Search results for: students’ learning achievements

Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges facing the water supply for the Machine Learning Database (MLDB) system at the piston foundry plant. In the MLDB system, one main unit, i.e., robotic, is connected by two sub-units. The functioning of the system depends on the robotic and water supply. Lack of water supply causes system failure. The system operates at full capacity with the help of two sub-units. If one sub-unit fails, the system runs at a low capacity. Reliability modeling is performed using semi-Markov processes and regenerative point techniques. Several system effects such as mean time to system failure, availability at full capacity, availability at reduced capacity, busy period for repair and expected number of visits have been achieved. Benefits have been analyzed. The graphical study is designed for a specific case using programming in C++ and MS Excel.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

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Authors: Rabeeya Raoof, Abrar Ul-Haq, Muhammad Arshad

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The current study is trying to explain the relationship between entrepreneurial education and entrepreneurial passion. This study introduces multiple mechanisms by which entrepreneurial education may induce entrepreneurial passion in business graduates. With the help of expectancy theory, we proposed that entrepreneurial education develops entrepreneurial passion through the mediation of desirability and feasibility. Furthermore, desirability is also influencing feasibility. Therefore, desirability and feasibility may also play their role as double mediators in the relationship between entrepreneurial education and passion. The role of gender has become very vital in entrepreneurship studies. Therefore, we also incorporated the role of gender as a moderator while studying the indirect effect of entrepreneurial education on entrepreneurial passion via desirability and feasibility. We proposed that entrepreneurial education may influence the passion of male individuals primarily through feasibility. On the other hand, entrepreneurial education may impact on the entrepreneurial passion of female individuals primarily through the mediation of desirability. Learning orientation may increase the direct effect of entrepreneurial education on entrepreneurial passion.

Keywords: entrepreneurial passion, perceived desirability, perceived feasibility, entrepreneurial intention

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Authors: Lindsey D. Sams, Dean R. Gorman, Cathy D. Lirgg, Steve W. Dittmore, Jack C. Kern

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Golf is a lifetime sport that provides numerous physical and psychological benefits. The game has struggled with attrition and retention within minority groups and this has exposed the lack of a modified introduction to the game that is uniformly accessible and developmentally appropriate. Factors that have been related to sport participatory behaviors include perceived competence, enjoyment and intention. The purpose of this study was to examine self-reported perception differences in competence and enjoyment between learners using modified and traditional equipment as well as the potential effects these factors could have on intent for future participation. For this study, SNAG Golf was chosen to serve as the scaled equipment used by the modified equipment group. The participants in this study were 99 children (24 traditional equipment users/ 75 modified equipment users) located across the U.S. with ages ranging from 7 to 12 years (2nd-5th grade). Utilizing a convenience sampling method, data was obtained on a voluntary basis through surveys measuring children’s golf participation and self-perceptions concerning perceived competence, enjoyment and intention to continue participation. The scales used for perceived competence and enjoyment included Susan Harter’s Self-Perception Profile for Children (SPPC) along with the Physical Activity Enjoyment Scale (PACES). Analysis revealed no significant differences for enjoyment, perceived competence or intention between children learning with traditional golf equipment and modified golf equipment. This was true even though traditional equipment users reported significantly higher experience levels than that of modified users. Intention was regressed on the enjoyment and perceived competence variables. Congruent with current literature, enjoyment was a strong predictor of intention to continue participation, for both groups. Modified equipment users demonstrated significantly lower experience levels but reported similar levels of competence, enjoyment and intent to continue participation as reported by the more experienced, and potentially more skilled, traditional users. The ability to immediately generate these positive affects suggests the potential adoption of a more effective way to learn golf and a method that is conducive to participatory behaviors related to attrition and retention. These implications in turn, highlight an equipment candidate ideal for inception into physical education programs where new learners are introduced to various sports in safe and developmentally appropriate environments. A major goal of this study was to provide foundational research that instigates the further examination of golf’s introductory teaching methodologies, as there is a lack of its presence in current literature. Future research recommendations range from improvements in the current research design to expansive approaches related to the topic, such as progressive skill development, knowledge of the game’s tactical and strategic concepts, playing ability and teaching effectiveness when utilizing modified versus traditional equipment.

Keywords: adaptive sports, enjoyment, golf participation, modified equipment, perceived competence, SNAG golf

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Authors: Raka Aldy Nugraha, Kiwah Andanni, Aditya Indra Pratama, Aswin Guntara

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Background: Torus palatinus is a bony protuberance in the hard palate. Sex and race are considered as influencing factors for the development of torus palatinus. Hence, the objective of this study was to determine the prevalence and characteristics of torus palatinus and its correlation with sex and ethnicity among Western Indonesian Population. Methods: We conducted a descriptive and analytical study employing cross-sectional design in 274 new students of Universitas Indonesia. Data were collected by using consecutive sampling method through questionnaire-filling and direct oral examination. Subject with racial background other than indigenous Indonesian Mongol were excluded from this study. Data were statistically analyzed using chi square test for categorical variables whereas logistic regression model was employed to assess the correlation between variables of interest with prevalence of torus palatinus. Results: Torus palatinus were found in 212 subjects (77.4%), mostly small in size (< 3 mm) and single in number, with percentage of 50.5% and 90.6%, respectively. The prevalence of torus palatinus were significantly higher in women (OR 2.88; 95% CI: 1.53-5.39; p = 0.001), dominated by medium-sized and single tori. There was no significant correlation between ethnicity and the occurrence of torus palatinus among Western Indonesian population. Conclusion: Torus palatinus was prevalent among Western Indonesian population. It showed significant positive correlation with sex, but not with ethnicity.

Keywords: characteristic, ethnicity, Indonesia, mongoloid, prevalence, sex, Torus palatinus

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Authors: LuoJiaoyang, Yu Hongyang

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In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Salman Imran, Chris Healey

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Traditionally, medical care of children in England and Wales starts from primary care with a referral to secondary care paediatricians who may not investigate further. Many primary care doctors do not undergo a paediatric rotation/exposure in training. As a result, there are many who have not acquired the necessary skills to manage children hence increasing hospital referral. With the current demand on hospitals in the National Health Service managing more problems in the community is needed. One way of handling this is to set up clinics, meetings and huddles in GP surgeries where professionals involved (general practitioner, paediatrician, health visitor, community nurse, dietician, school nurse) come together and share information which can help improve communication and care. The increased awareness and education that paediatricians can impart in this way will help boost confidence for primary care professionals to be able to be more self-sufficient. This has been tried successfully in other regions e.g., St. Mary’s Hospital in London but is crucial for a more rural setting like ours. The primary aim of this project would be to educate specifically GP’s and generally all other health professionals involved. Additional benefits would be providing care nearer home, increasing patient’s confidence in their local surgery, improving communication and reducing unnecessary patient flow to already stretched hospital resources. Methods: This was done as a plan do study act cycle (PDSA). Three clinics were delivered in different practices over six months where feedback from staff and patients was collected. Designated time for teaching/discussion was used which involved some cases from the actual clinics. Both new and follow up patients were included. Two clinics were conducted by a paediatrician and nurse whilst the 3rd involved paediatrician and local doctor. The distance from hospital to clinics varied from two miles to 22 miles approximately. All equipment used was provided by primary care. Results: A total of 30 patients were seen. All patients found the location convenient as it was nearer than the hospital. 70-90% clearly understood the reason for a change in venue. 95% agreed to the importance of their local doctor being involved in their care. 20% needed to be seen in the hospital for further investigations. Patients felt this to be a more personalised, in-depth, friendly and polite experience. Local physicians felt this to be a more relaxed, familiar and local experience for their patients and they managed to get immediate feedback regarding their own clinical management. 90% felt they gained important learning from the discussion time and the paediatrician also learned about their understanding and gaps in knowledge/focus areas. 80% felt this time was valuable for targeted learning. Equipment, information technology, and office space could be improved for the smooth running of any future clinics. Conclusion: The acute paediatric outpatient clinic can be successfully established in primary care facilities. Careful patient selection and adequate facilities are important. We have demonstrated a further step in the reduction of patient flow to hospitals and upskilling primary care health professionals. This service is expected to become more efficient with experience.

Keywords: clinics, education, paediatricians, primary care

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Authors: Prince Dacosta Aboagye, Ayyoob Sharifi

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Cities respond to climate concerns mainly through their climate action plans (CAPs). A comprehensive content analysis of the dynamics in existing urban CAPs is not well represented in the literature. This literature void presents a difficulty in appreciating the strengths and weaknesses of urban CAPs. Here, we perform a qualitative content analysis (QCA) on CAPs from 278 cities worldwide and use text-mining tools to map and visualize the relevant data. Our analysis showed a decline in the number of CAPs developed and published following the global COVID-19 lockdown period. Evidently, megacities are leading the deep decarbonisation agenda. We also observed a transition from developing mainly mitigation-focused CAPs pre-COP21 to both mitigation and adaptation CAPs. A lack of inclusiveness in local climate planning was common among European and North American cities. The evidence is a catalyst for understanding the trends in existing urban CAPs to shape future urban climate planning.

Keywords: urban, climate action plans, strengths, weaknesses

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

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Authors: Soha A. Bahanshal, Byung G. Kim

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Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: Michael J. Haslip

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Character strength application improves performance and well-being in adults across industries, but the potential impact of character strength training among early childhood educators is mostly unknown. To explore how character strengths are applied by early childhood educators at work, a qualitative study was completed alongside professional development provided to a group of in-service teachers of children ages 0-5 in Philadelphia, Pennsylvania, United States. Study participants (n=17) were all female. The majority of participants were non-white, in full-time lead or assistant teacher roles, had at least ten years of experience and a bachelor’s degree. Teachers were attending professional development weekly for 2 hours over a 10-week period on the topic of social and emotional learning and child guidance. Related to this training were modules and sessions on identifying a teacher’s character strength profile using the Values in Action classification of 24 strengths (e.g., humility, perseverance) that have a scientific basis. Teachers were then asked to apply their character strengths to help resolve current workplace challenges. This study identifies which character strengths the teachers reported using most frequently and the nature of the workplace challenges being resolved in this context. The study also reports how difficult these challenges were to the teachers and their success rate at resolving workplace challenges using a character strength application plan. The study also documents how teachers’ own use of character strengths relates to their modeling of these same traits (e.g., kindness, teamwork) for children, especially when the nature of the workplace challenge directly involves the children, such as when addressing issues of classroom management and behavior. Data were collected on action plans (reflective templates) which teachers wrote to explain the work challenge they were facing, the character strengths they used to address the challenge, their plan for applying strengths to the challenge, and subsequent results. Content analysis and thematic analysis were used to investigate the research questions using approaches that included classifying, connecting, describing, and interpreting data reported by educators. Findings reveal that teachers most frequently use kindness, leadership, fairness, hope, and love to address a range of workplace challenges, ranging from low to high difficulty, involving children, coworkers, parents, and for self-management. Teachers reported a 71% success rate at fully or mostly resolving workplace challenges using the action plan method introduced during professional development. Teachers matched character strengths to challenges in different ways, with certain strengths being used mostly when the challenge involved children (love, forgiveness), others mostly with adults (bravery, teamwork), and others universally (leadership, kindness). Furthermore, teacher’s application of character strengths at work involved directly modeling character for children in 31% of reported cases. The application of character strengths among early childhood educators may play a significant role in improving teacher well-being, reducing job stress, and improving efforts to model character for young children.

Keywords: character strengths, positive psychology, professional development, social-emotional learning

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Authors: Oluronke Odunjo

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The world is becoming increasingly urbanized and Nigeria is not left out. One of the indicators of human developments is housing and as such, water is needed by households for survival. This Paper assesses sources of water being used by residents in the newly urbanized areas of Ogbomoso, Southwest, Nigeria. Multistage sampling technique was used and Oke-Adunin Community was purposively selected for the study as it has large concentration of staff and students of Ladoke Akintola University of Technology. The area was captured with Google earth and two hundred and twenty two inhabited houses were found. Questionnaire was the instrument for data collection which was administered using total enumeration technique. Data obtained however, were analyzed with descriptive and inferential statistical analyses. Findings revealed that most of the respondents were male, while 36.03% house owners were between the ages of 46 and 55 years. Sources of water used by residents include well (56.94%), water vendors (17.77%), rain (15.29%) and borehole (3.72%). Distance travelled by house owners to sources of water was as high as 5.06 metres, resulting into stress (30.00 %), depression (25.00%) and aggressiveness (18.75%). Result of correlation analysis between the sources of water of respondents and disease prevalence showed that both rain water and water vendor had very strong positive correlation with typhoid, diarrhea and dysentery, while well water only had positive correlation with dysentery. Recommendations were therefore, proffered towards solving the problems associated with water in the area.

Keywords: newly urbanized area, Ogbomoso, sources of water, residents

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Authors: Faten Fares

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Undoubtedly, the world today faces difficult environmental, financial, and social challenges. In order to change people’s lifestyle to be more sustainable, one must change people’s culture then spaces by focusing on education. Further, the higher education has a key role to play in the move toward a more sustainable world. In the overall analysis, the true sustainable university will make a significant effect. Since the sustainable campus is not only a green built environment, which aims at energy efficiency, water efficiency, waste management, and conserving resources but also it is how to implement green built environment. This implementation takes place while engaging the campus stakeholders (students, academic staff, assistants, workers, and administrators) through educating for sustainability. The main purpose of the research is to develop a tool to assess the sustainable campus and to be a framework for achieving more sustainable campuses. In the case study, the data were analyzed to know existing efforts and capabilities then measure the sustainability performance using the proposal framework at Alexandria University Engineering Campus. Finally, the findings of the research explain that campus is partially adherence with the proposal tool and need to be more sustainable in a formally implemented.

Keywords: sustainability, higher education, sustainable campus, sustainability teaching and research, campus participation culture, environmental improvement

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Authors: Eftekhari M. H., Mozaffari-Khosravi H., Shidfar F.

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Background: Many Iranian adolescent girls are iron deficient, but it is unclear whether the iron deficiency is associated with other nutritional risk indicators. Objective: we aimed to investigate the association between iron deficiency and weight status (measured as BMI) among a reprehensive sample of teenage girls. Methods: A cross-sectional study was performed in a region of southern I.R.Iran. One hundred eighty-seven iron-deficient participants (aged between 11 to 14) were selected by systematic random sampling among all students in grades 1 to 3 from high schools for girls. We assayed hemoglobin, hematocrit, serum ferritin, iron and total iron binding capacity and measured weight and height. Body mass index was calculated according to age and gender-specific BMI growth charts for children 2 to 20 years of age. Results: 13% were at risk for being overweight and 8.3% were overweight. The severity of iron deficiency increased as BMI increased from normal to at risk for overweight and overweight. Iron deficiency anemia was most prevalent among overweight adolescents than at risk for overweight and normal weight adolescents (28%, 18%, and 13%, respectively). Conclusions: The results of this study showed an inverse association of BMI with serum ferritin. Overweight adolescents demonstrated an increased prevalence of anemia. Because of the potentially harmful effects of iron deficiency, obese adolescents should be routinely screened and treated as necessary.

Keywords: adolescent, over weight, iron deficiency, Iran

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Authors: Berlian Eka Kurnia, Mohamad Very Setiawan, Rahmat Fadhli

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Archives play an important role in organization’s continuity, especially related to the learning activities in the past. Archive management is considered accessible when the archive can be used when needed. University archive can support research activities for institutions, besides, archive management services also have to pay attention to the accessibility that became a barometer of how easy users get the data or information from an archive, use and understand it. This study identifies about the accessibility of archive services at the Universitas Gadjah Mada, with case study method. Universitas Gadjah Mada archives not only provide a service to the academicians, but also for public. Universitas Gadjah Mada archive can be traced online and offline. Online searching archives can be acceessed through an application “SIKS” and offline searching can be accessed by "finding aids" printed. Although Universitas Gadjah Mada Archives has its own procedures to access the archive directly, but they also remain guided by National Archive of Indonesia.

Keywords: archival institution, university archive, archive’s accessibility, archive management

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Authors: Fakieh Alrabai

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This study investigated the effects on learner anxiety of anxiety-reducing strategies utilized by English as foreign language teachers in Saudi Arabia. The study was conducted in two stages. In the first stage, sources of foreign language anxiety for Saudi learners of English (N = 596) were identified using The Foreign Language Classroom Anxiety Scale (FLCAS). In the second stage, 465 learners who were divided almost equally into two groups (experimental vs. control) and 12 teachers were recruited. Anxiety-reducing strategies were implemented exclusively in the treatment group for approximately eight weeks. FLCAS was used to assess learners’ FL anxiety levels before and after treatment. Statistical analyses (e.g. ANOVA and ANCOVA) were used to evaluate the study findings. These findings revealed that the intervention led to significantly decreased levels of FL anxiety for learners in the experimental group compared with increased levels of anxiety for those in the control group.

Keywords: communication apprehension, EFL teaching/learning, fear of negative evaluation, foreign language anxiety

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Authors: Haq Nawaz, Muhammad Amjad Iqbal, Kamran Malik

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"Altasreef" is an automated system available for Web and Android users which provide facility to the users to learn the Quran verbs. It provides the facility to the users to practice the learned material and also provide facility of exams of Arabic verbs variation focusing on Quran text. Arabic is a highly inflectional language. Almost all of its words connect to roots of three, four or five letters which approach the meaning of all their inflectional forms. In Arabic, a verb is formed by inserting the consonants into one of a set of verb patterns. Suffixes and prefixes are then added to generate the meaning of number, person, and gender. The active/passive voice and perfective aspect and other patterns are than generated. This application is designed for learners of Quranic Arabic who already have learn basics of Arabic conjugation. Application also provides the facility of translation of generated patterns. These translations are generated with the help of rule-based approach to give 100% results to the learners.

Keywords: NLP, Quran, Computational Linguistics, E Learning

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Authors: Rosemary I. Eneji, Stephen Adi Odey, Edem Carole, Eucharia Nwagbara

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Sexual and reproductive health behaviors are the main causes of death, disability, and disease among adolescents in Nigeria. In this study, we determined the accessibility of youth-friendly sexual and reproductive health services to secondary school adolescents in southern Cross River state, Nigeria. Nineteen randomly selected public secondary schools across the seven local government areas in the zone were used. The respondents were four hundred senior secondary (classes SSI - SS3) students aged 15-19 years, comprising 63.7% females and 36.3% males. A 50-item structured questionnaire was used for the study. There was a strong influence of age and sex of adolescents, income and occupation of parents, knowledge and awareness of adolescents, and tradition on the accessibility and use of youth-friendly sexual and reproductive health services (YFSRHS) to the adolescents. The attitude of health workers towards accessibility was of little effect. Overall, youth-friendly sexual and reproductive health services were not easily accessible to adolescents in the study area. Thus, there is need to enforce adolescent reproductive health policies in the area. Training and use of trained caregivers and peer educators to attend to adolescents and the inclusion of adolescent reproductive health as a subject in the curriculum are strongly recommended.

Keywords: youth, reproductive health, cross river state, secondary schools, Nigeria

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Authors: Luis Rodrigo Valencia Pérez, Juan Manuel Peña Aguilar, Adelina Morita Alexander, Alberto Lamadrid Alvarez, Héctor Fernando Valencia Pérez

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Financial education is among the areas of opportunity in the Spanish-speaking from an early age to high school, through mobile devices such as cell phones and tablets using ludic and fun applications like interactive games, children can learn money management and investment through time, thereby fostering the habit of saving and/or sound management of cash and family business resources, having interaction with an uncontrolled environment such as the involvement of other players in the external decisions of the environment in which the game is play. The application proposed in Phase 1 (design and development) was designed in multi-user environments, under methodologies of hybrid programming for any platform on the market and designed under CMMI standards that allow for quality production over time, following up on these improvements counting with continuous user feedback and usage statistics.

Keywords: mobile educational games, ludic games, children, multiuser, design and software development

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Authors: Divya Pande

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The dynamics of culture expresses itself in language. Even after India got independence in 1947 English subtly crept in the language of the masses with a silent and powerful flow towards the vernacular. The culture contact resulted in learning and emergence of a new language across the Hindi speaking belt of Northern and Central India. The hybrid words thus formed displaced the original word and got contextualized and absorbed in the language of the common masses. The research paper explores the interesting new vocabulary used extensively in the urban and rural districts of the state of Uttar- Pradesh which is the most populous state of India. The paper adopts a two way classification- formal and contextual for the analysis of the hybrid vocabulary of the linguistic items where one element is necessarily from the English language and the other from the Hindi. The new vocabulary represents languages of the wider world cutting across the geographical and the cultural barriers. The paper also broadly points out to the Hinglish commonly used in the state.

Keywords: assimilation, culture contact, Hinglish, hybrid words

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Authors: Daniel Benson, Yundan Gong, Hannah Kirk

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Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

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Authors: Khamdan Cahyari, Gumbolo Hadi Susanto, Pratikno Hidayat, Sukirman

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University canteen waste was used as raw material to produce biogas in Faculty of Industrial Technology, Islamic University of Indonesia. This faculty was home to more than 3000 students and lecturers who work and study for 5 days/week (8 hours/day). It produced approximately 85 ton/year organic fraction of canteen waste. Yet, this waste had been dumped for years in landfill area which cause severe environmental problems. It was proposed to utilize the waste as raw material for producing renewable energy source of biogas. This research activities was meant to investigate the effect of organic loading rate (OLR) and retention time (RT) of continuous anaerobic digestion process for 200 days. Organic loading rate was set at value 2, 3, 4 and 5 g VS/l/d whereas the retention time was adjusted at 30, 24, 18 and 14.4 days. Optimum condition was achieved at OLR 4 g VS/l/d and RT 24 days with biogas production rate between 0.75 to 1.25 liter/day (40-60% CH4). This indicated that the utilization of canteen waste to produce biogas was promising method to mitigate environmental problem of university canteen waste. Furthermore, biogas could be used as alternative energy source to supply energy demand at the university. This implementation is simultaneous solution for both waste and energy problems to achieve green campus.

Keywords: canteen waste, biogas, anaerobic digestion, university, green campus

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Authors: Kevin Smith

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Publicly traded company in the US are legally obligated to host earnings calls that discuss their most recent financial reports. During these calls, investors are able to ask these companies questions about these financial reports and on the future direction of the company. This paper examines whether common institutional owners use these calls as a way to indirectly signal to companies in their portfolio to not take actions that could hurt the common owner's interests. This paper uses transcripts taken from the earnings calls of the six largest health insurance companies in the US from 2014 to 2019. This data is analyzed using text analysis and sentiment analysis to look for patterns in the statements made by common owners. The analysis found that common owners where more likely to recommend against direct price competition and instead redirect the insurance companies towards more passive actions, like investing in new technologies. This result indicates a mechanism that common owners use to reduce competition in the health insurance market.

Keywords: common ownership, text analysis, sentiment analysis, machine learning

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Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari

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To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.

Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing

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Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

Abstract:

Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

Procedia PDF Downloads 114

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 72

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 56

Authors: Thao Thi Vu, Libby Lee-Hammond, Andrew McConney

Abstract:

In Vietnam, the Vietnamese language is normally used as the language of instruction. The dominance of this language places children who have a different first language such as Indigenous children at a disadvantage when commencing school. This study explores preschool teachers’ beliefs about second language acquisition in Lai Chau provinces where is typical of highland provinces of Vietnam and the proportion of Indigenous minority groups in high. Data were collected from surveys with both closed-end questions and opened-end questions. The participants in this study were more than 200 public preschool teachers who come from eight different districts in Lai Chau. An analysis of quantitative data survey is presented to indicate several practical implications, such as the connection between teachers’ knowledge background that gained from their pre-service and in-service teacher education programs regarding second language teaching for Indigenous children and their practice. It also explains some factors that influence teachers’ beliefs and perspective about Indigenous children and pedagogies in their classes.

Keywords: indigenous children, learning Vietnamese, preschool, teachers’ beliefs

Procedia PDF Downloads 404