Search results for: methods of information culture of students

Authors: Hanh Thi My Nguyen

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The purpose of this research is to examine the experiences of parents of children who are deaf or hard of hearing in supporting their children to access education in Vietnam. Parents play a crucial role in supporting their children to gain full access to education. It was widely reported that parents of those children confronted a range of problems to support their children to access education. To author’s best knowledge, there has been a lack of research exploring the experiences of those parents in literature. This research examines factors affecting those parents in supporting their children to access education. To conduct the study, qualitative approach using a phenomenological research design was chosen to explore the central phenomena. Ten parents of children who were diagnosed as deaf or hard of hearing and aged 6-9 years were recruited through the support of the Association of Parents of Children with Hearing Impairment. Participants were interviewed via telephone with a mix of open and closed questions; interviews were audio recorded, transcribed and thematically analysed. The research results show that there are nine main factors that affected the parents in this study in making decisions relating to education for their children including: lack of information resources, perspectives of those parents on communication approaches, the families’ financial capacity, the psychological impact on the participants after their children’ diagnosis, the attitude of family members, attitude of school administrators, lack of local schools and qualified teachers, and current education system for the deaf in Vietnam. Apart from those factors, the lack of knowledge of the participants’ partners about deaf education and the partners’ employment are barriers to educational access and successful communication with their child.

Keywords: Access to education, deaf, hard of hearing, parents experience.

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Authors: Sadaf Moeez, Madiha Khalid, Zoya Khalid, Sania Shaheen, Sumbul Khalid

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Background: Inter-individual variation in response to metformin, which has been considered as a first line therapy for T2DM treatment is considerable. In the current study, it was aimed to investigate the impact of two genetic variants Leu125Phe (rs77474263) and Gly64Asp (rs77630697) in gene SLC47A1 on the clinical efficacy of metformin in T2DM Pakistani patients. Methods: The study included 800 T2DM patients (400 metformin responders and 400 metformin non-responders) along with 400 ethnically matched healthy individuals. The genotypes were determined by allele-specific polymerase chain reaction. In-silico analysis was done to confirm the effect of the two SNPs on the structure of genes. Association was statistically determined using SPSS software. Results: Minor allele frequency for rs77474263 and rs77630697 was 0.13 and 0.12. For SLC47A1 rs77474263 the homozygotes of one mutant allele ‘T’ (CT) of rs77474263 variant were fewer in metformin responders than metformin non-responders (29.2% vs. 35.5 %). Likewise, the efficacy was further reduced (7.2% vs. 4.0 %) in homozygotes of two copies of ‘T’ allele (TT). Remarkably, T2DM cases with two copies of allele ‘C’ (CC) had 2.11 times more probability to respond towards metformin monotherapy. For SLC47A1 rs77630697 the homozygotes of one mutant allele ‘A’ (GA) of rs77630697 variant were fewer in metformin responders than metformin non-responders (33.5% vs. 43.0 %). Likewise, the efficacy was further reduced (8.5% vs. 4.5%) in homozygotes of two copies of ‘A’ allele (AA). Remarkably, T2DM cases with two copies of allele ‘G’ (GG) had 2.41 times more probability to respond towards metformin monotherapy. In-silico analysis revealed that these two variants affect the structure and stability of their corresponding proteins. Conclusion: The present data suggest that SLC47A1 Leu125Phe (rs77474263) and Gly64Asp (rs77630697) polymorphisms were associated with the therapeutic response of metformin in T2DM patients of Pakistan.

Keywords: Diabetes, T2DM, SLC47A1, Pakistan, polymorphism.

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Authors: H. Heidari-Bafroui, B. Ribeiro, A. Charbaji, C. Anagnostopoulos, M. Faghri

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In this paper, we report the development of a portable and inexpensive infrared lightbox for improving the detection limits of paper-based phosphate devices. Commercial paper-based devices utilize the molybdenum blue protocol to detect phosphate in the environment. Although these devices are easy to use and have a long shelf life, their main deficiency is their low sensitivity based on the qualitative results obtained via a color chart. To improve the results, we constructed a compact infrared lightbox that communicates wirelessly with a smartphone. The system measures the absorbance of radiation for the molybdenum blue reaction in the infrared region of the spectrum. It consists of a lightbox illuminated by four infrared light-emitting diodes, an infrared digital camera, a Raspberry Pi microcontroller, a mini-router, and an iPhone to control the microcontroller. An iPhone application was also developed to analyze images captured by the infrared camera in order to quantify phosphate concentrations. Additionally, the app connects to an online data center to present a highly scalable worldwide system for tracking and analyzing field measurements. In this study, the detection limits for two popular commercial devices were improved by a factor of 4 for the Quantofix devices (from 1.3 ppm using visible light to 300 ppb using infrared illumination) and a factor of 6 for the Indigo units (from 9.2 ppm to 1.4 ppm) with repeatability of less than or equal to 1.2% relative standard deviation (RSD). The system also provides more granular concentration information compared to the discrete color chart used by commercial devices and it can be easily adapted for use in other applications.

Keywords: Infrared lightbox, paper-based device, phosphate detection, smartphone colorimetric analyzer.

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: credit card fraud detection, user authentication, behavioral biometrics, machine learning, literature survey

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Authors: R. May, K. Jinno, I. Yusoff

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The paper aims at evaluating the effects of heavy groundwater withdrawal and artificial groundwater recharge of an ex-mining pond to the aquifer system of the Langat Basin through the three-dimensional (3D) numerical modeling. Many mining sites have been left behind from the massive mining exploitations in Malaysia during the England colonization era and from the last few decades. These sites are able to accommodate more than a million cubic meters of water from precipitation, runoff, groundwater, and river. Most of the time, the mining sites are turned into ponds for recreational activities. In the current study, an artificial groundwater recharge from an ex-mining pond in the Langat Basin was proposed due to its capacity to store >50 million m3 of water. The location of the pond is near the Langat River and opposite a steel company where >4 million gallons of groundwater is withdrawn on a daily basis. The 3D numerical simulation was developed using the Groundwater Modeling System (GMS). The calibrated model (error about 0.7 m) was utilized to simulate two scenarios (1) Case 1: artificial recharge pond with no pumping and (2) Case 2: artificial pond with pumping. The results showed that in Case 1, the pond played a very important role in supplying additional water to the aquifer and river. About 90,916 m3/d of water from the pond, 1,173 m3/d from the Langat River, and 67,424 m3/d from the direct recharge of precipitation infiltrated into the aquifer system. In Case 2, due to the abstraction of groundwater from a company, it caused a steep depression around the wells, river, and pond. The result of the water budget showed an increase rate of inflow in the pond and river with 92,493m3/d and 3,881m3/d respectively. The outcome of the current study provides useful information of the aquifer behavior of the Langat Basin.

Keywords: Groundwater and surface water interaction, groundwater modeling, GMS, artificial recharge pond, ex-mining site.

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Authors: Daohong Yang, Xiang Zhang, Wanting Zhou, Lei Li

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Visual Simultaneous Localization and Mapping (VSLAM) is a technology that gathers information about the surrounding environment to ascertain its own position and create a map. It is widely used in computer vision, robotics, and various other fields. Many visual SLAM systems, such as OBSLAM3, utilize a constant velocity motion model. The utilization of this model facilitates the determination of the initial pose of the current frame, thereby enhancing the efficiency and precision of feature matching. However, it is often difficult to satisfy the constant velocity motion model in actual situations. This can result in a significant deviation between the obtained initial pose and the true value, leading to errors in nonlinear optimization results. Therefore, this paper proposes a motion model based on acceleration that can be applied to most SLAM systems. To provide a more accurate description of the camera pose acceleration, we separate the pose transformation matrix into its rotation matrix and translation vector components. The rotation matrix is now represented by a rotation vector. We assume that, over a short period, the changes in rotating angular velocity and translation vector remain constant. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of the constant velocity model is analyzed theoretically. Finally, we apply our proposed approach to the ORBSLAM3 system and evaluate two sets of sequences from the TUM datasets. The results show that our proposed method has a more accurate initial pose estimation, resulting in an improvement of 6.61% and 6.46% in the accuracy of the ORBSLAM3 system on the two test sequences, respectively.

Keywords: Error estimation, constant acceleration motion model, pose estimation, visual SLAM.

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Authors: Daniel Murrant, Andrew Quinn, Lee Chapman

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A growing population has led to increasing global water and energy demand. This demand, combined with the effects of climate change and an increasing need to maintain and protect the natural environment, represents a potentially severe threat to many national infrastructure systems. This has resulted in a considerable quantity of published material on the interdependencies that exist between the supply of water and the thermal generation of electricity, often known as the water-energy nexus. Focusing specifically on the UK, there is a growing concern that the future availability of water may at times constrain thermal electricity generation, and therefore hinder the UK in meeting its increasing demand for a secure, and affordable supply of low carbon electricity. To provide further information on the threat the water-energy nexus may pose to the UK’s energy system, this paper models the regional water demand of UK thermal electricity generation in 2030 and 2050. It uses the strategically important Energy Systems Modelling Environment model developed by the Energy Technologies Institute. Unlike previous research, this paper was able to use abstraction and consumption factors specific to UK power stations. It finds that by 2050 the South East, Yorkshire and Humber, the West Midlands and North West regions are those with the greatest freshwater demand and therefore most likely to suffer from a lack of resource. However, it finds that by 2050 it is the East, South West and East Midlands regions with the greatest total water (fresh, estuarine and seawater) demand and the most likely to be constrained by environmental standards.

Keywords: Water-energy nexus, water resources, abstraction, climate change, power station cooling.

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Authors: S. Huber, B. Schnalzer, B. Alcalde, S. Hanke, L. Mpaltadoros, T. G. Stavropoulos, S. Nikolopoulos, I. Kompatsiaris, L. Pérez-Breva, V. Rodrigo-Casares, J. Fons-Martínez, J. de Bruin

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Developing new medicine and health solutions and improving patient health currently rely on the successful execution of clinical trials, which generate relevant safety and efficacy data. For their success, recruitment and retention of participants are some of the most challenging aspects of protocol adherence. Main barriers include: i) lack of awareness of clinical trials; ii) long distance from the clinical site; iii) the burden on participants, including the duration and number of clinical visits, and iv) high dropout rate. Most of these aspects could be addressed with a new paradigm, namely the Remote Decentralized Clinical Trials (RDCTs). Furthermore, the COVID-19 pandemic has highlighted additional advantages and challenges for RDCTs in practice, allowing participants to join trials from home and not depending on site visits, etc. Nevertheless, RDCTs should follow the process and the quality assurance of conventional clinical trials, which involve several processes. For each part of the trial, the Building Blocks, existing software and technologies were assessed through a systematic search. The technology needed to perform RDCTs is widely available and validated but is yet segmented and developed in silos, as different software solutions address different parts of the trial and at various levels. The current paper is analyzing the availability of technology to perform RDCTs, identifying gaps and providing an overview of Basic Building Blocks and functionalities that need to be covered to support the described processes.

Keywords: architectures and frameworks for health informatics systems, clinical trials, information and communications technology, remote decentralized clinical trials, technology availability

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Authors: Mei-Fang Wu, Shu-Li Wang, Feng-Tsung Cheng

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Highly developed technology and highly competitive global market highlight the important role of competitive advantages and operation performances in sustainable company operation. Activity-Based Costing (ABC) provides accurate operation cost and operation performance information. Rich literatures provide relevant research with cases study on Activity-Based Costing application, but the research on cause relationship between key success factors and its specific outcome, such as profitability or share market are few. These relationships provide the ways to handle the key success factors to achieve the specific outcomes for ensuring to promote the competitive advantages and operation performances. The main purposes of this research are exploring the key success paths by Key Success Paths approach which will lead the ways to apply Activity-Base Costing. The Key Success Paths is the innovative method which is exploring the cause relationships and explaining what are the effects of key success factors to specific outcomes of Activity-Based Costing implementation. The cause relationships between key success factors and successful specific outcomes are Key Success Paths (KSPs). KSPs are the guidelines to lead the cost management strategies to achieve the goals of competitive advantages and operation performances. The research findings indicate that good management system design may affect the well outcomes of Activity-Based Costing application and achieve to outstanding competitive advantage, operating performance and profitability as well by KSPs exploration.

Keywords: Activity-Based Costing, Key success factors, Key success paths approach, Key success paths, Key failure paths.

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Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

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Recent advances in cognitive neuroscience have allowed a step forward in perceiving the processes involved in learning from the point of view of acquiring new information or the modification of existing mental content. The evoked potentials technique reveals how basic brain processes interact to achieve adequate and flexible behaviours. The objective of this work, using evoked potentials, is to study if it is possible to distinguish if a patient suffers a specific type of learning disorder to decide the possible therapies to follow. The methodology used in this work is to analyze the dynamics of different brain areas during a cognitive activity to find the relationships between the other areas analyzed to understand the functioning of neural networks better. Also, the latest advances in neuroscience have revealed the exis-tence of different brain activity in the learning process that can be highlighted through the use of non-invasive, innocuous, low-cost and easy-access techniques such as, among others, the evoked potentials that can help to detect early possible neurodevelopmental difficulties for their subsequent assessment and therapy. From the study of the amplitudes and latencies of the evoked potentials, it is possible to detect brain alterations in the learning process, specifically in dyscalculia, to achieve specific corrective measures for the application of personalized psycho-pedagogical plans that allow obtaining an optimal integral development of the affected people.

Keywords: dyscalculia, neurodevelopment, evoked potentials, learning disabilities, neural networks

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Authors: A. Banovcinova, M. Zakova

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Labor market activity and paid employment should be a key factor in protecting individuals and families from falling into poverty and providing them with sufficient resources to meet the needs of their members. However, due to various processes in the labor market as well as the influence of individual factors and often insufficient social capital, there is a relatively large group of households that cannot eliminate paid employment and find themselves in a state of so-called working poverty. The aim of the research was to find out what strategies families use in managing poverty and meeting their needs and which of these strategies prevail in the Slovak population. A quantitative research strategy was chosen. The method of data collection was a structured interview focused on finding out the use of individual management strategies and also selected demographic indicators. The research sample consisted of members of families in which at least one member has a paid job. The condition for inclusion in the research was that the family's income did not exceed 60% of the national median equalized disposable income. The analysis of the results showed 5 basic areas to which management strategies are related - work, financial security, needs, social contacts and perception of the current situation. The prevailing strategies were strategies aimed at increasing and streamlining labor market activity and the planned and effective management of the family budget. Strategies that were rejected were mainly related to debt creation. The results make it possible to identify the preferred ways of managing poverty in individual areas of life, as well as the factors that influence this behavior. This information is important for working with families living in a state of working poverty and can help professionals develop positive ways of coping for families.

Keywords: Copying strategies, family, in-work poverty, quantitative research.

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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The problems arising from unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many researchers have found that the performance of existing classifiers tends to be biased towards the majority class. The k-nearest neighbors’ nonparametric discriminant analysis is a method that was proposed for classifying unbalanced classes with good performance. In this study, the methods of discriminant analysis are of interest in investigating misclassification error rates for classimbalanced data of three diabetes risk groups. The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification of class-imbalanced data of diabetes risk groups. Data from a project maintaining healthy conditions for 599 employees of a government hospital in Bangkok were obtained for the classification problem. The employees were divided into three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data including the variables of diabetes risk group, age, gender, blood glucose, and BMI were analyzed and bootstrapped for 50 and 100 samples, 599 observations per sample, for additional estimation of the misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples showed nonnormality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. Searching the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10) and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k=3 or k=4 and the defined prior probabilities of non-risk: risk: diabetic as 0.90: 0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of misclassification. The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: Bootstrap, diabetes risk groups, error rate, k-nearest neighbors.

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Authors: Ademuyiwa, M. O., Sanni, S. A.

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The importance of maternal nutritional practices during pregnancy cannot be overemphasized. This paper assessed the consumption pattern and dietary practices of 50 pregnant women selected using purposive sampling technique from three health care centres (Primary Health Care Centre, Obantoko; Primary Health Care Centre Alabata; and the General Hospital, Odeda) in Odeda Local Government Area of Ogun State, Nigeria. Structured questionnaire was used to elicit information on socioeconomic status, consumption pattern and dietary practices. Data were analyzed using the Statistical Package for Social Sciences (SPSS, 17). The results indicated that about 58% of the pregnant women were below the age of 30 while 42% were ages 28-40 years. Only 16% had tertiary education while (38%) had secondary education, 52% earn income through petty trading. On food intake, 52% got their energy source from rice on a daily basis, followed by pap (38%) and eko (34%). For protein intake, 36% consumed bean cake on a daily basis while 66% consumed moinmoin 2-3 times a week. Orange (48%) and Green Leafy vegetable (40%) accounted for the mostly consumed fruit and vegetable on daily basis. In terms of animal origin, fish (76%), meat (58%) and eggs (30%) were consumed daily, while chicken and snail were consumed occasionally by 54% and 42%, respectively. Forty-six percent (46%) of the pregnant women eat more than three times daily; while 60% of the women eat outside their homes with 42% respondents eat out lunch and only two percent least eaten out dinner. It is important to increase in awareness campaign to sensitize the pregnant women on the importance of good nutrition especially fruits, vegetables and dairy products. 

Keywords: Consumption Pattern, Dietary Practices, Pregnant, Women, Nigeria.

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Authors: A. A. Njoh, S. T. Ndoula, A. Adidja, G. N. Menan, A. Mengue, E. Mboke, H. B. Bachir, S. C. Nchinjoh, L. Adisso, Y. Saidu, L. Cleenewerck de Kiev

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Vaccines serve a great deal in protecting the population globally. Vaccine products are subject to rigorous quality control and approval before use to ensure safety. Even if all actors take the required precautions, some people could still have adverse events following immunization (AEFI) caused by the vaccine composition or an error in its administration. AEFI underreporting is pronounced in low-income settings like Cameroon. The Country introduced electronic platforms to strengthen surveillance. With the introduction of many novel vaccines, like COVID-19 and the novel Oral Polio Vaccine (nOPV) 2, there was a need to monitor AEFI in Cameroon. A cross-sectional study was conducted from July to December 2022. Data on AEFI per region of Cameroon were reviewed for the previous five years. Data were analyzed with MS Excel, and the results were presented in proportions. AEFI reporting was uncommon in Cameroon. With the introduction of novel vaccines in 2021, the health authorities engaged in new tools and training to capture cases. AEFI detected almost doubled using the open data kit (ODK) compared to previous platforms, especially following the introduction of the nOPV2 and COVID-19 vaccines. The AEFI rate was 1.9 and 160 per administered 100,000 doses of nOPV2 and COVID-19 vaccines, respectively. This mobile tool captured individual information for people with AEFI from all regions. The platform helped to identify common AEFI following the use of these new vaccines. The ODK mobile technology was vital in improving AEFI reporting and providing data to monitor the use of new vaccines in Cameroon.

Keywords: Adverse events following immunization, AEFI, Cameroon, COVID-19 vaccines, novel oral polio vaccine 2, open data kit.

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Authors: Serkan Solmaz, Jean-Baptiste Gouriet, Nicolas Van de Wyer, Christophe Schram

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Efficiency of the cooling process for cryogenic propellant boiling in engine cooling channels on space applications is relentlessly affected by the phase change occurs during the boiling. The effectiveness of the cooling process strongly pertains to the type of the boiling regime such as nucleate and film. Geometric constraints like a non-transparent cooling channel unable to use any of visualization methods. The ultrasonic (US) technique as a non-destructive method (NDT) has therefore been applied almost in every engineering field for different purposes. Basically, the discontinuities emerge between mediums like boundaries among different phases. The sound wave emitted by the US transducer is both transmitted and reflected through a gas-liquid interface which makes able to detect different phases. Due to the thermal and structural concerns, it is impractical to sustain a direct contact between the US transducer and working fluid. Hence the transducer should be located outside of the cooling channel which results in additional interfaces and creates ambiguities on the applicability of the present method. In this work, an exploratory research is prompted so as to determine detection ability and applicability of the US technique on the cryogenic boiling process for a cooling cycle where the US transducer is taken place outside of the channel. Boiling of the cryogenics is a complex phenomenon which mainly brings several hindrances for experimental protocol because of thermal properties. Thus substitute materials are purposefully selected based on such parameters to simplify experiments. Aside from that, nucleate and film boiling regimes emerging during the boiling process are simply simulated using non-deformable stainless steel balls, air-bubble injection apparatuses and air clearances instead of conducting a real-time boiling process. A versatile detection algorithm is perennially developed concerning exploratory studies afterward. According to the algorithm developed, the phases can be distinguished 99% as no-phase, air-bubble, and air-film presences. The results show the detection ability and applicability of the US technique for an exploratory purpose.

Keywords: Ultrasound, ultrasonic, multiphase flow, boiling, cryogenics, detection algorithm.

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Authors: Yudhajit Datta, Jonathan Bandi, Ankit Sethia, Hamsi Iyer

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Motion Tracking and Stereo Vision are complicated, albeit well-understood problems in computer vision. Existing softwares that combine the two approaches to perform stereo motion tracking typically employ complicated and computationally expensive procedures. The purpose of this study is to create a simple and effective solution capable of combining the two approaches. The study aims to explore a strategy to combine the two techniques of two-dimensional motion tracking using Kalman Filter; and depth detection of object using Stereo Vision. In conventional approaches objects in the scene of interest are observed using a single camera. However for Stereo Motion Tracking; the scene of interest is observed using video feeds from two calibrated cameras. Using two simultaneous measurements from the two cameras a calculation for the depth of the object from the plane containing the cameras is made. The approach attempts to capture the entire three-dimensional spatial information of each object at the scene and represent it through a software estimator object. In discrete intervals, the estimator tracks object motion in the plane parallel to plane containing cameras and updates the perpendicular distance value of the object from the plane containing the cameras as depth. The ability to efficiently track the motion of objects in three-dimensional space using a simplified approach could prove to be an indispensable tool in a variety of surveillance scenarios. The approach may find application from high security surveillance scenes such as premises of bank vaults, prisons or other detention facilities; to low cost applications in supermarkets and car parking lots.

Keywords: Kalman Filter, Stereo Vision, Motion Tracking, Matlab, Object Tracking, Camera Calibration, Computer Vision System Toolbox.

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Authors: G. Disciglio, G. Gatta, F. Lops, A. Libutti, A. Tarantino, E. Tarantino

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The experimental trial was carried out in open field at Foggia district (Apulia Region, Southern Italy), during the spring-summer season 2014, in order to evaluate the effect of four biostimulant products (RadiconÒ, Viormon plusÒ, LysodinÒ and SiaptonÒ 10L), compared with a control (no biostimulant), on the infestation of processing tomato crop (cv Dres) by the chlorophyll-lacking root parasite Phelipanche ramosa. Biostimulants consist in different categories of products (microbial inoculants, humic and fulvic acids, hydrolyzed proteins and aminoacids, seaweed extracts) which play various roles in plant growing, including the improvement of crop resistance and quali-quantitative characteristics of yield. The experimental trial was arranged according to a complete randomized block design with five treatments, each of one replicated three times. The processing tomato seedlings were transplanted on 5 May 2014. Throughout the crop cycle, P. ramosa infestation was assessed according to the number of emerged shoots (branched plants) counted in each plot, at 66, 78 and 92 day after transplanting. The tomato fruits were harvested at full-stage of maturity on 8 August 2014. From each plot, the marketable yield was measured and the quali-quantitative yield parameters (mean weight, dry matter content, colour coordinate, colour index and soluble solids content of the fruits) were determined. The whole dataset was tested according to the basic assumptions for the analysis of variance (ANOVA) and the differences between the means were determined using Tukey’s tests at the 5% probability level. The results of the study showed that none of the applied biostimulants provided a whole control of Phelipanche, although some positive effects were obtained from their application. To this respect, the RadiconÒ appeared to be the most effective in reducing the infestation of this root-parasite in tomato crop. This treatment also gave the higher tomato yield.

Keywords: Biostimulants, control methods, Phelipanche ramosa, processing tomato crop.

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Authors: Y. Harold Robinson, M. Rajaram

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Wireless mesh networking is rapidly gaining in popularity with a variety of users: from municipalities to enterprises, from telecom service providers to public safety and military organizations. This increasing popularity is based on two basic facts: ease of deployment and increase in network capacity expressed in bandwidth per footage; WMNs do not rely on any fixed infrastructure. Many efforts have been used to maximizing throughput of the network in a multi-channel multi-radio wireless mesh network. Current approaches are purely based on either static or dynamic channel allocation approaches. In this paper, we use a hybrid multichannel multi radio wireless mesh networking architecture, where static and dynamic interfaces are built in the nodes. Dynamic Adaptive Channel Allocation protocol (DACA), it considers optimization for both throughput and delay in the channel allocation. The assignment of the channel has been allocated to be codependent with the routing problem in the wireless mesh network and that should be based on passage flow on every link. Temporal and spatial relationship rises to re compute the channel assignment every time when the pattern changes in mesh network, channel assignment algorithms assign channels in network. In this paper a computing path which captures the available path bandwidth is the proposed information and the proficient routing protocol based on the new path which provides both static and dynamic links. The consistency property guarantees that each node makes an appropriate packet forwarding decision and balancing the control usage of the network, so that a data packet will traverse through the right path.

Keywords: Wireless mesh network, spatial time division multiple access, hybrid topology, timeslot allocation.

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: Autonomous vehicles, deformable part model, dpm, pedestrian recognition.

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: Benchmark collection, program educational objectives, student outcomes, ABET, Accreditation, machine learning, supervised multiclass classification, text mining.

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: Political tendency, prediction, sentiment analysis, Twitter.

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Authors: Saimir Heta, Kers Kapaj, Rialda Xhizdari, Ilma Robo

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Dealing with emerging cases of dental malpractice with justifications that stem from the clear rules of dental ethics is a phenomenon with an increasing trend in today's dental practice. Dentists should clearly understand how far the limit of malpractice goes, with or without minimal or major consequences, for the affected patient, which can be justified as a complication of dental treatment, in support of the rules of dental ethics in the dental office. Indeed, malpractice can occur in cases of lack of professionalism, but it can also come as a consequence of anatomical and physiological limitations in the implementation of the dental protocols, predetermined and indicated by the patient in the paragraph of the treatment plan in his personal card. Let this article serve as a short communication between readers and interested parties about the problems that dental malpractice can bring to the community. Malpractice should not be seen only as a professional wrong approach, but also as a phenomenon that can occur during dental practice. The aim of this article is presentation of the latest data published in the literature about malpractice. The combination of keywords is done in such a way with the aim to give the necessary space for collecting the right information in the networks of publications about this field, always first from the point of view of the dentist and not from that of the lawyer or jurist. From the findings included in this article, it was noticed that the diversity of approaches towards the phenomenon depends on the different countries based on the legal basis that these countries have. There is a lack of or a small number of articles that touch on this topic, and these articles are presented with a limited amount of data on the same topic. Dental malpractice should not be hidden under the guise of various dental complications that we justify with the strict rules of ethics for patients treated in the dental chair. The individual experience of dental malpractice must be published with the aim of serving as a source of experience for future generations of dentists.

Keywords: Dental ethics, malpractice, professional protocol, random deviation, dental tourism.

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Authors: Ah-young Jeon, In-cheol Kim, Jae-hee Jung, Soo-young Ye, Jae-hyung Kim, Ki-gon Nam, Seoung-wan Baik, Jung-hoon Ro, Gye-rok Jeon

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The aged are faced with increasing risk for falls. The aged have the easily fragile bones than others. When falls have occurred, it is important to detect this emergency state because such events often lead to more serious illness or even death. A implementation of PDA system, for detection of emergency situation, was developed using 3-axis accelerometer in this paper as follows. The signals were acquired from the 3-axis accelerometer, and then transmitted to the PDA through Bluetooth module. This system can classify the human activity, and also detect the emergency state like falls. When the fall occurs, the system generates the alarm on the PDA. If a subject does not respond to the alarm, the system determines whether the current situation is an emergency state or not, and then sends some information to the emergency center in the case of urgent situation. Three different studies were conducted on 12 experimental subjects, with results indicating a good accuracy. The first study was performed to detect the posture change of human daily activity. The second study was performed to detect the correct direction of fall. The third study was conducted to check the classification of the daily physical activity. Each test was lasted at least 1 min. in third study. The output of acceleration signal was compared and evaluated by changing a various posture after attaching a 3-axis accelerometer module on the chest. The newly developed system has some important features such as portability, convenience and low cost. One of the main advantages of this system is that it is available at home healthcare environment. Another important feature lies in low cost to manufacture device. The implemented system can detect the fall accurately, so will be widely used in emergency situation.

Keywords: Alarm System, Ambulatory monitoring, Emergency detection, Classification of activity, and 3-axis accelerometer.

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Authors: M. F. Nawaz, S. Gul, T. H. Farooq, M. T. Siddiqui, M. Asif, I. Ahmad, N. K. Niazi

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In Pakistan, major demands of fuel wood and timber wood are fulfilled by agroforestry. However, the information regarding economic significance of agroforestry and its productivity in Pakistan is still insufficient and unreliable. Survey of field conditions to examine the agroforestry status at local level helps us to know the future trends and to formulate the policies for sustainable wood supply. The objectives of this research were to examine the actual status and potential of agroforestry and to point out the barriers that are faced by farmers in the adoption of agroforestry. Research was carried out in Chiniot district, Pakistan because it is the famous city for furniture industry that is largely dependent on farm trees. A detailed survey of district Chiniot was carried out from 150 randomly selected farmer respondents using multi-objective oriented and pre-tested questionnaire. It was found that linear tree planting method was more adopted (45%) as compared to linear + interplanting (42%) and/or compact planting (12.6%). Chi-square values at P-value <0.5 showed that age (11.35) and education (17.09) were two more important factors in the quick adoption of agroforestry as compared to land holdings (P-value of 0.7). The major reason of agroforestry adoption was to obtain income, fodder and fuelwood. The most dominant species in farmlands was shisham (Dalbergia sissoo) but since last five years, mostly farmers were growing Sufeida (Eucalyptus camaldulensis), kikar (Acacia nilotica) and popular (Populus deltoides) on their fields due to “Shisham die-back” problem. It was found that agro-forestry can be increased by providing good quality planting material to farmers and improving wood markets.

Keywords: Agroforestry, trees, services, agriculture, farmers.

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Authors: Selvam M, Natarajan. A M, Thangarajan R

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Parsing is important in Linguistics and Natural Language Processing to understand the syntax and semantics of a natural language grammar. Parsing natural language text is challenging because of the problems like ambiguity and inefficiency. Also the interpretation of natural language text depends on context based techniques. A probabilistic component is essential to resolve ambiguity in both syntax and semantics thereby increasing accuracy and efficiency of the parser. Tamil language has some inherent features which are more challenging. In order to obtain the solutions, lexicalized and statistical approach is to be applied in the parsing with the aid of a language model. Statistical models mainly focus on semantics of the language which are suitable for large vocabulary tasks where as structural methods focus on syntax which models small vocabulary tasks. A statistical language model based on Trigram for Tamil language with medium vocabulary of 5000 words has been built. Though statistical parsing gives better performance through tri-gram probabilities and large vocabulary size, it has some disadvantages like focus on semantics rather than syntax, lack of support in free ordering of words and long term relationship. To overcome the disadvantages a structural component is to be incorporated in statistical language models which leads to the implementation of hybrid language models. This paper has attempted to build phrase structured hybrid language model which resolves above mentioned disadvantages. In the development of hybrid language model, new part of speech tag set for Tamil language has been developed with more than 500 tags which have the wider coverage. A phrase structured Treebank has been developed with 326 Tamil sentences which covers more than 5000 words. A hybrid language model has been trained with the phrase structured Treebank using immediate head parsing technique. Lexicalized and statistical parser which employs this hybrid language model and immediate head parsing technique gives better results than pure grammar and trigram based model.

Keywords: Hybrid Language Model, Immediate Head Parsing, Lexicalized and Statistical Parsing, Natural Language Processing, Parts of Speech, Probabilistic Context Free Grammar, Tamil Language, Tree Bank.

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Authors: Abdulkareem Hussein Bibire

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Job satisfaction and motivation have been given an important attention in psychology because they are seen as main instruments in maintaining organizational growth and development; they are also used to accomplish organizational aims and objectives. However, it has been observed that some institutions failed in motivating and stimulating their workers; in contrast, workers may be motivated but not satisfied with the job and failed to perform efficiently and effectively. It is hoped that the study of this nature would be of significance value to all stakeholders in education specifically, lecturers in higher institutions in Nigeria. Also, it is hoped that the findings of this study will enhance lecturers’ effectiveness and performance in discharging their duties. In the light of the above statements, this study investigated whether job satisfaction and motivation predict lecturers’ effectiveness in Nigeria Police Academy, Wudil, Kano State. Correlational research method was adopted for the study, while purposive sampling technique was used to choose the institution and the sampled lectures (70). Simple random sampling technique was used to select one hundred cadets across the academy. Two instruments were used to elicit information from both lecturers and cadets. These were job satisfaction and motivation; and lecturers’ effectiveness Questionnaires. The instruments were subjected to pilot testing and found to have reliability coefficient of 0.69 and 0.71 respectively. The results of the study revealed that there was a significance relationship among job satisfaction, motivation and lecturers effectiveness in Nigeria Police Academy. There was a significance relationship between job satisfaction and lecturers’ effectiveness in Nigeria Police Academy the cal r is 0.21 while the crt r is 0.19. at p<0.05 and; there was a significance relationship between job motivation and lecturers effectiveness in Nigeria Police Academy the cal r is 0.20 while the crt r is 0.19 at p<0.05This study therefore concluded that there was a significance relationship among job satisfaction, motivation and lecturers effectiveness in Nigeria Police Academy. Based on the data collected, collated and analyzed Recommendations were made for both the lecturers and the Academy management. It is also suggested that lecturers should be industrious in their primary assignment in other to make values to cadets lives and career. And management should also try to enhance lecturers performance by more motivational needs for the lecturers.

Keywords: Satisfaction, motivation, lecturer effectiveness, academy.

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Authors: Daehwan Kim, Jaemin Kim, Seongwon Cho, Yongsuk Jang, Sun-Tae Chung, Boo-Gyoun Kim

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AAM has been successfully applied to face alignment, but its performance is very sensitive to initial values. In case the initial values are a little far distant from the global optimum values, there exists a pretty good possibility that AAM-based face alignment may converge to a local minimum. In this paper, we propose a progressive AAM-based face alignment algorithm which first finds the feature parameter vector fitting the inner facial feature points of the face and later localize the feature points of the whole face using the first information. The proposed progressive AAM-based face alignment algorithm utilizes the fact that the feature points of the inner part of the face are less variant and less affected by the background surrounding the face than those of the outer part (like the chin contour). The proposed algorithm consists of two stages: modeling and relation derivation stage and fitting stage. Modeling and relation derivation stage first needs to construct two AAM models: the inner face AAM model and the whole face AAM model and then derive relation matrix between the inner face AAM parameter vector and the whole face AAM model parameter vector. In the fitting stage, the proposed algorithm aligns face progressively through two phases. In the first phase, the proposed algorithm will find the feature parameter vector fitting the inner facial AAM model into a new input face image, and then in the second phase it localizes the whole facial feature points of the new input face image based on the whole face AAM model using the initial parameter vector estimated from using the inner feature parameter vector obtained in the first phase and the relation matrix obtained in the first stage. Through experiments, it is verified that the proposed progressive AAM-based face alignment algorithm is more robust with respect to pose, illumination, and face background than the conventional basic AAM-based face alignment algorithm.

Keywords: Face Alignment, AAM, facial feature detection, model matching.

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: Interactive dashboards, optical fibers, structural health monitoring, visual analytics.

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Authors: Jinhwan Yu, Jooyeon Yook

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After Apple's first introduction its smart phone, iPhone in the end of 2009 in Korea, the number of Korean smarphone users had been rapidly increasing so that the half of Korean population became smart phone users as of February, 2012. Currently, smart phones are positioned as a major digital media with powerful influences in Korea. And, now, Koreans are leaning new information, enjoying games and communicating other people every time and everywhere. As smart phone devices' performances increased, the number of usable services became more while adequate GUI developments are required to implement various functions with smart phones. The strategy to provide similar experiences on smart phones through familiar features based on employment of existing media's functions mostly contributed to smart phones' popularization in connection with smart phone devices' iconic GUIs. The spread of Smart phone increased mobile web accesses. Therefore, the attempts to implement PC's web in the smart phone's web are continuously made. The mobile web GUI provides familiar experiences to users through designs adequately utilizing the smart phone's GUIs. As the number of users familiarized to smart phones and mobile web GUIs, opposite to reversed remediation from many parts of PCs, PCs are starting to adapt smart phone GUIs. This study defines this phenomenon as the reversed remediation, and reviews the reversed remediation cases of Smart phone GUI' characteristics of PCs. For this purpose, the established study issues are as under: · what is the reversed remediation? · what are the smart phone GUI's characteristics? · what kind of interrelationship exist s between the smart phone and PC's web site? It is meaningful in the forecast of the future GUI's change by understanding of characteristics in the paradigm changes of PC and smart phone's GUI designs. This also will be helpful to establish strategies for digital devices' development and design.

Keywords: Graphic User Interface, Remediation, Smart Phone, South Korea, Web Site

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Authors: May Paing Paing Zaw, Su Myat Marlar Soe

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Network Management Systems have played a great important role in information systems. Management is very important and essential in any fields. There are many managements such as configuration management, fault management, performance management, security management, accounting management and etc. Among them, configuration, fault and security management is more important than others. Because these are essential and useful in any fields. Configuration management is to monitor and maintain the whole system or LAN. Fault management is to detect and troubleshoot the system. Security management is to control the whole system. This paper intends to increase the network management functionalities including configuration management, fault management and security management. In configuration management system, this paper specially can support the USB ports and devices to detect and read devices configuration and solve to detect hardware port and software ports. In security management system, this paper can provide the security feature for the user account setting and user management and proxy server feature. And all of the history of the security such as user account and proxy server history are kept in the java standard serializable file. So the user can view the history of the security and proxy server anytime. If the user uses this system, the user can ping the clients from the network and the user can view the result of the message in fault management system. And this system also provides to check the network card and can show the NIC card setting. This system is used RMI (Remote Method Invocation) and JNI (Java Native Interface) technology. This paper is to implement the client/server network management system using Java 2 Standard Edition (J2SE). This system can provide more than 10 clients. And then this paper intends to show data or message structure of client/server and how to work using TCP/IP protocol.

Keywords: TCP/ IP based client server application

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