Search results for: mobile Ad Hoc networks

Authors: Cathal Ffrench, Ryan Barrett, Mike Quayle

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It is accepted in social psychology that categorization leads to ingroup favoritism, without further thought given to the processes that may co-occur or even precede categorization. These categorizations move away from the conceptualization of the self as a unique social being toward an increasingly collective identity. Subsequently, many individuals derive much of their self-evaluations from these collective identities. The seminal literature on this topic argues that it is primarily categorization that evokes instances of ingroup favoritism. Apropos to these theories, we argue that categorization acts to enhance and further intergroup processes rather than defining them. More accurately, we propose categorization aids initial ingroup contact and this first contact is predictive of subsequent favoritism on individual and collective levels. This analysis focuses on Virtual Interaction APPLication (VIAPPL) based studies, a software interface that builds on the flaws of the original minimal group studies. The VIAPPL allows the exchange of tokens in an intra and inter-group manner. This token exchange is how we classified the first contact. The study involves binary longitudinal analysis to better understand the subsequent exchanges of individuals based on who they first interacted with. Studies were selected on the criteria of evidence of explicit first interactions and two-group designs. Our findings paint a compelling picture in support of a motivated contact hypothesis, which suggests that an individual’s first motivated contact toward another has strong predictive capabilities for future behavior. This contact can lead to habit formation and specific favoritism towards individuals where contact has been established. This has important implications for understanding how group conflict occurs, and how intra-group individual bias can develop.

Keywords: categorization, group dynamics, initial contact, minimal social networks, momentary contact

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Authors: Pinal Patel

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The study defines the problems and issues of women in Maoist groups, also referred as ‘Naxalites’, in Chhattisgarh, India. It analyses the causes and consequences of increasing number of women joining Maoists groups and measures taken by the central and state government to retreat them. The main aspect of the study is, how to counter the challenges to resolve the issues and restore normalcy in the life of women Maoists to resettle them in mainstream once they become physically inactive and wish to become part of the society. The rationale behind this study is that women Maoists once inactive, has no place either with Maoist camps/rebel groups or particularly in society. The problems faced by the women Maoists, in society as well as in Maoists camps, can be studied through social, economic, cultural, political and humanitarian aspects. The methodology of the study is dependent on primary sources of information which includes a research survey in majorly affected areas, statistical analysis. Secondary sources of information are helpful for understanding the background of the problem. Government’s strategy of rewarding with cash and providing resettlement and rehabilitation benefits including houses and jobs to ex-women Maoists and their families is a well formulated and feasible policy and effectively implemented by the concerned authorities. But, the survey results show that the policy has not been able to have impacts as it was intended. Because inactive and physically disabled women are still left deserted in deep forests to die and police or authorities are not able to reach them and bring them back. The difficult terrain and dense forest areas are major hurdles to reach to Maoists camps. Moreover, to make people aware of government’s surrendering and rehabilitation schemes and policies as communication networks are very poor due to the lack of development in the state.

Keywords: maoists, women, government, policy

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Authors: Vijay Kumar Singh, Pooja Kushwaha, Prabhat Ranjan, Krishna Kumar Ojha, Jitendra Kumar

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Present day high-throughput genomic technologies, NGS/microarrays, are producing large volume of data that require improved analysis methods to make sense of the data. The correlation between genes and samples has been regularly used to gain insight into many biological phenomena including, but not limited to, co-expression/co-regulation, gene regulatory networks, clustering and pattern identification. However, presence of outliers and violation of assumptions underlying Pearson correlation is frequent and may distort the actual correlation between the genes and lead to spurious conclusions. Here, we report a method to measure the strength of association between genes. The method assumes that the expression values of a gene are Bernoulli random variables whose outcome depends on the sample being probed. The method considers the two genes as uncorrelated if the number of sample with same outcome for both the genes (Ns) is equal to certainly expected number (Es). The extent of correlation depends on how far Ns can deviate from the Es. The method does not assume normality for the parent population, fairly unaffected by the presence of outliers, can be applied to qualitative data and it uses the binomial distribution to assess the significance of association. At this stage, we would not claim about the superiority of the method over other existing correlation methods, but our method could be another way of calculating correlation in addition to existing methods. The method uses binomial distribution, which has not been used until yet, to assess the significance of association between two variables. We are evaluating the performance of our method on NGS/microarray data, which is noisy and pierce by the outliers, to see if our method can differentiate between spurious and actual correlation. While working with the method, it has not escaped our notice that the method could also be generalized to measure the association of more than two variables which has been proven difficult with the existing methods.

Keywords: binomial distribution, correlation, microarray, outliers, transcriptome

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Mengwei Li

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Since the 1990s, biennials, and large-scale transnational art exhibitions, have proliferated exponentially across the globe, particularly in Asia, Africa, and Latin America. It has spurred debates regarding the inclusion of "new art cultures" and the deconstruction of the mechanism of exclusion embedded in the Western monopoly on art. Hans Belting introduced the concept of "global art" in 2013 to denounce the West's privileged canons in art by emphasising the inclusion of art practices from alleged non-Western regions. Arguably, the rise of new biennial networks developed by these locations has contributed to the asserted "inclusion of new art worlds." However, phrases such as "non-Western" and "beyond Euro-American" attached to these discussions raise the question of non- or beyond- in relation to whom. In this narrative, to become "integrated" and "equal" implies entry into the "core," a universal system in which preexisting authoritative voices define "newcomers" by what they are not. Possibly, if there is a global biennial system that symbolises a "universal language" of the contemporary art world, it is centered on the inherently dynamic yet asymmetrical interaction and negotiation between the "core" and the rest of the world's "periphery." Engaging with theories of "minor literature" developed by Deleuze and Guattari, this research proposes an epistemological framework to comprehend the global biennial discourse since the 1990s. Using this framework, this research looks at two biennial models in China: the 13th Shanghai Biennale, which was organised in the country's metropolitan art centre, and the 2nd Yinchuan Biennale, which was inaugurated in a geographically and economically marginalised city compared to domestic centres. By analysing how these two biennials from different locations in China positioned themselves and conveyed their local profiles through the universal language of the biennial, this research identifies a potential "minor" positionality within the global biennial discourse from China's perspective.

Keywords: biennials, China, contemporary, global art, minor literature

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Authors: Marion Billard

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This paper will focus on the question of the real relationship between young people and fake news. Fake news is one of today’s main issues in the world of information and communication. Social media and its democratization helped to spread false information. According to traditional beliefs, young people are more inclined to believe what they read through social media. But, the individuals concerned, think that they are more inclined to make a distinction between real and fake news. This phenomenon is due to their use of the internet and social media from an early age. During the 2016 and 2017 French and American presidential campaigns, the term fake news was in the mouth of the entire world and became a real issue in the field of information. While young people were informing themselves with newspapers or television until the beginning of the ’90s, Gen Z (meaning people born between 1997 and 2010), has always been immersed in this world of fast communication. They know how to use social media from a young age and the internet has no secret for them. Today, despite the sporadic use of traditional media, young people tend to turn to their smartphones and social networks such as Instagram or Twitter to stay abreast of the latest news. The growth of social media information led to an “ambient journalism”, giving access to an endless quantity of information. Waking up in the morning, young people will see little posts with short texts supplying the essential of the news, without, for the most, many details. As a result, impressionable people are not able to do a distinction between real media, and “junk news” or Fake News. This massive use of social media is probably explained by the inability of the youngsters to find connections between the communication of the traditional media and what they are living. The question arises if this over-confidence of the young people in their ability to distinguish between accurate and fake news would not make it more difficult for them to examine critically the information. Their relationship with media and fake news is more complex than popular opinion. Today’s young people are not the master in the quest for information, nor inherently the most impressionable public on social media.

Keywords: fake news, youngsters, social media, information, generation

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

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Authors: J. K. Visser, H. T. Malan

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A need exists to identify the sources of risks associated with the process automation systems within petrochemical companies or similar energy related industries. These companies use many different process automation technologies in its value chain. A crucial part of the process automation system is the information technology component featuring in the supervisory control layer. The ever-changing technology within the process automation layers and the rate at which it advances pose a risk to safe and predictable automation system performance. The age of the automation equipment also provides challenges to the operations and maintenance managers of the plant due to obsolescence and unavailability of spare parts. The main objective of this research was to determine the risk sources associated with the equipment that is part of the process automation systems. A secondary objective was to establish whether technology managers and technicians were aware of the risks and share the same viewpoint on the importance of the risks associated with automation systems. A conceptual model for risk sources of automation systems was formulated from models and frameworks in literature. This model comprised six categories of risk which forms the basis for identifying specific risks. This model was used to develop a questionnaire that was sent to 172 instrument technicians and technology managers in the company to obtain primary data. 75 completed and useful responses were received. These responses were analyzed statistically to determine the highest risk sources and to determine whether there was difference in opinion between technology managers and technicians. The most important risks that were revealed in this study are: 1) the lack of skilled technicians, 2) integration capability of third-party system software, 3) reliability of the process automation hardware, 4) excessive costs pertaining to performing maintenance and migrations on process automation systems, and 5) requirements of having third-party communication interfacing compatibility as well as real-time communication networks.

Keywords: distributed control system, identification of risks, information technology, process automation system

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Authors: Ronald Villamar-Torres, Michael Staudt, Christopher Viot

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Cotton Gossypium hirsutum L. is one of the most important industrial crops, producing the world leading natural textile fiber, but is very prone to arthropod attacks that reduce crop yield and quality. Cotton cultivation, therefore, makes an outstanding use of chemical pesticides. In reaction to herbivorous arthropods, cotton plants nevertheless show natural defense reactions, in particular through volatile organic compounds (VOCs) emissions. These natural defense mechanisms are nowadays underutilized but have a very high potential for cotton cultivation, and elucidating their genetic bases will help to improve their use. Simulating herbivory attacks by mechanical wounding of cotton plants in greenhouse, we studied by qPCR the changes in gene expression for genes of the terpenoids biosynthesis pathway. Differentially expressed genes corresponded to higher levels of the terpenoids biosynthesis pathway and not to enzymes synthesizing particular terpenoids. The genes were mapped on the G. hirsutum L. reference genome; their global relationships inside the general metabolic pathways and the biosynthesis of secondary metabolites were visualized with iPath2. The chromatographic profiles of VOCs emissions indicated first monoterpenes and sesquiterpenes emissions, dominantly four molecules known to be involved in plant reactions to arthropod attacks. As a result, the study permitted to identify potential key genes for the emission of volatile terpenoids by cotton plants in reaction to an arthropod attack, opening possibilities for molecular-assisted cotton breeding in benefit of smallholder cotton growers.

Keywords: biosynthesis pathways, cotton, mechanisms of plant defense, terpenoids, volatile organic compounds

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Saddam Husain Dhobi, Bikrant Karki

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The main objective of this paper is save money, balance ecosystem of the terrestrial organism, control global warming, and enhancing the storage capacity of the battery with requiring weight and thinness by using Cyanobacteria in the battery. To fulfill this purpose of paper we can use different methods: Analysis, Biological, Chemistry, theoretical and Physics with some engineering design. Using this different method, we can produce the special type of battery that has the long life, high storage capacity, and clean environment, save money so on and by using the byproduct of Cyanobacteria i.e. glucose. Cyanobacteria are a special type of bacteria that produces different types of extracellular glucoses and oxygen with the help of little sunlight, water, and carbon dioxide and can survive in freshwater, marine and in the land as well. In this process, O₂ is more in the comparison to plant due to rapid growth rate of Cyanobacteria. The required materials are easily available in this process to produce glucose with the help of Cyanobacteria. Since CO₂, is greenhouse gas that causes the global warming? We can utilize this gas and save our ecological balance and the byproduct (glucose) C₆H₁₂O₆ can be utilized for raw material for the battery where as O₂ escape is utilized by living organism. The glucose produce by Cyanobateria goes on Krebs's Cycle or Citric Acid Cycle, in which glucose is complete, oxidizes and all the available energy from glucose molecule has been release in the form of electron and proton as energy. If we use a suitable anodes and cathodes, we can capture these electrons and protons to produce require electricity current with the help of byproduct of Cyanobacteria. According to "Virginia Tech Bio-battery" and "Sony" 13 enzymes and the air is used to produce nearly 24 electrons from a single glucose unit. In this output power of 0.8 mW/cm, current density of 6 mA/cm, and energy storage density of 596 Ah/kg. This last figure is impressive, at roughly 10 times the energy density of the lithium-ion batteries in your mobile devices. When we use Cyanobacteria in battery, we are able to reduce Carbon dioxide, Stop global warming, and enhancing the storage capacity of battery more than 10 times that of lithium battery, saving money, balancing ecology. In this way, we can produce energy from the Cyanobacteria and use it in battery for different benefits. In addition, due to the mass, size and easy cultivation, they are better to maintain the size of battery. Hence, we can use Cyanobacteria for the battery having suitable size, enhancing the storing capacity of battery, helping the environment, portability and so on.

Keywords: anode, byproduct, cathode, cyanobacteri, glucose, storage capacity

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Authors: David Cobham

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In higher education, a great degree of importance is placed on the internationalization of the student experience. This is seen as a valuable contributor to elements such as building confidence, broadening knowledge, creating networks and connections, and enhancing employability for current students who will become the next generation of managers in technology and business. The COVID-19 pandemic has affected all areas of people’s lives. The limitations of travel coupled with the fears and concerns generated by the health risks have dramatically reduced the opportunity for students to engage with this agenda. Institutions of higher education have been required to rethink fundamental aspects of their business model from recruitment and enrolment through learning approaches, assessment methods, and the pathway to employment. This paper presents a case study which focuses on student mobility and how the physical experience of being in another country, either to study, to work, to volunteer or to gain cultural and social enhancement, has of necessity been replaced by alternative approaches. It considers trans-national education as an alternative to physical study overseas, virtual mobility and internships as an alternative to international work experience, and adopting collaborative online projects as an alternative to in-person encounters. The paper concludes that although these elements have been adopted to address the current situation, the lessons learned and the feedback gained suggests that they have contributed successfully in new and sometimes unexpected ways and that they will persist beyond the present to become part of the 'new normal' for the future. That being the case, senior leaders of institutions of higher education will be required to revisit their international plans and to rewrite their international strategies to take account of and build upon these changes.

Keywords: higher education management, internationalization, transnational education, virtual mobility

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Authors: Daniela Gnarini

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This paper aims to contribute to the field of immigrants' entrepreneurial performance. The debate on immigrant entrepreneurship has been dominated by cultural explanations, which argue that immigrants’ entrepreneurial results are linked to groups’ characteristics. However, this approach does not consider important dimensions that influence entrepreneurial performances. Furthermore, cultural theories do not take into account the huge differences in performances also within the same ethnic group. For these reason, this study adopts a biographical approach, both at theoretical and at methodological level, which can allow to understand the main aspects that make the difference in immigrants' entrepreneurial performances, by exploring the narratives of immigrant entrepreneurs, who operate in the restaurant sector in two different Italian metropolitan areas: Milan and Rome. Through the qualitative method of biographical interviews, this study analyses four main dimensions and their combinations: a) individuals' entrepreneurial and migratory path: this aspect is particularly relevant to understand the biographical resources of immigrant entrepreneurs and their change and evolution during time; b) entrepreneurs' social capital, with a particular focus on their networks, through the adoption of a transnational perspective, that takes into account both the local level and the transnational connections. This study highlights that, though entrepreneurs’ connections are significant, especially as far as those with family members are concerned, often their entrepreneurial path assumes an individualised trajectory. c) Entrepreneurs' human capital, including both formal education and skills acquired through informal channels. The latter are particularly relevant since in the interviews and data collected the role of informal transmission emerges. d) Embeddedness within the social, political and economic context, to understand the main constraints and opportunities both at local and national level. The comparison between two different metropolitan areas within the same country helps to understand this dimension.

Keywords: biographies, immigrant entrepreneurs, life stories, performance

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Piero Favino, Luca Preis

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A settlement strategy is to anticipate and respond the needs of existing and future communities through the provision of primary health care facilities in marginalized areas. Access to a health care network is important to improving healthcare coverage, often lacking, in developing countries. The study explores that a good sanitary system strategy of rural contexts brings advantages to an existing settlement: improving transport, communication, water and social facilities. The objective of this paper is to define a possible methodology to implement primary health care facilities in disadvantaged areas of emerging countries. In this research, we analyze the case study of Lauro de Freitas, a municipality in the Brazilian state of Bahia, part of the Metropolitan Region of Salvador, with an area of 57,662 km² and 194.641 inhabitants. The health localization system in Lauro de Freitas is an integrated process that involves not only geographical aspects, but also a set of factors: population density, epidemiological data, allocation of services, road networks, and more. Data were collected also using semi-structured interviews and questionnaires to the local population. Synthesized data suggest that moving away from the coast where there is the greatest concentration of population and services, a network of primary health care facilities is able to improve the living conditions of small-dispersed communities. Based on the health service needs of populations, we have developed a methodological approach that is particularly useful in rural and remote contexts in emerging countries.

Keywords: healthcare, settlement strategy, urban health, rural

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Authors: Minwuyelet Maru, Solomon Habtemariam, Endalamaw Gadissa, Abraham Aseffa

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Background: Tuberculosis is a major public health problem in Ethiopia. The burden of TB is aggravated by emergence and expansion of drug resistant tuberculosis and different lineages of Mycobacterium tuberculosis (M. tuberculosis) have been reported in many parts of the country. Describing strains of Mycobacterial isolates and drug susceptibility pattern is necessary. Method: Sputum samples were collected from smear positive pulmonary TB patients age >= 7 years between October 1, 2012 to September 30, 2013 and Mycobacterial strains isolated on Loweensten Jensen (LJ) media. Each strain was characterized by deletion typing and Spoligotyping. Drug sensitivity testing was determined with the indirect proportion method using Middle brook 7H10 media and association to determine possible risk factors to drug resistance was done. Result: A total of 144 smear positive pulmonary tuberculosis patients were enrolled. The age of participants ranged from 7 to 78 with mean age of 29.22 (±10.77) years. In this study 82.2% (n=97) of the isolates were sensitive to the four first line anti-tuberculosis drugs and resistance to any of the four drugs tested was 17.8% (n=21). A high frequency of any resistance was observed in isoniazid, 13.6%, (n=16) followed by streptomycin, 11.8% (n=14). No significant association of isoniazid resistance with HIV, sex and history of previous TB treatment was observed but there was significant association with age, high between 31-35 years of age (p=0.01). Majority, 89.9% (n=128) of participants were new cases and only 11.1% (n=16) had history of previous TB treatment. No MDR-TB from new cases and 2 MDRTB (13.3%) was isolated from re-treatment cases which was significantly associated with previous TB treatment (p<0.01). Thirty two different types of spoligotype patterns were identified and 74.1% were grouped in to 13 clusters. The dominant strains were SIT 25, 18.1% (n=21), SIT 53, 17.2% (n=20) and SIT 149, 8.6% (n=10). Lineage 4 is the predominant lineage followed by lineage 3 and lineage 7 comprising 65.5% (n=76), 28.4% (n=33) and 6% (n=7) respectively. Majority of strains from lineage 3 and 4 were SIT 25 (63.6%) and SIT 53 (26.3%) whereas SIT 343 was the dominant strain from lineage 7 (71.4%). Conclusion: Wide spread of lineage 3 and lineage 4 of the modern lineage and high number of strain cluster indicates high ongoing transmission. The high proportion resistance to any of the first line anti-tuberculosis drugs may be a potential source in the emergence of MDR-TB. Wide spread of SIT 25 and SIT 53 having a tendency of ease transmission and presence of higher resistance of isoniazid in working and mobile age group, 31-35 years of age may increase risk of drug resistant strains transmission.

Keywords: tuberculosis, drug susceptibility, strain diversity, lineage, Ethiopia, spoligotyping

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Authors: Joy Ghosh, Debasmita Biswas

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The road network of any area is the most important indicator of regional planning. For proper utilization of urban road networks, the structural parameters such as connectivity and accessibility should be analyzed and evaluated. This paper aims to explain the application of GIS on urban road network connectivity and accessibility analysis with a case study of Chandannagar City. This paper has been made to analyze the road network connectivity through various connectivity measurements like the total number of nodes and links, Cyclomatic Number, Alpha Index, Beta Index, Gamma index, Eta index, Pi index, Theta Index, and Aggregated Transport Score, Road Density based on existing road network in Chandannagar city in India. Accessibility is measured through the shortest Path Matrix, associate Number, and Shimbel Index. Various urban services, such as schools, banks, Hospitals, petrol pumps, ATMs, police stations, theatres, parks, etc., are considered for the accessibility analysis for each ward. This paper also highlights the relationship between urban land use/ land cover (LULC) and urban road network and population density using various spatial and statistical measurements. The datasets were collected through a field survey of 33 wards of the Chandannagar Municipal Corporation area, and the secondary data were collected through an open street map and satellite image of LANDSAT8 OLI & TIRS from USGS. Chandannagar was actually once a French colony, and at that time, various sort of planning was applied, but now Chandannagar city continues to grow haphazardly because that city is facing some problems; the knowledge gained from this paper helps to create a more efficient and accessible road network. Therefore, it would be suggested that some wards need to improve their connectivity and accessibility for the future growth and development of Chandannagar.

Keywords: accessibility, connectivity, transport, road network

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Authors: Semanur Soyyigit Kaya, Ercan Eren

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Energy has a prominent role for development of nations. Countries which have energy resources also have strategic power in the international trade of energy since it is essential for all stages of production in the economy. Thus, it is important for countries to analyze the weakness and strength of the system. On the other side, it is commonly believed that international trade has complex network properties. Complex network is a tool for the analysis of complex systems with heterogeneous agents and interaction between them. A complex network consists of nodes and the interactions between these nodes. Total properties which emerge as a result of these interactions are distinct from the sum of small parts (more or less) in complex systems. Thus, standard approaches to international trade are superficial to analyze these systems. Network analysis provides a new approach to analyze international trade as a network. In this network countries constitute nodes and trade relations (export or import) constitute edges. It becomes possible to analyze international trade network in terms of high degree indicators which are specific to complex systems such as connectivity, clustering, assortativity/disassortativity, centrality, etc. In this analysis, international trade of crude oil and coal which are types of fossil fuel has been analyzed from 2005 to 2014 via network analysis. First, it has been analyzed in terms of some topological parameters such as density, transitivity, clustering etc. Afterwards, fitness to Pareto distribution has been analyzed. Finally, weighted HITS algorithm has been applied to the data as a centrality measure to determine the real prominence of countries in these trade networks. Weighted HITS algorithm is a strong tool to analyze the network by ranking countries with regards to prominence of their trade partners. We have calculated both an export centrality and an import centrality by applying w-HITS algorithm to data.

Keywords: complex network approach, fossil fuel, international trade, network theory

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Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

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In this work, we have described a new 3-dimensional (3D) network of cross-linked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: redox enzyme, nanomaterials, biosensors, electrical communication

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Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

Abstract:

In this work, we have described a new 3-dimensional (3D) network of crosslinked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: biosensor, nanomaterials, redox enzyme, thiol-modified Au surface

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Authors: Ahmad Alsolami, Darren Mundy, Manuel Hernandez-Perez

Abstract:

Social media networks, such as Twitter, offer the perfect opportunity to either positively or negatively affect political attitudes on large audiences. A most important factor contributing to this effect is the existence of influential users, who have developed a reputation for their awareness and experience on specific subjects. Therefore, knowledge of the mechanisms to identify influential users on social media is vital for understanding their effect on their audience. The concept of the influential user is based on the pioneering work of Katz and Lazarsfeld (1959), who created the concept of opinion leaders' to indicate that ideas first flow from mass media to opinion leaders and then to the rest of the population. Hence, the objective of this research was to provide reliable and accurate structural mechanisms to identify influential users, which could be applied to different platforms, places, and subjects. Twitter was selected as the platform of interest, and Saudi Arabia as the context for the investigation. These were selected because Saudi Arabia has a large number of Twitter users, some of whom are considerably active in setting agendas and disseminating ideas. The study considered the scientific methods that have been used to identify public opinion leaders before, utilizing metrics software on Twitter. The key findings propose multiple novel metrics to compare Twitter influencers, including the number of followers, social authority and the use of political hashtags, and four secondary filtering measures. Thus, using ratio and percentage calculations to classify the most influential users, Twitter accounts were filtered, analyzed and included. The structured approach is used as a mechanism to explore the top ten influencers on Twitter from the political domain in Saudi Arabia.

Keywords: twitter, influencers, structured mechanism, Saudi Arabia

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Authors: Ganiyu Rasaq Omokeji

Abstract:

The growing recognition of the pivotal role of universities in promoting socio-economic development has led to a focus upon the expansion of the sector around the world. As the economy and society become more ‘knowledge intensive’, the role of universities in development is more onerous than just teaching, research, and service. It is to help create the open society upon which the progress of ideas depends on. Driven to fulfill this role, universities are likely to become even more important in building regional networks of their host communities. Currently, there are about 129 universities in Nigeria, with a total number of 37 federal, 36 state, and 56 privately owned universities. Fountain University is among the private universities in Nigeria located in Osogbo, Osun State. The university is committed to the total development of men and women in an enabling environment, through appropriate teaching, research, and service to humanity, influenced by Islamic ethics and culture. The university focuses on educational development and growth that are relevant to the nation’s manpower needs and global competitiveness through a gradual but steady process. This paper examines the role of Private University in the socio-economic development of host community using Fountain University as a case study. The research methodology design for this paper has a total of 200 respondents. The research instrument of data collection was a questionnaire and in-depth interview (IDI). The finding reveals that Fountain University plays an important role in socio-economic and cultural development through their Islamic culture. The paper recommend that universities must bridge the gaps between creative individual with innovative ideas and the application of technology for economic progress and social betterment of their host communities. University also must serve as a bridge that carries the traffic of social and economic development.

Keywords: private university, socio-economic development, host communities, role of universities and community development

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Authors: Edeaghe Ehikhamenor, Jennifer Nnamdi

Abstract:

Introduction: Gender-based violence (GBV) was a well-known global crisis before the COVID-19 pandemic. The pandemic burden only intensified the crisis. With prevailing lockdowns, increased poverty due to high unemployment, especially affecting females, and other mobility restrictions that have left many women trapped with their abusers, plus isolation from social contact and support networks, GBV cases spiraled out of control. Prevalence of economic with cultural disparity, which is greatly manifested in Nigeria, is a major contributory factor to GBV. This is made worst by religious adherents where the females are virtually relegated to the background. Our societal approaches to investigations and sanctions to culprits have not sufficiently applied forensic/DNA tools in combating these major vices. Violence against women or some rare cases against men can prevent them from carrying out their duties regardless of the position they hold. Objective: The main objective of this research is to highlight the origin of GBV, the victims, types, contributing factors, and the applications of forensics/DNA tools and remedies so as to minimize GBV in our society. Methods: Descriptive information was obtained through the search on our daily newspapers, electronic media, google scholar websites, other authors' observations and personal experiences, plus anecdotal reports. Results: Findings from our exploratory searches revealed a high incidence of GBV with very limited or no applications of Forensics/DNA tools as an intervening mechanism to reduce GBV in Nigeria. Conclusion: Nigeria needs to develop clear-cut policies on forensics/DNA tools in terms of institutional framework to develop a curriculum for the training of all stakeholders to fast-track justice for victims of GBV so as to serve as a deterrent to other culprits.

Keywords: gender-based violence, forensics, DNA, justice

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Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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Authors: Hannah Evangeline Sangeetha

Abstract:

Ageing is an inevitable change in the life span of an individual. India’s old age population has increased from 19 million in 1947 to 100 million in the 21st century. The United Nations World Population ageing reports that the grey population has immensely increased from 9.2% in 1990 to 11.7 % in 2013, and it’s expected to triple by the year 2050 growing from 737 million to over 2 billion persons 60 years of age and older. Ageing is a period of physical, mental and social decline which brings a host of challenges to the individual and the family. Hence it requires attention at the micro, mezzo and the macro levels of the society. The concepts of healthy and successful aging are being used to help people to change their negative attitude towards aging. This perspective is important to make people realize their potentialities to bring about a change in the minds of senior citizens as well as the society. The objective of this study was to understand the level of active ageing among the rural elderly women and its impact on the quality of life. 330 elderly women from 12 villages of Sriperumbudur associated with the Mobile medical care of Help age India were interviewed using census method. The study revealed the following findings; most respondents in this study were young old between the age group of 60 to 75 years. All the three major religious groups were represented, 85.5percent were Hindus. Majority of the respondents 73.3percent had no education. It was interesting to know that majority of the respondents were self reliant (83.94 percent) and 82.73 percent of them very independent and took care of them by themselves (activities of daily living) without any support from their families. 76.9 percent of the senior women worked based on their competencies, 75.5 percent of them were involved in plenty of activities everyday including their occupation and household chores, which enabled them to be physically active. The chi square values that there is a significant association between the overall active ageing score, religion &number of members in the family. The other demographic variables like age, occupation, income marital status, age at marriage, number of children in the family and Socio –Economic Status were not significantly associated with the overall active aging score. The p-value 0.032 showed Social network and being self-reliant are significantly associated. The study surprisingly shows that most women enjoyed freedom and Independence in their family which is a positive indicator of active ageing.

Keywords: active ageing, quality of life, independence, self reliance

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Authors: S. Shakibaei, P. Alpkokin

Abstract:

The railway network is one of the major components of a transportation system in a country which may be an indicator of the country’s level of economic improvement. Since 2000s on, revival of national railways and development of High Speed Rail (HSR) lines are one of the most remarkable policies of Turkish government in railway sector. Within this trend, the railway age is to be revived and coming decades will be a golden opportunity. Indubitably, major infrastructures such as road and railway networks require sizeable investment capital, precise maintenance and reparation. Traditionally, governments are held responsible for funding, operating and maintaining these infrastructures. However, lack or shortage of financial resources, risk responsibilities (particularly cost and time overrun), and in some cases inefficacy in constructional, operational and management phases persuade governments to find alternative options. Financial power, efficient experiences and background of private sector are the factors convincing the governments to make a collaboration with private parties to develop infrastructures. Public-Private Partnerships (PPP or 3P or P3) and related regulatory issues are born considering these collaborations. In Turkey, PPP approaches have attracted attention particularly during last decade and these types of investments have been accelerated by government to overcome budget limitations and cope with inefficacy of public sector in improving transportation network and its operation. This study mainly tends to present a comprehensive overview of PPP concept, evaluate the regulatory procedure in Europe and propose a general framework for Turkish State Railways (TCDD) as an outlook on privatization, liberalization and deregulation of railway network.

Keywords: deregulation, high-speed railway, liberalization, privatization, public-private partnership

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Authors: Elham Fariborzi, Hoda Anvari Kazemabad

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Today, ICT plays an important role in all matters and it affects the development of creative cities. According to virtual space in this technology, it use especially for expand terms like smart schools, Virtual University, web-based training and virtual classrooms that is in parallel with the traditional teaching. Nowadays, the educational systems in different countries such as Iran are changing and start increasing creativity in the learning environment. It will contribute to the development of innovative ideas and thinking of the people in this environment; such opportunities might be cause scientific discovery and development issues. The creativity means the ability to generate ideas and numerous, new and suitable solutions for solving the problems of real and virtual individuals and society, which can play a significant role in the development of creative current physical cities or virtual borders ones in the future. The purpose of this paper is to study strategies to increase creativity in a virtual learning to develop a creative city. In this paper, citation/ library study was used. The full description given in the text, including how to create and enhance learning creativity in a virtual classroom by reflecting on performance and progress; attention to self-directed learning guidelines, efficient use of social networks, systematic discussion groups and non-intuitive targeted controls them by involved factors and it may be effective in the teaching process regarding to creativity. Meanwhile, creating a virtual classroom the style of class recognizes formally the creativity. Also the use of a common model of creative thinking between student/teacher is effective to solve problems of virtual classroom. It is recommended to virtual education’ authorities in Iran to have a special review to the virtual curriculum for increasing creativity in educational content and such classes to be witnesses more creative in Iran's cities.

Keywords: virtual learning, creativity, e-learning, bioinformatics, biomedicine

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Authors: Yudhitya Kusumawati, Yuki Mitsuya, Tomooki Shiba, Mitsuru Uesaka

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After the Fukushima Daiichi nuclear power reactor incident, there are a lot of unaccountable nuclear fuel debris in the reactor core area, which is subject to safeguard and criticality safety. Before the actual precise analysis is performed, preliminary on-site screening and mapping of nuclear debris activity need to be performed to provide a reliable data on the nuclear debris mass-extraction planning. Through a collaboration project with Japan Atomic Energy Agency, an on-site nuclear debris screening system by using dual energy X-Ray inspection and neutron energy resonance analysis has been established. By using the compact and mobile pulsed neutron source constructed from 3.95 MeV X-Band electron linac, coupled with Tungsten as electron-to-photon converter and Beryllium as a photon-to-neutron converter, short-distance neutron Time of Flight measurement can be performed. Experiment result shows this system can measure neutron energy spectrum up to 100 eV range with only 2.5 meters Time of Flightpath in regards to the X-Band accelerator’s short pulse. With this, on-site neutron Time of Flight measurement can be used to identify the nuclear debris isotope contents through Neutron Resonance Transmission Analysis (NRTA). Some preliminary NRTA experiments have been done with Tungsten sample as dummy nuclear debris material, which isotopes Tungsten-186 has close energy absorption value with Uranium-238 (15 eV). The results obtained shows that this system can detect energy absorption in the resonance neutron area within 1-100 eV. It can also detect multiple elements in a material at once with the experiment using a combined sample of Indium, Tantalum, and silver makes it feasible to identify debris containing mixed material. This compact neutron Time of Flight measurement system is a great complementary for dual energy X-Ray Computed Tomography (CT) method that can identify atomic number quantitatively but with 1-mm spatial resolution and high error bar. The combination of these two measurement methods will able to perform on-site nuclear debris screening at Fukushima Daiichi reactor core area, providing the data for nuclear debris activity mapping.

Keywords: neutron source, neutron resonance, nuclear debris, time of flight

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Authors: Daniel M. Muntean, Viorel Ungureanu

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More than half of the urban population in Romania lives today in residential buildings made out of large prefabricated reinforced concrete panels. Since their initial design was made in the 1960’s, these housing units are now being technically and morally outdated, consuming large amounts of energy for heating, cooling, ventilation and lighting, while failing to meet the needs of the contemporary life-style. Due to their widespread use, the design of a system that improves their energy efficiency would have a real impact, not only on the energy consumption of the residential sector, but also on the quality of life that it offers. Furthermore, with the transition of today’s existing power grid to a “smart grid”, buildings could become an active element for future electricity networks by contributing in micro-generation and energy storage. One of the most addressed issues today is to find locally adapted strategies that can be applied considering the 20-20-20 EU policy criteria and to offer sustainable and innovative solutions for the cost-optimal energy performance of buildings adapted on the existing local market. This paper presents a possible adaptive design scenario towards sustainable retrofitting of these housing units. The apartments are transformed in order to meet the current living requirements and additional extensions are placed on top of the building, replacing the unused roof space, acting not only as housing units, but as active solar energy collection systems. An adaptive building envelope is ensured in order to achieve overall air-tightness and an elevator system is introduced to facilitate access to the upper levels.

Keywords: adaptive building, energy efficiency, retrofitting, residential buildings, smart grid

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