysis since the sensibility of each parameter changes with the variation of the other parameters. Therefore, an exergoeconomic study is achieved as well as a cost optimization in order to reduce the electricity cost produced during the production phase. The optimizer used is OmOptim which is a genetic algorithms based optimizer.

Keywords: cost-effectiveness, Exergoeconomic analysis, isobaric adiabatic compressed air energy storage (IA-CAES) system, thermodynamic modeling

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Authors: Smita Singh

Abstract:

Through the constructivist perspective, this paper explores the transformation of India’s nuclear identity from an irresponsible nuclear weapon power to a ‘de-facto nuclear power’ in the emerging international nuclear order From a nuclear abstainer to a bystander and finally as a ‘de facto nuclear weapon state’, India has put forth its case as a unique and exceptional nuclear power as opposed to Iran, Iraq and North Korea with similar nuclear ambitions, who have been snubbed as ‘rogue states’ by the international community. This paper investigates the reasons behind international community’s gradual acceptance of India’s nuclear weapons capabilities and nuclear identity after the Indo-U.S. Nuclear Deal. In this paper, the central concept of analysis is the inter-subjective nature of identity in the nuclear arena. India’s nuclear behaviour has been discursively constituted by India through evolving images of the ‘self’ and the ‘other.’ India’s sudden heightened global status is not solely the consequence of its 1998 nuclear tests but a calibrated projection as a responsible stakeholder in other spheres such as economic potential, market prospects, democratic credentials and so on. By examining India’s nuclear discourse this paper contends that India has used its material and discursive power in presenting a n striking image as a responsible nuclear weapon power (though not yet a legal nuclear weapon state as per the NPT). By historicising India’s nuclear trajectory through an inter-subjective analysis of identities, this paper moves a step ahead in providing a theoretical interpretation of state actions and nuclear identity construction.

Keywords: nuclear identity, India, constructivism, international stakeholder

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Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

Abstract:

Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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Authors: Aris R. Terzopoulos, Georgia Z. Niolaki, Lynne G. Duncan, Mark A. J. Wilson, Antonios Kyparissiadis, Jackie Masterson

Abstract:

As word databases for bilingual children are not available, researchers, educators and textbook writers must rely on monolingual databases. The aim of this study is thus to develop a bilingual word database, BiLex-kids, an online open access developmental word database for 5-13 year old bilingual children who learn Greek as a second language and have English as their dominant one. BiLex-kids is compiled from 120 Greek textbooks used in Greek-English bilingual education in the UK, USA and Australia, and provides word translations in the two languages, pronunciations in Greek, and psycholinguistic variables (e.g. Zipf, Frequency per million, Dispersion, Contextual Diversity, Neighbourhood size). After clearing the textbooks of non-relevant items (e.g. punctuation), algorithms were applied to extract the psycholinguistic indices for all words. As well as one total lexicon, the database produces values for all ages (one lexicon for each age) and for three age bands (one lexicon per age band: 5-8, 9-11, 12-13 years). BiLex-kids provides researchers with accurate figures for a wide range of psycholinguistic variables, making it a useful and reliable research tool for selecting stimuli to examine lexical processing among bilingual children. In addition, it offers children the opportunity to study word spelling, learn translations and listen to pronunciations in their second language. It further benefits educators in selecting age-appropriate words for teaching reading and spelling, while special educational needs teachers will have a resource to control the content of word lists when designing interventions for bilinguals with literacy difficulties.

Keywords: bilingual children, psycholinguistics, vocabulary development, word databases

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Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

Abstract:

Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

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Authors: Tayyaba Hussain, Sobia Jangsher, Saqib Ali, Saqib Ejaz

Abstract:

Unmanned Aerial vehicles (UAV’s) have gained great popularity due to their remoteness, ease of deployment and high maneuverability in different applications like real-time surveillance, image capturing, weather atmospheric studies, disaster site monitoring and mapping. These applications can involve a real-time communication with the ground station. However, altitude and mobility possess a few challenges for the communication. UAV’s at high altitude usually require more transmit power. One possible solution can be with the use of multi hops (UAV’s acting as relays) and exploiting the mobility pattern of the UAV’s. In this paper, we studied a relay (UAV’s acting as relays) selection for a reliable transmission to a destination UAV. We exploit the mobility information of the UAV’s to propose a Mobility-Aware Relay Selection (MARS) algorithm with the objective of giving improved data rates. The results are compared with Non Mobility-Aware relay selection scheme and optimal values. Numerical results show that our proposed MARS algorithm gives 6% better achievable data rates for the mobile UAV’s as compared with Non MobilityAware relay selection scheme. On average a decrease of 20.2% in data rate is achieved with MARS as compared with SDP solver in Yalmip.

Keywords: mobility aware, relay selection, time division multiple acess, unmanned aerial vehicle

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Authors: Ekaterina Razuvalova, Konstantin Rudenko

Abstract:

In this article the most successful examples of international visual and virtual reconstructions of historical and culture objects, which are based on informative and communicative technologies, are represented. 3D reconstructions can demonstrate outward appearance, visualize different hypothesis, connected to represented object. Virtual reality can give us any daytime and season, any century and environment. We can see how different people from different countries and different era lived; we can get different information about any object; we can see historical complexes in real city environment, which are damaged or vanished. These innovations confirm the fact, that 3D reconstruction is important in museum development. Considering the most interesting examples of visual and virtual reconstructions, we can notice, that visual reconstruction is a 3D image of different objects, historical complexes, buildings and phenomena. They are constant and we can see them only as momentary objects. And virtual reconstruction is some environment with its own time, rules and phenomena. These reconstructions are continuous; seasons, daytime and natural conditions can change there. They can demonstrate abilities of virtual world existence. In conclusion: new technologies give us opportunities to expand the boundaries of museum space, improve abilities of museum expositions, create emotional atmosphere of game immersion, which can interest visitor. Usage of network sources allows increasing the number of visitors and virtual reconstruction opportunities show creative side of museum business.

Keywords: computer technologies, historical reconstruction, museums, museum expositions, virtual reconstruction

Procedia PDF Downloads 327