Search results for: difficulty score

Authors: Stephanie Lehmann, Esther Ruf, Sabina Misoch

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Background: Due to demographic change and shortage of skilled nursing staff, assistive robots are built to support older adults at home and nursing staff in care institutions. When assistive robots facilitate tasks that are usually performed by humans, user acceptance is essential. Even though they are an important aspect of acceptance, emotions towards different assistive robots and different situations of robot-use have so far not been examined in detail. The appearance of assistive robots can trigger emotions that affect their acceptance. Acceptance of robots is assumed to be greater when they look more human-like; however, too much human similarity can be counterproductive. Regarding different groups, it is assumed that older adults have a more negative attitude towards robots than younger adults. Within the framework of a simulated robot study, the aim was to investigate emotions of older adults compared to students towards robots with different appearances and in different situations and so contribute to a deeper view of the emotions influencing acceptance. Methods: In a questionnaire study, vignettes were used to assess emotions toward robots in different situations and of different appearance. The vignettes were composed of two situations (service and care) shown by video and four pictures of robots varying in human similarity (machine-like to android). The combination of the vignettes was randomly distributed to the participants. One hundred forty-two older adults and 35 bachelor students of nursing participated. They filled out a questionnaire that surveyed 30 positive and 30 negative emotions. For each group, older adults and students, a sum score of “positive emotions” and a sum score of “negative emotions” was calculated. Mean value, standard deviation, or n for sample size and % for frequencies, according to the scale level, were calculated. For differences in the scores of positive and negative emotions for different situations, t-tests were calculated. Results: Overall, older adults reported significantly more positive emotions than students towards robots in general. Students reported significantly more negative emotions than older adults. Regarding the two different situations, the results were similar for the care situation, with older adults reporting more positive emotions than students and less negative emotions than students. In the service situation, older adults reported significantly more positive emotions; negative emotions did not differ significantly from the students. Regarding the appearance of the robot, there were no significant differences in emotions reported towards the machine-like, the mechanical-human-like and the human-like appearance. Regarding the android robot, students reported significantly more negative emotions than older adults. Conclusion: There were differences in the emotions reported by older adults compared to students. Older adults reported more positive emotions, and students reported more negative emotions towards robots in different situations and with different appearances. It can be assumed that older adults have a different attitude towards the use of robots than younger people, especially young adults in the health sector. Therefore, the use of robots in the service or care sector should not be rejected rashly based on the attitudes of younger persons, without considering the attitudes of older adults equally.

Keywords: emotions, robots, seniors, young adults

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Authors: Syed Ahzam Tariq, Atharva Modi

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This paper presents a probabilistic analysis of the safety of water tube boilers using fault tree analysis (FTA). A fault tree has been constructed by considering all possible areas where a malfunction could lead to a boiler accident. Boiler accidents are relatively rare, causing a scarcity of data. The fuzzy approach is employed to perform a quantitative analysis, wherein theories of fuzzy logic are employed in conjunction with expert elicitation to calculate failure probabilities. The Fuzzy Fault Tree Analysis (FFTA) provides a scientific and contingent method to forecast and prevent accidents.

Keywords: fault tree analysis water tube boiler, fuzzy probability score, failure probability

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Authors: S. Md. Shaarani, J. Md. Jahim, R. A. Rahman, R. Md. Illias

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Modern developments in biotechnology have paved the way for extensive use of biocatalysis in industries. Although it offers immense potential, industrial application is usually hampered by lack of operational stability, difficulty in recovery as well as limited re-use of the enzyme. These drawbacks, however, can be overcome by immobilization. Cross-linked enzyme aggregates (CLEAs), a versatile carrier-free immobilization technique is one that is currently capturing global interest. This approach involves precipitating soluble enzyme with an appropriate precipitant and subsequent crosslinking by a crosslinking reagent. Without ineffective carriers, CLEAs offer high enzymatic activity, stability and reduced production cost. This study demonstrated successful CLEA synthesis of recombinant xylanase from Trichoderma reesei using ethanol as aggregating agent and glutaraldehyde (2% (v/v); 100 mM) as crosslinker. Effects of additives including proteic feeder such as bovine serum albumin (BSA) and poly-L-Lysine were investigated to reveal its significance in enhancing the performance of enzyme. Addition of 0.1 mg BSA/U xylanase showed considerable increment in CLEA development with approximately 50% retained activity.

Keywords: cross-linked, immobilization, recombinant, xylanase

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Authors: Hocini Yousra, Medjnoun Amal, Khiatine Mohamed, Bahar Ramdane

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The development of the regions of southern Algeria require the construction of numerous road, rail, and airport infrastructures. However, this development is very expensive given the very severe climatic conditions, the difficulty of reusing local materials, and the unavailability of water on the project sites; these regions are characterized by an arid or semi-arid climate, which means that water sources are very limited. The climatic conditions and the scarcity of water make soil compaction work very difficult and excessively expensive. These constraints related to the supply of water for irrigation of these construction sites make it necessary to examine the solution of compaction with low water content. This work studies the possibility of improving the compaction with a low water content of the soils of southern Algeria and this by using natural or recycled ecological materials. Local soils are first subjected to a series of laboratory characterization tests, then mixed with varying amounts of natural additives. The new materials are, in turn, subjected to road tests.

Keywords: compaction, low water content, sand, natural materials

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Authors: Gabriella Kengyel

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This study aims to describe the differences between the attitudes of the right-wing extremists with internal or external control towards migrants. They both have a significantly higher score on Rotter's Locus of Control Scale, and they are quite xenophobic (54%) according to Bogardus Social Distance Scale. Present research suggests their motives are different. Principle components analysis shows that extremists with internal control reject migrants because of welfare chauvinism and they think that there is some kind of political conspirationism behind the European Refugee Crisis. Contrarily extremist with external control believe in a common enemy and they are significantly more ethnocentric and less skeptical in politics. Results suggest that extremist with internal control shows hostility toward minorities and migrants mainly because of their own reference group.

Keywords: control, extremist, migrant, right-wing

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Esmat Kamel

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This paper aims to shed light on the extent to which the Agadir Association agreement has fostered inter regional trade between the E.U_26 and the Agadir_4 countries; once that we control for the evolution of Agadir agreement’s exports to the rest of the world. The next valid question will be regarding any remarkable variation in the spatial/sectoral structure of exports, and to what extent has it been induced by the Agadir agreement itself and precisely after the adoption of rules of origin and the PANEURO diagonal cumulative scheme? The paper’s empirical dataset covering a timeframe from [2000 -2009] was designed to account for sector specific export and intermediate flows and the bilateral structured gravity model was custom tailored to capture sector and regime specific rules of origin and the Poisson Pseudo Maximum Likelihood Estimator was used to calculate the gravity equation. The methodological approach of this work is considered to be a threefold one which starts first by conducting a ‘Hierarchal Cluster Analysis’ to classify final export flows showing a certain degree of linkage between each other. The analysis resulted in three main sectoral clusters of exports between Agadir_4 and E.U_26: cluster 1 for Petrochemical related sectors, cluster 2 durable goods and finally cluster 3 for heavy duty machinery and spare parts sectors. Second step continues by taking export flows resulting from the 3 clusters to be subject to treatment with diagonal Rules of origin through ‘The Double Differences Approach’, versus an equally comparable untreated control group. Third step is to verify results through a robustness check applied by ‘Propensity Score Matching’ to validate that the same sectoral final export and intermediate flows increased when rules of origin were relaxed. Through all the previous analysis, a remarkable and partial significance of the interaction term combining both treatment effects and time for the coefficients of 13 out of the 17 covered sectors turned out to be partially significant and it further asserted that treatment with diagonal rules of origin contributed in increasing Agadir’s_4 final and intermediate exports to the E.U._26 on average by 335% and in changing Agadir_4 exports structure and composition to the E.U._26 countries.

Keywords: agadir association agreement, structured gravity model, hierarchal cluster analysis, double differences estimation, propensity score matching, diagonal and relaxed rules of origin

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Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

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In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

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Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: compressed sensing, lest support orthogonal matching pursuit, partial knowing support, restricted isometry property, signal reconstruction

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Authors: R. O. Babatunde, O. M. Igbalajobi, F. Matambalya

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Moderate economic growth in developing and emerging countries has led to improvement in the food consumption and nutrition situation in the last two decades. Nevertheless, about 870 million people, with a quarter of them from Sub-Saharan Africa, are still suffering from hunger worldwide. As part of measures to reduce the widespread poverty and hunger, cash transfer programmes are now being implemented in many countries of the world. While nationwide cash transfer schemes are few in Sub-Saharan Africa generally, the available ones are more concentrated in East and Southern Africa. Much of the available literature on social protection had focused on the poverty impact of cash transfer schemes at the household level, with the larger proportion originating from Latin America. On the contrary, much less empirical studies have been conducted on the poverty impact of cash transfer in Sub-Saharan Africa, let alone on the food security and nutrition impact. To fill this gap in knowledge, this paper examines the impact of cash transfer on food security in Nigeria. As a case study, the paper analysed the Ekiti State Cash Transfer Scheme (ECTS). ECTS is an unconditional transfer scheme which was established in 2011 to directly provide cash transfer to elderly persons aged 65 years and above in Ekiti State of Nigeria. Using survey data collected in 2013, we analysed the impact of the scheme on food availability and dietary diversity of the beneficiary households. Descriptive and Propensity Score Matching (PSM) techniques were used to estimate the Average Treatment Effect (ATE) and Average Treatment Effect on the Treated (ATT) among the beneficiary and control groups. Thereafter, a model to test for the impact of participation in the cash transfer scheme on calorie availability and dietary diversity was estimated. The results indicate that while households in the sample are clearly vulnerable, there were statistically significant differences between the beneficiary and control groups. For instance, monthly expenditure, calorie availability and dietary diversity were significantly larger among the beneficiary and consequently, the prevalence and depth of hunger were lower in the group. Econometric results indicate that the cash transfer has a positive and significant effect on food availability and dietary diversity in the households. Expanding the coverage of the present scheme to cover all eligible households in the country and incorporating cash transfer into a comprehensive hunger reduction policy will make it to have a greater impact at improving food security among the most vulnerable households in the country.

Keywords: calorie availability, cash transfers, dietary diversity, propensity score matching

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Authors: Tahar Alimi, Rahma Boujebane, Wiem Derouich, Lamia Hadrich Belguith

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Machine translation task of low-resourced languages such as Arabic is a challenging task. Despite the appearance of sophisticated models based on the latest deep learning techniques, namely the transfer learning, and transformers, all models prove incapable of carrying out an acceptable translation, which includes Arabic Dialects (AD), because they do not have official status. In this paper, we present a machine translation model designed to translate Arabic multidialectal content into Modern Standard Arabic (MSA), leveraging both new and existing parallel resources. The latter achieved the best results for both Levantine and Maghrebi dialects with a BLEU score of 64.99.

Keywords: Arabic translation, dialect translation, fine-tune, MSA translation, transformer, translation

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Authors: Rajendar Kandan, Mohammad Zakaria Alli, Hong Ong

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Cloud computing is a business model which provides an easier management of computing resources. Cloud users can request virtual machine and install additional softwares and configure them if needed. However, user can also request virtual appliance which provides a better solution to deploy application in much faster time, as it is ready-built image of operating system with necessary softwares installed and configured. Large numbers of virtual appliances are available in different image format. User can download available appliances from public marketplace and start using it. However, information published about the virtual appliance differs from each providers leading to the difficulty in choosing required virtual appliance as it is composed of specific OS with standard software version. However, even if user choses the appliance from respective providers, user doesn’t have any flexibility to choose their own set of softwares with required OS and application. In this paper, we propose a referenced architecture for dynamically customizing virtual appliance and provision them in an easier manner. We also add our experience in integrating our proposed architecture with public marketplace and Mi-Cloud, a cloud management software.

Keywords: cloud computing, marketplace, virtualization, virtual appliance

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Authors: Katarzyna Wyka, Dana Sylvan, JoAnn Difede

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Background and significance: The following disaster, population-based screening programs are routinely established to assess physical and psychological consequences of exposure. These data sets are highly skewed as only a small percentage of trauma-exposed individuals develop health issues. Commonly used statistical methodology in post-disaster mental health generally involves population-averaged models. Such models aim to capture the overall response to the disaster and its aftermath; however, they may not be sensitive enough to accommodate population heterogeneity in symptomatology, such as post-traumatic stress or depressive symptoms. Methods: We use an archival longitudinal data set from Weill-Cornell 9/11 Mental Health Screening Program established following the World Trade Center (WTC) terrorist attacks in New York in 2001. Participants are rescue and recovery workers who participated in the site cleanup and restoration (n=2960). The main outcome is the post-traumatic stress symptoms (PTSD) severity score assessed via clinician interviews (CAPS). For a detailed understanding of response to the disaster and its aftermath, we are adapting quantile regression methodology with particular focus on predictors of extreme distress and resilience to trauma. Results: The response variable was defined as the quantile of the CAPS score for each individual under two different scenarios specifying the unconditional quantiles based on: 1) clinically meaningful CAPS cutoff values and 2) CAPS distribution in the population. We present graphical summaries of the differential effects. For instance, we found that the effect of the WTC exposures, namely seeing bodies and feeling that life was in danger during rescue/recovery work was associated with very high PTSD symptoms. A similar effect was apparent in individuals with prior psychiatric history. Differential effects were also present for age and education level of the individuals. Conclusion: We evaluate the utility of quantile regression in disaster research in contrast to the commonly used population-averaged models. We focused on assessing the distribution of risk factors for post-traumatic stress symptoms across quantiles. This innovative approach provides a comprehensive understanding of the relationship between dependent and independent variables and could be used for developing tailored training programs and response plans for different vulnerability groups.

Keywords: disaster workers, post traumatic stress, PTSD, quantile regression

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Authors: Eftah Bte. Moh Hj Abdullah, Izazol Binti Idris, Abd Aziz Bin Abd Shukor

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This study aims to identify the understanding expectations of school administrators concerning school assessment. The researcher utilized a qualitative descriptive study on 19 administrators from three secondary schools in the North Kinta district. The respondents had been interviewed on their understanding expectations of school assessment using the focus group discussion method. Overall findings showed that the administrators’ understanding expectations of school assessment was weak; especially in terms of content focus, articulation across age and grade, transparency and fairness, as well as the pedagogical implications. Findings from interviews indicated that administrators explained their understanding expectations of school assessment from the aspect of school management, and not from the aspect of instructional leadership or specifically as assessment leaders. The study implications from the administrators’ understanding expectations may hint at the difficulty of the administrators to function as assessment leaders, in order to reduce their focus as manager, and move towards their primary role in the process of teaching and learning. The administrator, as assessment leaders, would be able to reach assessment goals via collaboration in identifying and listing teacher assessment competencies, how to construct assessment capacity, how to interpret assessment correctly, the use of assessment and how to use assessment information to communicate confidently and effectively to the public.

Keywords: assessment leaders, assessment goals, instructional leadership, understanding expectation of assessment

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Authors: Sara Sousa

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The environmental goods and services have often been neglected in crucial decisions affecting the environment mainly because the difficulty in estimating their economic value, since we are dealing with non-market goods and, thus, without a price associated. Nevertheless, the inexistence of prices does not necessarily mean these goods have no value. The environment is a key element in today's society that seeks to be as sustainable as possible, where the environmental assets have both use and non-use values. To estimate the use value, researchers may apply the revealed preference methods. This paper provides a theoretical review of the main concepts and methodologies on the economic valuation of the environment, with particular emphasis on the revealed preference techniques. Based on a detailed literature review, this study concludes that, despite some inherent limitations, the revealed preference methodologies – travel cost, hedonic price, and averting behaviour – represent essential tools for the researchers who accept the challenge to estimate the use value of environmental goods and services based on the actual individuals` behaviour. The main purpose of this study is to contribute to an increased theoretical information on the economic valuation of environmental assets, allowing researchers and policymakers to improve future decisions regarding the environment.

Keywords: economic valuation, environmental goods, revealed preference methods, total economic value

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Authors: Jean Rosemond Dora, Karol Nemoga

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In this work, we tackle a frequent problem that frequently occurs in the cybersecurity field which is the exploitation of websites by XSS attacks, which are nowadays considered a complicated attack. These types of attacks aim to execute malicious scripts in a web browser of the client by including code in a legitimate web page. A serious matter is when a website accepts the “user-input” option. Attackers can exploit the web application (if vulnerable), and then steal sensitive data (session cookies, passwords, credit cards, etc.) from the server and/or from the client. However, the difficulty of the exploitation varies from website to website. Our focus is on the usage of ontology in cybersecurity against XSS attacks, on the importance of the ontology, and its core meaning for cybersecurity. We explain how a vulnerable website can be exploited, and how different JavaScript payloads can be used to detect vulnerabilities. We also enumerate some tools to use for an efficient analysis. We present detailed reasoning on what can be done to improve the security of a website in order to resist attacks, and we provide supportive examples. Then, we apply an ontology model against XSS attacks to strengthen the protection of a web application. However, we note that the existence of ontology does not improve the security itself, but it has to be properly used and should require a maximum of security layers to be taken into account.

Keywords: cybersecurity, web application vulnerabilities, cyber threats, ontology model

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Authors: Iniye Irene Wodi, Kennedy B. Gibson

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Students’ poor performance in mathematics in both internal and external examinations has been a source of concern to researchers in Nigeria. The cause of this has been attributed to both teachers and students. To this end, this study sought to find out students’ perceptions of teachers’ attributes as a cause of mathematics phobia among secondary school students in Bayelsa State Nigeria. The population of the study comprised of all students of senior secondary schools in Yenagoa metropolis. A sample of 120 students was drawn from this population using clustering and simple random sampling techniques. The instrument for data collection was a researcher constructed questionnaire titled Mathematics Phobia Questionnaire (MPQ). Data were analysed, and the results revealed that students perceived teachers’ attributes such as methods and styles of teaching, difficulty in communication, etc. as causes of mathematics phobia among students in senior secondary schools in Bayelsa State. Based on the result, it was therefore recommended that mathematics teachers should be retrained periodically in order to learn new and innovative ways of teaching mathematics to prevent its phobia among students.

Keywords: mathematics phobia, teacher attributes, teaching method, teaching style

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Authors: Amit Verma, Simranjeet Kaur, Sandeep Kaur

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Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.

Keywords: test case prioritization, classification, artificial neural networks, TF-IDF

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Authors: Julius A. Ademokoya, Grace C. Ilori

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Extreme public transport difficulty for persons with disabilities (PWDs) has always been one of the challenges which these individuals experience on a daily basis in Nigeria. Private and public transport vehicles are not disability- friendly. Operators of public transport are often very intolerant of PWDs' conditions. Indeed, many Nigerians believe it is luxury for PWDs to engage in public transport. They are rarely expected to be seen in public much less going to places via public transport means. Initiatives by a few Nigerian states to develop and implement public transport policies for PWDs, therefore, were a huge relief for them and some concerned Nigerians. A few years ago, three southwest Nigerian states (Lagos, Ondo, and Ekiti) came up with some legislative welfare provisions (including transport programmes) for PWDs. This study, therefore, sought to ascertain levels of awareness and implementation of public policies among the PWDs and those expected to implement the policies. The study adopted a mixed method research. Findings across the three states showed that: (1) awareness of public policies among PWDs is low and (2) a considerable scope of the policies is not yet implemented. Recommendations are, therefore, made on how to improve on awareness and implementation of transport policies for PWDs in three south-west Nigerian states.

Keywords: awareness, disability rights, implementation persons with disability, transport policies

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Authors: Sakshi Chopra, Ashima Nehra, Sumit Sinha, Harsimarpreet Kaur, Ravindra Mohan Pandey

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Background: Cognitive rehabilitation aims to retrain brain injured individuals with cognitive deficits to restore or compensate lost functions. As illiterates or people with low literacy levels represent a significant proportion of the world, specific rehabilitation modules for such populations are indispensable. Literacy is significantly associated with all neuropsychological measures and retraining programs widely use written or spoken techniques which essentially require the patient to read or write. So, the aim of the study was to develop and standardize a literacy free neuropsychological rehabilitation program for improving cognitive functioning in patients with mild and moderate Traumatic Brain Injury (TBI). Several studies have pointed out to the impairments seen in memory, executive functioning, and attention and concentration post-TBI, so the rehabilitation program focussed on these domains. Visual item memorization, stick constructions, symbol cancellations, and colouring techniques were used to construct the retraining program. Methodology: The development of the program consisted of planning, preparing, analyzing, and revising the different modules. The construction focussed on areas of retraining immediate and delayed visual memory, planning ability, focused and divided attention, concentration, and response inhibition (to control irritability and aggression). A total of 98 home based retraining modules were prepared in the 4 domains (42 for memory, 42 for executive functioning, 7 for attention and concentration, and 7 for response inhibition). The standardization was done on 20 healthy controls to review, select and edit items. For each module, the time, errors made and errors per second were noted down, to establish the difficulty level of each module and were arranged in increasing level of difficulty over a period of 6 weeks. The retraining tasks were then administered on 11 brain injured individuals (5 after Mild TBI and 6 after Moderate TBI). These patients were referred from the Trauma Centre to Clinical Neuropsychology OPD, All India Institute of Medical Sciences, New Delhi, India. Results: The time was taken, errors made and errors per second were analysed for all domains. Education levels were divided into illiterates, up to 10 years, 10 years to graduation and graduation and above. Mean and standard deviations were calculated. Between group and within group analysis was done using the t-test. The performance of 20 healthy controls was analyzed and only a significant difference was observed on the time taken for the attention tasks and all other domains had non-significant differences in performance between different education levels. Comparing the errors, time taken between patient and control group, there was a significant difference in all the domains at the 0.01 level except the errors made on executive functioning, indicating that the tool can successfully differentiate between healthy controls and patient groups. Conclusions: Apart from the time taken for symbol cancellations, the entire cognitive rehabilitation program is literacy free. As it taps the major areas of impairment post-TBI, it could be a useful tool to rehabilitate the patient population with low literacy levels across the world. The next step is already underway to test its efficacy in improving cognitive functioning in a randomized clinical controlled trial.

Keywords: cognitive rehabilitation, illiterates, India, traumatic brain injury

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Authors: Nadya Inda Syartanti

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This research aims to identify, classify, and analyze descriptively the aspects of grammatical and lexical cohesion in the speech text of Japan’s Prime Minister Shinzo Abe entitled Nihon wa Modotte kimashita delivered in Washington DC, the United States on February 23, 2013, as a research data source. The method used is qualitative research, which uses descriptions through words that are applied by analyzing aspects of grammatical and lexical cohesion proposed by Halliday and Hasan (1976). The aspects of grammatical cohesion consist of references (personal, demonstrative, interrogative pronouns), substitution, ellipsis, and conjunction. In contrast, lexical cohesion consists of reiteration (repetition, synonym, antonym, hyponym, meronym) and collocation. Data classification is based on the 6 aspects of the cohesion. Through some aspects of cohesion, this research tries to find out the frequency of using grammatical and lexical cohesion in Shinzo Abe's speech text entitled Nihon wa Modotte kimashita. The results of this research are expected to help overcome the difficulty of understanding speech texts in Japanese. Therefore, this research can be a reference for learners, researchers, and anyone who is interested in the field of discourse analysis.

Keywords: cohesion, grammatical cohesion, lexical cohesion, speech text, Shinzo Abe

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Authors: Muneeb Banday, Anukriti Dixit

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Change in organizations is viewed as a conversion process of the organizational functioning. One of the crucial elements of this conversion process is the employee resistance to organizational change. The existing literature on change resistance has generally treated resistance as a barrier or an opportunity for successful implementation of change. However, there is little empirical research exploring how resistance to change is managed. This may be partially due to difficulty in getting information on resistance to change. The top management does not divulge such information to avoid negative evaluation whereas employees face huge risk in sharing information related to resistance. The focus of the study is to understand how the organization under study dealt with the employee resistance to change. The conversion process is a story of how the organization went from one stage to another. We used narrative approach to change. Data was collected data through company visits and interviews. The interviews were transcribed, coded, and themes were identified. We focused on the strands that left huge scope for alternative interpretations than the dominant narrative of change prevalent in the organization. The study reveals that the top management strategically uses the legitimacy of leadership, roles of key employees, and rationality of change to manage resistance.

Keywords: employee resistance, legitimacy of leadership, narrative analysis, organisational change

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Authors: Pimpisa Rattanadilok Na Phuket

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This research study aims to examine: 1) teaching competency of the native English-speaking teacher (NEST) 2) the English language learning achievement of Thai students, and 3) students’ perceptions toward their NEST. The population considered in this research was a group of 39 undergraduate students of the academic year 2013. The tools consisted of a questionnaire employed to measure the level of competency of NEST, pre-test and post-test used to examine the students’ achievement on English pronunciation, and an interview used to discover how participants perceived their NEST. The data was statistically analysed as percentage, mean, standard deviation and One-sample-t-test. In addition, the data collected by interviews was qualitatively analyzed. The research study found that the level of teaching competency of native speaker teachers of English was mostly low, the English pronunciation achievement of students had increased significantly at the level of 0.5, and the students’ perception toward NEST is combined. The students perceived their NEST as an English expertise, but they felt that NEST had not recognized students' linguistic difficulty and cultural differences.

Keywords: competency, native English-speaking teacher (NET), English teaching, learning achievement

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Authors: Tanju Deveci

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It appears that the speech act of complaint has not received as much attention as other speech acts. However, the face-threatening nature of this speech act requires a special attention in multicultural contexts in particular. The teaching context in the UAE universities, where a big majority of teaching staff comes from other cultures, requires investigations into this speech act in order to improve communication between students and faculty. This session will outline the results of a study conducted with this purpose. The realization of complaints by Freshman English students in Communication courses at Petroleum Institute was investigated to identify communication patterns that seem to cause a strain. Data were collected using a role-play between a teacher and students, and a judgment scale completed by two of the instructors in the Communications Department. The initial findings reveal that the students had difficulty putting their case, produced the speech act of criticism along with a complaint and that they produced both requests and demands as candidate solutions. The judgement scales revealed that the students’ attitude was not appropriate most of the time and that the judges would behave differently from students. It is concluded that speech acts, in general, and complaint, in particular, need to be taught to learners explicitly to improve interpersonal communication in multicultural societies. Some teaching ideas are provided to help increase foreign language learners’ sociolinguistic competence.

Keywords: speech act, complaint, pragmatics, sociolinguistics, language teaching

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Authors: Panisa Harnpathananun

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This paper is 'Practical Experience Analysis' which aims to analyze critical obstacles hampering the growth of the functional milk industry and suggest recommendations to overcome those obstacles. Using the Sectoral Innovation System (SIS) along value chain analysis, it is found that restriction in regulation of milk disinfection process, difficulty of dairy entrepreneurs for health claim approval of functional food and beverage and lack of intermediary between entrepreneurs and certified units for certification of functional foods and milk are major causes that needed to be resolved. Consequently, policy recommendations are proposed to tackle the problems occurring throughout the value chain. For the upstream, a collaborative platform using the quadruple helix model is proposed in a pattern of effective dairy cooperatives. For the midstream, regulation issues of new process, extended shelf life (ESL) milk, or prolonged milk are necessary, which can be extended the global market opportunity. For the downstream, mechanism of intermediary between entrepreneurs and certified units can be assisted in certified process of functional milk, especially a process of 'health claim' approval.

Keywords: Thailand, functional milk, supply chain, quadruple helix, intermediary, functional food

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Authors: Yujin Jeong, Youkyung Son, Myounghwan Choi, Sanghyub Lee, Sangyeol Lee, Changho Hwang, Kyo-in Koo

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Dysphasia is difficulty in swallowing food because of oral cavity impairments induced by stroke, muscle damage, tumor. Intermittent oro-esophageal (IOE) tube feeding is one of the well-known feeding methods for the dysphasia patients. However, it is hard to insert at the proper position in esophagus. In this study, we design and fabricate the IOE tube guide using 3-dimensional (3D) printer. The printed IOE tube is tested in a mannequin (Airway Management Trainer, Co., Ltd., Copenhagen, Denmark) mimicking human’s esophagus. The gag reflex point is measured as the design point in the mannequin. To avoid the gag reflex, we design various shapes of IOE tube guide. One structure is separated into three parts; biting part, part through oral cavity, connecting part to oro-esophageal. We designed 6 types of IOE tube guide adjusting length and angle of these three parts. To evaluate the IOE tube guide, it is inserted in the mannequin, and through the inserted guide, an endoscopic camera successfully arrived at the oro-esophageal. We had planned to apply this mannequin-based design experience to patients in near future.

Keywords: dysphagia, feeding method, IOE tube guide, 3-D printer

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Authors: Ghoul Rachid Brahim

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Introduction: Degenerative disc disease is a process of premature and accelerated deterioration of the intervertebral disc; it is of multifactorial origin and is responsible for chronic low back pain. Objectives: Determine an epidemiological profile of patients with painful lumbar degenerative disc disease. Patients and methods: We performed a prospective study of 104 patients operated on for degenerative painful lumbar disc disease over a period of 25 months. The parameters analyzed were: age, sex, Body Mass Index (BMI), comorbidities, family history of low back pain, and difficulty with professional activity. Results: The average age was 43.3 years, with a clear predominance of men: 72 men for 32 women, the average BMI was 26.80Kg / m2, and 63.5% of the patients were overweight. The occurrence of disc degeneration in pathological conditions was noted in 14.4% of cases. The notion of familial low back pain was found in 49% of cases. The majority of patients perform more or less arduous work (51%) in the cases. Conclusion: In our series, degenerative painful lumbar disc disease predominates in the male subject, active obese who performs more or less painful work, in whom we find a family history of low back pain.

Keywords: degenerative disc disease, low back pain, body mass index, disque intervertebrale

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Authors: Ljubica Milanović Glavan

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Because of the increasing business pressures, companies must be adaptable and flexible in order to withstand them. Inadequate business processes and low level of business process orientation, that in its core accentuates business processes as opposed to business functions and focuses on process performance and customer satisfaction, hider the ability to adapt to changing environment. It has been shown in previous studies that the companies which have reached higher business process maturity level consistently outperform those that have not reached them. The aim of this paper is to provide a basic understanding of business process orientation concept and business process maturity model. Besides that the paper presents the state of business process orientation in Croatia that has been captured with a study conducted in 2013. Based on the results some practical implications and guidelines for managers are given.

Keywords: business process orientation, business process maturity, Croatia, maturity score

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Authors: Girma Yohannis Bade, Olga Kolesnikova, Grigori Sidorov

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Named entity recognition (NER) is a building block for information extraction. Though the information extraction process has been automated using a variety of techniques to find and extract a piece of relevant information from unstructured documents, the discovery of targeted knowledge still poses a number of research difficulties because of the variability and lack of structure in Web data. NER, a subtask of information extraction (IE), came to exist to smooth such difficulty. It deals with finding the proper names (named entities), such as the name of the person, country, location, organization, dates, and event in a document, and categorizing them as predetermined labels, which is an initial step in IE tasks. This survey paper presents the roles and importance of NER to IE from the perspective of different algorithms and application area domains. Thus, this paper well summarizes how researchers implemented NER in particular application areas like finance, medicine, defense, business, food science, archeology, and so on. It also outlines the three types of sequence labeling algorithms for NER such as feature-based, neural network-based, and rule-based. Finally, the state-of-the-art and evaluation metrics of NER were presented.

Keywords: the role of NER, named entity recognition, information extraction, sequence labeling algorithms, named entity application area

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Authors: Sunanta Klibthong

Abstract:

In view of the Thailand government policy creating increasing awareness of opportunity for children with special needs, the number of children with disabilities enrolled in kindergartens in Thailand has increased. This study explores early childhood teachers’ experiences and concerns of teaching children with disabilities in inclusive classrooms. The population of the study was private early childhood teachers who teach in inclusive classrooms in Thailand. Quantitative data obtained through a questionnaire were supplemented by early childhood teachers’ interviews to identify key experiences and concerns of the teachers when teaching children with and without disabilities in the same classrooms. The results of this study indicated that many teachers face challenges including lack of professional development opportunities, difficulty identifying the needs of all children and how to use effective strategies to support inclusive practices in their classrooms. Teachers also expressed concern about parents’ lack of willingness to accept children without disabilities studying together with those with disabilities in the same classrooms. Findings from this study can inform program support for parents and professional support needs of teachers in the provision of high-quality inclusive programs for all students.

Keywords: the concern, early childhood, experience, inclusive education, Thailand

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