Search results for: local stakeholders network

Authors: Dongwon Lee, Sunmyeng Kim

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Underwater acoustic networks (UANs) have become a very active research area in recent years. Compared with wireless networks, UANs are characterized by the limited bandwidth, long propagation delay and high channel dynamic in acoustic modems, which pose challenges to the design of medium access control (MAC) protocol. The characteristics severely affect network performance. In this paper, we study a MS-MAC (Multi-Sender MAC) protocol in order to improve network performance. The proposed protocol exploits temporal reuse by learning the propagation delays to neighboring nodes. A source node locally calculates the transmission schedules of its neighboring nodes and itself based on the propagation delays to avoid collisions. Performance evaluation is conducted using simulation, and confirms that the proposed protocol significantly outperforms the previous protocol in terms of throughput.

Keywords: acoustic channel, MAC, temporal reuse, UAN

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: M. Khalfa, H. Khachai, F. Chiker, K. Bougherara, R. Khenata, G. Murtaza, M. Harmel

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A theoretical study of structural, elastic, electronic and thermodynamic properties of Fe2VX, (with X = Al and Ga), were studied by means of the full-relativistic version of the full-potential augmented plane wave plus local orbitals method. For exchange and correlation potential we used both generalized-gradient approximation (GGA) and local-density approximation (LDA). Our calculated ground state properties like as lattice constants, bulk modulus and elastic constants appear more accurate when we employed the GGA rather than the LDA approximation, and these results agree very well with the available experimental and theoretical data. Further, prediction of the thermal effects on some macroscopic properties of Fe2VAl and Fe2VGa are given in this paper using the quasi-harmonic Debye model in which the lattice vibrations are taken into account. We have obtained successfully the variations of the primitive cell volume, volume expansion coefficient, heat capacities and Debye temperature with pressure and temperature in the ranges of 0–40 GPa and 0–1500 K.

Keywords: full Heusler, FP-LAPW, electronic properties, thermal properties

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Authors: Rodrigo T. Lourenço, Margarida Mano

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Higher Education Institutions (HEI), and other levels of Education, face important challenges. One of the most relevant one is the ability to adapt to a society that is changing over time, whilst guarantying levels of training that do not merely react to such changes. Thus, interacting with society, particularly with surrounding communities and key stakeholders, has become an essential requirement for the sustainability of these institutions. One of the formal mechanisms implemented in European educational institutions has been the design of organizational structures that include a top governance body sharing its constitution with both internal members, students and external members. Such frame holds the core mission of involving communities in the governance of educational institutions, assuming, both strategic decision-making functions, with the approval of the institutions’ strategic plans, and a supervision function, approved by activity reports. It also plays an essential role in the life of institutions by holding the responsibility of electing its top executives. In Portugal, it has been almost a decade since the publication of RJIES, the legal framework of Higher Education, such bodies being designated by General Councils. Thus, one may highlight that there has been a better understanding of the operative process of these bodies, as well as their added value to the education system. It has also been possible to analyse the extent to which their core mission has been fulfilled and to understand its growing relevance, particularly regarding the autonomy of institutions. This article aims to contribute to this theme by presenting the results of a study on the role of these bodies in the governance of Public Portuguese HEI, with a special focus on the supervisory competence of organizational performance. Through questionnaires made to board members and interviews with chairpersons of the bodies and top managers of the institutions, it was possible to conclude that there is a high concern with the connections to the external environment. However, regarding organizational performance and the role of the Council as a supervisor of that performance, the activity of the bodies has fallen short of what would be expected. Several reasons may be identified. It is important to emphasize the importance of the profile of the external members and the relationship between the organ’s standard functioning and the election of the head of the institution.

Keywords: governance, stakeholders, supervision, performance

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Authors: Seyed Mehran Kazemi, Bahare Fatemi

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Sudoku is a logic-based combinatorial puzzle game which is popular among people of different ages. Due to this popularity, computer softwares are being developed to generate and solve Sudoku puzzles with different levels of difficulty. Several methods and algorithms have been proposed and used in different softwares to efficiently solve Sudoku puzzles. Various search methods such as stochastic local search have been applied to this problem. Genetic Algorithm (GA) is one of the algorithms which have been applied to this problem in different forms and in several works in the literature. In these works, chromosomes with little or no information were considered and obtained results were not promising. In this paper, we propose a new way of applying GA to this problem which uses more-informed chromosomes than other works in the literature. We optimize the parameters of our GA using puzzles with different levels of difficulty. Then we use the optimized values of the parameters to solve various puzzles and compare our results to another GA-based method for solving Sudoku puzzles.

Keywords: genetic algorithm, optimization, solving Sudoku puzzles, stochastic local search

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Authors: E. O. E. Nnadi

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Transportation is a critical factor in the economic growth and development of any nation, region or state. Good transportation network supports every sector of the economy like the manufacturing, transportation and encourages investors thereby affect the overall economic prosperity. The paper evaluates the impact of transportation on the economic growth of Nigeria using south eastern states as a case study. The choice of the case study is its importance as the commercial and industrial nerve of the country. About 200 respondents who are of different professions such as dealers in goods, transporters, contractors, consultants, bankers were selected and a set of questionnaire were administered to using the systematic sampling technique in the five states of the region. Descriptive statistics and relative importance index (RII) technique was employed for the analysis of the data gathered. The findings of the analysis reveal that Nigeria has the least effective ratio per population in Africa of 949.91 km/Person. Conclusion was drawn to improve road network in the area and the country as a whole to enhance the economic activities of the people.

Keywords: economic growth, south-east, transportation, transportation cost, Nigeria

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Authors: Somdatta Saha

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The main purpose was to provide an implementable design scenario for underground coal mines using wireless sensor networks (WSNs). The main reason being that given the intricacies in the physical structure of a coal mine, only low power WSN nodes can produce accurate surveillance and accident detection data. The work mainly concentrated on designing and simulating various alternate scenarios for a typical mine and comparing them based on the obtained results to arrive at a final design. In the Era of embedded technology, the Zigbee protocols are used in more and more applications. Because of the rapid development of sensors, microcontrollers, and network technology, a reliable technological condition has been provided for our automatic real-time monitoring of coal mine. The underground system collects temperature, humidity and methane values of coal mine through sensor nodes in the mine; it also collects the number of personnel inside the mine with the help of an IR sensor, and then transmits the data to information processing terminal based on ARM.

Keywords: ARM, embedded board, wireless sensor network (Zigbee)

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Authors: Shu-Yen Wang, Shyh-Huei Hwang

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Designated as an important architectural complex of settlement by the Ministry of Culture, Hua-Zhai Settlement located in Wang-An Township, Peng-Hu County, of Taiwan has been progressively restored year by year and is now at the revitalization and reutilization stage. Over the last 5 years, YunTech has participated in the restoration project while being in compliance with the Bureau of Cultural Heritage’s spirit of 'Living Heritage Conservation'. In this study, reflections have been made to evaluate the contemporariness of traditional settlement development from the aspects of revitalization and reutilization. On the one hand, the connection between settlers’ experiences and emotions have been clarified through the living nodes, collective memory, and social-cultural connotation. On the other hand, activity design has promoted the reconstruction of living nodes and facilitated the reconnection of collective memory, enabling us to explore the contemporariness of living nodes after the reconstruction. With the adoption of literature review, participant observation, and interview analysis methods, this study concludes the following results: 1) The node reconstruction brings back the memories and makes emotional connections: the spatial collective memory is composed of different components. During the reconstruction of node space, villagers participated not only in the narration of the history but also in the restoration of the space. This process enables villagers to bring back their memories and make emotional connections thereto. 2) Villagers’ understanding towards revitalization has been facilitated through node reconstruction: as a medium of this project, activity design has facilitated node reconstruction by offering villagers a natural environment to build up emotional connections to the settlement. This also enables us to better understand the meaning of settlement activation for the local community. 3) New connections are established in life between villagers and the university through the construction of living nodes: through the local implementation of node reconstruction, new connections have been established in life between villagers who participated in the project and the university. In the meantime, the university’s entrance to the community has also been revalued.

Keywords: collective memory, local sense of belonging, reconstruction of living nodes, the important architectural complex of Wang-An Hua-Zhai settlement

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Roshanak Khodabakhsh Jolfaei, Javad Akbari Torkestani

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As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm.

Keywords: computational grid, job scheduling, learning automata, dynamic scheduling

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Authors: A. Llopis Alvarez, D. Muller-Eie

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Participatory GIS (geographic information systems) are designed for community mapping exercises in order to produce spatial representations of local knowledge. Ideally, participatory GIS caters to public participation through the use of spatial data in order to increase community-led policy-and decision-making. Having defined a spatial object, such as a neighborhood, subjective mapping involves attaining a description of the spatial, physical, social and psychological characteristics of that spatial object. This paper highlights an emerging appreciation of the subjective component, particularly in spatial analyses. The beliefs, feelings, and behaviors associated with an urban area reflect its sense of place for an individual or a group. It is important therefore to understand what types of beliefs, emotions, and behavioral patterns are relevant to particular resident, groups and urban scales. In this sense, resident’s emotional attachment to their urban areas motivates civic engagement and facilitates awareness of its strengths and its problems. Similarly, subjective perceptions act in complex ways to influence the formation and maintenance of social identity and quality of life. This paper reports on findings from a case study of immigrant population in Norwegian cities, their residential conditions and their relationship to quality of urban life. Cognitive mapping methodologies are used in this study to understand local perceptions of urban qualities. Thus, measures to alleviate disadvantages and improve quality of urban life are more likely to be effective when they are informed by an understanding of a place as constructed by those who live in it, meaning their subjective perceptions about it.

Keywords: mapping methodologies, participatory GIS, perceptual maps, public participation, spatial analysis, subjective perceptions

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Authors: Kavitha Puthanveedu, Kasi Sekar, Preeti Jacob, Kavita Jangam

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In India, The Juvenile Justice (Care and Protection of Children) Act, 2015, the law related to children alleged and found to be in conflict with law, proposes to address to the rehabilitation of children in conflict with law by catering to the basic rights by providing care and protection, development, treatment, and social re-integration. A major concern in addressing the issues of children in conflict with law in Kerala the southernmost state in India identified were: 1. Lack of psychological assessment for children in conflict with law, 2. Poor psychosocial intervention for children in conflict with law on bail, 3. Lack of psychosocial intervention or proper care and protection of CCL residing at observation and special home, 4. Lack convergence with systems related with mental health care. Aim: To develop individual care plan for children in conflict with law. Methodology: NIMHANS a premier Institute of Mental Health and Neurosciences, collaborated with Social Justice Department, Govt. of Kerala to address this issue by developing a participatory methodology to implement psychosocial care in the existing services by integrating the activities through multidisciplinary and multisectoral approach as per the Sec. 18 of JJAct 2015. Developing individual care plan: Key informant interviews, focus group discussion with multiple stakeholders consisting of legal officers, police, child protection officials, counselors, and home staff were conducted. Case studies were conducted among children in conflict with law. A checklist on 80 psychosocial problems among children in conflict with law was prepared with eight major issues identified through the quantitative process such as family and parental characteristic, family interactions and relationships, stressful life event, social and environmental factors, child’s individual characteristics, education, child labour and high-risk behavior. Standardised scales were used to identify the anxiety, caseness, suicidality and substance use among the children. This provided a background data understand the psychosocial problems experienced by children in conflict with law. In the second stage, a detailed plan of action was developed involving multiple stakeholders that include Special juvenile police unit, DCPO, JJB, and NGOs. The individual care plan was reviewed by a panel of 4 experts working in the area of children, followed by the review by multiple stakeholders in juvenile justice system such as Magistrates, JJB members, legal cum probation officers, district child protection officers, social workers and counselors. Necessary changes were made in the individual care plan in each stage which was pilot tested with 45 children for a period of one month and standardized for administering among children in conflict with law. Result: The individual care plan developed through scientific process was standardized and currently administered among children in conflict with law in the state of Kerala in the 3 districts that will be further implemented in other 14 districts. The program was successful in developing a systematic approach for the psychosocial intervention of children in conflict with law that can be a forerunner for other states in India.

Keywords: psychosocial care, individual care plan, multidisciplinary, multisectoral

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Authors: Valentina Adduci

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The developing research aims to define in general the criteria of environmental sustainability of rural buildings in Puglia and particularly in the manor farm. The main part of the study analyzes the relationship / dependence between the rural building and the landscape which, after many stratifications, results clearly identified and sometimes also characterized in a positive way. The location of the manor farm, in fact, is often conditioned by the infrastructural network and by the structure of the agricultural landscape. The manor farm, without the constraints due to the urban pattern’s density, was developed in accordance with a logical settlement that gives priority to the environmental aspects. These vernacular architectures are the most valuable example of how our ancestors have planned their dwellings according to nature. The 237 farms, analysis’ object, have been reported in cartography through the GIS system; a symbol has been assigned to each of them to identify the architectural typology and a different color for the historical period of construction. A datasheet template has been drawn up, and it has made possible a deeper understanding of each manor farm. This method provides a faster comparison of the most recurring characters in all the considered buildings, except for those farms which benefited from special geographical conditions, such as proximity to the road network or waterways. Below there are some of the most frequently constants derived from the statistical study of the examined buildings: southeast orientation of the main facade; placement of the sheep pen on the ground tilted and exposed to the south side; larger windowed surface on the south elevation; smaller windowed surface on the north elevation; presence of shielding vegetation near the more exposed elevations to the solar radiation; food storage’s rooms located on the ground floor or in the basement; animal shelter located in north side of the farm; presence of tanks and wells, sometimes combined with a very accurate channeling storm water system; thick layers of masonry walls, inside of which were often obtained hollow spaces to house stairwells or depots for the food storage; exclusive use of local building materials. The research aims to trace the ancient use of bioclimatic constructive techniques in the Apulian rural architecture and to define those that derive from an empirical knowledge and those that respond to an already encoded design. These constructive expedients are especially useful to obtain an effective passive cooling, to promote the natural ventilation and to built ingenious systems for the recovery and the preservation of rainwater and are still found in some of the manor farms analyzed, most of them are, today, in a serious state of neglect.

Keywords: bioclimatic devices, farmstead, rural landscape, sustainability

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Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: cascaded neural network, internal temperature, inverter, three-phase induction motor

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Authors: Sergio Andres Rojas, Julian Benavides Franco, Juan Tomas Sayago

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An increasing amount of research demonstrates how market mood affects financial markets, but their primary goal is to demonstrate how Trump's tweets impacted US interest rate volatility. Following that lead, this work evaluates the effect that Trump's tweets had during his presidency on local and international stock markets, considering not just volatility but the direction of the movement. Three indexes for Trump's tweets were created relating his activity with movements in the S&P500 using natural language analysis and machine learning algorithms. The indexes consider Trump's tweet activity and the positive or negative market sentiment they might inspire. The first explores the relationship between tweets generating negative movements in the S&P500; the second explores positive movements, while the third explores the difference between up and down movements. A pseudo-investment strategy using the indexes produced statistically significant above-average abnormal returns. The findings also showed that the pseudo strategy generated a higher return in the local market if applied to intraday data. However, only a negative market sentiment caused this effect on daily data. These results suggest that the market reacted primarily to a negative idea reflected in the negative index. In the international market, it is not possible to identify a pervasive effect. A rolling window regression model was also performed. The result shows that the impact on the local and international markets is heterogeneous, time-changing, and differentiated for the market sentiment. However, the negative sentiment was more prone to have a significant correlation most of the time.

Keywords: market sentiment, Twitter market sentiment, machine learning, natural dialect analysis

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Authors: B. S. Yadav, A. Mani, S. Srivastava

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Chickpea (Cicer arietinum L.) is an annual, self-pollinating, diploid (2n = 2x = 16) pulse crop that ranks second in world legume production after common bean (Phaseolus vulgaris). ICC 4958 flowers approximately 39 days after sowing under peninsular Indian conditions and the crop matures in less than 90 days in rained environments. The estimated collective yield losses due to abiotic stresses (6.4 million t) have been significantly higher than for biotic stresses (4.8 million t). Most legumes are known to be salt sensitive, and therefore, it is becoming increasingly important to produce cultivars tolerant to high-salinity in addition to other abiotic and biotic stresses for sustainable chickpea production. Our aim was to identify the genes that are involved in the defence mechanism against heavy metal toxicity in chickpea and establish the biological network of heavy metal toxicity in chickpea. ICC4958 variety of chick pea was taken and grown in normal condition and 150µM concentration of different heavy metal salt like CdCl₂, K₂Cr2O₇, NaAsO₂. At 15th day leave samples were collected and stored in RNA Later solution microarray was performed for checking out differential gene expression pattern. Our studies revealed that 111 common genes that involved in defense mechanism were up regulated and 41 genes were commonly down regulated during treatment of 150µM concentration of CdCl₂, K₂Cr₂O₇, and NaAsO₂. Biological network study shows that the genes which are differentially expressed are highly connected and having high betweenness and centrality.

Keywords: abiotic stress, biological network, chickpea, microarray

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Authors: Danilo López, Edwin Rivas, Leyla López

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This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.

Keywords: cognitive radio, base station, best effort, MLPNN, prediction, real time

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Authors: Mardianto

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Education and learning are now grown rapidly. Synergy of techonology especially instructional technology in the learning activities are very big influence on the effectiveness of learning and creativity to achieve optimal results. But on the other hand there is a education value that is difficult to be articulated through character-forming technology such as honesty, discipline, hard work, heroism, and so forth. Learning strategy and storytelling from the past until today is still an option for teachers to convey the message of character values. With the material was loaded from the local culture (stories folklore), the combination of learning objectives (build character child) strategy, and traditional methods (storytelling and story), and the preservation of local culture (dig tale folklore) is critical to maintaining the nation's culture. In the context of maintaining the nation's culture, then since the age of the child at the level of government elementary school a necessity. Globalization, the internet and technology sometimes feel can displace the role of the teacher in the learning activities. To the oral tradition is a mainstay of storytelling should be maintained and preserved. This research was conducted at the elementary school in the city of Medan, North Sumatra Indonesia, with a random sampling technique, the 27 class teachers were respondents who were randomly assigned to the Madrasah Ibtdaiyah (Islamic Elementary School) both public and private. Research conducted at the beginning of 2014 refers to a curriculum that is being transformed in the environment ministry Republic Religion Indonesia. The results of this study indicate that; the declining skills of teachers to develop storytelling this can be seen from; 74.07% of teachers have never attended a special training storytelling, 85.19% no longer nasakah new stories, only 22.22% are teachers who incorporate methods of stories in the learning plan. Most teachers are no longer concerned with storytelling, among those experiencing difficulty in developing methods because the story; 66.67% of children are more interested in children's cartoons like Bobo boy, Angrybirds and others, 59.26 children prefer other activities than listening to a story. The teachers hope, folklore books should be preserved, storytelling training should be provided by the government through the ministry of religion, race or competition of storytelling should be scheduled, writing a new script-based populist storytelling should be provided immediately. The teachers’ hope certainly not excessive, by realizing the story method becomes articulation as the efforts of child character development based populist, therefore the local knowledge can be a strong fortress facing society in the era of progress as at present, and future.

Keywords: story telling, local wisdom, education, technology development

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Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

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Authors: Brian J. Biroscak

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In the United States (US), “sex trafficking” is defined at the federal level in the Trafficking Victims Protection Act of 2000 as encompassing a number of processes such as recruitment, transportation, and provision of a person for the purpose of a commercial sex act. It involves the use of force, fraud, or coercion, or in which the person induced to perform such act has not attained 18 years of age. Accumulating evidence suggests that sex trafficking is exacerbated by social and environmental stressors (e.g., pandemics). Given that “provision” is a key part of the definition, “provisioning systems” may offer a useful lens through which to study sex trafficking dynamics. Provisioning systems are the social systems connecting individuals, small groups, entities, and embedded communities as they seek to satisfy their needs and wants for goods, services, experiences and ideas through value-based exchange in communities. This project presents a conceptual framework for understanding sex trafficking dynamics in the context of the COVID pandemic. The framework is developed as a system dynamics simulation model based on published evidence, social and behavioral science theory, and key informant interviews with stakeholders from the Protection, Prevention, Prosecution, and Partnership sectors in one US state. This “4 P Paradigm” has been described as fundamental to the US government’s anti-trafficking strategy. The present research question is: “How do sex trafficking systems (e.g., supply, demand and price) interact with other provisioning systems (e.g., networks of organizations that help sexually exploited persons) to influence trafficking over time vis-à-vis the COVID pandemic?” Semi-structured interviews with stakeholders (n = 19) were analyzed based on grounded theory and combined for computer simulation. The first step (Problem Definition) was completed by open coding video-recorded interviews, supplemented by a literature review. The model depicts provision of sex trafficking services for victims and survivors as declining in March 2020, coincidental with COVID, but eventually rebounding. The second modeling step (Dynamic Hypothesis Formulation) was completed by open- and axial coding of interview segments, as well as consulting peer-reviewed literature. Part of the hypothesized explanation for changes over time is that the sex trafficking system behaves somewhat like a commodities market, with each of the other subsystems exhibiting delayed responses but collectively keeping trafficking levels below what they would be otherwise. Next steps (Model Building & Testing) led to a ‘proof of concept’ model that can be used to conduct simulation experiments and test various action ideas, by taking model users outside the entire system and seeing it whole. If sex trafficking dynamics unfold as hypothesized, e.g., oscillated post-COVID, then one potential leverage point is to address the lack of information feedback loops between the actual occurrence and consequences of sex trafficking and those who seek to prevent its occurrence, prosecute the traffickers, protect the victims and survivors, and partner with the other anti-trafficking advocates. Implications for researchers, administrators, and other stakeholders are discussed.

Keywords: pandemics, provisioning systems, sex trafficking, system dynamics modeling

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Authors: Domingos Vita, Patrick Brady

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Background: There is a tuberculosis (TB) epidemic in Angola that has been getting worse for more than a decade despite the active implementation of the DOTS strategy. The aim of this study was to directly interrogate healthcare workers involved in TB control on what they consider to be the drivers of the TB epidemic in Angola. Methods: Twenty four in-depth qualitative interviews were conducted with medical staff working in this field in the provinces of Luanda and Benguela. Results: The healthcare professionals see the migrant working poor as a particular problem for the control of TB. These migrants are constructed as ‘Rural People’ and are seen as non-compliant and late-presenting. This is a stigmatized and marginal group contending with the additional stigma associated with TB infection. The healthcare professionals interviewed also see the interruption of treatment and self medication generally as a better explanation for the TB epidemic than urbanization or lack of medication. Conclusions: The local narrative is in contrast to previous explanations used elsewhere in the developing world. To be effective policy must recognize the local issues of the migrant workforce, interruption of treatment and the stigma associated with TB in Angola.

Keywords: Africa, Angola, migrants, qualitative, research, tuberculosis

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Authors: Alexander N. Pisarchik, Parth Chholak

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Intrinsic brain noise was estimated via magneto-encephalograms (MEG) recorded during perception of flickering visual stimuli with frequencies of 6.67 and 8.57 Hz. First, we measured the mean phase difference between the flicker signal and steady-state event-related field (SSERF) in the occipital area where the brain response at the flicker frequencies and their harmonics appeared in the power spectrum. Then, we calculated the probability distribution of the phase fluctuations in the regions of frequency locking and computed its kurtosis. Since kurtosis is a measure of the distribution’s sharpness, we suppose that inverse kurtosis is related to intrinsic brain noise. In our experiments, the kurtosis value varied among subjects from K = 3 to K = 5 for 6.67 Hz and from 2.6 to 4 for 8.57 Hz. The majority of subjects demonstrated leptokurtic kurtosis (K < 3), i.e., the distribution tails approached zero more slowly than Gaussian. In addition, we found a strong correlation between kurtosis and brain complexity measured as the correlation dimension, so that the MEGs of subjects with higher kurtosis exhibited lower complexity. The obtained results are discussed in the framework of nonlinear dynamics and complex network theories. Specifically, in a network of coupled oscillators, phase synchronization is mainly determined by two antagonistic factors, noise, and the coupling strength. While noise worsens phase synchronization, the coupling improves it. If we assume that each neuron and each synapse contribute to brain noise, the larger neuronal network should have stronger noise, and therefore phase synchronization should be worse, that results in smaller kurtosis. The described method for brain noise estimation can be useful for diagnostics of some brain pathologies associated with abnormal brain noise.

Keywords: brain, flickering, magnetoencephalography, MEG, visual perception, perception time

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Authors: Laura Seppälä, Ana Nuutinen

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Environmental concerns are increasing the interest in the potential uses of natural dyes. Natural dyes are more safe and environmentally friendly option than synthetic dyes. However, one must be also cautious with natural dyes, because, for example, some dyestuff such as plants or mushrooms, as well as some mordants are poisonous. By natural dyes we mean dyes that are derived from plants, fungi, bark, lichens, algae, insects, and minerals. Different plant parts, such as stems, leaves, flowers, roots, bark, berries, fruits, and cones, can be utilized for textile dyeing and printing, pigment manufacture, and other processes depending on the season. They may be utilized to produce distinctive colour tones that are challenging to do with synthetic dyes. This adds value to textiles and makes them stand out. Synthetic dyes quickly replaced natural dyes, after being developed in the middle of the 19th century, but natural dyes have remained the dyeing method of crafters until recently. This research examines the commercial solutions for natural dyes in many parts of the world, such as Europe, the United States, South America, Africa, Asia, New Zealand, and Australia. This study aims to determine the commercial status of natural dyes. Each continent has its own traditions and specific dyestuffs. The availability of natural dyes can vary depending on several aspects, including plant species, temperature, and harvesting techniques, which poses a challenge to the work of designers and crafters. While certain plants may only provide dyes during specific seasons, others may do so continuously. To find the ideal time to collect natural dyes, it is critical to research various plant species and their harvesting techniques. Furthermore, to guarantee the quality and colour of the dye, plant material must be handled and processed properly. This research was conducted via an internet search, and results were searched systematically for commercial stakeholders in the field. The research question looked at commercial players in the field of natural dyes. This qualitative case study interpreted the data using thematic analysis. Each webpage was screenshotted and analyzed in reflection on to research question. Online content analysis means systematically coding and analyzing qualitative data. The most evident result was that the natural dyes interest in different parts of the World. There are clothing collections dyed with natural dyes, dyestuff stores, and courses for natural dyeing. This article presents the designers who work with natural dyes and actors who are involved with the natural dye industry. Several websites emphasized the safety and environmental benefits of natural dyes. Many of them included eye-catching images of textiles dyed naturally, and the colours of such dyes are thought to be attractive since they are beautiful and natural hues. The search did not find big-scale industrial solutions for natural dyes, but there were several instances of dyeing with natural dyes. Understanding the players, designers, and stakeholders in the natural dye business is the purpose of this article. The comprehension of the current state of the art illustrates the direction that the natural dye business is currently taking.

Keywords: commercial solutions, environmental issues, key stakeholders, natural dyes, sustainability, textile dyeing

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Authors: Yili Wang, Jarmo Kinos, Tuire Palonen, Tarja-Riitta Hurme

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This longitudinal study aims to examine how five- and six-year-old children’s peer relationships are formed and fostered during one preschool year in a southwestern Finnish preschool. All 16 kindergarteners participated in the study (at dyad level N=240; i.e., 16 x 15 relationships among the children). The children were divided into four daily groups, based on the table order during the daily routines, and four intervention groups, based on the teachers’ pedagogical plan. During the intervention, one iPad was given to each group in order to stimulate interaction among peers and, thus, enable the children to form new peer relationships. In the data gathering, sociometric nomination techniques were used to investigate the nature (i.e., stability and mutuality) of the peer relationships. The data was collected five times during the year to see what kind of peer relationship changes occurred at the dyad level and the group level, i.e., in establishing and losing friendship ties among the children. Social network analyses were used to analyze the data. The results indicate that the children’s preference for gender segregation was strong compared to age preference and intervention. In all, the number of reciprocal friendship ties and the mutual absence of friendship ties increased towards the end of the year, whereas the number of unilateral friendship ties decreased. This indicates that children’s nominations narrow down; thus, the group structure becomes more crystalized. Instead of extending their friendship networks, children seek stable and mutual relationships with their peers in their middle childhood years. The intervention only had a slightly negative influence on children’s peer relationships.

Keywords: intervention study, peer relationship, preschool education, social network analysis, sociometric ratings

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Authors: Mihai Rebenciuc, Simona Mihaela Bibic

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Branch of modern mathematics, graphs represent instruments for optimization and solving practical applications in various fields such as economic networks, engineering, network optimization, the geometry of social action, generally, complex systems including contemporary urban problems (path or transport efficiencies, biourbanism, & c.). In this paper is studied the interconnection of some urban network, which can lead to a simulation problem of a digraph through another digraph. The simulation is made univoc or more general multivoc. The concepts of fragment and atom are very useful in the study of connectivity in the digraph that is simulation - including an alternative evaluation of k- connectivity. Rough set approach in (bi)digraph which is proposed in premier in this paper contribute to improved significantly the evaluation of k-connectivity. This rough set approach is based on generalized rough sets - basic facts are presented in this paper.

Keywords: (bi)digraphs, rough set theory, systems of interacting agents, complex systems

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Authors: Ahmed ElAzab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny

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Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, then the determined factors have been applied using different classification techniques, a comparison of the results for these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent research in the same area, this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts, moreover, the study can be applied on different Social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.

Keywords: fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques

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Authors: Zita Fomukong Andam

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The decision on where to host sport events does not depend on the national politicians or specific international sport event bodies but also involves the residents of the hosting country. Sport tourism is one of the fast growing industries in the world. Cameroonians consider sport as a point of unity and growth within the country. It has a huge variety of sporting activities like swimming, canoe racing, tug of war and most especially soccer well known as football. The football national team made an impact in 1990 at the FIFA world cup. They also won the African Nations Cup five times. Being the winner of the 2017 African Cup of Nations, they are to host the 2019 African cup of Nations. The purpose of this research is to analyse the impacts of sport tourism event in Cameroon and specifically examine how this event influences the residents. A deep research discourse conducted with randomly selected 300 inbound residents and 200 Cameroonian residents living abroad. Survey questionnaires, interviews and direct observations were carried out as a method of collecting data. The results showed that sport events brings a lot of prestige and honor to the country; generate revenues to the country’s economy and particularly to the local businesses. On the other hand, the results showed that the local residents lose their intimacy, privacy, and their daily life routine is affected. In addition to this, they face negative social inequalities and environmental impacts. Understanding these results the national government and international bodies might be able to contribute to future studies and propose efficient measures to maximize the positive benefits and minimize the negative benefits.

Keywords: sport Tourism, economic impact, resident altitude, african Cup of nations

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Authors: Wong Yat Cheung Maggie

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Occupational Safety and Health Ordinance (OS&HO) (Chap 509) was enacted in 1997, OHS in HK should be growing and maturing, with a holistic approach to occupational health and safety in the workplace including physical, mental, social and spiritual well-being. The question is “How effective are OHSPs in meeting the current needs of HK health workers?” This study was designed to explore the issue for the first time, to empirically analyse the views of those who work in the system. The study employed a mixed method approach to collect various data from Occupational Health Service Providers (OHSPs), Occupational Health Service Consumers (OHSC): Registered nurses working in the hospital setting. This study was designed in two phases and two stages. Phase I Stage I was a paper survey to collect the data on OHSP. Then Phase I Stage II was a follow-up interview. Phase II Stage I was a paper survey to collect the data on OHSC. Then Phase II Stage II was a follow-up focus group study on OHSC for further clarification of the Phase II and Stage I result. The Phase I result reflects HK OHSPs point of view and their experience in the existing OHS practice in the local hospitals. It reflects various styles of reporting systems, staff profiles background and resource in providing OHS in HK hospitals. However, the basic OHS concern is similar between hospitals. In general, the OHS policies and procedures are available on site even though they may have different foci. The Phase II result is reflecting the HKs OHSCs echoes the OHSP feedback at providing of OHS, OHS concern and related policies and procedure are available on site. However, the most significant feedback from the OHSC at Phase II Stage II shows, nurses experienced various OHS concern most commonly work stress, workplace harassment and back strain without formal or official report to the related parties. The lack of reporting was due to the management handling attitude, stakeholders’ compliance and term of definition still have room to be improved even the related policies and procedures are available on site.

Keywords: occupational health service, registered nurse, Hong Kong hospital, mixed method

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Authors: Bokkasam Sasidhar, Ibrahim Aljasser

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The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

Procedia PDF Downloads 122