Search results for: affective domains fo learning

Authors: Aynur Charkasova

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The scientific and economic contributions of international students cannot be underestimated. International education continues to be a competitive global industry, and many countries are seeking to recruit the best and the brightest to reinforce scientific innovations, boost intercultural learning, and bring more funding to the universities and colleges. Substantial changes in international educational policies and migration regulations have been made in the hopes of recruiting global talent. This paper explores and compares recruitment strategies, employment opportunities, and a legal path to permanent residency policies related to international students in the United States of America and Canada. This study will utilize the legal information available by the government websites of both countries, peer-reviewed scholarly articles and will highlight which approach promises a better path in recruiting and retention of international students. The findings from the study will be discussed and recommendations will be provided.

Keywords: international students, current immigration policies, STEM, visa reforms for international students

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Authors: Malla Vijayeta, Y. Vijaya Kumar, N. Ramakrishna Raju, K. Satyanarayana

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Global AEC (architecture, engineering, and construction) industry has been coined as one of the most resistive domains in embracing technology. Although this digital era has been inundated with software tools like CAD, STADD, CANDY, Microsoft Project, Primavera etc. the key stakeholders have been working in siloes and processes remain fragmented. Unlike the yesteryears’ simpler project delivery methods, the current projects are of fast-track, complex, risky, multidisciplinary, stakeholder’s influential, statutorily regulative etc. pose extensive bottlenecks in preventing timely completion of projects. At this juncture, a paradigm shift surfaced in construction industry, and Building Information Modeling, aka BIM, has been a panacea to bolster the multidisciplinary teams’ cooperative and collaborative work leading to productive, sustainable and leaner project outcome. Building information modeling has been integrative, stakeholder engaging and centralized approach in providing a common platform of communication. A common misconception that BIM can be used for building/high rise projects in Indian Construction Industry, while this paper discusses of the implementation of BIM processes/methodologies in water and waste water industry. It elucidates about BIM 4D planning and constructability reviews of a Sewage Treatment Plant in India. Conventional construction planning and logistics management involves a blend of experience coupled with imagination. Even though the excerpts or judgments or lessons learnt gained from veterans might be predictive and helpful, but the uncertainty factor persists. This paper shall delve about the case study of real time implementation of BIM 4D planning protocols for one of the Sewage Treatment Plant of Dravyavati River Rejuvenation Project in India and develops a Time Liner to identify logistics planning and clash detection. With this BIM processes, we shall find that there will be significant reduction of duplication of tasks and reworks. Also another benefit achieved will be better visualization and workarounds during conception stage and enables for early involvement of the stakeholders in the Project Life cycle of Sewage Treatment Plant construction. Moreover, we have also taken an opinion poll of the benefits accrued utilizing BIM processes versus traditional paper based communication like 2D and 3D CAD tools. Thus this paper concludes with BIM framework for Sewage Treatment Plant construction which will achieve optimal construction co-ordination advantages like 4D construction sequencing, interference checking, clash detection checking and resolutions by primary engagement of all key stakeholders thereby identifying potential risks and subsequent creation of risk response strategies. However, certain hiccups like hesitancy in adoption of BIM technology by naïve users and availability of proficient BIM trainers in India poses a phenomenal impediment. Hence the nurture of BIM processes from conception, construction and till commissioning, operation and maintenance along with deconstruction of a project’s life cycle is highly essential for Indian Construction Industry in this digital era.

Keywords: integrated BIM workflow, 4D planning with BIM, building information modeling, clash detection and visualization, constructability reviews, project life cycle

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Authors: Abdul Rofiq Badril Rizal M. Z.

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Reading becomes one of the most important skills in teaching and learning English. The purpose of this research was to improve the students' active participation, and reading comprehension achievement by using Know, Want to Know, Learned (KWL) strategy. The research design was Classroom Action Research. The area and participants of this research were chosen by using purposive method. The data were collected by observation, a reading comprehension test, interview, and documentation. The results showed that there was significant improvement in Cycle 1 to Cycle 2 of the research. In cycle 1, the students’ active participation increased 49.77% from 28% to 77.77. In addition, in cycle 2, the students’ active participation also increased by 14.17% from 77.77% to 81.94%. The students’ reading comprehension achievement also increased by 52.14% from 25% to 77.14% in Cycle 1 and increased by 5.71% from 77.14% to 82.85% in cycle 2. It indicated that using Know, Want to Know, Learned (KWL) strategy could enhance the Seventh C grade students’ descriptive text reading comprehension achievement, and active participation.

Keywords: active participation, reading comprehension, classroom action research, Indonesian folktales

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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: Iniye Irene Wodi, Allen A. Agih

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Goal theory perspective as an emerging trend in students’ motivation explores reasons why students engage in achievement related behaviour. While previous research typifies students’ goal orientations into two dimensions of mastery and performance orientations in various other parts of the world, not much has been done in this regard in Nigeria and specifically in Bayelsa state to the best of the researcher’s knowledge. To this end, the study explores the achievement goal orientations of schooling adolescents in Bayelsa State. The sample of the study consists of 220 schooling adolescents drawn from four urban schools in the state. A modified form of the Patterns of Adaptive learning survey (PALS) questionnaire was used to elicit data. Results indicated that schooling adolescents in Bayelsa state are mastery as well as performance oriented. The students also did not differ in goal orientations by gender. The implications of this for sustainable development were highlighted.

Keywords: achievement goals, goal orientations, schooling adolescents, sustainable development

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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: Theresa Bacon-Baguley, Martina Reinhold

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Introduction: The purpose of this paper is to discuss the importance of both formative and summative evaluation of a Physician Assistant (PA) program with a distant campus delivered through Interactive Television (ITV) to assure equity of educational experiences. Methodology: A needs assessment utilizing a case-control design determined the need and interest in expanding the existing PA program to northern Michigan. A federal grant was written and funded, which supported the hiring of two full-time faculty members and support staff at the distant site. The strengths and weaknesses of delivering a program through ITV were evaluated using weekly formative evaluation, and bi-semester summative evaluation. Formative evaluation involved discussion of lecture content to be delivered, special ITV needs, orientation of new lecturers to the system, student concerns, support staff updates, and scheduling of student/faculty traveling between the two campuses. The summative evaluation, designed from a literature review of barriers to ITV, included 19 statements designed to evaluate the following items: quality of technology (audio, video, etc.), confidence in the ITV system, quality of instruction and instructor interaction between the two locations, and availability of resources at each location. In addition, students were given the opportunity to write qualitative remarks for each course delivered between the two locations. This summative evaluation was given to all students at mid-semester and at the end of the semester. The goal of the summative evaluation was to have 80% or greater of the students respond favorably (‘Very Good’ or ‘Good’) to each of the 19 statements. Results: Prior to the start of the first cohort at the distant campus, the technology was tested. During this time period, the formative evaluations identified key components needing modification, which were rapidly addressed: ability to record lectures, lighting, sound, and content delivery. When the mid-semester summative survey was given to the first cohort of students, 18 of the 19 statements in the summative evaluation met the goal of 80% or greater in the favorable category. When the summative evaluation statements were stratified by the two cohorts, the summative evaluation identified that students at the home location responded that they did not have adequate access to printers, and students at the expansion location responded that they did not have adequate access to library resources. These results allowed the program to address the deficiencies through contacting informational technology for additional printers, and to provide students with knowledge on how to access library resources. Conclusion: Successful expansion of programs to a distant site utilizing ITV technology requires extensive monitoring using both formative and summative evaluation. The formative evaluation allowed for quick identification of issues that could immediately be addressed, both at the planning and developing stage, as well as during implementation. Through use of the summative evaluation the program is able to monitor the success/ effectiveness of the expansion and identify specific needs of students at each location.

Keywords: assessment, distance learning, formative feedback, interactive television (ITV), student experience, summative feedback, support

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Authors: Tugba Altin

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In an era where the impacts of climate change resonate more pronouncedly than ever, communities globally grapple with events bearing both tangible and intangible ramifications. Situating this within the evolving landscapes of Psychological and Behavioral Sciences, this research probes the profound psychological and behavioral responses evoked by such events. The Lytton Creek Fire of 2021 epitomizes these challenges. While tangible destruction is immediate and evident, the intangible repercussions—emotional distress, disintegration of cultural landscapes, and disruptions in place attachment (PA)—require meticulous exploration. PA, emblematic of the emotional and cognitive affiliations individuals nurture with their environments, emerges as a cornerstone for comprehending how environmental cataclysms influence cultural identity and bonds to land. This study, harmonizing the core tenets of an interpretive phenomenological approach with a hermeneutic framework, underscores the pivotal nature of this attachment. It delves deep into the realm of individuals' experiences post the Lytton Creek Fire, unraveling the intricate dynamics of PA amidst such calamity. The study's methodology deviates from conventional paradigms. Instead of traditional interview techniques, it employs walking audio sessions and photo elicitation methods, granting participants the agency to immerse, re-experience, and vocalize their sentiments in real-time. Such techniques shed light on spatial narratives post-trauma and capture the otherwise elusive emotional nuances, offering a visually rich representation of place-based experiences. Central to this research is the voice of the affected populace, whose lived experiences and testimonies form the nucleus of the inquiry. As they renegotiate their bonds with transformed environments, their narratives reveal the indispensable role of cultural landscapes in forging place-based identities. Such revelations accentuate the necessity of integrating both tangible and intangible trauma facets into community recovery strategies, ensuring they resonate more profoundly with affected individuals. Bridging the domains of environmental psychology and behavioral sciences, this research accentuates the intertwined nature of tangible restoration with the imperative of emotional and cultural recuperation post-environmental disasters. It advocates for adaptation initiatives that are rooted in the lived realities of the affected, emphasizing a holistic approach that recognizes the profundity of human connections to landscapes. This research advocates the interdisciplinary exchange of ideas and strategies in addressing post-disaster community recovery strategies. It not only enriches the climate change discourse by emphasizing the human facets of disasters but also reiterates the significance of an interdisciplinary approach, encompassing psychological and behavioral nuances, for fostering a comprehensive understanding of climate-induced traumas. Such a perspective is indispensable for shaping more informed, empathetic, and effective adaptation strategies.

Keywords: place attachment, community recovery, disaster response, restorative landscapes, sensory response, visual methodologies

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Authors: Julie Furst-Bowe

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Over the past decade, there has been significant growth in online courses and programs at all levels of education in the United States. This study explores the growth of online and blended (or hybrid) programs offered by the sixteen technical colleges in the Wisconsin Technical College System (WTCS). The WTCS provides education and training programs to more than 300,000 students each year in career clusters including agriculture, business, energy, information technology, healthcare, human services, manufacturing, and transportation. These programs range from short-term training programs that may lead to a certificate to two-year programs that lead to an associate degree. Students vary in age from high school students who are exploring career interests to employees who are seeking to gain additional skills or enter a new career. Because there is currently a shortage of skilled workers in nearly all sectors in the state of Wisconsin, it is critical that the WTCS is providing fully educated and trained graduates to fill workforce needs in a timely manner. For this study, information on online and blended programs for the past five years was collected from the WTCS, including types of programs, course and program enrollments, course completion rates, program completion rates, time to completion and graduate employment rates. The results of this study indicate that the number of online and blended courses and programs is continuing to increase each year. Online and blended programs are most commonly found in the business, human services, and information technology areas, and they are less commonly found in agriculture, healthcare, manufacturing, and transportation programs. Overall, course and program completion rates were higher for blended programs when compared to fully online programs. Students preferred the blended programs over the fully online programs. Overall, graduates were placed into related jobs at a rate of approximately 90 percent, although there was some variation in graduate placement rates by programs and by colleges. Differences in graduate employment rate appeared to be based on geography and sector as employers did not distinguish between graduates who had completed their programs via traditional, blended or fully online instruction. Recommendations include further exploration as to the reasons that blended courses and programs appear to be more effective than fully online courses and programs. It is also recommended that those program areas that are not using blended or online delivery methods, including agriculture, health, manufacturing and transportation, explore the use of these methods to make their courses and programs more accessible to students, particularly working adults. In some instances, colleges were partnering with specific companies to ensure that groups of employees were completing online coursework leading to a certificate or a degree. Those partnerships are to be encouraged in order for the state to continue to improve the skills of its workforce. Finally, it is recommended that specific colleges specialize in the delivery of specific programs using online technology since it is not bound by geographic considerations. This approach would take advantage of the strengths of the individual colleges and avoid unnecessary duplication.

Keywords: career and technical education, online learning, skills shortage, technical colleges

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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: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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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: Mukul Sharma, Madhusmita Das, Sundeep Chaitanya Vedithi

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Leprosy is a chronic human disease caused by Mycobacterium leprae, that cannot be cultured in vitro. Though treatable with multidrug therapy (MDT), recently, bacteria reported resistance to multiple antibiotics. Targeting DNA replication and repair pathways can serve as the foundation of developing new anti-leprosy drugs. Due to the absence of an axenic culture medium for the propagation of M. leprae, studying cellular processes, especially those belonging to DNA repair pathways, is challenging. Genomic understanding of M. Leprae harbors several protein-coding genes with no previously assigned function known as 'hypothetical proteins'. Here, we report identification and expression of known and hypothetical DNA repair genes from a human skin biopsy and mouse footpads that are involved in base excision repair, direct reversal repair, and SOS response. Initially, a bioinformatics approach was employed based on sequence similarity, identification of known protein domains to screen the hypothetical proteins in the genome of M. leprae, that are potentially related to DNA repair mechanisms. Before testing on clinical samples, pure stocks of bacterial reference DNA of M. leprae (NHDP63 strain) was used to construct standard graphs to validate and identify lower detection limit in the qPCR experiments. Primers were designed to amplify the respective transcripts, and PCR products of the predicted size were obtained. Later, excisional skin biopsies of newly diagnosed untreated, treated, and drug resistance leprosy cases from SIHR & LC hospital, Vellore, India were taken for the extraction of RNA. To determine the presence of the predicted transcripts, cDNA was generated from M. leprae mRNA isolated from clinically confirmed leprosy skin biopsy specimen across all the study groups. Melting curve analysis was performed to determine the integrity of the amplification and to rule out primer‑dimer formation. The Ct values obtained from qPCR were fitted to standard curve to determine transcript copy number. Same procedure was applied for M. leprae extracted after processing a footpad of nude mice of drug sensitive and drug resistant strains. 16S rRNA was used as positive control. Of all the 16 genes involved in BER, DR, and SOS, differential expression pattern of the genes was observed in terms of Ct values when compared to human samples; this was because of the different host and its immune response. However, no drastic variation in gene expression levels was observed in human samples except the nth gene. The higher expression of nth gene could be because of the mutations that may be associated with sequence diversity and drug resistance which suggests an important role in the repair mechanism and remains to be explored. In both human and mouse samples, SOS system – lexA and RecA, and BER genes AlkB and Ogt were expressing efficiently to deal with possible DNA damage. Together, the results of the present study suggest that DNA repair genes are constitutively expressed and may provide a reference for molecular diagnosis, therapeutic target selection, determination of treatment and prognostic judgment in M. leprae pathogenesis.

Keywords: DNA repair, human biopsy, hypothetical proteins, mouse footpads, Mycobacterium leprae, qPCR

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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

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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

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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: 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: Elisabetta Cianfanelli, Maria Claudia Coppola, Margherita Tufarelli

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Design practices throughout history return a critical understanding of society since they always conveyed values and meanings aimed at (re)framing reality by acting in everyday life: here, design gains cultural and normative character, since its artifacts, services, and environments hold the power to intercept, influence and inspire thoughts, behaviors, and relationships. In this sense, design can be persuasive, engaging in the production of worlds and, as such, acting in the space between poietics and politics so that chasing preferable futures and their aesthetic strategies becomes a matter full of political responsibility. This resonates with contemporary landscapes of radical interdependencies challenging designers to focus on complex socio-technical systems and to better support values such as equality and justice for both humans and nonhumans. In fact, it is in times of crisis and structural uncertainty that designers turn into visionaries at the service of society, envisioning scenarios and dwelling in the territories of imagination to conceive new fictions and frictions to be added to the thickness of the real. Here, design’s main tasks are to develop options, to increase the variety of choices, to cultivate its role as scout, jester, agent provocateur for the public, so that design for transformation emerges, making an explicit commitment to society, furthering structural change in a proactive and synergic manner. However, the exploration of possible futures is both a trap and a trampoline because, although it embodies a radical research tool, it raises various challenges when the design process goes further in the translation of such vision into an artefact - whether tangible or intangible -, through which it should deliver that bit of future into everyday experience. Today designers are making up new tools and practices to tackle current wicked challenges, combining their approaches with other disciplinary domains: futuring through design, thus, rises from research strands like speculative design, design fiction, and critical design, where the blending of design approaches and futures thinking brings an action-oriented and product-based approach to strategic insights. The contribution positions at the intersection of those approaches, aiming at discussing design’s tools of inquiry through which it is possible to grasp the agency of imagined futures into present time. Since futures are not remote, they actively participate in creating path-dependent decisions, crystallized into designed artifacts par excellence, prototypes, and their conceptual other, provotypes: with both being unfinished and multifaceted, the first ones are effective in reiterating solutions to problems already framed, while the second ones prove to be useful when the goal is to explore and break boundaries, bringing closer preferable futures. By focusing on some provotypes throughout history which challenged markets and, above all, social and cultural structures, the contribution’s final aim is understanding the knowledge produced by provotypes, understood as design spaces where designs’s humanistic side might help developing a deeper sensibility about uncertainty and, most of all, the unfinished feature of societal artifacts, whose experimentation would leave marks and traces to build up f(r)ictions as vital sparks of plurality and collective life.

Keywords: speculative design, provotypes, design knowledge, political theory

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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

Procedia PDF Downloads 406