Search results for: vector diversity

Authors: Adebola Adedugbe

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Agriculture is the mainstay of most countries in Africa. It employs up to 90 percent of the rural workforce, who are mostly youth and women. Engaging youths in Information and Communications Technology (ICT) in agriculture is critical to economic and agricultural development of the African continent. The objective of this paper is to identify and mobilize the potentials of young Africans in agriculture through ICT and recognize their role as the dominant driver for sustainable agricultural development in Africa. This paper identifies the role of ICT as a tool for attracting youths to agriculture. The development of ICT is important in stimulating youths in SME’s to compete favorably and effectively as a way to fight poverty through job and wealth creation. It is one of the strategies for promoting entrepreneurship by increasing the availability and diversity of online information.

Keywords: Africa, agriculture, ICT, tool, youth

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Authors: Hamid Havasi, Mohamad Reza Gholami Dehbalaei, Hamed Khorami, Shahram Karimi, Hamdi Abdi

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Doubly-fed induction generator (DFIG) equipped with a power converter is an efficient tool for converting mechanical energy of a variable speed system to a fixed-frequency electrical grid. Since electrical energy sources faces with production problems such as harmonics caused by nonlinear loads, so in this paper, compensation performance of DPC and FOC method on harmonics reduction of a DFIG wind turbine connected to a nonlinear load in MATLAB Simulink model has been simulated and effect of each method on nonlinear load harmonic elimination has been compared. Results of the two mentioned control methods shows the advantage of the FOC method on DPC method for harmonic compensation. Also, the fifth and seventh harmonic components of the network and THD greatly reduced.

Keywords: DFIG machine, energy conversion, nonlinear load, THD, DPC, FOC

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Authors: Natália Botica, Luís Luís, Paulo Bernardes

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The Côa Valley, listed World Heritage since 1998, presents more than 1300 open-air engraved rock panels. The Archaeological Park of the Côa Valley recorded the rock art motifs, testing various techniques based on direct tracing processes on the rock, using natural and artificial lighting. In this work, integrated in the "Open Access Rock Art Repository" (RARAA) project, we present the methodology adopted for the vectorial drawing of the rock art motifs based on orthophotos taken from the photogrammetric survey and 3D models of the rocks. We also present the information system designed to integrate the vector drawing and the characterization data of the motifs, as well as the open access sharing, in order to promote their reuse in multiple areas. The 3D models themselves constitute a very detailed record, ensuring the digital preservation of the rock and iconography. Thus, even if a rock or motif disappears, it can continue to be studied and even recreated.

Keywords: rock art, archaeology, iron age, 3D models

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Authors: Rabah Haoui

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Hypersonic flows around spatial vehicles during their reentry phase in planetary atmospheres are characterized by intense aerothermodynamics phenomena. The aim of this work is to analyze high temperature flows around an axisymmetric blunt body taking into account chemical and vibrational non-equilibrium for air mixture species and the no slip condition at the wall. For this purpose, the Navier-Stokes equations system is resolved by the finite volume methodology to determine the flow parameters around the axisymmetric blunt body especially at the stagnation point and in the boundary layer along the wall of the blunt body. The code allows the capture of shock wave before a blunt body placed in hypersonic free stream. The numerical technique uses the Flux Vector Splitting method of Van Leer. CFL coefficient and mesh size level are selected to ensure the numerical convergence.

Keywords: hypersonic flow, viscous flow, chemical kinetic, dissociation, finite volumes, frozen and non-equilibrium flow

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Authors: Fariba Sepahvand, Seyed Hassan Moosa-kazemi

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The objective was to determine the population dynamics of Anopheles maculipinnis s.l. in relation to probable malaria transmission. The study was carried out in three villages in Isfahan and charmahal bakhteari provinces of Iran, from April to March 2014. Mosquitoes were collected by Total catch, Human and Animal bait collection. An. maculipinnis play as a dominant vector with exophagic and endophilic behavior. Ovary dissection revealed four dilatations indicate at least 9% of the population can reach to the dangerous age to potentially malaria transmission. Two peaks of blood feeding were observed, 9.00-10.00 P.M, and the 12.00-00.01 A.M. The gonotrophic cycle, survival rate, life expectancy of the species was 4, 0.82 and five days, respectively. Vectorial capacity was measured as 0.028. In conclusion, moderate climatic conditions support the persistence, density and longevity of An maculipinnis s.l. could result in more significant malaria transmission.

Keywords: age determination, Anopheles maculipinnis, center of Iran, Malaria

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Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

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Authors: Yuping Zhang, Teng Ma, Nadia Everaert, Hongfu Zhang

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Supplying dietary fiber during gestation is known to improve the welfare of feed-restricted sows. However, whether high fiber supplementation during pregnancy can improve the performance of sows and their offspring depends on the type, amount, source, etc., in which the solubility plays a key important role. Insoluble fibers have been shown to increase feed intake of sows in lactation, meet the needs of sows for milk production, reduce sow’s weight and backfat loss, and thus improve the performance of sows and their offspring. In this study, we investigated the effect of the addition of fermented feed mulberry (FFM), rich in insoluble fiber, during the whole gestation on the performance of sows and their offspring and explored possible mechanisms by determining serum hormones and fecal microbiota. The FFM-diet contained 25.5% FFM (on dry matter basis) and was compared with the control–diet (CON, corn, and soybean meal diet). The insoluble fiber content of the FFM and CON diet are respectively 29.3% and 19.1%. both groups were allocated 20 multiparous sows, and they are fed different feed allowance to make sure all the sows get the same digestible energy for each day. After farrowing, all sows were fed the same lactation diet ad libitum. The serum estradiol, progesterone concentration, blood glucose, and insulin levels at gestation day 0, 20, and 60 were tested. And also, the composition and differences fecal microbiota at day 60 of gestation were analyzed. Fecal consistency was determined with Bristol stool scale method, those with a score below 3 were counted as constipation The results showed that there was no impact of the FFM treatment on sows’ backfat, bodyweight changes, blood glucose, serum estradiol, and progesterone concentration, litter size, and performance of the offspring(p > 0.05), Except significant decrease in the concentration of insulin in sows’ serum at 60 days of gestation were observed in the FFM group compare to the CON group (P < 0.01). FFM diet also significantly increased feed intake on the first, third, and 21st days of sow lactation. (p < 0.01); The α- and β- diversity and abundance of the microbiota were significant increased (p < 0.01) compared with the CON group, The abundance of Firmicutes and Bacteroidetes were significantly increased, meanwhile the abundances of Spirochetes, Proteobacteria, and Euryarchaeota, were significantly reduced in the feces of the FFM group. We also analyzed the fecal microbiota of constipated sows vs non-constipated sows and found that the diversity and abundance did also differ between these two groups. FFM and CON group < 0.01). The relationship between sow’s constipation and microbiota merits further investigation.

Keywords: fermented feed mulberry, reproductive performance, fecal flora, sow

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Authors: Chirawat Wattanapanich, Hong Wei

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This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Keywords: convolutional image, lower knee, gait

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Authors: Ronit German, Alexandra Beytenbrat

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Although English seems to be prevalent in every sphere of Israeli daily life, not many Israeli students have a sufficient level of writing and speaking in English which is necessary for academic studies. The inadequate level of English among Israeli students is because the sole focus is on teaching reading comprehension, and the need to adapt to the trends of the professional worldwide demands triggered a reform that requires implementing Common European Framework of Reference (CEFR) and English as a Medium of Instruction (EMI) courses in the Israeli academic institutions. However, it will be argued that this reform is challenging to implement. The fact that modern Hebrew is a revived language, and that English is L3 for more than 30% of the population, the diverse social and cultural students’ background, and psychological factors stand in the way of the new reform.

Keywords: CEFR, cultural diversity, EMI courses, English in Israel, reform

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Authors: Anupam Das

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Although financial liberalization has been one of the most important policy prescriptions of international organizations like the World Bank and the IMF, the effect of financial liberalization on economic growth in developing countries is far from unanimous. Since the '80s, South Asian countries made a significant development in liberalization the financial sector. However, due to unavailability of a sufficient number of time series observations, the relationship between economic growth and financial development has not been investigated adequately. We aim to fill this gap by examining time series data of five developing countries from the South Asian region: Bangladesh, India, Pakistan, Sri Lanka, and Nepal. Applying the cointegration tests and Granger causality within the vector error correction model (VECM), we do not find unanimous evidence of financial development on positive economic growth. These results are helpful for developing countries which have been trying to liberalize the financial sector in recent decades.

Keywords: economic growth, financial development, Granger causality, South Asia

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Authors: Hichem Kmimech, Achref Jabeur Telmoudi, Lotfi Nabli

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The estimation of the initial marking minimum (MIM) is a crucial problem in labeled Petri nets. In the case of multiple choices, the search for the initial marking leads to a problem of optimization of the minimum allocation of resources with two constraints. The first concerns the firing sequence that could be legal on the initial marking with respect to the firing vector. The second deals with the total number of tokens that can be minimal. In this article, the MIM problem is solved by the meta-heuristic particle swarm optimization (PSO). The proposed approach presents the advantages of PSO to satisfy the two previous constraints and find all possible combinations of minimum initial marking with the best computing time. This method, more efficient than conventional ones, has an excellent impact on the resolution of the MIM problem. We prove through a set of definitions, lemmas, and examples, the effectiveness of our approach.

Keywords: marking, production system, labeled Petri nets, particle swarm optimization

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Authors: Ronit German, Alexandra Beytenbrat

Abstract:

Although English seems to be prevalent in every sphere of Israeli daily life, not many Israeli students have a sufficient level of writing and speaking in English which is necessary for academic studies. The inadequate level of English among Israeli students, almost the sole focus on teaching reading comprehension, and the need to adapt to the trends of the professional worldwide demands triggered a reform that requires to implement Common European Framework of Reference (CEFR) and English as a Medium of Instruction (EMI) courses in the Israeli academic institutions. However, it will be argued that this reform is challenging to implement. The fact that modern Hebrew is a revived language, and that English is L3 for more than 30% of the population, the diverse social and cultural students’ background, and psychological factors stand in the way of the new reform.

Keywords: CEFR, cultural diversity, EMI courses, English in Israel, reform

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Authors: Geminne Manzano, Porfirio Aliño, Clairecynth Yu, Lilibeth Salvador-Reyes, Viviene Santiago

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Many marine benthic organisms produce secondary metabolites that serve as ecological roles to different biological and environmental factors. The secondary metabolites found in these organisms like algae, sponges, tunicates and worms exhibit variation at different scales. Understanding the chemical variation can be essential in deriving the evolutionary and ecological function of the secondary metabolites that may explain their patterns. Ecological surveys were performed on two collection sites representing from two Philippine marine biogeographic regions – in Oriental Mindoro located on the West Philippine Sea (WPS) and in Zamboanga del Sur located at Celebes Sea (CS), where a total of 39 Xestospongia sp. sponges were collected using SCUBA. The sponge samples were transported to the laboratory for taxonomic identification and chemical analysis. Biological and environmental factors were investigated to determine their relation to the abundance and distribution patterns and its spatial variability of their secondary metabolite production. Extracts were subjected to thin-layer chromatography and anti-proliferative assays to confirm the presence of Renieramycin-M and to test its cytotoxicity. The blue sponges were found to be more abundant on the WPS than in CS. Both the benthic community and the fish community in Oriental Mindoro, WPS and Zamboanga del Sur, CS sites are characterized by high species diversity and abundance and a very high biomass category. Environmental factors like depth and monsoonal exposure were also compared showing that wave exposure and depth are associated with the abundance and distribution of the sponges. Renieramycin-M presence using the TLC profiles between the sponge extracts from WPS and from CS showed differences in the Reniermycin-M presence and the presence of other functional groups were observed between the two sites. In terms of bioactivity, different responses were also exhibited by the sponge extracts coming from the different region. Different responses were also noted on its bioactivity depending on the cell lines tested. Exploring the influence of ecological parameters on the chemical variation can provide deeper chemical ecological insights in the knowledge and their potential varied applications at different scales. The results of this study provide further impetus in pursuing studies into patterns and processes of the chemical diversity of the Philippine blue sponge, Xestospongia sp. and the chemical ecological significance of the coral triangle.

Keywords: chemical ecology, porifera, renieramycin-m, spatial variability, Xestospongia sp.

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Authors: Khairani Omar, Shalinawati Ramli, Nurul Azmawati Mohamed, Zarini Ismail, Nur Syahrina Rahim, Nurul Hayati Chamhuri

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Choosing a career which matches a student’s personality traits is one of the key factors for future work satisfaction. This is because career satisfaction is at the highest when it is in line with one’s personality strength, values and attitudes. Personality traits play a major role in determining the success of a student in the medical course. In the pre-clinical years, medical theories are being emphasized, thus, conscientious students would perform better than those with lower level of this trait. As the emphasis changes in the clinical years during which patient interaction is important, personality traits which involved interpersonal values become more essential for success. The aim of this study was to determine the personality traits of students who had chosen medicine as their career. It was a cross-sectional study conducted at the Islamic Science University of Malaysia. The respondents consisted of 81 students whose age ranged between 20-21 years old. A set of personality assessment inventory index which has been validated for the local context was used to determine the students’ personality traits. The instrument assessed 15 personality traits namely: aggressive, analytical, autonomy, creativity, extrovert, intellectual, motivation, diversity, resiliency, self-criticism, control, helpful, support, structured and achievement. The scores ranged between 1-100%, and they were categorized into low (1-30%), moderate (40-60%) and high scores (70-100%). The respondents were Year 3 pre-clinical medical students and there were more female students (69%) compared to male students (31%). Majority of them were from middle-income families. Approximately 70% of both parents of the respondents had tertiary education. Majority of the students had high scores in autonomy, creativity, diversity, helpful, structured and achievement. In other words, more than 50% of them scored high (70-100%) in these traits. Scoring high in these traits was beneficial for the medical course. For aggressive trait, 54% of them had moderate scores which is compatible for medicine as this indicated an inclination to being assertive. In the analytical and intellectual components, only 40% and 25% had high scores respectively. These results contradicted the usual expectation of medical students whereby they are expected to be highly analytical and intellectual. It would be an added value if the students had high scores in being extrovert as this reflects on good interpersonal values, however, the students had approximately similar scores in all categories of this trait. Being resilient in the medical school is important as the course is difficult and demanding. The students had good scores in this component in which 46% had high scores while 39% had moderate scores. In conclusion, by understanding their personality traits, strengths and weaknesses, the students will have an opportunity to improve themselves in the areas they lack. This will help them to become better doctors in future.

Keywords: career, medical students, medicine, personality traits

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Authors: Luigi Delle Rose, Oliver Fischer, Ahmed Hammad

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In this article, we study the prospects of the proposed Large Hadron electron Collider (LHeC) in the search for heavy neutral scalar particles. We consider a minimal model with one additional complex scalar singlet that interacts with the Standard Model (SM) via mixing with the Higgs doublet, giving rise to an SM-like Higgs boson and a heavy scalar particle. Both scalar particles are produced via vector boson fusion and can be tested via their decays into pairs of SM particles, analogously to the SM Higgs boson. Using multivariate techniques, we show that the LHeC is sensitive to heavy scalars with masses between 200 and 800 GeV down to scalar mixing of order 0.01.

Keywords: beyond the standard model, large hadron electron collider, multivariate analysis, scalar singlet

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Authors: Wu Yiqun, Weng Jiantao

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The human settlements of China are picked up from the land use vector map by interpreting the Thematic Map of 2014. This paper established the sustainable human settlements geographical division evaluation system and division model using GIS. The results show that: The density of human residential areas in China is different, and the density of sustainable human areas is higher, and the west is lower than that in the West. The regional differences of sustainable human settlements are obvious: the north is larger than that the south, the plain regions are larger than those of the hilly regions, and the developed regions are larger than the economically developed regions. The geographical distribution of the sustainable human settlements is measured by the degree of porosity. The degree of porosity correlates with the sustainable human settlement density. In the area where the sustainable human settlement density is high the porosity is low, the distribution is even and the gap between the settlements is low.

Keywords: GIS, geographical division, sustainable human settlements, China

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Authors: Nadia el Atlas, Mohammed el Aroussi, Mohammed Wahbi

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In this paper a novel technique of mass characterization based on robust features-fusion is presented. The proposed method consists of mainly four stages: (a) the first phase involves segmenting the masses using edge information’s. (b) The second phase is to calculate and fuse the most relevant morphological features. (c) The last phase is the classification step which allows us to classify the images into benign and malignant masses. In this step we have implemented Support Vectors Machines (SVM) and Artificial Neural Networks (ANN), which were evaluated with the following performance criteria: confusion matrix, accuracy, sensitivity, specificity, receiver operating characteristic ROC, and error histogram. The effectiveness of this new approach was evaluated by a recently developed database: INBREAST database. The fusion of the most appropriate morphological features provided very good results. The SVM gives accuracy to within 64.3%. Whereas the ANN classifier gives better results with an accuracy of 97.5%.

Keywords: breast cancer, mammography, CAD system, features, fusion

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Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

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Authors: K. Thamizhmaran, Akshaya Devi Arivazhagan, M. Anitha

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On the case of most important systematic issue that must need to be solved in means of implementing a data transmission algorithm on the source of Mobile adhoc networks (MANETs). That is, how to save mobile nodes energy on meeting the requirements of applications or users as the mobile nodes are with battery limited. On while satisfying the energy saving requirement, hence it is also necessary of need to achieve the quality of service. In case of emergency work, it is necessary to deliver the data on mean time. Achieving quality of service in MANETs is also important on while. In order to achieve this requirement, Hence, we further implement the Energy-Aware routing protocol for system of Mobile adhoc networks were it being proposed, that on which saves the energy as on every node by means of efficiently selecting the mode of energy efficient path in the routing process by means of Enhanced AODV routing protocol.

Keywords: Ad-Hoc networks, MANET, routing, AODV, EAODV

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Authors: Saughmon Boujkian

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This study delves into the intricate interplay between semantics and emotional connotation in linguistic expression, focusing on the role of expressive adjectives (EAs). Through a blend of theoretical frameworks from linguistics and computational techniques from natural language processing, native speakers' judgments are curated to capture the nuanced interpretations elicited by EAs in diverse linguistic contexts. Leveraging mathematical tools like least squares analysis, the study translates qualitative linguistic phenomena into quantitative measures, unveiling the differential impact of EAs on sentence sentiment. The derived expressive vectors offer insights into the nature of expressive meaning, underscoring the complex dynamics inherent in linguistic expression. While the study's outcomes provide valuable insights, future research endeavors could explore more sophisticated linguistic models to enhance the accuracy and granularity of expressive vector representations.

Keywords: vectors, expressive meaning, multi-dimentionality, least squares regression

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Authors: Digby Warren, Jiri Kropac

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While aspirations of social justice are often articulated by universities as a “feel good” mantra, what is meant by education for social justice deserves deeper consideration. Based on in-depth interviews with academics (voluntary participants in this research) in different disciplines and institutions in the UK, Czech Republic, and other EU countries, this comparative study presents thematic findings regarding lecturers’ conceptions of education for social justice -what it is, why it is important, why they are personally committed to it, how it connects with their own values- and their practice of it- how it is implemented through curriculum content, teaching and learning activities, and assessment tasks. It concludes by presenting an analysis of the challenges, constraints, and enabling factors in practising social justice education in different subject, institutional and national contexts.

Keywords: higher education, social justice, inclusivity, diversity

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Authors: Rachel Danielson, Brendan Bohannan, S.M. Tsai, Kyle Meyer, Jorge L.M. Rodrigues

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The Amazon Rainforest is a global diversity hotspot and crucial carbon sink, but approximately 20% of its total extent has been deforested- primarily for the establishment of cattle pasture. Understanding the impact of this large-scale disturbance on soil microbial community composition and activity is crucial in understanding potentially consequential shifts in nutrient or greenhouse gas cycling, as well as adding to the body of knowledge concerning how these complex communities respond to human disturbance. In this study, surface soils (0-10cm) were collected from three forests and three 45-year-old pastures in Rondonia, Brazil (the Amazon state with the greatest rate of forest destruction) in order to determine the impact of forest conversion on microbial communities involved in nitrogen fixation. Soil chemical and physical parameters were paired with measurements of microbial activity and genetic profiles to determine how community composition and process rates relate to environmental conditions. Measuring both the natural abundance of 15N in total soil N, as well as incorporation of enriched 15N2 under incubation has revealed that conversion of primary forest to cattle pasture results in a significant increase in the rate of nitrogen fixation by free-living diazotrophs. Quantification of nifH gene copy numbers (an essential subunit encoding the nitrogenase enzyme) correspondingly reveals a significant increase of genes in pasture compared to forest soils. Additionally, genetic sequencing of both nifH genes and transcripts shows a significant increase in the diversity of the present and metabolically active diazotrophs within the soil community. Levels of both organic and inorganic nitrogen tend to be lower in pastures compared to forests, with ammonium rather than nitrate as the dominant inorganic form. However, no significant or consistent differences in total, extractable, permanganate-oxidizable, or loss-on-ignition carbon are present between the two land-use types. Forest conversion is associated with a 0.5- 1.0 unit pH increase, but concentrations of many biologically relevant nutrients such as phosphorus do not increase consistently. Increases in free-living diazotrophic community abundance and activity appear to be related to shifts in carbon to nitrogen pool ratios. Furthermore, there may be an important impact of transient, low molecular weight plant-root-derived organic carbon on free-living diazotroph communities not captured in this study. Preliminary analysis of nitrogenase gene variant composition using NovoSeq metagenomic sequencing indicates that conversion of forest to pasture may significantly enrich vanadium-based nitrogenases. This indication is complemented by a significant decrease in available soil molybdenum. Very little is known about the ecology of diazotrophs utilizing vanadium-based nitrogenases, so further analysis may reveal important environmental conditions favoring their abundance and diversity in soil systems. Taken together, the results of this study indicate a significant change in nitrogen cycling and diazotroph community composition with the conversion of the Amazon Rainforest. This may have important implications for the sustainability of cattle pastures once established since nitrogen is a crucial nutrient for forage grass productivity.

Keywords: free-living diazotrophs, land use change, metagenomic sequencing, nitrogen fixation

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Authors: Sonia Bedhiaf-Romdhani

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The sheep (Ovis aries) was domesticated, approximately 11,000 years ago (YBP), in the Fertile Crescent from Asian Mouflon (Ovis Orientalis). The Northern African (NA) sheep is 7,000 years old, represents a remarkable diversity of sheep populations reared under traditional and low input farming systems (LIFS) over millennia. The majority of small ruminants in developing countries are encountered in low input production systems and the resilience of local communities in rural areas is often linked to the wellbeing of small ruminants. Regardless of the rich biodiversity encountered in sheep ecotypes there are four main sheep breeds in the country with 61,6 and 35.4 percents of Barbarine (fat tail breed) and Queue Fine de l’Ouest (thin tail breed), respectively. Phoenicians introduced the Barbarine sheep from the steppes of Central Asia in the Carthaginian period, 3000 years ago. The Queue Fine de l’Ouest is a thin-tailed meat breed heavily concentrated in the Western and the central semi-arid regions. The Noire de Thibar breed, involving mutton-fine wool producing animals, has been on the verge of extinction, it’s a composite black coated sheep breed found in the northern sub-humid region because of its higher nutritional requirements and non-tolerance of the prevailing harsher condition. The D'Man breed, originated from Morocco, is mainly located in the southern oases of the extreme arid ecosystem. A genetic investigation of Tunisian sheep breeds using a genome-wide scan of approximately 50,000 SNPs was performed. Genetic analysis of relationship between breeds highlighted the genetic differentiation of Noire de Thibar breed from the other local breeds, reflecting the effect of past events of introgression of European gene pool. The Queue Fine de l’Ouest breed showed a genetic heterogeneity and was close to Barbarine. The D'Man breed shared a considerable gene flow with the thin-tailed Queue Fine de l'Ouest breed. Native small ruminants breeds, are capable to be efficiently productive if essential ingredients and coherent breeding schemes are implemented and followed. Assessing the status of genetic variability of native sheep breeds could provide important clues for research and policy makers to devise better strategies for the conservation and management of genetic resources.

Keywords: sheep, farming systems, diversity, SNPs.

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Authors: Jamal Takhchi

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The understanding of vibration propagation in complex structures such as automotive body in white remains a challenging issue in car design regarding NVH performances. The current analysis is limited to the low frequency range where modal concepts are dominant. Higher frequencies, between 200 and 1000 Hz, will become critical With the rise of electrification. EVs annoying sounds are mostly whines created by either Gears or e-motors between 300 Hz and 2 kHz. Structural intensity analysis was Experienced a few years ago on finite element models. The application was promising but limited by the fact that the propagating 3D intensity vector field is masked by a rotational Intensity field. This rotational field should be filtered using a differential operator. The expression of this operator in the framework of finite element modeling is not yet known. The aim of the proposed work is to implement this operator in the current dynamic solver (NASTRAN) of Stellantis and develop the Expected methodology for the mid-frequency structural analysis of electrified vehicles.

Keywords: structural intensity, NVH, body in white, irrotatational intensity

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Authors: Abdulla D. Alblooshi

Abstract:

The stock market is a representation of human behavior and psychology, such as fear, greed, and discipline. Those are manifested in the form of price movements during the trading sessions. Therefore, predicting the stock movement and prices is a challenging effort. However, those trading sessions produce a large amount of data that can be utilized to train an AI agent for the purpose of predicting the stock movement. Predicting the stock market price action will be advantageous. In this paper, the stock movement data of three DFM listed stocks are studied using historical price movements and technical indicators value and used to train an agent using KNN and SVM methods to predict the future price movement. MATLAB Toolbox and a simple script is written to process and classify the information and output the prediction. It will also compare the different learning methods and parameters s using metrics like RMSE, MAE, and R².

Keywords: KNN, ANN, style, SVM, stocks, technical indicators, RSI, MACD, moving averages, RMSE, MAE

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Authors: Colleen Cleveland, W. Adam Baldowski

Abstract:

In the dynamic realm of online education, the integration of games and entertainment has emerged as a powerful strategy to captivate learners, drive active participation, and cultivate meaningful learning experiences. This abstract presents an overview of the upcoming conference, "Game On," dedicated to exploring the transformative impact of gamification, interactive simulations, and multimedia content in the digital learning landscape. Introduction: The conference aims to blur the traditional boundaries between education and entertainment, inspiring learners of diverse ages and backgrounds to actively engage in their online learning journeys. By leveraging the captivating elements of games and entertainment, educators can enhance motivation, retention, and deep understanding among virtual classroom participants. Conference Highlights: Commencing with an exploration of theoretical foundations drawing from educational psychology, instructional design, and the latest pedagogical research, participants will gain valuable insights into the ways gamified elements elevate the quality of online education. Attendees can expect interactive sessions, workshops, and case studies showcasing best practices and innovative strategies, including game-based assessments and virtual reality simulations. Inclusivity and Diversity: The conference places a strong emphasis on inclusivity, accessibility, and diversity in the integration of games and entertainment for educational purposes. Discussions will revolve around accommodating diverse learning styles, overcoming potential challenges, and ensuring equitable access to engaging educational content for all learners. Educational Transformation: Educators, instructional designers, and e-learning professionals attending "Game On" will acquire practical techniques to elevate the quality of their online courses. The conference promises a stimulating and informative exploration of blending education with entertainment, unlocking the untapped potential of games and entertainment in online education. Conclusion: "Game On" invites participants to embark on a journey that transforms online education by harnessing the power of entertainment. This event promises to be a cornerstone in the evolution of virtual learning, offering valuable insights for those seeking to create a more engaging and effective online educational experience. Join us as we explore new horizons, pushing the boundaries of online education through the fusion of games and entertainment.

Keywords: online education, games, entertainment, psychology, therapy, pop culture

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Authors: Vaida Jurgile

Abstract:

Intercultural learning is one of the approaches taken to understand the cultural diversity of the modern world and to accept changes in cultural identity and otherness and the expression of tolerance. During intercultural learning, students develop their abilities to interact and communicate with their group members. These abilities help to understand social and cultural differences, to form one’s identity, and to give meaning to intercultural learning. Intercultural education recognizes that a true understanding of differences and similarities of another culture is necessary in order to lay the foundations for working together with others, which contributes to the promotion of intercultural dialogue, appreciation of diversity, and cultural exchange. Therefore, it is important to examine the concept of intercultural learning, revealed through students’ learning experiences and understanding of how this learning takes place and what significance this phenomenon has in higher education. At a scientific level, intercultural learning should be explored in order to uncover the influence of cultural identity, i.e., intercultural learning should be seen in a local context. This experience would provide an opportunity to learn from various everyday intercultural learning situations. Intercultural learning can be not only a form of learning but also a tool for building understanding between people of different cultures. The research object of the study is the process of intercultural learning. The aim of the dissertation is to develop a grounded theory of the process of learning in an intercultural study environment, revealing students’ learning experiences. The research strategy chosen in this study is a constructivist grounded theory (GT). GT is an inductive method that seeks to form a theory by applying the systematic collection, synthesis, analysis, and conceptualization of data. The targeted data collection was based on the analysis of data provided by previous research participants, which revealed the need for further research participants. During the research, only students with at least half a year of study experience, i.e., who have completed at least one semester of intercultural studies, were purposefully selected for the research. To select students, snowballing sampling was used. 18 interviews were conducted with students representing 3 different fields of sciences (social sciences, humanities, and technology sciences). In the process of intercultural learning, language expresses and embodies cultural reality and a person’s cultural identity. It is through language that individual experiences are expressed, and the world in which Others exist is perceived. The increased emphasis is placed on the fact that language conveys certain “signs’ of communication and perception with cultural value, enabling the students to identify the Self and the Other. Language becomes an important tool in the process of intercultural communication because it is only through language that learners can communicate, exchange information, and understand each other. Thus, in the process of intercultural learning, language either promotes interpersonal relationships with foreign students or leads to mutual rejection.

Keywords: intercultural learning, grounded theory, students, other

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Authors: Jo Rhodes, Peter Lok, Zahra Sadeghinejad

Abstract:

The aim of this study is to determine the impact of metacognition on top management team members and firm performance based on full team integration. A survey of 1500 small to medium enterprises (SMEs) was initiated and 140 firms were obtained in this study (with response rate of 9%). The result showed that different metacognitive abilities of managers [knowledge and experience] could enhance team decision-making and problem solving, resulting in greater firm performance. This is a significant finding for SMEs because these organisations have small teams with owner leadership and entrepreneurial orientation.

Keywords: metacognition, behavioural integration, top management team (TMT), performance

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Authors: Nadia Chagtmi, Nejla Rejab, Noureddine Boulejfen

Abstract:

This paper presents a calibration approach based on artificial neural networks (ANN) to determine the envelop signal (I+jQ) of a six-port based receiver (SPR). The memory effects called also dynamic behavior and the nonlinearity brought by diode based power detector have been taken into consideration by the ANN. Experimental set-up has been performed to validate the efficiency of this method. The efficiency of this approach has been confirmed by the obtained results in terms of waveforms. Moreover, the obtained error vector magnitude (EVM) and the mean absolute error (MAE) have been calculated in order to confirm and to test the ANN’s performance to achieve I/Q recovery using the output voltage detected by the power based detector. The baseband signal has been recovered using ANN with EVMs no higher than 1 % and an MAE no higher than 17, 26 for the SPR excited different type of signals such QAM (quadrature amplitude modulation) and LTE (Long Term Evolution).

Keywords: six-port based receiver; calibration, nonlinearity, memory effect, artificial neural network

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Authors: Farshideh Einsele, Hassan Foroosh

Abstract:

In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using wellknown geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: camera-based OCR, feature extraction, document, image processing, grocery products

Procedia PDF Downloads 394