Search results for: Score Fusion

Authors: Kanda Runapongsa Saikaew, Patcharaporn Jiranuwattanawong, Patinya Taearak

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Currently, there is excessively growing information about places on Facebook, which is the largest social network but such information is not explicitly organized and ranked. Therefore users cannot exploit such data to recommend places conveniently and quickly. This paper proposes a Facebook application and an Android application that recommend places based on the number of check-ins of those places, the distance of those places from the current location, the number of people who like Facebook page of those places, and the number of talking about of those places. Related Facebook data is gathered via Facebook API requests. The experimental results of the developed applications show that the applications can recommend places and rank interesting places from the most to the least. We have found that the average satisfied score of the proposed Facebook application is 4.8 out of 5. The users’ satisfaction can increase by adding the app features that support personalization in terms of interests and preferences.

Keywords: Mobile computing, location-based services, recommendation system, social network analysis.

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Authors: J. L. Andrade-Pineda, J.M. León-Blanco, M. Calle, P. L. González-R

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The enrollment in current Master's degree programs usually pursues gaining the expertise required in real-life workplaces. The experience we present here concerns the learning process of "Project Management Methodology (PMM)", around a cooperative/collaborative mechanism aimed at affording students measurable learning goals and providing the teacher with the ability of focusing on the weaknesses detected. We have designed a mixed summative/formative evaluation, which assures curriculum engage while enriches the comprehension of PMM key concepts. In this experience we converted the students into active actors in the evaluation process itself and we endowed ourselves as teachers with a flexible process in which along with qualifications (score), other attitudinal feedback arises. Despite the high level of self-affirmation on their discussion within the interactive assessment sessions, they ultimately have exhibited a great ability to review and correct the wrong reasoning when that was the case.

Keywords: Cooperative-collaborative learning, educational management, formative-summative assessment, leadership training.

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Authors: Mohamed Ben Aouicha, Mohamed Tmar, Mohand Boughanem, Mohamed Abid

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This paper presents an information retrieval model on XML documents based on tree matching. Queries and documents are represented by extended trees. An extended tree is built starting from the original tree, with additional weighted virtual links between each node and its indirect descendants allowing to directly reach each descendant. Therefore only one level separates between each node and its indirect descendants. This allows to compare the user query and the document with flexibility and with respect to the structural constraints of the query. The content of each node is very important to decide weither a document element is relevant or not, thus the content should be taken into account in the retrieval process. We separate between the structure-based and the content-based retrieval processes. The content-based score of each node is commonly based on the well-known Tf × Idf criteria. In this paper, we compare between this criteria and another one we call Tf × Ief. The comparison is based on some experiments into a dataset provided by INEX1 to show the effectiveness of our approach on one hand and those of both weighting functions on the other.

Keywords: XML retrieval, INEX, Tf × Idf, Tf × Ief

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Authors: Nitesh Pandey, Manish Kumar, Pankaj Gupta, Amit Kumar Srivastava

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The convertible table is a versatile and adaptable item designed to provide numerous solutions in one. The design incorporates numerous features that offer both ease and functionality. The description of the versatile convertible table in this overview encompasses a range of features that can be tailored to accommodate various user requirements. With its changeable functionality, this piece can easily transform into a workstation, dining table, or coffee table to suit various needs. Significantly, this multipurpose convertible laptop table includes a specific section for electronic devices such as computers and tablets, offering convenience for remote workers and online learners. In addition, providing storage space for essential equipment promotes a tidy workspace by facilitating the organization of many items. The integrated flash system offers supplementary illumination for dimly lit surroundings, while the cooling fans prevent the table's surface from overheating in hot weather or during prolonged laptop usage, making it an optimal and superior choice for laptop users. In order to cater to the needs of students, painters, and other individuals who require writing tools on a regular basis, a pencil and pen stand is included, hence enhancing the versatility of the table. The scissor lift mechanism allows for easy modifications in height, making it convenient to customize usage and providing the option of using it as a standing desk. Overall, this convertible table exemplifies its ability to adapt, its user-friendly nature, and its usefulness in a wide range of situations and settings.

Keywords: Furniture design, laptop stand, study table, learning tool, furniture manufacturing, contemporary design.

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Authors: M. Kalamani, S. Valarmathy, M. Krishnamoorthi

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In this paper, Least Mean Square (LMS) adaptive noise reduction algorithm is proposed to enhance the speech signal from the noisy speech. In this, the speech signal is enhanced by varying the step size as the function of the input signal. Objective and subjective measures are made under various noises for the proposed and existing algorithms. From the experimental results, it is seen that the proposed LMS adaptive noise reduction algorithm reduces Mean square Error (MSE) and Log Spectral Distance (LSD) as compared to that of the earlier methods under various noise conditions with different input SNR levels. In addition, the proposed algorithm increases the Peak Signal to Noise Ratio (PSNR) and Segmental SNR improvement (ΔSNRseg) values; improves the Mean Opinion Score (MOS) as compared to that of the various existing LMS adaptive noise reduction algorithms. From these experimental results, it is observed that the proposed LMS adaptive noise reduction algorithm reduces the speech distortion and residual noise as compared to that of the existing methods.

Keywords: LMS, speech enhancement, speech quality, residual noise.

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Authors: Pitaktiratham J., Sinlan T., Anuntavoranich P., Sinthupinyo S.

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The Kansei engineering is a technology which converts human feelings into quantitative terms and helps designers develop new products that meet customers- expectation. Standard Kansei engineering procedure involves finding relationships between human feelings and design elements of which many researchers have found forward and backward relationship through various soft computing techniques. In this paper, we proposed the framework of Kansei engineering linking relationship not only between human feelings and design elements, but also the whole part of product, by constructing association rules. In this experiment, we obtain input from emotion score that subjects rate when they see the whole part of the product by applying semantic differentials. Then, association rules are constructed to discover the combination of design element which affects the human feeling. The results of our experiment suggest the pattern of relationship of design elements according to human feelings which can be derived from the whole part of product.

Keywords: Association Rules Mining, Kansei Engineering, Product Design, Semantic Differentials

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Authors: Petar Halachev

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Forecasting the values of the indicators, which characterize the effectiveness of performance of organizations is of great importance for their successful development. Such forecasting is necessary in order to assess the current state and to foresee future developments, so that measures to improve the organization-s activity could be undertaken in time. The article presents an overview of the applied mathematical and statistical methods for developing forecasts. Special attention is paid to artificial neural networks as a forecasting tool. Their strengths and weaknesses are analyzed and a synopsis is made of the application of artificial neural networks in the field of forecasting of the values of different education efficiency indicators. A method of evaluation of the activity of universities using the Balanced Scorecard is proposed and Key Performance Indicators for assessment of e-learning are selected. Resulting indicators for the evaluation of efficiency of the activity are proposed. An artificial neural network is constructed and applied in the forecasting of the values of indicators for e-learning efficiency on the basis of the KPI values.

Keywords: artificial neural network, balanced scorecard, e-learning

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Authors: Vaishali P. Joshi, Pallav Joshi

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The objective of this study is to examine the differences fashion innovators and non-fashion innovators in their fashion consumption behavior in terms of their pre-purchase behavior, purchase behavior and post purchase behavior. The questionnaire was distributed to a female college student for data collection for achieving the objective of the first part of the study. Question-related to fashion innovativeness and fashion consumption behavior was asked. The sample was comprised of 81 college females ages 18 through 30 who were attending Business Management degree. A series of attitude questions was used to categorize respondents on the Innovativeness Scale. 32 respondents with a score of 21 and above were designated as Fashion innovators and the remainder (49) as Non-fashion innovators. Findings showed that there exist significant differences between innovators and non-innovators in their fashion consumption behavior. Data was analyzed through frequency distribution table. Many differences were found in the behavior of innovators and non-innovators in terms of their pre-purchase, actual purchase, and post-purchase behavior.

Keywords: Consumption behavior, fashion, innovativeness, frequency distribution table.

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper presents sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for CHD prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, coronary heart disease, ECG, electrocardiogram, ResNet, sliding window.

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Authors: Teerawach Khamkorn, Laongtip Mathurasa, Savittree Rochanasmita Arnold, Witthaya Mekhum

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The objective of this research seeks to transmit a distance training model to the community in the upper northeastern region. The group sampling consists of 60 community leaders in the municipality of sub-district Kumphawapi, Kumphawapi Disrict, Udonthani Province. The research tools rely on the following instruments, they are : 1) the achievement test of community leaders- training and 2) the satisfaction questionnaires of community leaders. The statistics used in data analysis takes the statistical mean, percentage, standard deviation, and statistical T-test. The resulted findings reveal : 1) the efficiency of the distance training developed by the researcher for the community leaders joining in the training received the average score between in-training and post-training period higher than the setup criterion, 2) the two groups of participants in the training achieved higher knowledge than their pre-training state, 3) the comparison of the achievements between the two group presented no different results, 4) the community leaders obtained the high-to-highest satisfaction.

Keywords: Distance Training, Management, Technology, Transmitting.

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Authors: Angela R. Roundy, Philip T. Roundy

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Fluency is a skill that, unfortunately, many students lack. This deficiency causes students to be frustrated with, and overwhelmed by, the act of reading. However, research suggests that the repeated reading method may help students to improve their fluency. This study examines the effects of repeated readings on student fluency. The study-s overarching question is: What effect do increases in repeated reading have on reading fluency among middle school students from diverse backgrounds? More specifically, the authors examine whether repeated reading improves the fluency, reading speed, reading-oriented self-esteem, and confidence of students of diverse academic abilities, socio-economics statuses, and racial and ethnic backgrounds. To examine these questions the authors conducted a study using repeated reading strategies with a sample of students from an urban, middle school in the southeastern United States. We found that, on average, the use of repeated reading strategies increased students- fluency, words per minute (wpm) reading score, reading-oriented self-esteem, and confidence.

Keywords: Comprehension, Diverse Learners, Reading Fluency, Repeated Reading.

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Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

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Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: GraphViz representation, semantic relatedness, similarity measurement, WordNet similarity.

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Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis

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Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.

Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.

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Authors: K. Paisal

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The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: Constructivism, learning management, Mathematical Analysis courses.

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Authors: Akbar Soleimani, Alireza Heravi Moussavi, Mohsen Danesh Mesgaran, Abolqasem Golian

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Twenty - nine Holstein cows were used to evaluate the effects of different dry period (DP) lengths on milk yield and composition, some blood metabolites, and complete blood count (CBC). Cows were assigned to one of 2 treatments: 1) 60-d dry period, 2) 35-d DP. Milk yield, from calving to 60 days, was not different for cows on the treatments (p =0.130). Cows in the 35-d DP produced more milk protein and SNF compare with cows in treatment 1 (p ≤ 0.05). Serum glucose, non-esterified fatty acids (NEFA), beta hydroxyl butyrate acid (BHBA), blood urea nitrogen (BUN), urea, and glutamic oxaloacetic transaminase (GOT) were all similar among the treatments. Body condition score (BCS), body weight (BW), complete blood count (CBC) and health problems were similar between the treatments. The results of this study demonstrated we can reduce the dry period length to 35 days with no problems.

Keywords: complete blood count, dairy cows, dry period, milk yield

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Authors: JiEun Jeong, Se-Won Kang, Hee-Ju Hwang, Sung-Hwa Chae, Sang-Haeng Choi, Hong-SeogPark, YeonSoo Han, Bok-Reul Lee, Dae-Hyun Seog, Yong Seok Lee

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Tofurther advance research on immune-related genes from T. molitor, we constructed acDNA library and analyzed expressed sequence taq (EST) sequences from 1,056 clones. After removing vector sequence and quality checkingthrough thePhred program (trim_alt 0.05 (P-score>20), 1039 sequences were generated. The average length of insert was 792 bp. In addition, we identified 162 clusters, 167 contigs and 391 contigs after clustering and assembling process using a TGICL package. EST sequences were searchedagainst NCBI nr database by local BLAST (blastx, EKeywords: EST, Innate immunity, Tenebriomolitor

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Authors: Jong Hoon Kim, Hyun-Soo Lee, Moonseo Park, Min Jeong, Inbeom Lee

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Pre-construction is essential in achieving the success of a construction project. Due to the early involvement of project participants in the construction phase, project managers are able to plan ahead and solve issues well in advance leading to the success of the project and the satisfaction of the client. This research utilizes quantitative data derived from construction management projects in order to identify the relationship between pre-construction, construction schedule, and client satisfaction. A total of 65 construction projects and 93 clients were investigated for this research in an attempt to identify (a) the relationship between pre-construction and schedule reduction, and (b) pre-construction and client loyalty. Based on the quantitative analysis, this research was able to establish a negative correlation based on 65 construction projects between pre-construction and project schedule existed. This finding represents that the more pre-construction is performed for a certain project, the overall construction schedule decreased. Then, to determine the relationship between pre-construction and client satisfaction, Net Promoter Score (NPS) of 93 clients from the 65 projects was utilized. Pre-construction and NPS was further analyzed and a positive correlation was found between the two. This infers that clients tend to be more satisfied with projects with higher ratio of pre-construction than those projects with less pre-construction.

Keywords: Client loyalty, NPS, pre-construction, schedule reduction.

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial neural network, competitive dynamics, logistic regression, text classification, text mining.

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: Convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation.

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Authors: Ratthapong Bunyanuwat

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The purposes of this research were to study the citizen participation in preventing illegal drugs in one of a poor and small community of Bangkok, Thailand and to compare the level of participation and concern of illegal drugs problem by using demographic variables. This paper drew upon data collected from a local citizens survey conducted in Bangkok, Thailand during summer of 2012. A total of 200 respondents were elicited as data input for, and one way ANOVA test. The findings revealed that the overall citizen participation was in the level of medium. The mean score showed that benefit from the program was ranked as the highest and the decision to participate was ranked as second while the follow-up of the program was ranked as the lowest. In terms of the difference in demographic such as gender, age, level of education, income, and year of residency, the hypothesis testing’s result disclosed that there were no difference in their level of participation. However, difference in occupation showed a difference in their level of participation and concern which was significant at the 0.05 confidence level.

Keywords: Citizen Participation, Illegal drug, Preventing drug problem, Resolving drug problem

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Authors: Kasra Afsahi, Maryam Soheilifar, Noureddin Nakhostin Ansari

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COVID-19 has been associated with stroke and neurological complications. The patient was a 59-year-old male presented with sudden left hemiparesis and diplopia due to cavernous sinus thrombosis (CST) on 28/03/2020. The COVID-19 test was positive. Multislice computerized tomography (MSCT) showed ischemic infarction. He underwent surgical sinectomy 9 days after admission. Physiotherapy began for him on August 2020. Our game-based virtual reality (VR) technology developed for stroke patients was based on upper extremity exercises and function for stroke. After 6 weeks of VR therapy plus conventional physiotherapy exercises (18 sessions, three times per week, 60 minutes each session), there were significant improvements in Brunnstrom Motor Recovery Stage (from “4” to “5”), Fugl-Meyer Scale score of upper extremity section (from 49 to 54), and Modified Barthel Index (from 15 to 18). There were no adverse effects. This case with stroke post COVID-19 due to the CST showed the usefulness of VR therapy used as an adjunct to conventional physiotherapy in improving affected upper extremity.

Keywords: COVID-19, stroke, virtual reality, rehabilitation.

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Authors: Jia-Ru Li, Chih-Hung Wang, Ching-Wen Lin

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The association between emotional inhibition strategies linked to depression has been showed inconsistent among studies. Mild emotional inhibition maybe benefit for social interaction, especially for female among East Asian cultures. The present study aimed to examine whether the inhibition–depression relationship is dependent on level of emotion inhibition and gender context, given differing value of suppressing emotional displays. We hypothesized that the negative associations between inhibition and adolescent depression would not directly, in which affected by interaction between emotion inhibition and gender. To test this hypothesis, we asked 309 junior high school students which age range from 12 to14 years old to report on their use of emotion inhibition and depression syndrome. A multiple regressions analysis revealed that significant interaction that gender as a moderator to the relationships between emotion inhibition and adolescent depression. The group with the highest level of depression was girls with high levels of emotion inhibition, whose depression score was higher than that of boys with high levels of emotion inhibition. The result highlights that the importance of context in understanding the inhibition-depression relationship.

Keywords: Emotional inhibition strategies, gender, adolescent depression.

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Authors: Horia Păunescu

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Purpose: The study aimed to assess the depressant or antidepressant effects of several Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) in mice: the selective cyclooxygenase-2 (COX-2) inhibitor meloxicam, and the non-selective COX-1 and COX-2 inhibitors lornoxicam, sodium metamizole, and ketorolac. The current literature data regarding such effects of these agents are scarce. Materials and methods: The study was carried out on NMRI mice weighing 20-35 g, kept in a standard laboratory environment. The study was approved by the Ethics Committee of the University of Medicine and Pharmacy „Carol Davila”, Bucharest. The study agents were injected intraperitoneally, 10 mL/kg body weight (bw) 1 hour before the assessment of the locomotor activity by cage testing (n=10 mice/ group) and 2 hours before the forced swimming tests (n=15). The study agents were dissolved in normal saline (meloxicam, sodium metamizole), ethanol 11.8% v/v in normal saline (ketorolac), or water (lornoxicam), respectively. Negative and positive control agents were also given (amitryptilline in the forced swimming test). The cage floor used in the locomotor activity assessment was divided into 20 equal 10 cm squares. The forced swimming test involved partial immersion of the mice in cylinders (15/9cm height/diameter) filled with water (10 cm depth at 28C), where they were left for 6 minutes. The cage endpoint used in the locomotor activity assessment was the number of treaded squares. Four endpoints were used in the forced swimming test (immobility latency for the entire 6 minutes, and immobility, swimming, and climbing scores for the final 4 minutes of the swimming session), recorded by an observer that was „blinded” to the experimental design. The statistical analysis used the Levene test for variance homogeneity, ANOVA and post-hoc analysis as appropriate, Tukey or Tamhane tests. Results: No statistically significant increase or decrease in the number of treaded squares was seen in the locomotor activity assessment of any mice group. In the forced swimming test, amitryptilline showed an antidepressant effect in each experiment, at the 10 mg/kg bw dosage. Sodium metamizole was depressant at 100 mg/kg bw (increased the immobility score, p=0.049, Tamhane test), but not in lower dosages as well (25 and 50 mg/kg bw). Ketorolac showed an antidepressant effect at the intermediate dosage of 5 mg/kg bw, but not so in the dosages of 2.5 and 10 mg/kg bw, respectively (increased the swimming score, p=0.012, Tamhane test). Meloxicam and lornoxicam did not alter the forced swimming endpoints at any dosage level. Discussion: 1) Certain NSAIDs caused changes in the forced swimming patterns without interfering with locomotion. 2) Sodium metamizole showed a depressant effect, whereas ketorolac proved antidepressant. Conclusion: NSAID-induced mood changes are not class effects of these agents and apparently are independent of the type of inhibited cyclooxygenase (COX-1 or COX-2). Disclosure: This paper was co-financed from the European Social Fund, through the Sectorial Operational Programme Human Resources Development 2007-2013, project number POSDRU /159 /1.5 /S /138907 "Excellence in scientific interdisciplinary research, doctoral and postdoctoral, in the economic, social and medical fields -EXCELIS", coordinator The Bucharest University of Economic Studies.

Keywords: Antidepressant, depressant, forced swim, NSAIDs.

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Authors: Haohao Wang

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Technology, multimedia in Open Educational Resources, can contribute positively to student performance in an online instructional environment. Student performance data of past four years were obtained from an online course entitled Applied Calculus (MA139). This paper examined the data to determine whether multimedia (independent variable) had any impact on student performance (dependent variable) in online math learning, and how students felt about the value of the technology. Two groups of student data were analyzed, group 1 (control) from the online applied calculus course that did not use multimedia instructional materials, and group 2 (treatment) of the same online applied calculus course that used multimedia instructional materials. For the MA139 class, results indicate a statistically significant difference (p = .001) between the two groups, where group 1 had a final score mean of 56.36 (out of 100), group 2 of 70.68. Additionally, student testimonials were discussed in which students shared their experience in learning applied calculus online with multimedia instructional materials.

Keywords: Online learning, Open Educational Resources, Multimedia, Technology.

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Authors: F. P., Chew, M. H., Teong, Z. Ishak

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School homework has been synonymous with students- life in Chinese national type primary schools in Malaysia. Although many reports in the press claimed that students were burdened with too much of it, homework continues to be a common practice in national type schools that is believed to contribute to academic achievement. This study is conducted to identify the relationship between the burden of school homework and academic achievement among pupils in Chinese National Type Primary School in the state of Perak, Malaysia. A total of 284 students (142 from urban and 142 from rural) respectively were chosen as participants in this study. Variables of gender and location (urban/rural areas) has shown significant difference in student academic achievement. Female Chinese student from rural areas showed a higher mean score than males from urban area. Therefore, the Chinese language teachers should give appropriate and relevant homework to primary school students to achieve good academic performance.

Keywords: homework, academic achievement, Chinese National Type Primary Schools

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Authors: Thanapol Wisuttikul, Choochart Haruechaiyasak, Santipong Thaiprayoon

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Thailand has evolved many unique culture and knowledge, and the leading is the Thai traditional medicine (TTM). Recently, a number of researchers have tried to save this indigenous knowledge. However, the system to do so has still been scant. To preserve this ancient knowledge, we therefore invented and integrated multi-linguistic techniques to create the system of the collected all of recipes. This application extracted the medical recipes from antique scriptures then normalized antiquarian words, primitive grammar and antiquated measurement of them to the modern ones. Then, we applied ingredient-duplication-calculation, proportion-similarity-calculation and score-ranking to examine duplicate recipes. We collected the questionnaires from registrants and people to investigate the users’ satisfaction. The satisfactory results were found. This application assists not only registrants to validating the copyright violation in TTM registration process but also people to cure their illness that aids both Thai people and all mankind to fight for intractable diseases.

Keywords: Medicine Registration, Search Engine, Text Approximation, Traditional Medicine.

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Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: Color space, neural network, random forest, skin detection, statistical feature.

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Authors: Phumelele P. Kubheka, Pius A. Owolawi, Gbolahan Aiyetoro

Abstract:

Twitter is one of the most popular social media platforms where users share their opinions on different subjects. Twitter can be considered a great source for mining text due to the high volumes of data generated through the platform daily. Many industries such as telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model in this experiment. A higher topic coherence score indicates better performance of the model.

Keywords: Big data, latent Dirichlet allocation, latent semantic indexing, Telco, topic modeling, Twitter.

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Authors: Gomes C. C. Izabel, Lanzotti B. Rafaela, Orlandi S. Fabiana

Abstract:

Chronic Kidney Disease is considered a serious public health problem. The exploitation of resilience has been guided by studies conducted in various contexts, especially in hemodialysis, since the impact of diagnosis and restrictions produced during the treatment process because, despite advances in treatment, remains the stigma of the disease and the feeling of pain, hopelessness, low self-esteem and disability. The objective was to evaluate the level of resilience of patients in chronic renal dialysis. This is a descriptive, correlational, cross and quantitative research. The sample consisted of 100 patients from a Renal Replacement Therapy Unit in the countryside of São Paulo. For data collection were used the characterization instrument of Participants and the Resilience Scale. There was a predominance of males (70.0%) were Caucasian (45.0%) and had completed elementary education (34.0%). The average score obtained through the Resilience Scale was 131.3 (± 20.06) points. The resiliency level submitted may be considered satisfactory. It is expected that this study will assist in the preparation of programs and actions in order to avoid possible situations of crises faced by chronic renal patients.

Keywords: Hemodialysis units, hospital, renal dialysis, renal insufficiency chronic, resilience psychological.

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Authors: Samir Abdelhamid, Noureddine Bouguechal

Abstract:

We report in this paper the model adopted by our system of continuous speech recognition in Arab language SySRA and the results obtained until now. This system uses the database Arabdic-10 which is a corpus of word for the Arab language and which was manually segmented. Phonetic decoding is represented by an expert system where the knowledge base is translated in the form of production rules. This expert system transforms a vocal signal into a phonetic lattice. The higher level of the system takes care of the recognition of the lattice thus obtained by deferring it in the form of written sentences (orthographical Form). This level contains initially the lexical analyzer which is not other than the module of recognition. We subjected this analyzer to a set of spectrograms obtained by dictating a score of sentences in Arab language. The rate of recognition of these sentences is about 70% which is, to our knowledge, the best result for the recognition of the Arab language. The test set consists of twenty sentences from four speakers not having taken part in the training.

Keywords: Continuous speech recognition, lexical analyzer, phonetic decoding, phonetic lattice, vocal signal.

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