Search results for: multiple group analysis

Authors: Anunya Thanasrisuebwong

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This research paper aimed to find out how was the ethical climate in an organization and job performance satisfaction of employees affected employees’ engagement and commitment by using the case study of PTT Exploration and Production Public Company Limited, Thailand. The population of this research was 4,383 Thai employees of PTTEP, Thailand. From a total of 420 questionnaires sent out, 345 respondents replied. The statistics utilized was mean score and Multiple Regression Analysis. The findings revealed that the respondents had opinion towards ethical climate of their organization, job performance satisfaction and organization engagement and commitment at a high level. The test of hypothesis disclosed the determinant attributes of job performance satisfaction that affected the respondents’ overall level of organization engagement and commitment. The set of these determinant attributes consisted of employees’ responsibilities for duties, organization’s policies and practice, relationship with organization’s commanders, work security and stability, job description, career path and relationship with colleagues. These variables were able to predict the employees’ organization engagement and commitment at 50.6 percent.

Keywords: ethical climate in organization, job performance satisfaction, organization engagement, commitment

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Authors: Yongqi Dong, Zuo Zhang, Rui Fu, Li Li

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The records generated by taxicabs which are equipped with GPS devices is of vital importance for studying human mobility behavior, however, here we are focusing on taxi drivers' operation strategies between workdays and weekends temporally and spatially. We identify a group of valuable characteristics through large scale drivers' behavior in a complex metropolis environment. Based on the daily operations of 31,000 taxi drivers in New York City, we classify drivers into top, ordinary and low-income groups according to their monthly working load, daily income, daily ranking and the variance of the daily rank. Then, we apply big data analysis and visualization methods to compare the different characteristics among top, ordinary and low income drivers in selecting of working time, working area as well as strategies between workdays and weekends. The results verify that top drivers do have special operation tactics to help themselves serve more passengers, travel faster thus make more money per unit time. This research provides new possibilities for fully utilizing the information obtained from urban taxicab data for estimating human behavior, which is not only very useful for individual taxicab driver but also to those policy-makers in city authorities.

Keywords: big data, operation strategies, comparison, revenue, temporal, spatial

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Authors: Hyun-Ju Oh, Soon-Rim Suh, Mihan Kim

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The steady and rapid increase of the older population is a global phenomenon. Chronic diseases and disabilities are increased due to aging. In general, exercise has been known to be most effective in preventing and managing chronic back pain. However, it is hard for the older women to initiate and maintain the exercise. Transtheoretical model (TTM) is one of the theories explain behavioral changes such as exercise. The application of the program considering the stage of behavior change is effective for the elderly woman to start and maintain the exercise. The purpose of this study was to develop TTM based exercise program and to examine its effect for elderly women with chronic back-pain. For the program evaluation, the non-equivalent control pre-posttest design was applied. The independent variable of this study is exercise intervention program. The contents of the program were constructed considering the characteristics of the elderly women with chronic low back pain, focusing on the process of change, the stage of change by the previous studies. The developed exercise program was applied to the elderly women with chronic low back pain in the planning stage and the preparation stage. The subjects were 50 older women over 65 years of age with chronic back-pain who did not practice regular exercise. The experimental group (n=25) received the 8weeks TTM based exercise program. The control group received the book which named low back pain management. Data were collected at three times: before the exercise intervention, right after the intervention, and 4weeks after the intervention. The dependent variables were the processes of change, decisional balance, exercise self-efficacy, back-pain, depression and muscle strength. The results of this study were as follows. Processes of change (<.001), pros of decisional balance (<.001), exercise self-efficacy (<.001), back pain (<.001), depression (<.001), muscle strength (<.001) were higher in the experimental group than in the control group right after the program and 4weeks after the programs. The results of this study show that applying the TTM based exercise program increases the use of the change process, increases the exercise self-efficacy, increases the stage of changing the exercise behavior and strengthens the muscular strength by lowering the degree of pain and depression Respectively. The significance of the study was to confirm the effect of continuous exercise by maintaining regular exercise habits by applying exercise program of the transtheoretical model to the chronic low back pain elderly with exercise intention.

Keywords: chronic back pain, elderly, exercise, women

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Authors: D. Garg, S. Luthra, A. Haleem

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Reverse logistics (RL) is supposed to be a systematic procedure that helps in improving the environmental hazards and maintain business sustainability for industries. Industries in Indian are now opting for adoption of RL techniques in business. But, RL practices are not popular in Indian industries because of many barriers for its successful implementation. Therefore, need arises to identify and evaluate the barriers to implement RL practices by taking an Indian industries perspective. Literature review approach and case study approach have been adapted to identify relevant barriers to implement RL practices. Further, Fuzzy Decision Making Trial and Evaluation Laboratory methodology has been brought into use for evaluating causal relationships among the barriers to implement RL practices. Seven barriers out of ten barriers have been categorized into the cause group and remaining into effect group. This research will help Indian industries to manage these barriers towards effective implementing RL practices.

Keywords: barriers, decision making trial and evaluation laboratory (DEMATEL), fuzzy set theory, Indian industries, reverse logistics (RL)

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Authors: Simin Sasani

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This study will explore a group of English language teachers’ understanding of intercultural competence to find out if they are aware of the concept and how important it is for them. It will investigate how much they are concerned about the challenges that the learners might face in their intercultural communications and to what extent they can help the learners to overcome the barriers to increase students’ insight into cultural differences. In addition, it will explore how a group of non-native English language teachers define culture in relation to their English language teaching practices. More specifically, the research tries to take the how and why of inclusion of intercultural competence into consideration and how non-native teachers think they can improve their learners’ knowledge and skills in this domain. The study will be conducted in the UK and the participants are eight non-native English language teachers who are currently teaching general English language courses for foreigners. A pilot study have been conducted for this research which its results show three non-native English teachers are aware of the notion although they have not had any formal education about intercultural competence. Their challenges and limitation were also highlighted through interviews and observations.

Keywords: English, English language teachers, intercultural communications, intercultural competence, non-natives

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Authors: Eric Jacob Bacon, Chaoyang Jin, Dianning He, Shuaishuai Hu, Lanbo Wang, Han Li, Shouliang Qi

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Objective: Refractory epilepsy is a complicated type of epilepsy that can be difficult to diagnose. Recent technological advancements have made resting-state functional magnetic resonance (rsfMRI) a vital technique for studying brain activity. However, there is still much to learn about rsfMRI. Investigating rsfMRI connectivity may aid in the detection of abnormal activities. In this paper, we propose studying the functional connectivity of rsfMRI candidates to diagnose epilepsy. Methods: 45 rsfMRI candidates, comprising 26 with refractory epilepsy and 19 healthy controls, were enrolled in this study. A data-driven approach known as independent component analysis (ICA) was used to achieve our goal. First, rsfMRI data from both patients and healthy controls were analyzed using group ICA. The components that were obtained were then spatially sorted to find and select meaningful ones. A two-sample t-test was also used to identify abnormal networks in patients and healthy controls. Finally, based on the fractional amplitude of low-frequency fluctuations (fALFF), a chi-square statistic test was used to distinguish the network properties of the patient and healthy control groups. Results: The two-sample t-test analysis yielded abnormal in the default mode network, including the left superior temporal lobe and the left supramarginal. The right precuneus was found to be abnormal in the dorsal attention network. In addition, the frontal cortex showed an abnormal cluster in the medial temporal gyrus. In contrast, the temporal cortex showed an abnormal cluster in the right middle temporal gyrus and the right fronto-operculum gyrus. Finally, the chi-square statistic test was significant, producing a p-value of 0.001 for the analysis. Conclusion: This study offers evidence that investigating rsfMRI connectivity provides an excellent diagnosis option for refractory epilepsy.

Keywords: ICA, RSN, refractory epilepsy, rsfMRI

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Authors: Chiung-Ju Huang

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This study utilizes the quantile regression analysis to examine the impact of governance (including democratic quality and technical quality) on happiness in 101 countries worldwide, classified as “developed countries” and “developing countries”. The empirical results show that the impact of democratic quality and technical quality on happiness is significantly positive for “developed countries”, while is insignificant for “developing countries”. The results suggest that the authorities in developed countries can enhance the level of individual happiness by means of improving the democracy quality and technical quality. However, for developing countries, promoting the quality of governance in order to enhance the level of happiness may not be effective. Policy makers in developed countries may pay more attention on increasing real GDP per capita instead of promoting the quality of governance to enhance individual happiness.

Keywords: governance, happiness, multiple regression, quantile regression

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Authors: Behdokht Mall-Amiri, Sara Farzaminejad

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The purpose of the present study was to discover which of the two writing activities, a self-assessment questioner or a critical thinking skills handout, is more effective on Iranian EFL learners’ writing ability. To fulfill the purpose of the study, a sample of 120 undergraduate students of English SAT for a standardized sample of PET. Eighty-two students whose scores fell one standard deviation above and below the sample mean were selected and randomly divided into two equal groups. One group practiced self-assessment and the other group practiced critical thinking skills while they were learning process writing. A writing posttest was finally administered to the students in both groups and the mean rank scores were compared by t-test. The result led to the rejection of the null hypothesis, indicating that practicing critical thinking skills had a significantly higher effect on the writing ability. The implications of the study for students and teachers as well as course book designers are discussed.

Keywords: writing ability, process writing, critical thinking skills, self-assessment

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Authors: Qinglu Wu, Anna Wai-Man Choi, Peilian Chi

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Gratitude is one individual strength that not only facilitates the mental health, but also fosters the relationship satisfaction in the romantic relationship. In terms of moral effect theory and stress-and-coping theory of forgiveness, present study not only investigated the association between grateful disposition and relationship satisfaction, but also explored the mechanism by comprehensively examining the potential mediating roles of three profiles of forgiveness (trait forgivingness, decisional forgiveness, emotional forgiveness), another character strength that highly related to the gratitude and relationship satisfaction. Structural equation modeling was used to conduct the multiple mediator model with a sample of 103 Chinese college students in dating relationship (39 male students and 64 female students, Mage = 19.41, SD = 1.34). Findings displayed that both gratitude and relationship satisfaction positively correlated with decisional forgiveness and emotional forgiveness. Emotional forgiveness was the only mediator, and it completely mediated the relationship between gratitude and relationship satisfaction. Gratitude was helpful in enhancing individuals’ perception of satisfaction in romantic relationship through replacing negative emotions toward partners with positive ones after transgression in daily life. It highlighted the function of emotional forgiveness in personal healing and peaceful state, which is important to the perception of satisfaction in relationship. Findings not only suggested gratitude could provide a stability for forgiveness, but also the mechanism of prosocial responses or positive psychological processes on relationship satisfaction. The significant roles of gratitude and emotional forgiveness could be emphasized in the intervention working on the romantic relationship development or reconciliation.

Keywords: decisional forgiveness, emotional forgiveness, gratitude, relationship satisfaction, trait forgivingness

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Authors: Amir Ghasemlouei, Alireza Khalaj

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In women, cancer of the breast is one of the most common incident cancer and cause of death from cancer .we reviewed the prevalence of obesity and its association with breast cancer. In this study, a total of 25 articles regarding the subject matter of the article have been presented in which 640 patients were examined that 320 patients with breast cancer and 320 were controls. The distribution of breast cancer patients and controls with respect to their anthropometric indices in patients with higher weight, which was statistically significant (60.2 ± 10.2 kg) compared with control group (56.1 ± 11.3 kg). The body mass index of patients was (26.06+/-3.42) and significantly higher than the control group (24.1+/-1.7). Obesity leads to increased levels of adipose tissue in the body that can be stored toxins and carcinogens to produce a continuous supply. Due to the high level of fat and the role of estrogen in a woman is endogenous estrogen of the tumor and regulate the activities of growth steroids, obesity is a risk factor for breast cancer is confirmed. Our study and other studies show that obesity is a risk factor for breast cancer. And with a weight loss intervention for breast cancer can be prevented in the future.

Keywords: breast cancer, review study, obesity, overweight

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Authors: Ronit Chakraborty, Sugata Banerji

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There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.

Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling

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Authors: M. R. Martinez-Torres, S. L. Toral, M. Olmedilla

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Typically, virtual communities exhibit the well-known phenomenon of participation inequality, which means that only a small percentage of users is responsible of the majority of contributions. However, the sustainability of the community requires that the group of active users must be continuously nurtured with new users that gain expertise through a participation process. This paper analyzes the time evolution of Open Source Software (OSS) communities, considering users that join/abandon the community over time and several topological properties of the network when modeled as a social network. More specifically, the paper analyzes the role of those users rejoining the community and their influence in the global characteristics of the network.

Keywords: open source communities, social network Analysis, time series, virtual communities

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: Young Hee Geum

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In this paper, we present the iterative method and determine the control parameters to converge cubically for solving nonlinear equations. In addition, we derive the asymptotic error constant.

Keywords: asymptotic error constant, iterative method, multiple root, root-finding, order of convergent

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Authors: Olfat Shaker, Miriam Wadie, Reham Ali, Ayman Yosry

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Colorectal cancer (CRC) is a major cause of mortality and morbidity and accounts for over 9% of cancer incidence worldwide. Silent information regulator 2 homolog 1 (SIRT1) gene is located in the nucleus and exert its effects via modulation of histone and non-histone targets. They function in the cell via histone deacetylase (HDAC) and/or adenosine diphosphate ribosyl transferase (ADPRT) enzymatic activity. The aim of this work was to study the relationship between SIRT1 polymorphism and its protein level in colorectal cancer patients in comparison to control cases. This study includes 2 groups: thirty healthy subjects (control group) & one hundred CRC patients. All subjects were subjected to: SIRT-1 serum level was measured by ELISA and gene polymorphisms of rs12778366, rs375891 and rs3740051 were detected by real time PCR. For CRC patients clinical data were collected (size, site of tumor as well as its grading, obesity) CRC patients showed high significant increase in the mean level of serum SIRT-1 compared to control group (P<0.001). Mean serum level of SIRT-1 showed high significant increase in patients with tumor size ≥5 compared to the size < 5 cm (P<0.05). In CRC patients, percentage of T allele of rs12778366 was significantly lower than controls, CC genotype and C allele C of rs 375891 were significantly higher than control group. In CRC patients, the CC genotype of rs12778366, was 75% in rectosigmoid and 25% in cecum & ascending colon. According to tumor size, the percentage of CC genotype was 87.5% in tumor size ≥5 cm. Conclusion: serum level of SIRT-1 and T allele, C allele of rs12778366 and rs 375891 respectively can be used as diagnostic markers for CRC patients.

Keywords: CRC, SIRT1, polymorphisms, ELISA

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Authors: Syhalath Xaphakdy, Toshio Nagata, Saykham Phommathat, Pavy Souwannavong, Vilayvanh Srithilat, Phoxay Sengdala, Bounaom Phetarnousone, Boualay Siharath, Xaya Chemcheng

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The National University of Laos (NUOL) invited a group of volunteers from the Japan International Cooperation Agency (JICA) to revise the physics experiments to utilize the materials that were already available to students. The intension was to review and revise the materials regularly utilized in physics class. The project had access to limited materials and a small budget for the class in the unit; however, by developing experimental textbooks related to mechanics, electricity, and wave and vibration, the group found a way to apply them in the classroom and enhance the students teaching activities. The aim was to introduce a way to incorporate the materials and practices in the classroom to enhance the students learning and teaching skills, particularly when they graduate and begin working as high school teachers.

Keywords: NUOL, JICA, physics experiment materials, small budget, mechanics, electricity

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Authors: Dileep G., Akash Singh, Dalchand Ahirwar, Arkadeep Ghosh, Ashutosh Purohit, Gaurav Guleria, Kshatriya Om Prashant, Pushkar Patel, Saksham Kumar, Vanshaj Nathani, Vikas Dangi, Shubhajit Roy Chowdhury, Varun Dutt

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Transcranial direct current stimulation (tDCS) has shown promise as a novel approach to enhance cognitive performance and provide therapeutic benefits for various brain disorders. However, the exact underlying brain mechanisms are not fully understood. We conducted a study to examine the brain's functional changes when subjected to simultaneous tDCS and music (Indian classical raga). During the study, participants in the experimental group underwent a 20-minute session of tDCS at two mA while listening to music (raga) for a duration of seven days. In contrast, the control group received a sham stimulation for two minutes at two mA over the same seven-day period. The objective was to examine whether repetitive tDCS could lead to the formation of additional functional connections between the medial prefrontal cortex (the stimulated area) and the auditory cortex in comparison to a sham stimulation group. In this study, 26 participants (5 female) underwent pre- and post-intervention scans, where changes were compared after one week of either tDCS or sham stimulation in conjunction with music. The study revealed significant effects of tDCS on functional connectivity between the stimulated area and the auditory cortex. The combination of tDCS applied over the mPFC and music resulted in newly formed connections. Based on our findings, it can be inferred that applying anodal tDCS over the mPFC enhances functional connectivity between the stimulated area and the auditory cortex when compared to the effects observed with sham stimulation.

Keywords: fNIRS, tDCS, neuroplasticity, music

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

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Diving is an important Olympic sport. In this sport, the effective performance of the athlete is related to his capability to interact correctly with the springboard. In fact, the elevation of the jump and the correctness of the dive are influenced by the vibrations of the board. In this paper, the vibrations of the springboard will be analyzed by means of typical tools for vibration analysis: Firstly, a modal analysis will be done on two different models of the springboard, then, these two model and another one will be analyzed with a time analysis, done integrating the equations of motion od deformable bodies. All these analyses will be compared with experimental data measured on a real springboard by means of a 6-axis accelerometer; these measurements are aimed to assess the models proposed. The acquired data will be analyzed both in frequency domain and in time domain.

Keywords: springboard analysis, modal analysis, time domain analysis, vibrations

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Authors: Aditya Sharma

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Profits earned from relative strength strategy of zero-cost portfolio i.e. taking long position in winner stocks and short position in loser stocks from recent past are termed as momentum profits. In recent times, there has been lot of controversy and concern about sources of momentum profits, since the existence of these profits acts as an evidence of earning non-normal returns from publicly available information directly contradicting Efficient Market Hypothesis. Literature review reveals conflicting theories and differing evidences on sources of momentum profits. This paper aims at re-examining the sources of momentum profits in Indian capital markets. The study focuses on assessing the effect of fundamental as well as behavioral sources in order to understand the role of investor behavior in stock returns and suggest (if any) improvements to existing behavioral asset pricing models. This Paper adopts calendar time methodology to calculate momentum profits for 6 different strategies with and without skipping a month between ranking and holding period. For each J/K strategy, under this methodology, at the beginning of each month t stocks are ranked on past j month’s average returns and sorted in descending order. Stocks in upper decile are termed winners and bottom decile as losers. After ranking long and short positions are taken in winner and loser stocks respectively and both portfolios are held for next k months, in such manner that at any given point of time we have K overlapping long and short portfolios each, ranked from t-1 month to t-K month. At the end of period, returns of both long and short portfolios are calculated by taking equally weighted average across all months. Long minus short returns (LMS) are momentum profits for each strategy. Post testing for momentum profits, to study the role market risk plays in momentum profits, CAPM and Fama French three factor model adjusted LMS returns are calculated. In the final phase of studying sources, decomposing methodology has been used for breaking up the profits into unconditional means, serial correlations, and cross-serial correlations. This methodology is unbiased, can be used with the decile-based methodology and helps to test the effect of behavioral and fundamental sources altogether. From all the analysis, it was found that momentum profits do exist in Indian capital markets with market risk playing little role in defining them. Also, it was observed that though momentum profits have multiple sources (risk, serial correlations, and cross-serial correlations), cross-serial correlations plays a major role in defining these profits. The study revealed that momentum profits do have multiple sources however, cross-serial correlations i.e. the effect of returns of other stocks play a major role. This means that in addition to studying the investors` reactions to the information of the same firm it is also important to study how they react to the information of other firms. The analysis confirms that investor behavior does play an important role in stock returns and incorporating both the aspects of investors’ reactions in behavioral asset pricing models help make then better.

Keywords: investor behavior, momentum effect, sources of momentum, stock returns

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Authors: Mehrnoosh Mirzaei

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Children are among the most vulnerable at the occurrence of natural disasters such as earthquakes. Most of the management and measures which are considered for both before and during an earthquake are neither suitable nor efficient for this age group and cannot be applied. On the other hand, due to their age, it is hard to educate and train children to learn and understand the concept of earthquake risk mitigation as matters like earthquake prevention and safe places during an earthquake are not easily perceived. To our knowledge, children’s awareness of such concepts via their own world with the help of games is the best training method in this case. In this article, the researcher has tried to consider the child an active element before and during the earthquake. With training, provided by adults before the incidence of an earthquake, the child has the ability to learn disaster risk reduction (DRR). The focus of this research is on learning risk reduction behavior and regarding children as an individual element. The information of this article has been gathered from library resources, observations and the drawings of 10 children aged 5 whose subject was their conceptual definition of an earthquake who were asked to illustrate their conceptual definition of an earthquake; the results of 20 questionnaires filled in by preschoolers along with information gathered by interviewing them. The design of the suitable educational game, appropriate for the needs of this age group, has been made based on the theory of design with help of the user and the priority of children’s learning needs. The final result is a package of a game which is comprised of a learning table and matching cards showing sign marks for safe and unsafe places which introduce the safe behaviors and safe locations before and during the earthquake. These educational games can be used both in group contexts in kindergartens and on an individual basis at home, and they help in earthquake risk reduction.

Keywords: disaster education, earthquake sign marks, learning table, matching card, risk reduction behavior

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Authors: I. Sonia d’Apolito, Bianca Sisinni, Mirko Grimaldi, Barbara Gili Fivela

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The American English contrast /ɑ-ʌ/ (cop-cup) is difficult to be produced by Italian learners since they realize L2-/ɑ-ʌ/ as L1-/ɔ-a/ respectively, due to differences in phonetic-phonological systems and also in grapheme-to-phoneme conversion rules. In this paper, we try to answer the following research questions: Can a short training improve the production of English /ɑ-ʌ/ by Italian learners? Is a perceptual training better than an articulatory (ultrasound - US) training? Thus, we compare a perceptual training with an US articulatory one to observe: 1) the effects of short trainings on L2-/ɑ-ʌ/ productions; 2) if the US articulatory training improves the pronunciation better than the perceptual training. In this pilot study, 9 Salento-Italian monolingual adults participated: 3 subjects performed a 1-hour perceptual training (ES-P); 3 subjects performed a 1-hour US training (ES-US); and 3 control subjects did not receive any training (CS). Verbal instructions about the phonetic properties of L2-/ɑ-ʌ/ and L1-/ɔ-a/ and their differences (representation on F1-F2 plane) were provided during both trainings. After these instructions, the ES-P group performed an identification training based on the High Variability Phonetic Training procedure, while the ES-US group performed the articulatory training, by means of US video of tongue gestures in L2-/ɑ-ʌ/ production and dynamic view of their own tongue movements and position using a probe under their chin. The acoustic data were analyzed and the first three formants were calculated. Independent t-tests were run to compare: 1) /ɑ-ʌ/ in pre- vs. post-test respectively; /ɑ-ʌ/ in pre- and post-test vs. L1-/a-ɔ/ respectively. Results show that in the pre-test all speakers realize L2-/ɑ-ʌ/ as L1-/ɔ-a/ respectively. Contrary to CS and ES-P groups, the ES-US group in the post-test differentiates the L2 vowels from those produced in the pre-test as well as from the L1 vowels, although only one ES-US subject produces both L2 vowels accurately. The articulatory training seems more effective than the perceptual one since it favors the production of vowels in the correct direction of L2 vowels and differently from the similar L1 vowels.

Keywords: L2 vowel production, perceptual training, articulatory training, ultrasound

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Authors: Kiran Nair, Jincy George, Suhaib Anagreh

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Artificial intelligence (AI) in a marketing context is a form of a deterministic tool designed to optimize and enhance marketing tasks, research tools, and techniques. It is on the verge of transforming marketing roles and revolutionize the entire industry. This paper aims to explore the current dissemination of the application of artificial intelligence (AI) in the marketing mix, reviewing the scope and application of AI in various aspects of sales and distribution management. The paper also aims at identifying the areas of the strong impact of AI in factors of sales and distribution management such as distribution channel, purchase automation, customer service, merchandising automation, and shopping experiences. This is a qualitative research paper that aims to examine the impact of AI on sales and distribution management of 30 multinational brands in six different industries, namely: airline; automobile; banking and insurance; education; information technology; retail and telecom. Primary data is collected by means of interviews and questionnaires from a sample of 100 marketing managers that have been selected using convenient sampling method. The data is then analyzed using descriptive statistics, correlation analysis and multiple regression analysis. The study reveals that AI applications are extensively used in sales and distribution management, with a strong impact on various factors such as identifying new distribution channels, automation in merchandising, customer service, and purchase automation as well as sales processes. International brands have already integrated AI extensively in their day-to-day operations for better efficiency and improved market share while others are investing heavily in new AI applications for gaining competitive advantage.

Keywords: artificial intelligence, sales and distribution, marketing mix, distribution channel, customer service

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Authors: Leona Ondrejikova, Martin Hill, Antonin Parizek

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The incidence of gestational diabetes mellitus (GDM) is higher in women predisposed to developing intrahepatic cholestasis of pregnancy (ICP). Both diseases are associated with altered steroidogenesis when compared with none-ICP controls. However, the effect of GDM on circulating steroids in ICP patients remains unclear. The question remains, whether the levels of circulating steroids differ between ICP patients with and without GDM. In total 10 ICP patients without GDM (ICP+GDM-), 7 ICP patients with GDM (ICP+GDM+), and 15 controls (ICP-GDM-) were monitored during late gestation, at labor, and during three periods postpartum (day 5, week 3, and week 6 postpartum) (Šimják et al., 2018). The relationships between steroid profiles and patients’ status were evaluated using the ANOVA model consisting of subject factor, between-subject factors Group (ICP+GDM+, ICP+GDM-, ICP-GDM-), gestational age at the diagnosis of ICP and gestational age at labor, and within-subject factor Stage and ICP × Stage interaction. The levels of the C21 and C19 Δ5 steroids and 5α/β-reduced C19 steroids were highest in ICP+GDM+, while those for the ICP-GDM-, and ICP+GDM- groups were lower. In the C21 Δ4 steroids and their 5α/β-reduced metabolites, the steroid levels were highest in the ICP+GDM-, intermediate in the ICP-GDM- and lowest in the ICP+GDM+ group. This higher concentration in ICP+GDM- group may be of importance as the 5α-pregnane-3α,20α-diol disulfate, is considered as the substance inducing ICP. In general, these data show that the comorbidity with GDM substantially changes the steroidome in ICP patients towards the higher activity of steroid CYP17A1 lyase step in adrenal zona reticularis reduced CYP17A1 hydroxylase step in zona fasciculata. This is consistent with our previously published hypothesis about the critical role of maternal zona reticularis in the pathophysiology of ICP. Our present data also indicate that the comorbidity with GDM might moderate the gravity of the ICP in this way.

Keywords: CYP17A1, GC-MS, gestational diabetes mellitus, intrahepatic cholestasis of pregnancy

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Authors: Bello Abdullahi, Yahaya M. Ibrahim, Ahmed D. Ibrahim, Kabir Bala

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Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Keywords: e-Tendering, e-Procurement, group decision making, tender evaluation, tender evaluation committee, UML, object-oriented methodologies, system development

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Authors: G. L. Rithika, Arvind B. S., Akash R., Ananda Vinayak, Hema M. S.

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Cryptocurrencies were first launched in the year 2009 and have been a great asset to own. Cryptocurrencies are a representation of a completely distinct decentralization model for money. They also contribute to the elimination of currency monopolies and the liberation of money from control. The fact that no government agency can determine a coin's value or flow is what cryptocurrency advocates believe makes them safe and secure. The aim of this paper is to analyze the economic implications of cryptocurrency and how it would disrupt traditional financial systems. This paper analyses the growth of Cryptocurrency over the years and the potential threats of cryptocurrency to financial systems. Our analysis shows that although the DeFi design, like the traditional financial system, may have the ability to lower transaction costs, there are multiple layers where rents might build up because of endogenous competition limitations. The permissionless and anonymous design of DeFi poses issues for ensuring tax compliance, anti-money laundering laws and regulations, and preventing financial misconduct.

Keywords: cryptocurrencies, bitcoin, blockchain technology, traditional financial systems, decentralisation, regulatory framework

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Authors: Georges F. Hatoum, Thomas H. Temple, Silvio Garcia, Xiaodong Wu

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Soft Tissue Sarcomas (STS) represent a diverse group of malignancies with heterogeneous clinical and pathological features. The treatment of extremity STS aims to achieve optimal local tumor control, improved survival, and preservation of limb function. The National Comprehensive Cancer Network guidelines, based on the cumulated clinical data, recommend radiation therapy (RT) in conjunction with limb-sparing surgery for large, high-grade STS measuring greater than 5 cm in size. Such treatment strategy can offer a cure for patients. However, when recurrence occurs (in nearly half of patients), the prognosis is poor, with a median survival of 12 to 15 months and with only palliative treatment options available. The spatially-fractionated-radiotherapy (SFRT), with a long history of treating bulky tumors as a non-mainstream technique, has gained new attention in recent years due to its unconventional therapeutic effects, such as bystander/abscopal effects. Combining single fraction of GRID, the original form of SFRT, with conventional RT was shown to have marginally increased the rate of pathological necrosis, which has been recognized to have a positive correlation to overall survival. In an effort to consistently increase the pathological necrosis rate over 90%, multiple fractions of Lattice RT (LRT), a newer form of 3D SFRT, interdigitated with the standard RT as neoadjuvant therapy was conducted in a preliminary clinical setting. With favorable results of over 95% of necrosis rate in a small cohort of patients, a Phase I/II clinical study was proposed to exam the safety and feasibility of this new strategy. Herein the design of the clinical study is presented. In this single-arm, two-stage phase I/II clinical trial, the primary objectives are >80% of the patients achieving >90% tumor necrosis and to evaluation the toxicity; the secondary objectives are to evaluate the local control, disease free survival and overall survival (OS), as well as the correlation between clinical response and the relevant biomarkers. The study plans to accrue patients over a span of two years. All patient will be treated with the new neoadjuvant RT regimen, in which one of every five fractions of conventional RT is replaced by a LRT fraction with vertices receiving dose ≥10Gy while keeping the tumor periphery at or close to 2 Gy per fraction. Surgical removal of the tumor is planned to occur 6 to 8 weeks following the completion of radiation therapy. The study will employ a Pocock-style early stopping boundary to ensure patient safety. The patients will be followed and monitored for a period of five years. Despite much effort, the rarity of the disease has resulted in limited novel therapeutic breakthroughs. Although a higher rate of treatment-induced tumor necrosis has been associated with improved OS, with the current techniques, only 20% of patients with large, high-grade tumors achieve a tumor necrosis rate exceeding 50%. If this new neoadjuvant strategy is proven effective, an appreciable improvement in clinical outcome without added toxicity can be anticipated. Due to the rarity of the disease, it is hoped that such study could be orchestrated in a multi-institutional setting.

Keywords: lattice RT, necrosis, SFRT, soft tissue sarcoma

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Authors: Ifeoma Anozie, Teka Apalata, Dominic Abaver

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Introduction: Despite use of Anti-retroviral therapy to reduce the incidence of opportunistic infections among HIV/AIDS patients, rapid episodes of re-infection after deworming are still common occurrences because pharmaceutical intervention alone does not prevent reinfection. Unsafe water and inadequate personal hygiene and parasitic infections are widely expected to accelerate the progression of HIV infection. This is because the chronic immunosuppression of HIV infection encourages susceptibility to opportunistic (including parasitic) infections which is linked to CD4+ cell count of <200 cells/μl. Intestinal parasites such as G. intestinalis and Entamoeba spp are ubiquitous protozoa that remain infectious over a long time in an environment and show resistance to standard disinfection. To control re-infection, the social factors that underpin the prevention need to be controlled. This study aims at prevention of intestinal parasites in people living with HIV/AIDS by using a treatment, hygiene education and sanitation (THEdS) bundle approach. Methods: This study was conducted in four clinics (Ngangelizwe health centre, Tsolo gateway clinic, Idutywa health centre and Nqamakwe health centre) across the seven districts in Eastern cape, South Africa. The four clinics were divided in two: experimental and control, for the purpose of intervention. Data was collected from March 2019 to February 2020. Six hundred participants were screened for intestinal parasitic infections. Stool samples were collected and analysed twice: before (Pre-test infection screening) and after (Post-test re-infection) THEdS bundle intervention. The experimental clinics received full intervention package, which include therapeutic treatment, health education on personal hygiene and sanitation training, while the control clinics received only therapeutic treatment for those found with intestinal parasitic infections. Results: Baseline prevalence of Intestinal Parasites isolated shows 12 intestinal parasites with overall frequency of 65, with Ascaris lumbricoides having most frequency (44.6%). The intervention had a cure rate of 60%, with odd ratio of 1.42, which indicates that the intervention group is 1.42 times more likely of parasite clearing as compared to the control group. The relative risk ratio of 1.17 signifies that there is 1.17 times more likelihood to clear intestinal parasite if there no intervention. Discussion and conclusion: Infection with multiple parasites can cause health defects, especially among HIV/AIDS patients. Efficiency of some HIV vaccines in HIV/AIDS patients is affected because treatment of re-infection amplifies drug resistance, affects the efficacy of the front-line drugs, and still permits transmission. In South Africa, treatment of intestinal parasites is usually offered to clinic attending HIV/AIDS patients upon suspicion but not as a mandate for patients being initiated into Antiretroviral (ART) program. The effectiveness of THEdS bundle advocates for inclusiveness of mandatory screening for intestinal parasitic infections among attendees of HIV/Aids clinics on regular basis.

Keywords: cure rate, , HIV/AIDS patients, intestinal parasites, intervention studies, reinfection rate

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Authors: Hsiu Tan Liu, Chun Jung Liu

Abstract:

It has multiple purposes to develop a sign language receptive skills test. For example, this test can be used to be an important tool for education and to understand the sign language ability of deaf children. There is no available test for these purposes in Taiwan. Through the discussion of experts and the references of standardized Taiwanese Sign Language Receptive Test for adults and adolescents, the frame of Taiwanese Sign Language Receptive Skills Test (TSL-RST) for deaf children was developed, and the items were further designed. After multiple times of pre-trials, discussions and corrections, TSL-RST is finally developed which can be conducted and scored online. There were 33 deaf children who agreed to be tested from all three deaf schools in Taiwan. Through item analysis, the items were picked out that have good discrimination index and fair difficulty index. Moreover, psychometric indexes of reliability and validity were established. Then, derived the regression formula was derived which can predict the sign language receptive skills of deaf children. The main results of this study are as follows. (1). TSL-RST includes three sub-test of vocabulary comprehension, syntax comprehension and paragraph comprehension. There are 21, 20, and 9 items in vocabulary comprehension, syntax comprehension, and paragraph comprehension, respectively. (2). TSL-RST can be conducted individually online. The sign language ability of deaf students can be calculated fast and objectively, so that they can get the feedback and results immediately. This can also contribute to both teaching and research. The most subjects can complete the test within 25 minutes. While the test procedure, they can answer the test questions without relying on their reading ability or memory capacity. (3). The sub-test of the vocabulary comprehension is the easiest one, syntax comprehension is harder than vocabulary comprehension and the paragraph comprehension is the hardest. Each of the three sub-test and the whole test are good in item discrimination index. (4). The psychometric indices are good, including the internal consistency reliability (Cronbach’s α coefficient), test-retest reliability, split-half reliability, and content validity. The sign language ability are significantly related to non-verbal IQ, the teachers’ rating to the students’ sign language ability and students’ self-rating to their own sign language ability. The results showed that the higher grade students have better performance than the lower grade students, and students with deaf parent perform better than those with hearing parent. These results made TLS-RST have great discriminant validity. (5). The predictors of sign language ability of primary deaf students are age and years of starting to learn sign language. The results of this study suggested that TSL-RST can effectively assess deaf student’s sign language ability. This study also proposed a model to develop a sign language tests.

Keywords: comprehension test, elementary school, sign language, Taiwan sign language

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