Search results for: government support

Authors: Shin-Jer Yang, Kai-Tai Yang

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In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: Cloud service, multi-tenancy, NFC, IAM, mobile device.

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Authors: Saeed Sedighizadeh, Abbas Mansoori, Mohammad Reza Pirestani, Davoud Sedighizadeh

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The usual method of river flow diversion involves construction of tunnels and cofferdams. Given the fact that the cost of diversion works could be as high as 10-20% of the total dam construction cost, due attention should be paid to optimum design of the diversion works. The cost of diversion works depends, on factors, such as: the tunnel dimensions and the intended tunneling support measures during and after excavation; quality and characterizes of the rock through which the tunnel should be excavated; the dimensions of the upstream (and downstream) cofferdams; and the magnitude of river flood the system is designed to divert. In this paper by use of the cost of unit prices for tunnel excavation, tunnel lining, tunnel support (rock bolt + shotcrete) and cofferdam fill the cost function was determined. The function is then minimized by the aid of PSO Algorithm (particle swarm optimization). It is found that the optimum diameter and the total diversion cost are directly related to the river flood discharge (Q). It has also shown that in addition to optimum diameter design discharge (Q), river length, tunnel length, is mainly a function of the ratios (not the absolute values) of the unit prices and does not depend on the overall price levels in the respective country. The results of optimization use in some of the case study lead us to significant changes in the cost.

Keywords: Diversion Tunnel, Optimization, PSO Algorithm

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Authors: C. Gunavathi, K. Premalatha

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Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.

Keywords: F-Test, Gene Expression, Genetic Algorithm, k- Nearest-Neighbor, Microarray, Signal-to-Noise Ratio, Support Vector Machine, T-statistics, Tumor Classification.

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Authors: Mrs.K.Kavitha, S.Arivazhagan

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A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Keywords: Multi-class, Run Length features, PCA, ICA, classification and Support Vector Machines.

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Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

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One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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Authors: Raúl González Muñoz, Essam Shehab, Martin Weinitzke, Chris Fowler, Paul Baguley

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Software applications have become crucial to the aerospace industry, providing a wide range of functionalities and capabilities used during the design, manufacturing and support of aircraft. However, as this criticality increases, so too does the risk for business operations when facing a software failure. Hence, there is a need for new methodologies to be developed to support aerospace companies in effectively managing their software portfolios, avoiding the hazards of business disruption and additional costs. This paper aims to provide a definition of operational software maturity, and how this can be used to assess software operational behaviour, as well as a view on the different aspects that drive software maturity within the aerospace industry. The key research question addressed is, how can operational software maturity monitoring assist the aerospace industry in effectively managing large software portfolios? This question has been addressed by conducting an in depth review of current literature, by working closely with aerospace professionals and by running an industry case study within a major aircraft manufacturer. The results are a software maturity model composed of a set of drivers and a prototype tool used for the testing and validation of the research findings. By utilising these methodologies to assess the operational maturity of software applications in aerospace, benefits in maintenance activities and operations disruption avoidance have been observed, supporting business cases for system improvement.

Keywords: Aerospace, capability maturity model, software maturity, software lifecycle.

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Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

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Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: Decision support system, event sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine.

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Authors: Aleksandra Zysk, Pawel Badura

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Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: Classification, singing, spectral analysis, vocal emission, vocal register.

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Authors: Subramaniam Chandran

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This paper presents an assessment study conducted among the distance learners in India. Open and distance learning systems have traveled a long way since its inception and its journey has witnessed the evolution and adoption of different generations of technology. This study focuses on the distant learners in India. Sampling for this study has been derived from the mass enrollment from Tamil Nadu area, a southern state of India. Learners were chosen from dual mode universities, private universities, Tamil Nadu Open University and IGNOU. The main focus of the study is to examine the coverage and appropriation of students support services and learning aids. It explores two aspects: the facilities available and the awareness and use of such services. It includes, self-learning materials, face-to-face counseling, multimedia learning materials, website, e-learning, radio and television services etc. While exploring the student-s perspective on these learning aspects, it is important to understand the perspectives of the teachers. Two different interests are visible among the teachers. Majority of the teachers support faceto- face counseling. However, the young teachers are in favour of online learning and multimedia supports in teaching. Through the awareness is somewhat high, the actual participation in online is very low. This is due to the inadequate infrastructure as well as the traditional attitudes of the teachers. Still the face-to-face sessions remain popular than online.

Keywords: Face-to-face session, online session, distance learning, multimedia

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Authors: Xun Ge

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Recently, X. Ge and J. Qian investigated some relations between higher mathematics scores and calculus scores (resp. linear algebra scores, probability statistics scores) for Chinese university students. Based on rough-set theory, they established an information system S = (U,CuD,V, f). In this information system, higher mathematics score was taken as a decision attribute and calculus score, linear algebra score, probability statistics score were taken as condition attributes. They investigated importance of each condition attribute with respective to decision attribute and strength of each condition attribute supporting decision attribute. In this paper, we give further investigations for this issue. Based on the above information system S = (U, CU D, V, f), we analyze the decision rules between condition and decision granules. For each x E U, we obtain support (resp. strength, certainty factor, coverage factor) of the decision rule C —>x D, where C —>x D is the decision rule induced by x in S = (U, CU D, V, f). Results of this paper gives new analysis of on higher mathematics scores for Chinese university students, which can further lead Chinese university students to raise higher mathematics scores in Chinese graduate student entrance examination.

Keywords: Rough set, support, strength, certainty factor, coverage factor.

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Authors: M. Graus, K. Westhoff, X. Xu

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The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: Data analytics, green production, industrial energy management, optimization, renewable energies, simulation.

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Authors: Odenigbo Veronica Ngozi, Lorreta Chika Ukwuaba

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This study focuses on how the strengthening adult literacy programs can help accelerate transformative strategies to end Female Genital Mutilation (FGM) in Nigeria, specifically in Nsukka Local Government Area of Enugu State. The research delved into the definition of FGM, adult literacy programs, and how to achieve ending FGM in order to attain Sustainable Development Goals (SDGs) in 2030. It further discussed the practice of FGM in Nigeria and emphasized the statement of the problem. Main purpose of the study was to investigate how strengthening adult literacy programs can help accelerate transformative strategies to end FGM in Nigeria and achieve SDGs in 2030. A survey research design was used to conduct the study in Nsukka L.G.A. The population was composed of 26 facilitators and adult learners in five adult learning centres in the area. The entire population was used as a sample. Structured questionnaires were employed to elicit information from the respondents. The items on the questionnaire were face-validated by three experts while the reliability of the instrument was verified using Cronbach Alpha Reliability Technique. The research questions were analysed using means and standard deviation while the hypothesis was tested at 0.05 level of degree of significance using a t-test statistics. The result of the findings shows that the practices of FGM can end through strengthening adult literacy programs. Strengthening adult literacy programs is a good channel to end or stop FGM through the knowledge and skill acquired from the learning centres. The theoretical importance of the study lies in the fact that it highlights the role of adult literacy programs in accelerating transformative strategies to combat harmful cultural practices such as FGM. It further supports the importance of education and knowledge in achieving SDGs by 2030. The study addressed the question of how strengthening adult literacy programs can help accelerate transformative strategies which can end FGM in Nigeria and achieve SDGs by 2030. In conclusion, the study revealed that adult literacy is a good tool to end FGM in Nigeria. The recommendation was that (NGOs), community-based organizations (CBOs), and individuals should support the funding and establishment of adult literacy centres in communities so as to reach all illiterate parents or individuals so that they can acquire the knowledge and skill needed to understand the negative effect of FGM in the life of a girl child.

Keywords: Adult literacy, female genital mutilation, learning centres, Sustainable Development Goals.

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Authors: Nooraneda Mutalip Laidey

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Privacy is sacred and would normally be expected and preserved by an individual. Online privacy is no longer about the right to be left alone, but also includes the right not to be monitored. However, with the revelations made by United States National Security Agency former employee Edward Snowden that the government is spying on internet communications, individuals’ privacy can no longer be expected. Therefore, this paper is intended to evaluate law related to privacy protection in the digital domain, who should govern it and whether invasion to a person’s privacy is a necessary justification to preserve national security.

Keywords: Cyberspace, data protection, national security, privacy.

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Authors: Mustafa Engin Başoğlu, Bekir Çakir

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Since large part of electricity is generated by using fossil based resources, energy is an important agenda for countries. In this context, renewable energy sources are alternative to conventional sources due to the depletion of fossil resources, increasing awareness of climate change and global warming concerns. Solar, wind and hydropower energy are the main renewable energy sources. Among of them, since installed capacity of wind power has increased approximately eight times between 2008 - November of 2014, wind energy is a promising source for Turkey. Furthermore, signing of Kyoto Protocol can be accepted as a milestone for Turkey's energy policy. Turkish Government has announced Vision 2023 (energy targets by 2023) in 2010-2014 Strategic Plan prepared by Ministry of Energy and Natural Resources (MENR). Energy targets in this plan can be summarized as follows: Share of renewable energy sources in electricity generation is 30% of total electricity generation by 2023. Installed capacity of wind energy will be 20 GW by 2023. Other renewable energy sources such as solar, hydropower and geothermal are encouraged with new incentive mechanisms. Dependence on foreign energy is reduced for sustainability and energy security. On the other hand, since Turkey is surrounded by three coastal areas, wind energy potential is convenient for wind power application. As of November of 2014, total installed capacity of wind power plants is 3.51 GW and a lot of wind power plants are under construction with capacity 1.16 GW. Turkish government also encourages the locally manufactured equipments. In this context, one of the projects funded by private sector, universities and TUBİTAK names as MILRES is an important project aimed to promote the use wind energy in electricity generation. Within this project, wind turbine with 500 kW power has been produced and will be installed at the beginning of the 2015. After that, by using the experience obtained from the first phase of the project, a wind turbine with 2.5 MW power will be manufactured in an industrial scale.

Keywords: Wind energy, wind speed, Vision 2023, MILRES (national wind energy system), wind energy potential, Turkey.

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Authors: Koko Iwan Agus Kurniawan, Dwi Purnomo, Anas Bunyamin, Arif Rahman Jaya

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Fruters model is a concept of technopreneurship-based on empowerment, in which technology research results were designed to create high value-added products and implemented as a locomotive of collaborative empowerment; thereby, the impact was widely spread. This model still needs to be inventoried and validated concerning the influenced variables in the business growth process. Model validation accompanied by mapping was required to be applicable to Small Medium Enterprises (SMEs) agro-industry based on sustainable social business and existing real cases. This research explained the empowerment model of Yourgood, an SME, which emphasized on empowering the farmers/ breeders in farmers in rural areas, Cipageran, Cimahi, to housewives in urban areas, Bandung, West Java, Indonesia. This research reviewed some works of literature discussing the agro-industrial development associated with the empowerment and social business process and gained a unique business model picture with the social business platform as well. Through the mapped business model, there were several advantages such as technology acquisition, independence, capital generation, good investment growth, strengthening of collaboration, and improvement of social impacts that can be replicated on other businesses. This research used analytical-descriptive research method consisting of qualitative analysis with design thinking approach and that of quantitative with the AHP (Analytical Hierarchy Process). Based on the results, the development of the enterprise’s process was highly affected by supplying farmers with the score of 0.248 out of 1, being the most valuable for the existence of the enterprise. It was followed by university (0.178), supplying farmers (0.153), business actors (0.128), government (0.100), distributor (0.092), techno-preneurship laboratory (0.069), banking (0.033), and Non-Government Organization (NGO) (0.031).

Keywords: Agro-Industry, small medium enterprises (SMEs), empowerment, design thinking, AHP, business model canvas, social business.

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Authors: J. Cheeneebash, V. Beeharry, A. Gopaul

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The aim of this paper is to express the input-output matrix as a linear ordering problem which is classified as an NP-hard problem. We then use a Tabu search algorithm to find the best permutation among sectors in the input-output matrix that will give an optimal solution. This optimal permutation can be useful in designing policies and strategies for economists and government in their goal of maximizing the gross domestic product.

Keywords: Input-Output matrix, linear ordering problem, Tabusearch.

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Authors: J. P. Dubois, O. M. Abdul-Latif

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Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.

Keywords: Least square-support vector machine, on-off keying, matched filter, maximum likelihood detector, wireless infrared communication.

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Authors: Sadaf Khalid, Fahim Arif

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Wide applicability of concurrent programming practices in developing various software applications leads to different concurrency errors amongst which data race is the most important. Java provides greatest support for concurrent programming by introducing various concurrency packages. Aspect oriented programming (AOP) is modern programming paradigm facilitating the runtime interception of events of interest and can be effectively used to handle the concurrency problems. AspectJ being an aspect oriented extension to java facilitates the application of concepts of AOP for data race detection. Volatile variables are usually considered thread safe, but they can become the possible candidates of data races if non-atomic operations are performed concurrently upon them. Various data race detection algorithms have been proposed in the past but this issue of volatility and atomicity is still unaddressed. The aim of this research is to propose some suggestions for incorporating certain conditions for data race detection in java programs at the volatile fields by taking into account support for atomicity in java concurrency packages and making use of pointcuts. Two simple test programs will demonstrate the results of research. The results are verified on two different Java Development Kits (JDKs) for the purpose of comparison.

Keywords: Aspect Bench Compiler (abc), Aspect OrientedProgramming (AOP), AspectJ, Aspects, Concurrency packages, Concurrent programming, Cross-cutting Concerns, Data race, Eclipse, Java, Java Development Kits (JDKs), Pointcuts

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Authors: Angelica S. Valeriani, Lorenzo Biasiolo

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In recent years, the scale of the impact of climate change and its related side effects has become ever more massive and devastating. Sustainable Development Goals (SDGs), promoted by United Nations, aim to front issues related to climate change, among others. In particular, the project CROWD4SDG focuses on a bunch of SDGs, since it promotes environmental activities and climate-related issues. In this context, we developed a prototype of an application, under advanced development considering web design, that focuses on SDG 13 (SDG on climate action) by providing users with useful instruments to face environmental crises and climate-related disasters. Our prototype is thought and structured for both web and mobile development. The main goal of the application, POLI4SDG, is to help users to get through emergency services. To this extent, an organized overview and classification prove to be very effective and helpful to people in need. A careful analysis of data related to environmental crises prompted us to integrate the user contribution, i.e. exploiting a core principle of Citizen Science, into the realization of a public catalog, available for consulting and organized according to typology and specific features. In addition, gender equality and opportunity features are considered in the prototype, in order to allow women, often the most vulnerable category, to have direct support. The overall description of the application functionalities is detailed. Moreover, implementation features and properties of the prototype are discussed.

Keywords: Crowdsourcing, social media, SDG, climate change, natural disasters, gender equality.

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Authors: C. A. Roberts, J. G. Andrae, S. R. Smith, M. H. Poore, C. A. Young, D. W. Hancock, G. J. Pent

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To the author’s best knowledge, there are no published reports of effective methods for teaching fescue toxicosis and grass endophyte technology in the USA. To address this need, a group of university scientists, industry representatives, government agents, and livestock producers formed an organization called the Alliance for Grassland Renewal. One goal of the Alliance was to develop a teaching method that could be employed across all regions in the USA and all sectors of the agricultural community. The first step in developing this method was identification of experts who were familiar with the science and management of fescue toxicosis. The second step was curriculum development. Experts wrote a curriculum that addressed all aspects of toxicosis and management, including toxicology, animal nutrition, pasture management, economics, and mycology. The curriculum was created for presentation in lectures, laboratories, and in the field. The curriculum was in that it could be delivered across state lines, regardless of peculiar, in-state recommendations. The curriculum was also unique as it was unanimously supported by private companies otherwise in competition with each other. The final step in developing this teaching method was formulating a delivery plan. All experts, including university, industry, government, and production, volunteered to travel from any state in the USA, converge in one location, teach a 1-day workshop, then travel to the next location. The results of this teaching method indicate widespread success. Since 2012, experts across the entire USA have converged to teach Alliance workshops in Kansas, Oklahoma, Missouri, Kentucky, Georgia, South Carolina, North Carolina, and Virginia, with ongoing workshops in Arkansas and Tennessee. Data from post-workshop surveys indicate that instruction has been effective, as at least 50% of the participants stated their intention to adopt the endophyte technology presented in these workshops. The teaching method developed by the Alliance for Grassland Renewal has proved to be effective, and the Alliance continues to expand across the USA.

Keywords: Endophyte, Epichloë coenophiala, ergot alkaloids, fescue toxicosis, tall fescue.

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Authors: M. Peña Aguilar Juan, Ríos Hernández Ezequiel, R. Valencia Luis

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For certification, certain goods of public interest, such as medicines and food, it is required the preparation and delivery of a dossier. For its elaboration, legal and administrative knowledge must be taken, as well as organization of the documents of the process, and an order that allows the file verification. Therefore, a virtual platform was developed to support the process of management and elaboration of the dossier, providing accessibility to the information and interfaces that allow the user to know the status of projects. The development of dossier system on the cloud allows the inclusion of the technical requirements for the software management, including the validation and the manufacturing in the field industry. The platform guides and facilitates the dossier elaboration (report, file or history), considering Mexican legislation and regulations, it also has auxiliary tools for its management. This technological alternative provides organization support for documents and accessibility to the information required to specify the successful development of a dossier. The platform divides into the following modules: System control, catalog, dossier and enterprise management. The modules are designed per the structure required in a dossier in those areas. However, the structure allows for flexibility, as its goal is to become a tool that facilitates and does not obstruct processes. The architecture and development of the software allows flexibility for future work expansion to other fields, this would imply feeding the system with new regulations.

Keywords: Electronic dossier, technologies for management, web software, dossier elaboration, pharmaceutical industry.

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Authors: Emre Kara, Ahmet F. Geylan, Kadir Koç, Şura Karakuzu, Metehan Demir, Halil Aykul

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The structures obtained with the use of sandwich technologies combine low weight with high energy absorbing capacity and load carrying capacity. Hence, there is a growing and markedly interest in the use of sandwiches with aluminum foam core because of very good properties such as flexural rigidity and energy absorption capability. In the current investigation, the static threepoint bending tests were carried out on the sandwiches with aluminum foam core and glass fiber reinforced polymer (GFRP) skins at different values of support span distances aiming the analyses of their flexural performance. The influence of the core thickness and the GFRP skin type was reported in terms of peak load and energy absorption capacity. For this purpose, the skins with two different types of fabrics which have same thickness value and the aluminum foam core with two different thicknesses were bonded with a commercial polyurethane based flexible adhesive in order to combine the composite sandwich panels. The main results of the bending tests are: force-displacement curves, peak force values, absorbed energy, collapse mechanisms and the effect of the support span length and core thickness. The results of the experimental study showed that the sandwich with the skins made of S-Glass Woven fabrics and with the thicker foam core presented higher mechanical values such as load carrying and energy absorption capacities. The increment of the support span distance generated the decrease of the mechanical values for each type of panels, as expected, because of the inverse proportion between the force and span length. The most common failure types of the sandwiches are debonding of the lower skin and the core shear. The obtained results have particular importance for applications that require lightweight structures with a high capacity of energy dissipation, such as the transport industry (automotive, aerospace, shipbuilding and marine industry), where the problems of collision and crash have increased in the last years.

Keywords: Aluminum foam, Composite panel, Flexure, Transport application.

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Authors: Srikiat Anansawat, Pitsamai Ubonsri

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The purpose of this study was to study postpartum breastfeeding mothers to determine the impact their psychosocial and spiritual dimensions play in promoting full-term (6 month duration) breastfeeding of their infants. Purposive and snowball sampling methods were used to identify and recruit the study's participants. A total of 23 postpartum mothers, who were breastfeeding within 6 weeks after giving birth, participated in this study. In-depth interviews combined with observations, participant focus groups, and ethnographic records were used for data collection. The Data were then analyzed using content analysis and typology. The results of this study illustrated that postpartum mothers experienced fear and worry that they would lack support from their spouse, family and peers, and that their infant would not get enough milk It was found that the main barrier mothers faced in breastfeeding to full-term was the difficulty of continuing to breastfeed when returning to work. 81.82% of the primiparous mothers and 91.67% of the non-primiparous mothers were able to breastfeed for the desired full-term of 6 months. Factors found to be related to breastfeeding for six months included 1) belief and faith in breastfeeding, 2) support from spouse and family members, 3) counseling from public health nurses and friends. The sample also provided evidence that religious principles such as tolerance, effort, love, and compassion to their infant, and positive thinking, were used in solving their physical, mental and spiritual problems.

Keywords: health promotion, mental health, spiritual health, breastfeeding

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Authors: J. P. Dubois, Omar M. Abdul-Latif

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Support Vector Machine (SVM) is a statistical learning tool developed to a more complex concept of structural risk minimization (SRM). In this paper, SVM is applied to signal detection in communication systems in the presence of channel noise in various environments in the form of Rayleigh fading, additive white Gaussian background noise (AWGN), and interference noise generalized as additive color Gaussian noise (ACGN). The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these advanced stochastic noise models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to conventional binary signaling optimal model-based detector driven by binary phase shift keying (BPSK) modulation. We show that the SVM performance is superior to that of conventional matched filter-, innovation filter-, and Wiener filter-driven detectors, even in the presence of random Doppler carrier deviation, especially for low SNR (signal-to-noise ratio) ranges. For large SNR, the performance of the SVM was similar to that of the classical detectors. However, the convergence between SVM and maximum likelihood detection occurred at a higher SNR as the noise environment became more hostile.

Keywords: Colour noise, Doppler shift, innovation filter, least square-support vector machine, matched filter, Rayleigh fading, Wiener filter.

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Authors: C. Ardil

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This paper presents preference programming technique based multiple criteria decision making analysis for selecting a facility location for a new organization or expansion of an existing facility which is of vital importance for a decision support system and strategic planning process. The implementation of decision support systems is considered crucial to sustain competitive advantage and profitability persistence in turbulent environment. As an effective strategic management and decision making is necessary, multiple criteria decision making analysis supports the decision makers to formulate and implement the right strategy. The investment cost associated with acquiring the property and facility construction makes the facility location selection problem a long-term strategic investment decision, which rationalize the best location selection which results in higher economic benefits through increased productivity and optimal distribution network. Selecting the proper facility location from a given set of alternatives is a difficult task, as many potential qualitative and quantitative multiple conflicting criteria are to be considered. This paper solves a facility location selection problem using preference programming, which is an effective multiple criteria decision making analysis tool applied to deal with complex decision problems in the operational research environment. The ranking results of preference programming are compared with WSM, TOPSIS and VIKOR methods.

Keywords: Facility Location Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, Preference Programming, Location Selection, WSM, TOPSIS, VIKOR

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Authors: Tibor Kulcsar, Gabor Sarossy, Gabor Bereznai, Robert Auer, Janos Abonyi

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On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.

Keywords: indexing high dimensional databases, dimensional reduction, clustering, similarity, k-nn algorithm.

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Authors: Khadiga Kahwa, Aniza Ismail

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Depression, anxiety, and stress are associated with decreased role functioning, productivity, and quality of life. International students are more prone to psychological distress as they face many stressors while studying abroad. The objectives of the study were to determine the prevalence and associated factors of depression, anxiety, and stress among international students, their help-seeking behavior, and their awareness of the available on-campus mental support services. A cross-sectional study with a purposive sampling method was performed on 280 international students at Universiti Kebangsaan Malaysia (UKM) between the age of 18 and 35 years. The Depression Anxiety Stress Scale-21 (DASS-21) questionnaire was used anonymously to assess the mental health of students. Socio-demographic, help-seeking behavior, and awareness data were obtained. Independent sample t-test, one-way ANOVA test, and multiple linear regression were used to explore associated factors. The overall prevalence of depression, anxiety, and stress among international students were 58.9%, 71.8%, and 53.9%, respectively. Age was significantly associated with depression and anxiety. Ethnicity showed a significant association with depression and stress. No other factors were found to be significantly associated with psychological distress. Only 9.6% of the international students had sought help from on-campus mental support services. Students who were aware of the presence of such services were only 21.4% of the participants. In conclusion, this study addressed the gap in the literature on the mental health of international students and provided data that could be used in intervention programs to improve the mental health of the increasing number of international students in Malaysia.

Keywords: Anxiety, depression, stress, help-seeking behavior, students.

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Authors: J. F. Arthur, R. M. Hodge

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The Defence Materials Technology Centre has evolved from the Australian Cooperative Research Centres Program. The Centre receives funding from Government, industry and research sources to fund collaborative research within its participant organisations. The research centre is structured as a company with a small administrative staff and plays the role of the “honest broker” within the collaboration. A corporate culture has been established that is pervasive into the research projects are undertaken. The model is an effective mechanism to deliver outcomes to each of the participant stakeholders.

Keywords: Collaboration, Research Centre.

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Authors: Oktia Woro Kasmini Handayani, Bambang Budi Raharjo, Efa Nugroho, Bertakalswa Hermawati

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Obesity prevalence and severe malnutrition in Indonesia has increased from 2007 to 2013. The utilization of local resources in nutritional program planning can be used to program efficiency and to reach the goal. The aim of this research is to plan a nutrition program based on local resources for urban fringe areas in a developing country. This research used a qualitative approach, with a focus on local resources including social capital, social system, cultural system. The study was conducted in Mijen, Central Java, as one of the urban fringe areas in Indonesia. Purposive and snowball sampling techniques are used to determine participants. A total of 16 participants took part in the study. Observation, interviews, focus group discussion, SWOT analysis, brainstorming and Miles and Huberman models were used to analyze the data. We have identified several local resources, such as the contributions from nutrition cadres, social organizations, social financial resources, as well as the cultural system and social system. The outstanding contribution of nutrition cadres is the participation and creativity to improve nutritional status. In addition, social organizations, like the role of the integrated health center for children (Pos Pelayanan Terpadu), can be engaged in the nutrition program planning. This center is supported by House of Nutrition to assist in nutrition program planning, and provide social support to families, neighbors and communities as social capitals. The study also reported that cultural systems that show appreciation for well-nourished children are a better way to improve the problem of balanced nutrition. Social systems such as teamwork and mutual cooperation can also be a potential resource to support nutritional programs and overcome associated problems. The impact of development in urban areas such as the introduction of more green areas which improve the perceived status of local people, as well as new health services facilitated by people and companies, can also be resources to support nutrition programs. Local resources in urban fringe areas can be used in the planning of nutrition programs. The expansion of partnership with all stakeholders, empowering the community through optimizing the roles of nutrition care centers for children as our recommendation with regard to nutrition program planning.

Keywords: Developing country, local resources, nutrition program, urban fringe.

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Authors: Ahmad Khoirul Umam

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This paper investigates the role of vested interests and its impacts on anti-corruption agenda in Indonesia following the collapse of authoritarian regime in 1998. A pervasive and rampant corruption has been believed as the main cause of the state economy’s fragility. Hence, anti-corruption measures were implemented by applying democratization and market liberalization since the establishment of a consolidated democracy which go hand in hand with a liberal market economy is convinced to be an efficacious prescription for effective anti-corruption. The reform movement has also mandated the establishment of the independent, neutral and professional special anti-corruption agency namely Corruption Eradication Commission (KPK) to more intensify the fight against the systemic corruption. This paper will examine whether these anti-corruption measures have been effective to combat corruption, and investigate to what extend have the anti-corruption efforts, especially those conducted by KPK, been impeded by the emergence of a nexus of vested interests as the side-effect of democratization and market liberalization. Based on interviews with key stakeholders from KPK, other law enforcement agencies, government, prominent scholars, journalists and NGOs in Indonesia, it is found that since the overthrow of Soeharto, anti-corruption movement in the country have become more active and serious. After gradually winning the hearth of people, KPK successfully touched the untouchable corruption perpetrators who were previously protected by political immunity, legal protection and bureaucratic barriers. However, these changes have not necessarily reduced systemic and structural corruption practices. Ironically, intensive and devastating counterattacks were frequently posed by the alignment of business actors, elites of political parties, government, and also law enforcement agencies by hijacking state’s instruments to make KPK deflated, powerless, and surrender. This paper concludes that attempts of democratization, market liberalization and the establishment of anti-corruption agency may have helped Indonesia to reduce corruption. However, it is still difficult to imply that such anti-corruption measures have fostered the more effective anti-corruption works in the newly democratized and weakly regulated liberal economic system.

Keywords: Vested interests, democratization, market liberalization, anti-corruption, leadership.

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