Search results for: learning delivery modes

Authors: Asma Ben Abdallah

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Interlanguage Pragmatics (ILP) Instruction has brought a lot of enlightenment for Foreign Language Teaching and has secured itself a deserved position in SLA research. In the Tunisian context, ILP instruction remains less explored for academics and educational practitioners. In our experience as teachers, both at secondary school and at university levels, the instruction and assessment of pragmatics seem to be contentious. This paper firstly introduces the theoretical models of Interlanguage pragmatics Instruction and focuses on their implications for foreign language teaching. This study builds on the work of Ben Abdallah (2015) that investigated the effects of pragmatic Instruction on Tunisian EFL Learners where pragmatic Instruction has been approached from the perspective of students and their learning strategies. The data for the present study, however, come from Tunisian EFL teachers by investigating their pragmatics practices and their perceptions of pragmatic instruction. The findings indicated that EFL teachers have pragmatic awareness; yet, their reflections revealed that their awareness was mostly on theoretical pragmatic knowledge, and not explicitly brought into practical pragmatic applications. The paper concludes by promoting pragmatics instruction with the suggestion that EFL teachers should teach pragmatics in class.

Keywords: interlanguage pragmatics theory, pragmatics, pragmatic instruction, SLA

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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: Weldeabrha Kiros Kidanemaryam

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The investigation is to examine intra-organizational supply chain relationships of firms, which will help to look at and give an emphasis on internal processes and operations strength and achievements to make an influence even for external relationship management and outstanding performances of organizations. The purpose of the study is to scrutinize the internal supply chain relationships within manufacturing companies located in Tigray. The qualitative and quantitative data analysis methods were employed during the study by applying the primary data sources (questionnaires & interviews) and secondary data sources (organizational reports and documents) with the purposive sampling method. Thus, a descriptive research design was also applied in the research project in line with the cross-sectional research design which portrays simply the magnitude of the issues and problems by collecting the required and necessary data once from the sample respondents. This is because the study variables don’t have any cause-and-effect relationship in the research project that requires other types of research design than a descriptive research design; it already needs to be assessed and analyzed with a detailed description of the results after quantifying the outcomes and degree of the issues and problems based on the data gathered from respondents. The collected data was also analyzed by using the statistical package for social sciences (SPSS Version 20). The intra-organizational relationships of the companies are moderately accomplished, which requires an improvement for enhancing the performances of each unit or department within the firms so as to upgrade and ensure the progress of the companies’ effectiveness and efficiency. Moreover, the manufacturing companies have low industrial discipline and working culture, weak supervision of manpower, delayed delivery in the process within the companies, unsatisfactory quality of products, underutilization of capacity, and low productivity and profitability, which in turn results in minimizing the performance of intra-organizational supply chain relationships and to reduce the companies’ organizational efficiency, effectiveness and sustainability. Hence, the companies should have to give emphasize building and managing the intra-organizational supply chain relationships effectively because nothing can be done without creating successful and progressive relationships with internal units or functional areas and individuals for the production and provision of the required and qualified products that permits to meet the intended customers’ desires. The study contributes to improving the practical applications and gives an emphasis on the policy measurements and implications of the manufacturing companies with regard to intra-organizational supply chain relationships.

Keywords: supply chain, supply chain relationships, intra-organizational relationships, manufacturing companies

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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: 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

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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

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Authors: Behdoukht Mall Amiri, Zohreh Gheydar

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The thrust of the current study was to investigate the relationship among EFL learners' creativity (CR), emotional intelligence (EI), and self-efficacy (SE). To this end, a group of 120 male and female learners, between the ages of 19 and 35 studying BA in English Translation and MA in Teaching English at Islamic Azad University, Central Tehran were selected using convenient sampling and were given three questionnaires: Bar-On’s EQ-I questionnaire by Bar-On (1997), the General Self-Efficacy Scale questionnaire (SGSES) by Sherer et al. (1982), and a questionnaire of creativity (CR) by O'Neil, Abedi, and Spielberger (1992). Analysis of the results through Pearson Moment Correlation Coefficient showed that there was not a significant relationship between students’ CR and EI, and EI and SE. In addition, CR and SE were correlated significantly but negatively. Multiple regressions revealed that CR could significantly predict SE. Regarding the findings of the study, the obtained results may help EFL teachers, teacher trainers, materials developers, and educational policy makers to possess a broader perspective and heightened degree knowledge toward the TEFL practice and to take practical steps toward the attainments of the desired objectives of the profession.

Keywords: creativity, emotional intelligence, self-efficacy, learning

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Authors: Arezou Javadi

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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 82

Authors: Arezou Javadi

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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

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

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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

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Authors: Sabri Serkan Güllüoğlu

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Analysis can be defined as the process of gathering, recording and researching data related to products and services, in order to learn something. But for marketers, analyses are not only used for learning but also an essential and critical part of the business, because this allows companies to offer products or services which are focused and well targeted. Market analysis also identify market trends, demographics, customer’s buying habits and important information on the competition. Data mining is used instead of traditional research, because it extracts predictive information about customer and sales from large databases. In contrast to traditional research, data mining relies on information that is already available. Simply the goal is to improve the efficiency of supermarkets. In this study, the purpose is to find dependency on products. For instance, which items are bought together, using association rules in data mining. Moreover, this information will be used for improving the profitability of customers such as increasing shopping time and sales of fewer sold items.

Keywords: data mining, association rule mining, market basket analysis, purchasing

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Rinat Gabbay-Benziv, Merav Ben-Natan, Ariel Roguin, Benyamine Abbou, Anna Ofir, Adi Klein, Dikla Dahan-Shriki, Mordechai Hallak, Boris Kessel, Mickey Dudkiewicz

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Introduction: Over recent decades, technology has become integral to healthcare, with electronic health records and advanced medical equipment now standard. However, this reliance has made healthcare systems increasingly vulnerable to ransomware attacks. On October 13, 2021, Hillel Yaffe Medical Center experienced a severe ransomware attack that disrupted all IT systems, including electronic health records, laboratory services, and staff communications. The attack, carried out by the group DeepBlueMagic, utilized advanced encryption to lock the hospital's systems and demanded a ransom. This incident caused significant operational and patient care challenges, particularly impacting the obstetrics department. Objective: The objective is to describe the challenges facing the obstetric division following a cyberattack and discuss ways of preparing for and overcoming another one. Methods: A retrospective descriptive study was conducted in a mid-sized medical center. Division activities, including the number of deliveries, cesarean sections, emergency room visits, admissions, maternal-fetal medicine department occupancy, and ambulatory encounters, from 2 weeks before the attack to 8 weeks following it (a total of 11 weeks), were compared with the retrospective period in 2019 (pre-COVID-19). In addition, we present the challenges and adaptation measures taken at the division and hospital levels leading up to the resumption of full division activity. Results: On the day of the cyberattack, critical decisions were made. The media announced the event, calling on patients not to come to our hospital. Also, all elective activities other than cesarean deliveries were stopped. The number of deliveries, admissions, and both emergency room and ambulatory clinic visits decreased by 5%–10% overall for 11 weeks, reflecting the decrease in division activity. Nevertheless, in all stations, there were sufficient activities and adaptation measures to ensure patient safety, decision-making, and workflow of patients were accounted for. Conclusions: The risk of ransomware cyberattacks is growing. Healthcare systems at all levels should recognize this threat and have protocols for dealing with them once they occur.

Keywords: ransomware attack, healthcare cybersecurity, obstetrics challenges, IT system disruption

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Authors: Keivan Seyyedi, Leila Esmaeilpour, Seyed Jamal Sadeghi

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Investigating the effectiveness of explicit focus on form on the written performance of the EFL learners was the aim of this study. To provide empirical support for this study, sixty male English learners were selected and randomly assigned into two groups of explicit focus on form and meaning focused. Narrative writing was employed for data collection. To measure writing performance, participants were required to narrate a story. They were given 20 minutes to finish the task and were asked to write at least 150 words. The participants’ output was coded then analyzed utilizing Independent t-test for grammatical accuracy and fluency of learners’ performance. Results indicated that learners in explicit focus on form group appear to benefit from error correction and rule explanation as two pedagogical techniques of explicit focus on form with respect to accuracy, but regarding fluency they did not yield any significant differences compared to the participants of meaning-focused group.

Keywords: explicit focus on form, rule explanation, accuracy, fluency

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Authors: Ashish Kumar, Kaptan Singh, Amit Saxena

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Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.

Keywords: K-nearest neighbor, random forest, decision tree, pre-processing

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Authors: Chui-Hsin Chen, Yu-Ting Chen

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Special concentrically braced frames is one of the seismic load resisting systems, which dissipates seismic energy when bracing members within the frames undergo yielding and buckling while sustaining their axial tension and compression load capacities. Most of the inelastic deformation of a buckling bracing member concentrates in the mid-length region. While experiencing cyclic loading, the region dissipates most of the seismic energy being input into the frame. Such a concentration makes the braces vulnerable to failure modes associated with low-cycle fatigue. In this research, a strategy to improve the cyclic behavior of the conventional steel bracing member is proposed by filling the Hollow Structural Shape (HSS) member with reinforcement. It prevents the local section from concentrating large plastic deformation caused by cyclic loading. The infill helps spread over the plastic hinge region into a wider area hence postpone the initiation of local buckling or even the rupture of the braces. The finite element method is introduced to simulate the complicated bracing member behavior and member-versus-infill interaction under cyclic loading. Fifteen 3-D-element-based models are built by ABAQUS software. The verification of the FEM model is done with unreinforced (UR) HSS bracing members’ cyclic test data and aluminum honeycomb plates’ bending test data. Numerical models include UR and filled HSS bracing members with various compactness ratios based on the specification of AISC-2016 and AISC-1989. The primary variables to be investigated include the relative bending stiffness and the material of the filling reinforcement. The distributions of von Mises stress and equivalent plastic strain (PEEQ) are used as indices to tell the strengths and shortcomings of each model. The result indicates that the change of relative bending stiffness of the infill is much more influential than the change of material in use to increase the energy dissipation capacity. Strengthen the relative bending stiffness of the reinforcement results in additional energy dissipation capacity to the extent of 24% and 46% in model based on AISC-2016 (16-series) and AISC-1989 (89-series), respectively. HSS members with infill show growth in 𝜂Local Buckling, normalized energy cumulated until the happening of local buckling, comparing to UR bracing members. The 89-series infill-reinforced members have more energy dissipation capacity than unreinforced 16-series members by 117% to 166%. The flexural rigidity of infills should be less than 29% and 13% of the member section itself for 16-series and 89-series bracing members accordingly, thereby guaranteeing the spread over of the plastic hinge and the happening of it within the reinforced section. If the parameters are properly configured, the ductility, energy dissipation capacity, and fatigue-life of HSS SCBF bracing members can be improved prominently by the infill-reinforced method.

Keywords: special concentrically braced frames, HSS, cyclic loading, infill reinforcement, finite element analysis, PEEQ

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Authors: Nora Alomar, Bianca Alexandra Stefa, Saleh Bazi

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This research uncovers the determinants that drive millennial consumers to adhere to product return of fast-fashion products purchases via e-commerce and what effects it has on consumer experience and satisfaction. Online consumption has skyrocketed, with e-commerce being the only, most reliable, and safe method of shopping during and post Covid-19. It has been noted customers are demanding a wide variety of product characteristics and a generous optimal return policy. The authors have selected to examine millennial consumers as they are digital natives and have an affinity for researching, reading product reviews, and shopping online, with a great spending power due to a higher disposable income in comparison to other generations. A multi-study approach is adopted, where study one (interviews, sample of 20 respondents) investigates the factors that drive product return, and study two (PLS-SEM, sample of 250 respondents) looks into the relationships of product return management against behavioral outcomes by having the generated factors (from study one) as moderators. Five themes are generated from study one (return policies, product characteristics, delivery lead time, seasonality, product trial & overspending). The authors identify that two out of the five factors (seasonality, product trial & overspending) have not been highlighted by the literature. The paper examines 11 hypotheses, where 10 are supported. Findings highlight the quality of the product return management influences the overall millennial customer experience and satisfaction. Findings also indicate that product return management was identified to have a significant negative effect on customer experience. Additionally, seasonality has a significant but negative moderation, which means increasing seasonality decreases the relationship between product return management and customer experience and satisfaction. Results highlight that return policies have a significant negative influence on the relationship between returning a product and customer experience and satisfaction. Moreover, product characteristics are also identified to have a significant negative influence on the relationship between returning a product and customer experience and satisfaction. This study further examines the influence of the factors on direct e-commerce websites and third-party e-commerce websites. Findings showcase a strong statistical significance for the increased rate of return of fast-fashion products on third-party websites. This paper aids practitioners in taking strategic decisions related to return management, to improve the quality of logistical services and, in turn, increase profitability.

Keywords: customer experience, customer satisfaction, e-commerce, fast-fashion, product returns

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Authors: Mohamed Chabi, Mahmoud I. Syam, Sarah Aw

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In Summer 2012, the Foundation Program Unit of Qatar University has started implementing new ways of teaching Math by introducing MML (MyMathLab) as an innovative interactive tool to support standard teaching. In this paper, we focused on the effect of proper use of the Study Plan component of MML on student’s performance. Authors investigated the results of students of pre-calculus course during Fall 2013 in Foundation Program at Qatar University. The results showed that there is a strong correlation between study plan results and final exam results, also a strong relation between homework results and final exam results. In addition, the attendance average affected on the student’s results in general. Multiple regression is determined between passing rate dependent variable and study plan, homework as independent variable.

Keywords: MyMathLab, study plan, assessment, homework, attendance, correlation, regression

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Authors: Fuad M. Alkoot

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We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

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Authors: Serge Provost, Yishan Zang

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Copulas are currently utilized in finance, reliability theory, machine learning, signal processing, geodesy, hydrology and biostatistics, among several other fields of scientific investigation. It follows from Sklar's theorem that the joint distribution function of a multidimensional random vector can be expressed in terms of its associated copula and marginals. Since marginal distributions can easily be determined by making use of a variety of techniques, we address the problem of securing the distribution of the copula. This will be done by using several approaches. For example, we will obtain bivariate least-squares approximations of the empirical copulas, modify the kernel density estimation technique and propose a criterion for selecting appropriate bandwidths, differentiate linearized empirical copulas, secure Bernstein polynomial approximations of suitable degrees, and apply a corollary to Sklar's result. Illustrative examples involving actual observations will be presented. The proposed methodologies will as well be applied to a sample generated from a known copula distribution in order to validate their effectiveness.

Keywords: copulas, Bernstein polynomial approximation, least-squares polynomial approximation, kernel density estimation, density approximation

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Authors: Deborah Amas

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Global accreditation standards require Higher Education Institutions to ensure social work students develop self-awareness by reflecting on their personal values and critically evaluating how these influence their thinking for professional practice. The knowledge base indicates there are benefits and vulnerabilities for students when they self-reflect and more needs to be understood about the learning environments that nurture self-awareness. The connection between teaching methods and self-awareness is of interest in this paper which reports findings from an on-line survey with students on BA and MA qualifying social work programs in an English university (n=120). Students were asked about the importance of self-awareness and their experiences of teaching methods for self-reflection. Generally, students thought that self-awareness is of high importance in their education. Students also shared stories that illuminated deeper feelings about the potential risks associated with self-disclosure. The findings indicate that students appreciate safe opportunities for self-reflection, but can be wary of associated assessments or feeling judged. The research supports arguments to qualitatively improve facilitation of self-awareness through the curriculum.

Keywords: reflection, self-awareness, self-reflection, social work education

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Authors: Yi-De Liu

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The aim of this paper is to discuss how the construct of networking and social capital can be used to understand the effect events can have on the cultural sector. Based on case study, this research sought the views of those working in the cultural sector on Liverpool’s year as the European Capital of Culture (ECOC). Methodologically, this study involves literature review to prompt theoretical sensitivity, the collection of primary data via online survey (n= 42) and follow-up telephone interviews (n= 8) to explore the emerging findings in more detail. The findings point to a number of ways in which the ECOC constitutes a boost for networking and its effects on city’s cultural sector, including organisational learning, aspiration and leadership. The contributions of this study are two-fold: (1) Evaluating the long-term effects on network formation in the cultural sector following major event; (2) conceptualising the impact assessment of organisational social capital for future ECOC or similar events.

Keywords: network, social capital, cultural impact, european capital of culture

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Authors: Martina Marinelli, Samanta Vellante, Francesco Pilotti, Daniele Di Valerio, Gaetanino Paolone

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Any development in web marketing technology requires changes in information engineering to identify instruments and techniques suitable for the production of software applications for informative marketing. Moreover, for large web solutions, designing an interface that enables human interactions is a complex process that must bridge between informative marketing requirements and the developed solution. A user-friendly interface in web marketing applications is crucial for a successful business. The paper introduces mkInfo - a software platform that implements informative marketing. Informative marketing is a new interpretation of marketing which places the information at the center of every marketing action. The creative team includes software engineering researchers who have recently authored an article on automatic code generation. The authors have created the mkInfo software platform to generate informative marketing web applications. For each web application, it is possible to automatically implement an opt in page, a landing page, a sales page, and a thank you page: one only needs to insert the content. mkInfo implements an autoresponder to send mail according to a predetermined schedule. The mkInfo platform also includes e-commerce for a product or service. The stakeholder can access any opt-in page and get basic information about a product or service. If he wants to know more, he will need to provide an e-mail address to access a landing page that will generate an e-mail sequence. It will provide him with complete information about the product or the service. From this point on, the stakeholder becomes a user and is now able to purchase the product or related services through the mkInfo platform. This paper suggests a possible definition for Informative Marketing, illustrates its basic principles, and finally details the mkInfo platform that implements it. This paper also offers some Informative Marketing models, which are implemented in the mkInfo platform. Informative marketing can be applied to products or services. It is necessary to realize a web application for each product or service. The mkInfo platform enables the product or the service producer to send information concerning a specific product or service to all stakeholders. In conclusion, the technical contributions of this paper are: a different interpretation of marketing based on information; a modular architecture for web applications, particularly for one with standard features such as information storage, exchange, and delivery; multiple models to implement informative marketing; a software platform enabling the implementation of such models in a web application. Future research aims to enable stakeholders to provide information about a product or a service so that the information gathered about a product or a service includes both the producer’s and the stakeholders' point of view. The purpose is to create an all-inclusive management system of the knowledge regarding a specific product or service: a system that includes everything about the product or service and is able to address even unexpected questions.

Keywords: informative marketing, opt in page, software platform, web application

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Authors: Elaine Crable, Amit Sen

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Short-term study abroad programs have become a mainstay of MBA programs. The benefits of international business experiences, along with its exposure to global cultures, are well documented. However, developing a rewarding study, abroad program at the graduate level can be challenging for Faculty, especially when devising such a program for a group of part-time MBA students who come with a wide range of experiences and demographic characteristics. Each student has individual expectations for the study abroad experience. This study provides suggestions and considerations for Faculty that are planning to design a short-term study abroad program, especially for part-time MBA students. Insights are based on a recent experience leading a group of twenty-one students on a ten-day program to Morocco. The trip was designed and facilitated by two faculty members and a local Moroccan facilitator. This experience led to a number of insights and recommendations. First, the choice of location is critical. The choice of Morocco was very deliberate, owing to its multi-faceted cultural landscape and international business interest. It is an Islamic State with close ties to Europe both culturally and geographically and Morocco is a multi-lingual country with some combination of three languages spoken by most – English, Arabic, and French. Second, collaboration with a local ‘academic’ partner allowed the level of instruction to be both rigorous and significantly more engaging. Third, allowing students to participate in the planning of the trip enabled the trip participants to collaborate, negotiate, and share their own experiences and strengths. The pre-trip engagement was structured by creating four sub-groups, each responsible for an assigned city. Each student sub-group had to provide a historical background of the assigned city, plan the itinerary including sites to visit, cuisine to experience, industries to explore, markets to visit, plus provide a budget for that city’s expenses. The pre-planning segment of the course was critical for the success of the program as students were able to contribute to the design of the program through collaboration and negotiation with their peers. Fourth, each student sub-group was assigned industry to study within Morocco. The student sub-group prepared a presentation and a group paper with their analysis of the chosen industries. The pre-planning activities created strong bonds among the trip participants, which was evident when faced with on-ground challenges, especially when it was necessary to quickly evacuate due to a surprise USA COVID evacuation notice. The entire group supported each other when quickly making their way back to the United States. Unfortunately, the trip was cut short by two days due to this emergency exit, but the feedback regarding the program was very positive all around. While the program design put pressure on the Faculty leads regarding planning and coordination upfront, the outcome in terms of student engagement, student learning, collaboration and negotiation were all favorable and worth the effort. Finally, an added value, the cost of the program for the student was significantly lower compared to running a program with a professional provider.

Keywords: business education, experiential learning, international education, study abroad

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Authors: Anietie J. Atangwho, Udeme E. Asibong, Item J. Atangwho, Ndifreke E. Udonwa

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Diabesity, a syndrome where diabetes and obesity occur simultaneously in a single patient, has emerged as a recent challenge to the medical world and is already at epidemic proportion in some countries. Therefore, this study aimed to determine the prevalence of diabesity among adult patients attending the General Outpatient clinic of three healthcare facilities in Calabar in a bid to improve healthcare delivery to patients at risk. A cross-sectional descriptive study design was employed using a mixed method approach that comprised quantitative and qualitative components i.e., Focused Group Discussion (FGD) and Key Informant Interview (KII). One hundred and ninety (190) participants aged 18 to 72 years and body mass index (BMI) ≥ 30kg/m2 were recruited as the study population for the quantitative study using systematic random sampling technique and analysed using SPSS version 25. The qualitative component performed 4 FGDs and 3 KIIs. Results of sociodemographic variables showed respondents aged 35 – 44 as highest in number (37.3%). Of this number, 83.7% were females, 76.8% married, and 3.7% earned USD1,110.00 monthly. Whereas majority of the participants (65.8 %) were within class 1 obesity, only 38% considered themselves obese. Diabesity occurrence was found to be 12.6% (i.e. BMI ≥ 30 to 45.2kg/m2 vs FBS ≥ 7.0 – 14.8mmo/l), with 38% of them being previously undiagnosed. About 48.4 % of the respondents ate two meals only per day; with 90.5% eating between meals. Snacking was predominant, mostly pastries (67.9%), with 58.9% taking cola drinks alongside. Sixty-one percent participated in one form of exercise or the other, with walking/trekking as the most common; 34.4 % had no regular exercise schedule. Only about 39.5% of the participants spent less than an hour on devices like phone, television, and laptops. Additionally, previously known and newly diagnosed hypertensive patients were 27.9% and 7.2%, respectively. Qualitative assessment with KII and FGDs showed eating unhealthy diets and lack of exercise as major factors responsible for diabesity. The bivariate analysis revealed significant association between diabesity with marital status and hypertension (p = 0.007 and p = 0.005, respectively). Also, positive association with diabesity were eating snacking (p = 0.017) and number of times a respondent snacks per day (p = 0.035). Overall, the study has revealed the occurrence of diabesity in Calabar at 12.6 % of the study population, with 38 % of them previously undiagnosed; it identified unhealthy diets and lack of exercise as causative factors as well as hypertension as snacking associatory indicators of diabesity.

Keywords: diabesity, obesity, diabetes, unhealthy diet

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Authors: Aditya Purohit, Neha Bansal

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Unplanned urbanization and multidirectional sprawl of the cities have resulted in increased motorization and deteriorating transport conditions like traffic congestion, longer commuting, pollution, increased carbon footprint, and above all increased fatalities. In order to overcome these problems, various practices have been adopted including– promoting and implementing mass transport; traffic junction channelization; smart transport etc. However, these methods are found to be primarily focusing on vehicular mobility rather than people accessibility. With this research gap, this paper tries to resolve the mobility issues for Ahmedabad city in India, which being the economic capital Gujarat state has a huge commuter and visitor inflow. This research aims to resolve the traffic congestion and urban mobility issues focusing on Gujarat State Regional Transport Corporation (GSRTC) for the city of Ahmadabad by analyzing the existing operations and network structure of GSRTC followed by finding possibilities of integrating it with other modes of urban transport. The network restructuring (NR) methodology is used with appropriate variations, based on commuter demand and growth pattern of the city. To do these ‘scenarios’ based on priority issues (using 12 parameters) and their best possible solution, are established after route network analysis for 2700 population sample of 20 traffic junctions/nodes across the city. Approximately 5% sample (of passenger inflow) at each node is considered using random stratified sampling technique two scenarios are – Scenario 1: Resolving mobility issues by use of Special Purpose Vehicle (SPV) in joint venture to GSRTC and Private Operators for establishing feeder service, which shall provide a transfer service for passenger for movement from inner city area to identified peripheral terminals; and Scenario 2: Augmenting existing mass transport services such as BRTS and AMTS for using them as feeder service to the identified peripheral terminals. Each of these has now been analyzed for the best suitability/feasibility in network restructuring. A desire-line diagram is constructed using this analysis which indicated that on an average 62% of designated GSRTC routes are overlapping with mass transportation service routes of BRTS and AMTS in the city. This has resulted in duplication of bus services causing traffic congestion especially in the Central Bus Station (CBS). Terminating GSRTC services on the periphery of the city is found to be the best restructuring network proposal. This limits the GSRTC buses at city fringe area and prevents them from entering into the city core areas. These end-terminals of GSRTC are integrated with BRTS and AMTS services which help in segregating intra-state and inter-state bus services. The research concludes that absence of integrated multimodal transport network resulted in complexity of transport access to the commuters. As a further scope of research comparing and understanding of value of access time in total travel time and its implication on generalized cost on trip and how it varies city wise may be taken up.

Keywords: mass transportation, multi-modal integration, network restructuring, travel behavior, urban transport

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