Search results for: Taiwan Machinery Cluster (TMC)

Authors: Wan-Ling Chang, Hsiu-Ju Huang, Jui-Hsiu Chang

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In 2004, the Ministry of Foreign Affairs Taiwan launched ‘An Arrangement on Working Holiday Scheme’ with 15 countries including New Zealand, Japan, Canada, Germany, South Korea, Britain, Australia and others. The aim of the scheme is to allow young people to work and study English or other foreign languages. Each year, there are 30,000 Taiwanese youths applied for participating in the working holiday schemes. However, frequent accidents could cause huge medical expenses and post-delivery fee, which are usually unaffordable for most families. Therefore, this study explored the relationship among perceived risk toward working holiday, insurance product knowledge, brand image and insurance purchase intention for Taiwanese youths who plan to apply for working holiday. A survey questionnaire was distributed for data collection. A total of 316 questionnaires were collected for data analyzed. Data were analyzed using descriptive statistics, independent samples T-test, one-way ANOVA, correlation analysis, regression analysis and hierarchical regression methods of analysis and hypothesis testing. The results of this research indicate that perceived risk has a negative influence on insurance purchase intention. On the opposite, product knowledge has brand image has a positive influence on the insurance purchase intention. According to the mentioned results, practical implications were further addressed for insurance companies when developing a future marketing plan.

Keywords: insurance product knowledges, insurance purchase intention, perceived risk, working holiday

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Authors: Africa Makasi

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The research explored factors influencing the adoption of disruptive technologies in the mobile telecommunications industry in Zimbabwe. Data was gathered from the second biggest competitor in the industry with over 3 million subscribers as the main case of study. The survey was conducted by purposively selecting 70 respondents from a population of 3,000,000 (three million) active subscribers from the company’s database. A skip interval of 42,857 was used to randomly select the sample. Customer representatives were selected from the company’s five regional offices using a two-stage cluster sampling technique. Employee participants were purposively selected from the company’s head office. Self-administered questionnaires were used in the research. A pilot test was conducted and the assessment of the reliability of the research instruments used in the research performed. Results of the pilot study were analyzed to test for reliability using SPSS. The results confirmed that the style of leadership and its thrust may help speed up or reduce the adoption of disruptive technologies. This was reflected by a p–value of 0.01 which is less than 0.05. The null hypothesis was thus rejected and the strong relationship between leadership and adoption of disruptive technology is confirmed. Similar results were also obtained with respect to staff competence, availability of funding and the type of infrastructure available Future research should look at organizational ambidexterity as well as exploitation and exploration paradigms in organizations in the telecommunications industry and their impact on the adoption of disruptive technologies.

Keywords: disruptive innovation, adoption, mobile telecommunication industry, exploration and exploitation

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Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems does not scale well on multi-CPU/multi-GPUs clusters. For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration instead of two for standard CG. The standard and pipelined CG methods need the vector entries generated by the current GPU and other GPUs for matrix-vector products. So the communication between GPUs becomes a major performance bottleneck on multi GPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using the pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP, and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: conjugate gradient, GPU, parallel programming, pipelined algorithm

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Milica Karadžić

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The present study is based on the quantitative structure-activity relationship (QSAR) analysis of eighteen compounds with anti-prion activity. The structures and anti-prion activities (expressed in response units, RU%) of the analyzed compounds are taken from CHEMBL database. In the first step of analysis 85 molecular descriptors were calculated and based on them the hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out in order to detect potential significant similarities or dissimilarities among the studied compounds. The calculated molecular descriptors were physicochemical, lipophilicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) descriptors. The first stage of the QSAR analysis was simple linear regression modeling. It resulted in one acceptable model that correlates Henry's law constant with RU% units. The obtained 2D-QSAR model was validated by cross-validation as an internal validation method. The validation procedure confirmed the model’s quality and therefore it can be used for prediction of anti-prion activity. The next stage of the analysis of anti-prion activity will include 3D-QSAR and molecular docking approaches in order to select the most promising compounds in treatment of prion diseases. These results are the part of the project No. 114-451-268/2016-02 financially supported by the Provincial Secretariat for Science and Technological Development of AP Vojvodina.

Keywords: anti-prion activity, chemometrics, molecular modeling, QSAR

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Authors: Lai Wenfang

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Tthis study will describe how to use artificial intelligence (AI) technology to build the user-oriented platform for integrated archival service. The platform will be launched in 2020 by the National Archives Administration (NAA) in Taiwan. With the progression of information communication technology (ICT) the NAA has built many systems to provide archival service. In order to cope with new challenges, such as new ICT, artificial intelligence or blockchain etc. the NAA will try to use the natural language processing (NLP) and machine learning (ML) skill to build a training model and propose suggestions based on the data sent to the platform. NAA expects the platform not only can automatically inform the sending agencies’ staffs which records catalogues are against the transfer or destroy rules, but also can use the model to find the details hidden in the catalogues and suggest NAA’s staff whether the records should be or not to be, to shorten the auditing time. The platform keeps all the users’ browse trails; so that the platform can predict what kinds of archives user could be interested and recommend the search terms by visualization, moreover, inform them the new coming archives. In addition, according to the Archives Act, the NAA’s staff must spend a lot of time to mark or remove the personal data, classified data, etc. before archives provided. To upgrade the archives access service process, the platform will use some text recognition pattern to black out automatically, the staff only need to adjust the error and upload the correct one, when the platform has learned the accuracy will be getting higher. In short, the purpose of the platform is to deduct the government digital transformation and implement the vision of a service-oriented smart government.

Keywords: artificial intelligence, natural language processing, machine learning, visualization

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Authors: Chi Wu, Dean Wu, Wen-Te Liu, Cheng-Yu Tsai, Shin-Mei Hsu, Yin-Tzu Lin, Ru-Yin Yang

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Background: The results of previous studies compared the benefits and risks of receiving insomnia medication. However, the effects between hypnotic drugs used and enhancement of sleep quality were still unclear. Objective: The aim of this study is to establish a prediction model for hypnotic drugs' dosage used for insomnia subjects and associated the relationship between sleep stage ratio change and drug types. Methodologies: According to American Academy of Sleep Medicine (AASM) guideline, sleep stages were classified and transformed to hypnogram via the polysomnography (PSG) in a hospital in New Taipei City (Taiwan). The subjects with diagnosis for insomnia without receiving hypnotic drugs treatment were be set as the comparison group. Conversely, hypnotic drugs dosage within the past three months was obtained from the clinical registration for each subject. Furthermore, the collecting subjects were divided into two groups for training and testing. After training convolution neuron network (CNN) to predict types of hypnotics used and dosages are taken, the test group was used to evaluate the accuracy of classification. Results: We recruited 76 subjects in this study, who had been done PSG for transforming hypnogram from their sleep stages. The accuracy of dosages obtained from confusion matrix on the test group by CNN is 81.94%, and accuracy of hypnotic drug types used is 74.22%. Moreover, the subjects with high ratio of wake stage were correctly classified as requiring medical treatment. Conclusion: CNN with hypnogram was potentially used for adjusting the dosage of hypnotic drugs and providing subjects to pre-screening the types of hypnotic drugs taken.

Keywords: convolution neuron network, hypnotic drugs, insomnia, polysomnography

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Authors: Mostafa Mohammadpour, Christoph Kapeller, Christy Li, Josef Scharinger, Christoph Guger

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Interictal spikes provide valuable information on electrocorticography (ECoG), which aids in surgical planning for patients who suffer from refractory epilepsy. However, the shape and temporal dynamics of these spikes remain unclear. The purpose of this work was to analyze the shape of interictal spikes and measure their distance to the seizure onset zone (SOZ) to use in epilepsy surgery. Thirteen patients' data from the iEEG portal were retrospectively studied. For analysis, half an hour of ECoG data was used from each patient, with the data being truncated before the onset of a seizure. Spikes were first detected and grouped in a sequence, then clustered into interictal epileptiform discharges (IEDs) and non-IED groups using two-step clustering. The distance of the spikes from IED and non-IED groups to SOZ was quantified and compared using the Wilcoxon rank-sum test. Spikes in the IED group tended to be in SOZ or close to it, while spikes in the non-IED group were in distance of SOZ or non-SOZ area. At the group level, the distribution for sharp wave, positive baseline shift, slow wave, and slow wave to sharp wave ratio was significantly different for IED and non-IED groups. The distance of the IED cluster was 10.00mm and significantly closer to the SOZ than the 17.65mm for non-IEDs. These findings provide insights into the shape and spatiotemporal dynamics of spikes that could influence the network mechanisms underlying refractory epilepsy.

Keywords: spike propagation, spike pattern, clustering, SOZ

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Authors: Rizki Nor Amelia, Farida A. Setiawati

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This study aimed to: (1) describe the characteristics of teacher-made test instrument used to measure the ability of students’chemistry, and (2) identify the presence of the compability difficulty level set by teachers to difficulty level by empirical results. Based on these objectives, this study was a descriptive research. The analysis in this study used the Rasch model and Chi-square statistics. Analysis using Rasch Model was based on the response patterns of high school students to the teacher-made test instrument on chemistry subject Academic Year 2015/2016 in the Yogyakarta. The sample of this research were 358 students taken by cluster random sampling technique. The analysis showed that: (1) a teacher-made tests instrument has a medium on the mean difficulty level. This instrument is capable to measure the ability on the interval of -0,259 ≤ θ ≤ 0,659 logit. Maximum Test Information Function obtained at 18.187 on the ability +0,2 logit; (2) 100% items categorized either as easy or difficult by rasch model is match with the teachers’ judgment; while 37 items are categorized according to rasch model which 8.10% and 10.81% categorized as easy and difficult items respectively according to the teachers, the others are medium categorized. Overall, the distribution of the level of difficulty formulated by the teachers has the distinction (not match) to the level of difficulty based on the empirical results.

Keywords: chemistry, items parameter fitness, Rasch model, teacher-made test

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Authors: An-Na Li, Ying-Yu Chen, Yu-Lung Lin

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Food tourism is one of the growing industries in the tourism industry today. The Destination Marketing Organizations (DMOs) are aware of the importance of gastronomy to stimulate local and regional economic development. From the heritage and cultural aspects, gastronomy is becoming a more important part of the cultural heritage of the region. Heritage destinations provide culinary heritage, which fits the current interest in traditional food, and cuisine is a part of a general desire for authentic experience. However, few studies have empirically examined antecedents of food tourists’ behavioral intentions. This study examined the effects of cuisine experience; emotions, place attachment and tourists’ revisit behavioral intentions. A total of 408 individuals responded to the on-site survey in the historic town of Lu-Kang in Taiwan. The results indicated that tourists’ cuisine experience include place flavor, media recommendation, local learning, life transfer and interpersonal share. In addition, cuisine experience had significant impacts on emotions and place attachment, emotions had significant effects on place attachment, furthermore, which in turn place attachment had significant effects on tourists’ revisit behavioral intentions. The findings suggested that the cuisine experience is a multi-dimensions construct. On the other hands, the good quality of cuisine experience could evoke tourists’ positive emotions and it could play a significant role in promoting tourist revisit intentions or word of mouth. Implications for theory and practice are discussed.

Keywords: culinary tourism, cuisine experiences, emotions, revisit intentions

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Authors: Yi-Ning Chang

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With the rapid advancement of technology, it has become crucial for educators to adeptly integrate technology into their teaching and develop a robust Computer-Assisted Language Learning (CALL) competency. Addressing this need, the present study adopted a technology-based Lesson Study approach to assess its impact on the CALL competency and professional capabilities of EFL teachers. Additionally, the study delved into teachers' perceptions of the benefits derived from participating in the creation of technologically integrated lesson plans. The iterative process of technology-based Lesson Study facilitated ample peer discussion, enabling teachers to flexibly design and implement lesson plans that incorporate various technological tools. This 15-week study included 10 in- service teachers from a university of science and technology in the central of Taiwan. The collected data included pre- and post- lesson planning scores, pre- and post- TPACK survey scores, classroom observation forms, designed lesson plans, and reflective essays. The pre- and post- lesson planning and TPACK survey scores were analyzed employing a pair-sampled t test; students’ reflective essays were respectively analyzed applying content analysis. The findings revealed that the teachers’ lesson planning ability and CALL competencies were improved. Teachers perceived a better understanding of integrating technology with teaching subjects, more effective teaching skills, and a deeper understanding of technology. Pedagogical implications and future studies are also discussed.

Keywords: CALL, language learning, lesson study, lesson plan

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Authors: Chen Chou, Feng-Tyan Lin

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Big Data has been attracted a lot of attentions in many fields for analyzing research issues based on a large number of maternal data. Electronic Toll Collection (ETC) is one of Intelligent Transportation System (ITS) applications in Taiwan, used to record starting point, end point, distance and travel time of vehicle on the national freeway. This study, taking advantage of ETC big data, combined with urban planning theory, attempts to explore various phenomena of inter-city transportation activities. ETC, one of government's open data, is numerous, complete and quick-update. One may recall that living area has been delimited with location, population, area and subjective consciousness. However, these factors cannot appropriately reflect what people’s movement path is in daily life. In this study, the concept of "Living Area" is replaced by "Influence Range" to show dynamic and variation with time and purposes of activities. This study uses data mining with Python and Excel, and visualizes the number of trips with GIS to explore influence range of Tainan city and the purpose of trips, and discuss living area delimited in current. It dialogues between the concepts of "Central Place Theory" and "Living Area", presents the new point of view, integrates the application of big data, urban planning and transportation. The finding will be valuable for resource allocation and land apportionment of spatial planning.

Keywords: Big Data, ITS, influence range, living area, central place theory, visualization

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Authors: Somayeh Akrami, Habib Onsori, Elham Tahmassebian

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Species of Anemone narcissiflora is belonged to Anemone genus of Ranunculaceae family. This species has two subspecies named narcissiflora and willdenowii which the latest is recorded in Iran in 2010. Some samples of A. narcissiflora is gathered from kuhkamar-zonouz region of East -Azerbaijan province, Iran to study the genetic diversity of the species by using RAPD molecular markers, and estimation of genetic diversity were evaluated with the using 10mer RAPD primers by PCR-RAPD method. 39 polymorphic bands were produced from the six primers used in this technique that the maximum band is related to the RP1 primer, the lowest band is related to the RP7 and the average band for all primers were 6.5 polymorphic bands. Cluster analysis of samples in done by UPGMA method in NTSYSpc 2.02 software. Dendrogram resulting from migrating bands showed that the studied samples can be divided into two groups. The first group includes samples with 1-2 flowers and the second group consists of two sub-groups which the first subgroup consists of samples with 3-5 flowers, and the second subgroup consists of samples with 6-7 flowers. The results of the comparison and analysis of the data obtained from RAPD technique and similarity matrix represents the genetic variation between collected samples. This study shows that RAPD markers can determine the polymorphisms between different genotypes of A. narcissiflora and their hybrids. So RAPD technique can serve as a suitable molecular method to determine the genetic diversity of samples.

Keywords: Anemone narcissiflora, genetic diversity, RAPD-PCR

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Authors: Swati Srivastava, Ashish Kumar Upadhyay

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Haemophilus influenzae Type B (Hib) cause infections of pneumonia, meningitis, epiglottises and other invasive disease exclusively among children under age five. Occurrence of these infections may impair child growth by causing micronutrient deficiency. Using longitudinal data from first and second waves of Young Lives Study conducted in India during 2002 and 2006-07 respectively and multivariable logistic regression models (using generalised estimation equation to take into account the cluster nature of sample), this study aims to examine the impact of Hib vaccination on child anthropometric outcomes (stunting, underweight and wasting) in India. Bivariate result shows that, a higher percent of children were stunted and underweight among those who were not vaccinated against Hib (39% & 48% respectively) as compare to those who were vaccinated (31% and 39% respectively).The risk of childhood stunting and underweight was significantly lower among children who were vaccinated against Hib (odds ratio: 0.77, 95% CI: 0.62-0.96 and odds ratio: 0.79, 95% C.I: 0.64-0.98 respectively) as compare to the unvaccinated children. No significant association was found between vaccination status against Hib and childhood wasting. Moreover, in the statistical models, about 13% of stunting and 12% of underweight could be attributable to lack of vaccination against Hib in India. Study concludes that vaccination against Hib- in addition to being a major intervention for reducing childhood infectious disease and mortality- can be consider as a potential tool for reducing the burden of undernutrition in India. Therefore, the Government of India must include the vaccine against Hib into the Universal Immunization Programme in India.

Keywords: Haemophilus influenzae Type-B, Stunting, Underweight, Wasting, Young Lives Study (YLS), India

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Authors: Yoseph Gela Ali

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Inadequate quality and quantity diet is one of the major reasons for high levels of malnutrition in pregnant women. Across-sectional survey was conducted in Shashemene District, Southern Oromia Region. A two-stage cluster sampling technique was used to select a representative sample of 15190 pregnant women aged 20-50 years from four rural villages Energy and nutrient intakes from foods were calculated from one-day weighed food records on a sub-sample (n = 83). The result of the study showed that the intakes of most nutrients were lower than the recommended intake. The energy intake of the study participants both in 2nd and 3rd trimesters of pregnancy were 2,308 kcal and 1,420.5 kcal compared to the recommended 2,340 kcal and 2,452 kcal, respectively. Except iron, almost all micronutrient intakes were lower than the recommended intake. Vitamin A intake was 3 µg compared with the recommended 800 µg, while protein intake of the study respondents in 2nd and 3rd trimester of pregnancy was 45.9 g and 31.5 g, respectively, compared with the recommended 71 g. Risk factors for under nutrition were multiple pregnancy and no consumption of cereal-based foods. This study revealed that the energy and nutrient intake of the pregnant women in the study area was below the recommended intakes. Furthermore, the situation might be aggravated by the high phytate content food consumption reported. Nutritional status of pregnant women in the study area was not adequate to support the increased energy and nutrient requirement of the participants.

Keywords: nutrition, pregnancy, protein, vitamin, energy

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Authors: Han Song, Tingting Wei, Dong Chen

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The combination of capital and rural areas in China has shown its great significance in promoting urban-rural integration and new-style urbanization, enhancing regional capacity for sustainable rural development and optimizing human settlement environment. The purpose of this study is to find capital operation mechanism in rural area and rural planning guidance in China. Based on case studies in Chinese rural areas, two types of capital operation mechanism in rural areas are summed up: intervention in the field of agriculture promoting the upgrading and innovation of agricultural industry chain, intervention in rural life and leisure areas updating rural connotation and form. In the light of experiences in Japan and Taiwan, it is proposed that government's norms and guidance, rural investment intensity and rural self-organization are three important factors for capital to drive rural development. It is also found that the unique land tenure and rural governance tradition are two important factors effecting the combination of capital and rural regions in China, which requires full attention in rational policy-making and rural planning. It comes to a conclusion as four directions of the overall reform of the rural planning: targeting at enhancing the viability of rural and sustainable capacity, encouraging differences in investment incentives and planning policies, providing land usage in the rural areas with planning support and reforming the village system. Directional guidance is also made for different types of capital investments, suggesting that capital should be rooted in agriculture and rural land to benefit farmers and update human settlements.

Keywords: capital, rural areas, rural planning, rural governance

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Authors: Dung V. H. Pham, Kathryn Cullen

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Introduction: 40% of adolescents with major depression (MDD) are unresponsive to 1st line antidepressant treatment. The neural mechanism underlying treatment-responsive and treatment-resistant depression in adolescent are unclear. Amygdala is important for emotion processing and has been implicated in mood disorders. Past research has shown abnormal amygdala connectivity in adolescents with MDD. This research study changes in amygdala resting-state functional connectivity to find neural correlates of successful antidepressant treatment. Methods: Thirteen adolescents aged 12-19 underwent rfMRI before and after 8-week antidepressant treatment and completed BDI-II at each scan. A whole-brain approach, using anatomically defined amygdala ROIs (1) identified brain regions that are highly synchronous with the amygdala, (2) correlated neural changes with changes in overall depression and specific symptom clusters within depression. Results: Some neural correlates were common across domains: (1) decreased amygdala RSFC with the default mode network (posterior cingulate, precuneus) is associated with improvement in overall depression and many symptom clusters, (2) increased amygdala RSFC with fusiform gyrus is associated with symptom improvement across many symptom clusters. We also found unique neural changes associated with symptom improvement in each symptom cluster. Conclusion: This is the first preliminary study that looks at neural correlates of antidepressant treatment response to overall depression as well as different clusters of symptoms of depression. The finding suggests both overlapping and distinct neural mechanisms underlying improvement in each symptom clusters within depression. Some brain regions found are also implicated in MDD among adults in previous literature.

Keywords: depression, adolescents, fMRI, antidepressants

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Authors: Pei-Fan Mu

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Background: Lung cancer is the most common cancer with the highest mortality rate. Patients with lung cancer under chemotherapy treatment experience life-threatening uncertainty. This study was based on the broaden-and-build theory using intentionality reflection of the body and internalization of positive prioritization strategies to enhance positive emotions of patients with lung cancer. Purpose: The purpose of this study was to use a quasi-experimental research design to examine the effectiveness of the enhancing positive emotion program. Method: Data were collected from a medical center in Taiwan. Fifty-four participants with lung cancer were recruited. Thirty participants were in the experiential group receiving the two weeks program. The content of the program includes awareness and understanding of the symptom experience, co-existing with illness and establishing self-identity, cognitive-emotion adjustment and establishing a new body schema, and symptom management to reach spiritual well-being. Twenty-four participants were in the control group receiving regular nursing care. Baseline, one month later and two months later, programmed measurements of symptoms of distress, positive emotion, and psychological well-being. Results: These two weeks of enhancing the positive emotion program resulted in a significantly improved positive emotion score for the experimental group compared to the control group. The findings of this study indicated that the positive emotion had significant differences between the two groups. There were no differences in symptom distress between the two groups. Discussion: The findings indicated that the enhancing positive emotion program could help patients enhance their life-threatening facing conditions.

Keywords: positive emotion, lung cancer, experimental design, symptom distress

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Authors: Abiodun Ezekiel Adesina, Ijeoma Ginikanwa Akubugwo

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Information and Communication Technology, ICT can heighten pre-service teachers’ attitudes toward learning and metacognitive learning; however, there is a dearth of literature on the perception of the pre-service teachers on heightening their attitude toward learning and metacognitive learning. Thus, this study investigates the perception of pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT. Two research questions and four hypotheses guided the research. A mixed methods research was adopted for the study in concurrent triangulation type of integrating qualitative and quantitative approaches to the study. The cluster random sampling technique was adopted to select 250 pre-service science teachers in Oyo township. Two self-constructed instruments: Heightening Pre-service Science Teachers’ Attitude towards Learning and Metacognitive Learning through Information and Communication Technology Scale (HPALMIS, r=.73), and an unstructured interview were used for data collection. Thematic analysis, frequency counts and percentages, t-tests, and analysis of variance were used for data analysis. The perception level of the pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT is above average, with the majority perceiving that ICT can enhance their thinking about their learning. The perception was significant (mean=92.68, SD=10.86, df=249, t=134.91, p<.05). The perception was significantly differentiated by gender (t=2.10, df= 248, p<.05) in favour of the female pre-service teachers and based on the first time of ICTs use (F(5,244)= 9.586, p<.05). Lecturers of science and science related courses should therefore imbibe the use of ICTs in heightening pre-service teachers’ attitude towards learning and metacognitive learning. Government should organize workshops, seminars, lectures, and symposia along with professional bodies for the science education lecturers to keep abreast of the trending ICT.

Keywords: pre-service teachers’ attitude towards learning, metacognitive learning, ICT, pre-service teachers’ perspectives

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Authors: Maheshwari Payal, Shapurkar Mayaan

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The present research aimed at studying the awareness and attitudes of teachers towards inclusive education. The sample consisted of 60 teachers, teaching in the primary section (1st – 4th) of regular schools affiliated to the SSC board in Mumbai. The sample was selected by Multi-stage cluster sampling technique. A semi-structured self-constructed interview schedule and a self-constructed attitude scale were used to study the awareness of teachers about disability and Inclusive education, and their attitudes towards inclusive education respectively. Themes were extracted from the interview data and quantitative data was analyzed using SPSS package. Results revealed that teachers had some amount of awareness but an inadequate amount of information on disabilities and inclusive education. Disability to most (37) teachers meant “an inability to do something”. The difference between disability and handicap was stated by most as former being cognitive while handicap being physical in nature. With regard to Inclusive education, a large number (46) stated that they were unaware of the term and did not know what it meant. The majority (52) of them perceived maximum challenges for themselves in an inclusive set up, and emphasized on the role of teacher training courses in the area of providing knowledge (49) and training in teaching methodology (53). Although, 83.3% of teachers held a moderately positive attitude towards inclusive education, a large percentage (61.6%) of participants felt that being in inclusive set up would be very challenging for both children with special needs and without special needs. Though, most (49) of the teachers stated that children with special needs should be educated in a regular classroom, but they further clarified that only those should be in a regular classroom who have physical impairments of mild or moderate degree.

Keywords: attitude, awareness, inclusive education, teachers

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Authors: Ting-Yu Lin, Han-Liang Lin

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This article is about the urban form of visualization by Cityengine. City is composed of different domains, and each domain has its own fabric because of arrangement. For example, a neighborhood unit contains fabrics such as schools, street networks, residential and commercial spaces. Therefore, studying urban morphology can help us understand the urban form in planning process. Streets, plots, and buildings seem as urban fabrics, and they configure urban form. Traditionally, urban morphology usually discussed single parameter, which is building type, ignoring other parameters such as streets and plots. However, urban space is three-dimensional, instead of two-dimensional. People perceive urban space by their visualization. Therefore, using visualization can fill the gap between two dimensions and three dimensions. Hence, the study of urban morphology will strengthen the understanding of whole appearance of a city. Cityengine is a software which can edit, analyze and monitor the data and visualize the result for GIS, a common tool to analyze data and display the map for urban plan and urban design. Cityengine can parameterize the data of streets, plots and building types and visualize the result in three-dimensional way. The research will reappear the real urban form by visualizing. We can know whether the urban form can be parameterized and the parameterized result can match the real urban form. Then, visualizing the result by software in three dimension to analyze the rule of urban form. There will be three stages of the research. It will start with a field survey of Tainan East District in Taiwan to conclude the relationships between urban fabrics of street networks, plots and building types. Second, to visualize the relationship, it will turn the relationship into codes which Cityengine can read. Last, Cityengine will automatically display the result by visualizing.

Keywords: Cityengine, urban fabric, urban morphology, visual simulation

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Yin-Tzu Lin, Chen-Chen Lo, Kang Lo

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Background: Driving drowsiness related to inadequate or disordered sleep accounts for a major percentage of traffic accidents. Sleep-disordered breathing (SDB) syndrome is a common respiratory disorder during sleep. However, the effects of SDB syndrome on driving fatigue remain unclear. Objective: This study aims to investigate the relationship between SDB pattern and driving drowsiness. Methodologies: The physical condition while driving was obtained from the questionnaires to classify the state of driving fatigue. SDB syndrome was quantified as the polysomnography, and the air flow pattern was collected by the thermistor and nasal pressure cannula. To evaluate the desaturation, the mean hourly number of greater than 3% dips in oxygen saturation was sentenced by reregistered technologist during examination in a hospital in New Taipei City (Taiwan). The independent T-test was used to investigate the correlations between sleep disorders related index and driving drowsiness. Results: There were 880 subjects recruited in this study, who had been done polysomnography for evaluating severity for obstructive sleep apnea syndrome (OSAS) as well as completed the driver condition questionnaire. Four-hundred-eighty-four subjects (55%) were classified as fatigue group, and 396 subjects (45%) were served as the control group. Significantly higher values of snoring index (242.14 ± 205.51 /hours) were observed in the fatigue group (p < 0.01). The value of respiratory disturbance index (RDI) (31.82 ± 19.34 /hours) in fatigue group were significantly higher than the control group (p < 0.01). Conclusion: We observe the considerable association between SDB syndrome and driving drowsiness. To promote traffic safety, SDB syndrome should be controlled and alleviated.

Keywords: driving drowsiness, sleep-disordered breathing syndrome, snoring index, respiratory disturbance index.

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Authors: Shima Behkami, Nor Shahirul Umirah Idris, Sharifuddin Md. Zain, Kah Hin Low, Mehrdad Gholami, Nima A. Behkami, Ahmad Firdaus Kamaruddin

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In this work, Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Isotopic Ratio Mass Spectrometry (IRMS) and Ultrasound Milko Tester were used to study milk samples obtained from various geographical locations in Malaysia. ICP-MS was used to determine the concentration of trace elements in milk, water and soil samples obtained from seven dairy farms at different geographical locations in peninsular Malaysia. IRMS was used to analyze the milk samples for isotopic ratios of δ13C, 15N and 18O. Nutritional parameters in the milk samples were determined using an ultrasound milko tester. Data obtained from these measurements were evaluated by Principal Component Analysis (PCA) and Hierarchical Analysis (HA) as a preliminary step in determining geographical origin of these milk samples. It is observed that the isotopic ratios and a number of the nutritional parameters are responsible for the discrimination of the samples. It was also observed that it is possible to determine the geographical origin of these milk samples solely by the isotopic ratios of δ13C, 15N and 18O. The accuracy of the geographical discrimination is demonstrated when several milk samples from a milk factory taken from one of the regions under study were appropriately assigned to the correct PCA cluster.

Keywords: inductively coupled plasma mass spectroscopy ICP-MS, isotope ratio mass spectroscopy IRMS, ultrasound, principal component analysis, hierarchical analysis, geographical origin, milk

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Adepoju A. A., Olapade-Ogunwole F., Ganiyu M. O.

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This study examined women's empowerment in cassava production in southwest Nigeria. The contributions of the five domains namely decision about agricultural production, decision-making power over productive resources, control of the use of income, leadership and time allocation to women disempowerment, profiled the women based on their socio-economics features and determined factors influencing women's disempowerment. Primary data were collected from the women farmers and processors through the use of structured questionnaires. Purposive sampling was used to select the LGAs and villages based on a large number of cassava farmers and processors, while cluster sampling was used to select 360 respondents in the study area. Descriptive statistics such as bar charts and percentages, Women Empowerment in Agriculture (WEAI), and the Logit regression model were used to analyze the data collected. The results revealed that 63.88% of the women were disempowered. Lack of decision-making power over productive resources; 36.47% and leadership skills; 33.26% contributed mostly to the disempowerment of the women. About 85% of the married women were disempowered, while 76.92% of the women who participated in social group activities were more empowered than their disempowered counterparts. The findings showed that women with more years of processing experience have the probability of being disempowered while those who engage in farming as a primary livelihood activity, and participate in social groups among others have the tendency to be empowered. In view of this, it was recommended that women should be encouraged to farm and contribute to social group activities.

Keywords: cassava, production, empowerment, southwest, Nigeria

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Authors: Yi-Hsiu Lai

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The present study aimed to elucidate the lexical-semantic processing for Chinese as second language (CSL) learners. Twenty L1 speakers of Chinese and twenty CSL learners in Taiwan participated in a picture naming task and a category fluency task. Based on their Chinese proficiency levels, these CSL learners were further divided into two sub-groups: ten CSL learners of elementary Chinese proficiency level and ten CSL learners of intermediate Chinese proficiency level. Instruments for the naming task were sixty black-and-white pictures: thirty-five object pictures and twenty-five action pictures. Object pictures were divided into two categories: living objects and non-living objects. Action pictures were composed of two categories: action verbs and process verbs. As in the naming task, the category fluency task consisted of two semantic categories – objects (i.e., living and non-living objects) and actions (i.e., action and process verbs). Participants were asked to report as many items within a category as possible in one minute. Oral productions were tape-recorded and transcribed for further analysis. Both error types and error frequency were calculated. Statistical analysis was further conducted to examine these error types and frequency made by CSL learners. Additionally, category effects, pictorial effects and L2 proficiency were discussed. Findings in the present study helped characterize the lexical-semantic process of Chinese naming in CSL learners of different Chinese proficiency levels and made contributions to Chinese vocabulary teaching and learning in the future.

Keywords: lexical-semantic processing, Mandarin Chinese, naming, category effects

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Authors: Hirbaye Mokona, Abebaw Gebeyehu, Aemro Zerihun

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Introduction: Attention deficit hyperactivity disorder is serious public health problem affecting millions of children throughout the world. Method: A cross-sectional study conducted from May to June 2015 among children age 6 to 17 years living in rural area of Girja district. Multi-stage cluster sampling technique was used to select 1302 study participants. Disruptive Behavior Disorder rating scale was used to collect the data. Data were coded, entered and cleaned by Epi-Data version 3.1 and analyzed by SPSS version 20. Logistic regression analysis was used and Variables that have P-values less than 0.05 on multivariable logistic regression was considered as statistically significant. Results: Prevalence of Attention deficit hyperactivity disorder (ADHD) among children age 6 to 17 years was 7.3%. Being male [AOR=1.81, 95%CI: (1.13, 2.91)]; living with single parent [AOR=5.0, 95%CI: (2.35, 10.65)]; child birth order/rank [AOR=2.35, 95%CI: (1.30, 4.25)]; low family socio-economic status [AOR= 2.43, 95%CI: (1.29, 4.59)]; maternal alcohol/khat use during pregnancy [AOR=3.14, 95%CI: (1.37, 7.37)] and complication at delivery [AOR=3.56, 95%CI: (1.19, 10.64)] were more likely to develop Attention deficit hyperactivity disorder. Conclusion: In this study, the prevalence of Attention deficit hyperactivity disorder was similar with worldwide prevalence. Prevention and early management of its modifiable risk factors should be carryout alongside increasing community awareness.

Keywords: attention deficit hyperactivity disorder, ADHD, associated factors, children, prevalence

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Authors: Amir Ahmadi, Hossein Ahmadi, Alireza Ahmadi

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Emotional Intelligence (EI) has been defined as the ability to empathize, persevere, control impulses, communicate clearly, make thoughtful decisions, solve problems, and work with others in a way that earns friends and success. These abilities allow an individual to recognize and regulate emotion, develop self-control, set goals, develop empathy, resolve conflicts, and develop skills needed for leadership and effective group participation. Due to the increasing complexity of organizations and different ways of thinking, attitudes and beliefs of individuals, conflict as an important part of organizational life has been examined frequently. The main point is that the conflict is not necessarily in organization, unnecessary; but it can be more creative (increase creativity), to promote innovation. The purpose of this study was to investigate the relation between principals emotional intelligence as one of the factors affecting conflict management among teachers. This relation was analyzed through cluster sampling with a sample size consisting of 120 individuals. The results of the study showed that at the 95% level of confidence, the two secondary hypotheses (i.e. relation between emotional intelligence of principals and use of competition and cooperation strategies of conflict management among teachers) were confirmed, but the other three secondary hypotheses (i.e. the relation between emotional intelligence of managers and use of avoidance, adaptation and adaptability strategies of conflict management among teachers) were rejected. The primary hypothesis (i.e. relation between emotional intelligence of principals with conflict management among teachers) is supported.

Keywords: emotional intelligence, conflict, conflict management, strategies of conflict management

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Authors: Janis E. Campbell

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Most of what is known about complementary, alternative or traditional medicine (CATM) in the United States today is known from either the National Health Interview Survey a cross-sectional survey with a few questions or from small cross-sectional or cohort studies with specific populations. The broad geographical distribution in CATM use or providers is not known. For this project, we used geospatial cluster analysis to determine if there were clusters of CATM provider by county in the US. In this analysis, we used the National Provider Index to determine the geographic distribution of providers in the US. Of the 215,769 CAMT providers 211,603 resided in the contiguous US: Acupuncturist (26,563); Art, Poetry, Music and Dance Therapist (2,752); Chiropractor (89,514); Doula/Midwife (3,535); Exercise (507); Homeopath (380); Massage Therapist (36,540); Mechanotherapist (1,888); Naprapath (146); Naturopath (4,782); Nutrition (42,036); Reflexologist (522); Religious (2,438). ESRI® spatial autocorrelation was used to determine if the geographic location of CATM providers were random or clustered. For global analysis, we used Getis-Ord General G and for Local Indicators of Spatial Associations with an Optimized Hot Spot Analysis using an alpha of 0.05. Overall, CATM providers were clustered with both low and high. With Chiropractors, focusing in the Midwest, religious providers having very small clusters in the central US, and other types of CAMT focused in the northwest and west coast, Colorado and New Mexico, the great lakes areas and Florida. We will discuss some of the implications of this study, including associations with health, economic, social, and political systems.

Keywords: complementary medicine, alternative medicine, geospatial, United States

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Authors: Sweta Pandey, Samridhi Dhyani, Susmita Chaudhuri

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Klebsiella pneumoniae bacteria is a global threat to human health due to an increase in multi-drug resistance among strains. The hypervirulent strains of Klebsiella pneumoniae is a major trouble due to their association with life-threatening infections in a healthy population. One of the major virulence factors of hyper virulent strains of Klebsiella pneumoniae is the T6SS (Type six secretary system) which is majorly involved in microbial antagonism and causes interaction with the host eukaryotic cells during infections. T6SS mediates some of the crucial factors for establishing infection by the bacteria, such as cell adherence, invasion, and subsequent in vivo colonisation. The antibacterial activity and the cell invasion property of the T6SS system is a major requirement for the establishment of K. pneumoniae infections within the gut. The T6SS can be an appropriate target for developing therapeutics. The T6SS consists of an inner tube comprising hexamers of Hcp (Haemolysin -regulated protein) protein, and at the top of this tube sits VgrG (Valine glycine repeat protein G); the tip of the machinery consists of PAAR domain containing proteins which act as a delivery system for bacterial effectors. For this study, immune response to recombinant VgrG protein was generated to establish this protein as a potential immunogen for the development of therapeutic leads. The immunogenicity of the selected protein was determined by predicting the B cell epitopes by the BCEP analysis tool. The gene sequence for multiple domains of VgrG protein (phage_base_V, T6SS_Vgr, DUF2345) was selected and cloned in pMAL vector in E. coli. The construct was subcloned and expressed as a fusion protein of 203 residue protein with mannose binding protein tag (MBP) to enhance solubility and purification of this protein. The purified recombinant VgrG fusion protein was used for mice immunisation. The antiserum showed reactivity with the recombinant VgrG in ELISA and western blot. The immunised mice were challenged with K. pneumoniae bacteria and showed bacterial clearance in immunised mice. The recombinant VgrG protein can further be used for studying downstream signalling of VgrG protein in mice during infection and for therapeutic MAb development to eradicate K. pneumoniae infections.

Keywords: immune response, Klebsiella pneumoniae, multi-drug resistance, recombinant protein expression, T6SS, VgrG

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Authors: Zichao Zhang, Yifan Zhao, Samuel Court

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The carbon emission problem of the traditional construction industry has long been a pressing issue. With the growing emphasis on environmental protection and advancement of science and technology, the organic integration of digital technology and emission reduction has gradually become a mainstream solution. Among various sophisticated digital technologies, digital twins, which involve creating virtual replicas of physical systems or objects, have gained enormous attention in recent years as tools to improve productivity, optimize management and reduce carbon emissions. However, the relatively high implementation costs including finances, time, and manpower associated with digital twins have limited their widespread adoption. As a result, most of the current applications are primarily concentrated within a few industries. In addition, the creation of digital twins relies on a large amount of data and requires designers to possess exceptional skills in information collection, organization, and analysis. Unfortunately, these capabilities are often lacking in the traditional construction industry. Furthermore, as a relatively new concept, digital twins have different expressions and usage methods across different industries. This lack of standardized practices poses a challenge in creating a high-quality digital twin framework for construction. This paper firstly reviews the current academic studies and industrial practices focused on reducing greenhouse gas emissions in the construction industry using digital twins. Additionally, it identifies the challenges that may be encountered during the design and implementation of a digital twin framework specific to this industry and proposes potential directions for future research. This study shows that digital twins possess substantial potential and significance in enhancing the working environment within the traditional construction industry, particularly in their ability to support decision-making processes. It proves that digital twins can improve the work efficiency and energy utilization of related machinery while helping this industry save energy and reduce emissions. This work will help scholars in this field to better understand the relationship between digital twins and energy conservation and emission reduction, and it also serves as a conceptual reference for practitioners to implement related technologies.

Keywords: digital twins, emission reduction, construction industry, energy saving, life cycle, sustainability

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