Search results for: clinical prediction score

Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

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In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

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Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

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Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

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Authors: Cinzia Cruder, Deborah Falla, Francesca Mangili, Laura Azzimonti, Liliana Araujo, Aaron Williamon, Marco Barbero

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Background and aims: According to the existing literature, musicians are at risk to experience a range of musculoskeletal painful conditions. Recently, digital technology has been developed to investigate pain location and pain extent. The aim of this study was to describe pain location and pain extent in musicians using a digital method for pain drawing analysis. Additionally, the association between pain drawing (PD) variables and clinical features in musicians with pain were explored. Materials and Methods: One hundred fifty-eight musicians (90 women and 68 men; age 22.4±3.6 years) were recruited from Swiss and UK conservatoires. Participants were asked to complete a survey including both background musical information and clinical features, the Quick Dash (QD) questionnaire and the digital PDs. Results: Of the 158 participants, 126 musicians (79.7%) reported having pain, with more prevalence in the areas of the neck and shoulders, the lower back and the right arm. The mean of pain extent was 3.1% ±6.5. The mean of QD was larger for musicians showing the presence of pain than for those without pain. Additionally, the results indicated a positive correlation between QD score and pain extent, and there were significant correlations between age and pain intensity, as well as between pain extent and pain intensity. Conclusions: The high prevalence of pain among musicians has been confirmed using a digital PD. In addition, positive correlations between pain extent and upper limb disability has been demonstrated. Our findings highlight the need for effective prevention and treatment strategies for musicians.

Keywords: pain location, pain extent, musicians, pain drawings

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Authors: Minhui Chiu

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According to relevant studies, clinical nurses have high work pressure and relatively high job adaptation needs. The nurses who work in oncology wards have more adaptation needs when they face repeating hospitalization patients. The aims of this study were to investigate the job stress adaptation and related factors of nurses in oncology wards and to understand the predictors of job stress adaptation needs. Convenience sampling was used in this study. The nurses in the oncology specialist ward of a regional teaching hospital in southern Taiwan were selected as the research objects. A cross-sectional survey was conducted using a structured questionnaire, random sampling, and the questionnaires were filled out by the participating nurses. A total of 68 people were tested, and 65 valid questionnaires (95.6%). One basic data questionnaire and nurses’ job stress adaptation needs questionnaire were used. The data was archived with Microsoft Excel, and statistical analysis was performed with JMP12.0. The results showed that the average age was 28.8 (±6.7) years old, most of them were women, 62 (95.38%), and the average clinical experience in the hospital was 5.7 years (±5.9), and 62 (95.38%) were university graduates. 39 people (60.0%) had no work experience. 39 people (60.0%) liked nursing work very much, and 23 people (35.3%) just “liked”. 47 (72.3%) people were supported to be oncology nurses by their families. The nurses' job stress adaptation needs were 119.75 points (±17.24). The t-test and variance analysis of the impact of nurses' job pressure adaptation needs were carried out. The results showed that the score of college graduates was 121.10 (±16.39), which was significantly higher than that of master graduates 96.67 (±22.81), and the degree of liking for nursing work also reached a Significant difference. These two variables are important predictors of job adaptation needs, and the R Square is 24.15%. Conclusion: Increasing the love of clinical nurses in nursing and encouraging university graduation to have positive effects on job pressure adaptation needs and can be used as a reference for the management of human resources hospitals for oncology nurses.

Keywords: oncology nurse, job stress, job stress adaptation needs, manpower

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Authors: Phitsanu Phunphetchphan

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The purposes of this research was to investigate opinions of Rajabhat University staff towards performance of the university council committee by focusing on (1) personal characteristics of the committees; (2) duties designated by the university council; and (3) relationship between university council and staff. The population of this study included all high level of management from Suan Sunandha Rajabhat University which made a total of 200 respondents. Data analysis included frequency, percentage, mean and standard deviation. The findings revealed that the majority of staff rated the performance of university council at a high level. The 'overall appropriate qualification of the university council' was rated as the highest score while 'good governance' was rated as the lowest mean score. Moreover, the findings also revealed that the relationship between university council’s members and the staff was rated at a high level while 'the integrity of policy implementation' was rated as the lowest score.

Keywords: investigation, performance, university council, management

Procedia PDF Downloads 229

Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

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Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

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In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

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Authors: Karla Lebedoff, Susan Walsh, Michelle Bain

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Eczema is a chronic atopy condition requiring long-term daily management in children. Written action plans for other chronic atopic conditions, such as asthma and food allergies, are widely recommended and distributed to pediatric patients' parents and caregivers, seeking to improve clinical outcomes and become empowered to manage the patient's ever-changing symptoms. Written action plans for eczema, referred to as "asthma of the skin," are not routinely used in practice. Parents of children suffering from eczema rarely receive a written action plan to follow, and commendations supporting eczema action plans are inconsistent. Pediatric patients between birth and 18 years old who were followed for eczema at an urban Midwest community hospital were eligible to participate in this quality improvement project. At the initial visit, parents received instructions on individualized eczema action plans for their child and completed two validated surveys: Health Confidence Score (HCS) and Patient-Oriented Eczema Measure (POEM). Pre- and post-survey responses were collected, and clinical symptom presentation at follow-up were outcome determinants. Project implementation was guided by Institute for Healthcare Improvement's Step-up Framework and the Plan-Do-Study-Act cycle. This project measured clinical outcomes and parent confidence in self-management of their child's eczema symptoms with the responses from 26 participant surveys. Pre-survey responses were collected from 36 participants, though ten were lost to follow-up. Average POEM scores improved by 53%, while average HCS scores remained unchanged. Of seven completed in-person follow-up visits, six clinical progress notes documented improvement. Individualized eczema action plans can be seamlessly incorporated into primary and specialty care visits for pediatric patients suffering from eczema. Following a patient-specific eczema action plan may lessen the daily physical and mental burdens of uncontrolled eczema for children and parents, managing symptoms that chronically flare and recede. Furthermore, incorporating eczema action plans into practice potentially reduces the likely underestimated $5.3 billion economic disease burden of eczema on the U.S. healthcare system.

Keywords: atopic dermatitis, eczema action plan, eczema symptom management, pediatric eczema

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Authors: Zhi-Wei Zheng, Zhong-Qi Liu, Jia-Ling Qiu, Shan-Qing Guo, Zhong-Wei Jia, Chun Hao

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Objectives: The purpose of this study was to understand and examine the association between diurnal mood variation and sexual/health-related status among men who have sex with men (MSM) using data from MSM Chinese Twitter messages. The study consists of 843,745 postings of 377,610 MSM users located in Guangdong that were culled from the MSM Chinese Twitter App. Positive affect, negative affect, sexual related behaviors, and health-related status were measured using the Simplified Chinese Linguistic Inquiry and Word Count. Emotions, including joy, sadness, anger, fear, and disgust were measured using the Weibo Basic Mood Lexicon. A positive sentiment score and a positive emotions score were also calculated. Linear regression models based on a permutation test were used to assess associations between affective states and sexual/health-related status. In the results, 5,871 active MSM users and their 477,374 postings were finally selected. MSM expressed positive affect and joy at 8 a.m. and expressed negative affect and negative emotions between 2 a.m. and 4 a.m. In addition, 25.1% of negative postings were directly related to health and 13.4% reported seeking social support during that sensitive period. MSM who were senior, educated, overweight or obese, self-identified as performing a versatile sex role, and with less followers, more followers, and less chat groups mainly expressed more negative affect and negative emotions. MSM who talked more about sexual-related behaviors had a higher positive sentiment score (β=0.29, p < 0.001) and a higher positive emotions score (β = 0.16, p < 0.001). MSM who reported more on their health status had a lower positive sentiment score (β = -0.83, p < 0.001) and a lower positive emotions score (β = -0.37, p < 0.001). The study concluded that psychological intervention based on an app for MSM should be conducted, as it may improve mental health.

Keywords: affect, men who have sex with men, sexual related behavior, health-related status, social media

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Authors: Bela Siska Afrida, Wisnu Barlianto, Desy Wulandari, Ery Olivianto

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Background: Allergic asthma, caused by IgE-mediated allergic reactions, remains a global health issue with high morbidity and mortality rates. Immunotherapy is the only etiology-based approach to treating asthma, but no standard biomarkers have been established to evaluate the therapy’s effectiveness. This study aims to determine the correlation between the ratios of serum levels of HDM-specific IgE/total IgE and Asthma Control Test (ACT) score as a biomarker of the response to immunotherapy in pediatric allergic asthma patients. Patient and Methods: This retrospective cohort study involved 26 pediatric allergic asthma patients who underwent HDM-specific subcutaneous immunotherapy for 14 weeks at the Pediatric Allergy Immunology Outpatient Clinic at Saiful Anwar General Hospital, Malang. Serum levels of HDM-Specific IgE and Total IgE were measured before and after immunotherapy using Chemiluminescence Immunoassay and Enzyme-linked Immunosorbent Assay (ELISA) method. Changes in asthma control were assessed using the ACT score. The Wilcoxon Signed Ranked Test and Spearman correlation test were used for data analysis. Results: There were 14 boys and 12 girls with a mean age of 6.48 ± 2.54 years. The study showed a significant decrease in serum HMD-specific levels before immunotherapy [9.88 ± 5.74 kuA/L] compared to those of 14 weeks after immunotherapy [4.51 ± 3.98 kuA/L], p = 0.000. Serum Total IgE levels significant decrease before immunotherapy [207.6 ± 120.8IU/ml] compared to those of 14 weeks after immunotherapy [109.83 ± 189.39 IU/mL], p = 0.000. The ratios of serum HDM-specific IgE/total IgE levels significant decrease before immunotherapy [0.063 ± 0.05] compared to those of 14 weeks after immunotherapy [0.041 ± 0.039], p = 0.012. There was also a significant increase in ACT scores before and after immunotherapy (each 15.5 ± 1.79 and 20.96 ± 2.049, p = 0.000). The correlation test showed a weak negative correlation between the ratios of HDM-specific IgE/total IgE levels and ACT score (p = 0.034 and r = -0.29). Conclusion: In conclusion, this study showed that a decrease in HDM-specific IgE levels, total IgE levels, and HDM-specific IgE/total IgE ratios, and an increase in ACT score, was observed after 14 weeks of HDM-specific subcutaneous immunotherapy. The weak negative correlation between the HDM-specific IgE/total IgE ratio and the ACT score suggests that this ratio can serve as a potential biomarker of the effectiveness of immunotherapy in treating pediatric allergic asthma patients.

Keywords: HDM-specific IgE/total IgE ratio, ACT score, immunotherapy, allergic asthma

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Authors: Amel Fayed, Shaden AlSubaih, Nouf Al-Qahtani, Asmaa Gosty, Asma Aljuhaimi

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Introduction: Sleep difficulties are vastly predominant among adults and affect different aspects of their life. Many literatures found out that females are more liable to suffer from sleeping problems. College students are typical example of people dealing with daily pressure and stress to fulfill the daily tasks and responsibilities. In addition to their ultimate goal of achieving excellent academic records which require their full concentration and effort. Consequently, many of them start complaining of sleep deprivations which can undesirably affect their academic achievements. This study was aiming to investigate how prevalent is sleeping disorders among different colleges in the university and its relation their academic achievements. Methods: A cross-sectional study of female university students at Princess Norah Bint Abdulrahman University using self-administered questionnaire was conducted. Insomnia Severity Index (ISI) was used to assess different grades of insomnia. Students were requested to answer the questions evaluating their sleeping habits over the last two weeks. Participants reported their latest Grade Point Average (GPA). According to ISI, insomnia severity is reported as ‘No clinically significant’, ‘Subthreshold ‘,’ Clinical moderate insomnia’ and ‘Clinical severe’. Results: In the current study, 228 students participated; 172(75.4%) from medical colleges and 56 (24.6%) from non-medical colleges. About 80% of them claimed to have never taken any medications to help them sleep while only three students confirmed their regular use of sleep-inducing medications. About 16% of the students drink milk or other hot drinks to help them fall asleep. None of the students was suspected of having obstructive sleep apnea or apparent psychiatric disorder. According to ISI, 182 (79.8%) students suffered from subthreshold insomnia, 37 (16.2%) had clinical insomnia (moderate severity) and 9 (3.9%) of students had sleeping problems of non-clinically significance level. However, none of students was found to have severe clinical insomnia. Clinical moderate insomnia was reported in 15.1% of medical students and 19.6% of non-medical students. Moreover, about 82% of medical students suffered from subthreshold insomnia compared to 73.2% of non-medical students. This difference was not statistically significant (P=0.24). About 63% of medical students and 48% of non-medical students believed that high percentage of their colleagues are suffering from insomnias (p-value 0.08) The association between GPA and insomnia revealed that; 19.5% of low GPA group compared to 9.3% of high GPA group had clinical moderate insomnia. This association was not statistically significant (p=0.15). The correlation between the GPA and the ISI score was negative but not conclusive (r=-0.08, p-value = 0.29). More than 92% of all students agreed that sleeping problems affect their academic achievement to varying degrees. Conclusion: our results suggest that insomnia is commonly prevalent among female university students and might affect the students’ achievement. This study provides preliminary data about the quality of sleep among medical and non-medical university students which may be used to promote the healthy sleeping habits among female students.

Keywords: academic achievement, females, insomnia, university student

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Authors: Katsumi Mera

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The purpose of this study was to clarify the relationship between strengths/weaknesses on studying and subjective well-being among Japanese working adults. We conducted an online questionnaire survey of Japanese working adults (aged 20-69) and obtained 1,063 valid responses. Subjective well-being was evaluated using the Cantril Self-Anchoring Striving Scale, the method used in the World Happiness Survey, in which the highest possible life is set at 10, and the lowest possible life is set at 0. The mean subjective well-being of all 1,063 respondents was 5.87, which is a very similar value that was obtained in the Japanese World Happiness Survey in 2023. First, we investigated the respondents' strengths/weaknesses in studying and their subjective well-being. The results showed that the subjective well-being of the group who answered that they were good at studying (6.62) was significantly higher than that of the group who answered that they were poor at studying (5.15). Next, we investigated the subjective well-being of students who answered that they were good at Japanese, Math, English, Social studies, and Science, the major subjects in Japan, and found that the subjective well-being of the group that answered that they were good at these subjects was higher than that of the group that answered that they were poor at these subjects. When the correlation between the score of "strengths/weaknesses on studying" and the score of "subjective well-being" was examined, those who answered that they were good at studying had higher subjective well-being (correlation coefficient r = 0.26, p < 0.001). The correlation between the subjective well-being score and the score of "strengths/weaknesses on studying each subject” was examined. Among the subjects, the subjective well-being score was the highest for those who answered that they were good at English (correlation coefficient r = 0.17, p < 0.001). These results indicate a relationship between strengths/weaknesses on studying and subjective well-being among workers in Japan. These findings may provide an important basis for considering what kind of education should be focused on in order to nurture working adults with high levels of well-being.

Keywords: subject well-being, strengths/weaknesses, studying, Japanese working adults

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

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Authors: Jacob Nortey

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Introduction: In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. According to the Ibero – American Study of Adverse Effects (IBEAS), about 10% of hospital patients suffer from secondary damage during the care process, and approximately 2% die from this process. Many clinical decision support systems have been developed to help mitigate some healthcare medical errors. Method: Relevant databases were searched, including ones that were peculiar to the clinical decision support system (that is, using google scholar, Pub Med and general google searches). The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of Dxplain Clinical decision support systems. Results: Inferences drawn from the articles showed high usage of Dxplain clinical decision support system for problem-based learning among students in developed countries as against little or no usage among students in Low – and Middle – income Countries. The results also indicated high usage among general practitioners. Conclusion: Despite the challenges Dxplain presents, the benefits of its usage to clinicians and students are enormous.

Keywords: dxplain, clinical decision support sytem, diagnosis, support systems

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Authors: Inaam Nasrallah, Pascale Salameh, Abbas El-Outa, Assem Alkak, Rihab Nasr, Wafa Toufic Bawab

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Background: Hazardous Waste Management(HWM). is critical to human health outcomes and environmental protection. This study evaluated the knowledge regarding safety measures to be applied when collecting and storing waste in scientific laboratories of two universities in Lebanon.Method: A survey-based observational study was conducted in scientific laboratories of the public university and that of a private university, where a total of 309 participants were recruited.Result: The mean total knowledge score on safety measures of HWM was 9.02±4.34 (maximum attainable score, 13). Significant association (p<0.05) was found between knowledge score and job function, years of experience, educational level, professional status, work schedule, and training on proper HWM. Participants had adequate perceptions regarding the impact of HWM on health and the environment. Linear regression modeling revealed that knowledge score was significantly higher among bachelor level lab workers compared to those with doctoral degrees (p=0.043), full-time schedule workers versus part-timers (p=0.03), and among public university participants as compared to those of the private university (p<0.001).Conclusion: This study showed good knowledge concerning HWM in the scientific laboratoriesof the studied universities in Lebanon and a good awareness of the HWM on health and the environment. It highlights the importance of culture, attitude, and practice on proper HWM in the academic scientific laboratory.

Keywords: hasardous waste, safety measures, waste management, knwoledge score, scientific laboratory workers

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Authors: Kittivate Boonyopakorn

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The purposes of this study were to find the English competence of the public health volunteers and to develop the use of their English. The samples for the study were 41 public health village volunteers at Ban Prasukchai, in Thailand. The findings showed that the sum of all scores for the pre-test was 452, while the score for the post-test was 1,080. Therefore, the results of the experiment confirm that the post-test scores (1,080) significantly are higher than the pre-test (452). The mean score (N=41) for the pre-test was 11.02 while the mean score (N=41) for the post-test was 18.10. The standard deviation for the pre-test was 2.734; however, for the post-test it was 1.934. In addition to the experts-evaluated research tools, the results of the evaluation for the structured interviews (IOC) were 1 in value. The evaluation of congruence for the content with learning objectives (IOC) were 0.66 to 1.00 in value. The evaluation of congruence for the pre and post-test with learning objectives (IOC) are 1 in value.

Keywords: finding the English competency, developing public health, village volunteers

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Authors: Iqbal Pramukti, Mamat Lukman, Hasniatisari Harun, Kusman Ibrahim

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Introduction: People living with HIV had a higher risk of osteoporotic fracture than the general population. The purpose of this study was to predict the 10-year risk of fracture among people living with HIV (PLWH) using FRAX™ and to identify characteristics related to the fracture risk. Methodology: This study consisted of 75 subjects. The ten-year probability of major osteoporotic fractures (MOF) and hip fractures was assessed using the FRAX™ algorithm. A cross-tabulation was used to identify the participant’s characteristics related to fracture risk. Results: The overall mean 10-year probability of fracture was 2.4% (1.7) for MOF and 0.4% (0.3) for hip fractures. For MOF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use showed a higher MOF score than those who were not (3.1 vs. 2.5; 4.6 vs 2.5; and 3.4 vs 2.5, respectively). For HF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use also showed a higher HF score than those who were not (0.5 vs. 0.3; 0.8 vs. 0.3; and 0.5 vs. 0.3, respectively). Conclusions: The 10-year risk of fracture was higher among PLWH with several factors, including the parent’s hip. Fracture history, smoking behavior and glucocorticoid used. Further analysis on determining factors using multivariate regression analysis with a larger sample size is required to confirm the factors associated with the high fracture risk.

Keywords: HIV, PLWH, osteoporotic fractures, hip fractures, 10-year risk of fracture, FRAX

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Authors: Natcha Lueangapapong, Chariya Chuthapisith, Lunliya Thampratankul

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Background: There is a need to find an appropriate tool to help healthcare providers determine sleep problems in children for early diagnosis and management. The Japanese Sleep Questionnaire for Preschoolers (JSQ-P) is a parent-reported sleep questionnaire that has good psychometric properties and can be used in the context of Asian culture, which is likely suitable for Thai children. Objectives: This study aimed to translate and validate the Japanese Sleep Questionnaire for Preschoolers (JSQ-P) into a Thai version and to evaluate factors associated with sleep disorders in preschoolers. Methods: After approval by the original developer, the cross-cultural adaptation process of JSQ-P was performed, including forward translation, reconciliation, backward translation, and final approval of the Thai version of JSQ-P (TH-JSQ-P) by the original creator. This study was conducted between March 2021 and February 2022. The TH-JSQ-P was completed by 2,613 guardians whose children were aged 2-6 years twice in 10-14 days to assess its reliability and validity. Content validity was measured by an index of item-objective congruence (IOC) and a content validity index (CVI). Face validity, content validity, structural validity, construct validity (discriminant validity), criterion validity and predictive validity were assessed. The sensitivity and specificity of the TH-JSQ-P were also measured by using a total JSQ-P score cutoff point 84, recommended by the original JSQ-P and each subscale score among the clinical samples of obstructive sleep apnea syndrome. Results: Internal consistency reliability, evaluated by Cronbach’s α coefficient, showed acceptable reliability in all subscales of JSQ-P. It also had good test-retest reliability, as the intraclass correlation coefficient (ICC) for all items ranged between 0.42-0.84. The content validity was acceptable. For structural validity, our results indicated that the final factor solution for the Th-JSQ-P was comparable to the original JSQ-P. For construct validity, age group was one of the clinical parameters associated with some sleep problems. In detail, parasomnias, insomnia, daytime excessive sleepiness and sleep habits significantly decreased when the children got older; on the other hand, insufficient sleep was significantly increased with age. For criterion validity, all subscales showed a correlation with the Epworth Sleepiness Scale (r = -0.049-0.349). In predictive validity, the Epworth Sleepiness Scale was significantly a strong factor that correlated to sleep problems in all subscales of JSQ-P except in the subscale of sleep habit. The sensitivity and specificity of the total JSQ-P score were 0.72 and 0.66, respectively. Conclusion: The Thai version of JSQ-P has good internal consistency reliability and test-retest reliability. It passed 6 validity tests, and this can be used to evaluate sleep problems in preschool children in Thailand. Furthermore, it has satisfactory general psychometric properties and good reliability and validity. The data collected in examining the sensitivity of the Thai version revealed that the JSQ-P could detect differences in sleep problems among children with obstructive sleep apnea syndrome. This confirmed that the measure is sensitive and can be used to discriminate sleep problems among different children.

Keywords: preschooler, questionnaire, validation, Thai version

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

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Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

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Authors: Mehdi Mirzaei Alavijeh, Farzad Jalilian

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Background: Marijuana is the most widely used illicit drug worldwide, especially among adolescents and young adults, which can cause numerous complications. The aim of this study was to determine the pattern, motivation use, and factors related to marijuana use among Iranian youths based on the integrative model of behavioral prediction Methods: A cross-sectional study was conducted among 174 youths marijuana user in Kermanshah County and Isfahan County, during summer 2014 which was selected with the convenience sampling for participation in this study. A self-reporting questionnaire was applied for collecting data. Data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean marijuana use of respondents was 4.60 times at during week [95% CI: 4.06, 5.15]. Linear regression statistical showed, the structures of integrative model of behavioral prediction accounted for 36% of the variation in the outcome measure of the marijuana use at during week (R2 = 36% & P < 0.001); and among them attitude, marijuana refuse, and subjective norms were a stronger predictors. Conclusion: Comprehensive health education and prevention programs need to emphasize on cognitive factors that predict youth’s health-related behaviors. Based on our findings it seems, designing educational and behavioral intervention for reducing positive belief about marijuana, marijuana self-efficacy refuse promotion and reduce subjective norms encourage marijuana use has an effective potential to protect youths marijuana use.

Keywords: marijuana, youth, integrative model of behavioral prediction, Iran

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Authors: Safak Akdemir

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The main purpose of this research is to evaluate the relationships between childhood traumas and dissociative experiences, self-perceptions and early maladaptive schemas in male convicts convicted of sexual assault crimes in prison. In our study, male convicts in prison for the crime of sexual assault constitute the experimental group, and the participants matched with this experimental group in terms of education, age and gender constitute the control group. The experimental group of the research consists of 189 male individuals who are convicted in the Ministry of Justice, General Directorate of Prisons, Istanbul/Maltepe L Type Closed Prison. The control group of this study consists of 147 adult males matched with the experimental group in terms of age, gender and education parameters. A total of 336 adult male individuals are included in the sample of this study. 46% of the experimental group were convicted of only sexual assault, 54% of them were convicted of both sexual assault and murder, injury and drug crimes. Total of five data collection tools, namely the Personal Information Form created by S. A. & E. O., Childhood Trauma Questionnaire (CTQ), the Dissociative Experiences Scale (DES), the Rosenberg Self-Esteem Scale (RSES), and the Young Schema Questionnaire-Short Form (YSQ-SF3), were completed. DES cut-off score of 99 (52.39%) of 189 convicts in the experimental group and 12 (8.17%) of 147 people in the control group was found to be 30 and above, and this result indicates the presence of pathological dissociative experiences. 180 (95.23%) of the sexual assault convicts in the experimental group had at least one childhood trauma, 154 (81.48%) were emotional neglect, 140 (74.07%) were emotional abuse, 121 (64.02%) were physical neglect, 91 (4814%) physical abuse and 70 (37.03%) sexual abuse. 168 (88.88%) of the experimental group reported multiple type of trauma and 12 (6.34%) reported single type of trauma. While the childhood traumas, isolation, abandonment and emotional deprivation schema levels of the convicts with a DES cut-off score of 30 and above are higher than the convicts with a DES cut-off score of 30 and above, their self-esteem is lower than this group. Experimental group while childhood traumas, dissociative experiences and early maladaptive schemas are higher than the control group, their self-esteem levels are lower. Dissociative experiences, abandonment and emotional deprivation early maladaptive schemas are more common in convicts aged between 18-30 years compared to convicts aged 31 and over. In addition, dissociative experiences and early maladaptive schemas of male convicts who reported physical and sexual abuse were higher than those who did not report physical and sexual abuse, while their self-esteem was at a lower level. As a result, in terms of psychotraumatology and clinical forensic psychology, dissociative disorders developed under the influence of chronic childhood traumas, with clinical interviews and psychometric measurements to be made in terms of forensic psychiatry; it is of fundamental importance to evaluate it in terms of neurosis-psychosis distinction, disability retirement, custody, malpractice, criminal and legal capacity criteria.

Keywords: crime, sexual assault, criminology, rape crimes, dissocitative disorders, maladative schemas

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Authors: Lee P. Leon, Raymond Charles

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This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: aggregate angularity, asphalt concrete, permanent deformation, rutting prediction

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Authors: P. V. Pramila , V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

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Authors: Naqoosh Haidry

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Objective & Goal: Enucleation of the maxillomandibular cysts will lead to the creation of post-surgical bone defects which may take more than a year for complete bone healing. The use of bone grafts is common to aid bone regeneration in large defects. The study aimed to evaluate the healing and bone formation capabilities of polymer of injectable platelet fibrin (i-PRF) and hydroxyapatite (HA) as bone graft substitute in maxilla-mandibular postsurgical defects compared to hydroxyapatite alone. The primary objective was to find out the clinical and radiological assessment of healing postoperatively and compare the outcome of both groups. Material and Methods: After surgical enucleation of 19 maxillomandibular cysts/tumors, either HA or HA+ i-PRF graft was adapted to the defect. Clinical outcome variables such as pain (VAS score), edema, and mucosal color were evaluated on postoperative days 01, 03, and 07 while radiological outcome variables such as volume of defect (cc), density of new bone (HU) on computed tomography were evaluated at 2nd and 4th month. The results obtained were tabulated and compared with the inferential analysis. Results: Clinical parameters seem to be better in the HA + i-PRF group, but the result was non-significant. Radiologically, the mean healing ratios were significantly greater in the HA + i-PRF group (63.5 ± 2.34 at 2nd month, 90.3 ± 7.32 at 4th month) compared to the HA group (57.2 ± 5.21at 2nd month, 80.8 ± 5.33 at 4th month). When comparing the mean density of new bone, there was a statistically significant difference with a mean difference of 95.2 HU more in the HA + i-PRF (623 HU ± 42.9) compared to the HA group (528 HU ± 96.5) in 2nd month. Conclusion: The polymer of i-PRF and HA prepared as the sticky bone yields faster and better bone healing in post-enucleation maxillomandibular bony defects as compared to hydroxyapatite alone based on radiological findings till four months.

Keywords: bone defect, density of new bone, hydroxyapatite, injectable platelet rich fibrin, maxillomandibular cysts, surgical defect

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Authors: Chia-Jung Li, Kuan-Hao Tsui

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As women age, the quality of their oocytes deteriorates irreversibly, leading to reduced fertility. To better understand the role of Ferroptosis-related genes in ovarian aging, we employed a multi-omics analysis approach, including spatial transcriptomics, single-cell RNA sequencing, human ovarian pathology, and clinical biopsies. Our study identified excess lipid peroxide accumulation in aging germ cells, metal ion accumulation via oxidative reduction, and the interaction between ferroptosis and cellular energy metabolism. We used multi-histological prediction of ferroptosis key genes to evaluate 75 patients with ovarian aging insufficiency and then analyzed changes in hub genes after supplementing with DHEA, Ubiquinol CoQ10, and Cleo-20 T3 for two months. Our results demonstrated a significant increase in TFRC, GPX4, NCOA4, and SLC3A2, which were consistent with our multi-component prediction. We theorized that these supplements increase the mitochondrial tricarboxylic acid cycle (TCA) or electron transport chain (ETC), thereby increasing antioxidant enzyme GPX4 levels and reducing lipid peroxide accumulation and ferroptosis. Overall, our findings suggest that supplementation intervention significantly improves IVF outcomes in senescent cells by enhancing metal ion and energy metabolism and enhancing oocyte quality in aging women.

Keywords: multi-omics, nutrients, ferroptosis, ovarian aging

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Authors: Denys Osipenko, Jonathan Crook

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Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

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Authors: Zeeshan Muzammal, Usama Latif, Fouzia Younas, Syed Muhammad Hassan, Samia Razaq

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Unexpected rainfall has always been an issue in the lifetime of crops and brings destruction for the farmers who harvest them. Unfortunately, Pakistan is one of the countries in which untimely rain impacts badly on crops like wash out of seeds and pesticides etc. Pakistan’s GDP is related to agriculture, especially in rural areas farmers sometimes quit farming because leverage of huge loss to their crops. Through our surveys and research, we came to know that farmers in the rural areas of Pakistan need rain information to avoid damages to their crops from rain. We developed a prototype using ICTs to inform the farmers about rain one week in advance. Our proposed solution has two ways of informing the farmers. In first we send daily messages about weekly prediction and also designed a helpline where they can call us to ask about possibility of rain.

Keywords: ICTD, farmers, mobile based, Pakistan, rural areas, weather prediction

Procedia PDF Downloads 553

Authors: Zehra Buyuktuncer, Aylin H. Büyükkaragöz, Tuğçe N. Balcı, Nevin Ergun

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Background: Undergoing rigid dietary habits for enhancing athletic performance could lead to eating disorders. High prevalence of eating disorders among female athletes has been already reported. However, the risk of disordered eating among disabled athletes is not known. A better knowledge of the different eating behaviors and their prevalence in disabled athletes would be helpful to understand interactions between eating and health. This study aimed to examine the cognitive restraint, uncontrolled eating and emotional eating behaviors in a disabled athlete population. Method: A total of 70 disabled Turkish national athletes (33 female, 37 male) from 5 sport branches (soccer, weight lifting, shooting, table tennis and basketball) were involved in the study. The cognitive restraint, uncontrolled eating and emotional eating behaviors were assessed using the revised version of Three Factor Eating Questionnaire-R18 (TFEQ-R18). The questionnaires were conducted by dietitian during the preparation camps of athletes. Body weight, height and waist circumference (WC) were measured; and body composition was analyzed by bioelectrical impedance analysis method. Results: The TFEQ scales showed a cognitive dietary restraint score of 13.9±4.2, uncontrolled eating score of 17.7±5.8 and emotional eating score of 4.9±2.5. The mean score of total TFEQ-R18 was 36.5±8.62. Neither total TFEQ-R18 score nor subscale scores differed significantly by gender or sport branches (p>0.05, for each). The scores were also similar in BMI groups (n=63; p>0.05). Total TFEQ, uncontrolled eating and emotional eating scores were significantly higher among the athletes with congenital disabilities compared to the scores of the athletes with acquired disabilities (p<0.05, for each). Moreover, the cognitive dietary restraint score was significantly high in athletes who would like to lose weight (p=0.009). Conclusion: Disabled athletes might have a risk of disordered eating. The different eating behaviors among disabled athletes should be assessed using validated tools to develop personalized nutritional strategies for those athletes.

Keywords: disabled athletes, eating behaviour, three-factor eating questionnaire-r18, body composition

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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