Search results for: learning through movement

Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Vahid Bayrami Rad

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In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

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Authors: Lee Bih Ni, Kiu Su Na

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This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.

Keywords: a second language, Chinese language teaching, immersion teaching, instructional strategies

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Authors: Leah Plocharczyk, Matthew Conner

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This paper analyzes the relatively new trend of PSE programs which seek to provide education, vocational training, and a college experience to individuals with an intellectual and developmental disability (IDD). Specifically, the paper examines the degree of interaction between PSE programs and the libraries of their college campuses. Using ThinkCollege, a clearinghouse and advocate for PSE programs, the researchers identified 293 programs throughout the country. These were all contacted with an email survey asking them about the nature of their involvement, if any, with the academic libraries on their campus. Where indicated by the responses, the libraries of PSE programs were contacted for additional information about their programming. Responses to the survey questions were tabulated and analyzed quantitatively. Written comments were analyzed for themes which were then tabulated. This paper presents the results of this study. They show obvious preferences for library programming, such as group formal instruction, individual liaisons, embedded reference, and various instructional designs. These are discussed in terms of special education principles of mainstreaming, level of restriction, training demands and cost effectiveness. The work serves as a foundation for best practices that can advance the field.

Keywords: disability studies, instructional design, universal design for learning, assessment methodology

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Douglas Shabe

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The world of the performing musician is one of high pressure that comes from the expected high standards they have to live up to and that they expect from themselves. The pressure that musicians put themselves under can manifest itself in physical problems such as focal dystonia. Knowledge of the contributing factors and potential rehabilitation strategies cannot only give players hope for recovery but also the information to prevent it from happening in the first place. This dissertation presents a multiple case study of two performing brass musicians who developed focal dystonia of the embouchure, also known as embouchure dystonia, combined with an autoethnography of the author’s experience of battling embouchure dystonia and our attempts at recovery. Extensive research into the current state of focal dystonia research was done to establish a base of knowledge. That knowledge was used to develop interview questions for the two participants and interpret the findings of the qualitative data collected. The research knowledge, as well as the qualitative data from the case studies, was also used to interpret the author’s experience. The author determined that behavioral, environmental, and psychological factors were of prime importance in the subjects’ development of focal dystonia and that modifications of those factors are essential for the best chance at recovery.

Keywords: focal dystonia, embouchure dystonia, music teaching and learning, music education

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Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno, Venice Cristine Dangaran

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The present study determines whether there will be differences in the self-regulation dispositions that learners utilize when writing different types of composition. There were 7 self-regulation factors that were used to develop a scale in this study such as memory strategy, goal setting, self-evaluation, seeking assistance, learning responsibility, environmental structuring, and organizing. The scale was made specific for writing a composition. The researcher-made scale was administered to 150 participants who all came from a university in the Philippines. The participants were asked to write two compositions namely opinion essay and research introduction/review of related literature. The zero-order correlation revealed that all the factors of self-regulation are correlated with one another. However, only seeking assistance and self-evaluation are correlated with opinion essay and technical writing is not correlated to any of the self-regulation factors. However, when path analysis was used, it was shown that seeking assistance can predict opinion essay scores whereas memory strategy, self-evaluation, and organizing can predict technical writing scores.

Keywords: opinion essay, self-regulation, technical writing, writing skills

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Authors: Sakapas Saengchai, Vilasinee Jintalikhitdee, Mathinee Khongsatid, Nattapol Pourprasert

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This paper studied the participation of people of the five villages of Bang Nang Li Community in Ampawa District, Samut Songkram Province, in designing community planning. The population was 2,755 villagers from the 5 villages with 349 people sampled. The level of involvement was measured by using Likert Five Scale for: preparing readiness of local people in the community, providing information for community and self analysis and learning, designing goals and directions for community development, designing strategic plans for community projects, and operating according to the plans. All process items reported a medium level of involvement except the item of preparing readiness for local people that presented the highest mean score. A test of a correlation between personal factors and level of involvement in designing the community planning unveiled no correlation between gender, age and career. Contrarily, the findings revealed that the villagers’ educational level and community membership status had a correlation with their level of involvement in designing the community planning.

Keywords: community development, community planning, people participation, educational level

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Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, A. Lamadrid Álvarez, A. Pastrana Palma, H. F. Valencia Pérez, M. Vivanco Vargas

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This work proposes a Cooperation-Competitive (Coopetitive) approach that allows coordinated work among the Secretary of Public Education (SEP), the Autonomous University of Querétaro (UAQ) and government funds from National Council for Science and Technology (CONACYT) or some other international organizations. To work on an overall knowledge transfer strategy with e-learning over the Cloud, where experts in junior high and high school education, working in multidisciplinary teams, perform analysis, evaluation, design, production, validation and knowledge transfer at large scale using a Cloud Computing platform. Allowing teachers and students to have all the information required to ensure a homologated nationally knowledge of topics such as mathematics, statistics, chemistry, history, ethics, civism, etc. This work will start with a pilot test in Spanish and initially in two regional dialects Otomí and Náhuatl. Otomí has more than 285,000 speaking indigenes in Queretaro and Mexico´s central region. Náhuatl is number one indigenous dialect spoken in Mexico with more than 1,550,000 indigenes. The phase one of the project takes into account negotiations with indigenous tribes from different regions, and the Information and Communication technologies to deliver the knowledge to the indigenous schools in their native dialect. The methodology includes the following main milestones: Identification of the indigenous areas where Otomí and Náhuatl are the spoken dialects, research with the SEP the location of actual indigenous schools, analysis and inventory or current schools conditions, negotiation with tribe chiefs, analysis of the technological communication requirements to reach the indigenous communities, identification and inventory of local teachers technology knowledge, selection of a pilot topic, analysis of actual student competence with traditional education system, identification of local translators, design of the e-learning platform, design of the multimedia resources and storage strategy for “Cloud Computing”, translation of the topic to both dialects, Indigenous teachers training, pilot test, course release, project follow up, analysis of student requirements for the new technological platform, definition of a new and improved proposal with greater reach in topics and regions. Importance of phase one of the project is multiple, it includes the proposal of a working technological scheme, focusing in the cultural impact in Mexico so that indigenous tribes can improve their knowledge about new forms of crop improvement, home storage technologies, proven home remedies for common diseases, ways of preparing foods containing major nutrients, disclose strengths and weaknesses of each region, communicating through cloud computing platforms offering regional products and opening communication spaces for inter-indigenous cultural exchange.

Keywords: Mexicans indigenous tribes, education, knowledge transfer, cloud computing, otomi, Náhuatl, language

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Authors: Verónica Díaz Quezada

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The importance given to the development of the problem solving skill and the requirement to solve problems framed in mathematical or real life contexts, in practice, they are not evidence in relation to the teaching of proportional variations. This qualitative and descriptive study aims to (1) to improve problem solving ability of high school students in Chile, (ii) to elaborate and describe a didactic intervention strategy based on learning situations in proportional variations, focused on solving types of routine problems of various contexts and non-routine problems. For this purpose, participant observation was conducted, test of mathematics problems and an opinion questionnaire to thirty-six high school students. Through the results, the highest academic performance is evidenced in the routine problems of purely mathematical context, realistic, fantasy context, and non-routine problems, except in the routine problems of real context and compound proportionality problems. The results highlight the need to consider in the curriculum different types of problems in the teaching of mathematics that relate the discipline to everyday life situations

Keywords: algebra, high school, proportion variations, nonroutine problem solving, routine problem solving

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Authors: B. Alajmi, L. Marouf, A. S. Chaudhry

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In recent years, increasing emphasis has been placed upon issues concerning the evaluation of health care. In this regard, knowledge management has also been considered an important component of the evaluation process. KM facilitates the transfer of existing knowledge or the development of new knowledge among healthcare staff and patients. This research aimed to examine how hospitals in Kuwait employ knowledge management practices, including capturing, sharing, and generating, and the perceived impact of KM practices on performance of hospitals in Kuwait. Through adopting a quantitative survey method with 277 sample of doctors, the study found that in terms of the three major knowledge management practices – knowledge capturing, sharing, and generating – the adoption of KM practices were rated very low in the sampled hospitals in Kuwait. Hospitals paid little attention to the main activities that support the transfer of expertise among doctors in hospitals. However, as predicted by previous studies, knowledge management practices were perceived to have an impact on hospitals’ performance. Through knowledge capturing, sharing, and generating, hospitals could improve the services they provide through documenting best practices, transforming their hospitals into learning organizations in which lessons learned are captured, stored, and made available for others to learn from.

Keywords: knowledge management, hospitals, knowledge management practices, knowledge management tools, performance

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Authors: Hamad Aldosari

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The purpose of this study is to investigate the status of sexism, or gender discrepancies, in current pedagogical and curricular practices in EFL learning higher education settings. Qualitative and quantitative analyses of both course contents and pedagogies in Saudi higher education institutions are to be discussed with reference to female/male topic presentation in dialogs and reading passages, sex-based activity types, stereotyped sex roles and the masculine generic conceptions of male superiority subliminally related in EFL curriculum and pedagogical practices, as well as the causes and effects of segregated language education practices in Saudi Arabia from a holistic vantage point of analysis. Analysis findings show that language educational practices including educational settings and segregation are gender-biased in attitude, but with regard to curriculum, sexism has not been traced. Findings also show that sexism is rampant due to socio-cultural aspects of language education rather than to religious reasons: a finding that seems to mirror the institutionalized unfair sex discrimination to the disadvantage of women in the Arabian societies at large.

Keywords: genderism, sex segregation, Saudi Arabia, EFL

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Authors: Poom Thiparapkul, Tanat Jiravansirikul, Pakpoom Thongsari

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This study explores the design of electric vehicle (EV) dashboards with a focus on user interaction. Findings from a Thai sample reveal a preference for physical buttons over touch interfaces due to their immediate feedback. Touchscreens lack this assurance, leading to potential uncertainty. Users' smartphone experiences create a learning curve that doesn't translate well to in-car touch systems. Gender-wise, females exhibit slightly longer decision times. Designing EV dashboards should consider these factors, prioritizing user experience while avoiding overreliance on smartphone principles. A successful example is Subaru XV's design, which calculates screen angles and button positions for targeted users. In summary, EV dashboards should be intuitive, minimize touch dependency, and accommodate user habits. Balancing modernity with functionality can enhance driving experiences while ensuring safety. A user-centered approach, acknowledging gender differences, will yield efficient and safe driving environments.

Keywords: user experience design, user experience, electric vehicle, dashboard design, Thailand driver.

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Authors: Khaled M. Alhawiti

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Reading capability is a major segment of language competency. On the other hand, discovering topical writings at a fitting level for outside and second language learners is a test for educators. We address this issue utilizing natural language preparing innovation to survey reading level and streamline content. In the connection of outside and second-language learning, existing measures of reading level are not appropriate to this errand. Related work has demonstrated the profit of utilizing measurable language preparing procedures; we expand these thoughts and incorporate other potential peculiarities to measure intelligibility. In the first piece of this examination, we join characteristics from measurable language models, customary reading level measures and other language preparing apparatuses to deliver a finer technique for recognizing reading level. We examine the execution of human annotators and assess results for our finders concerning human appraisals. A key commitment is that our identifiers are trainable; with preparing and test information from the same space, our finders beat more general reading level instruments (Flesch-Kincaid and Lexile). Trainability will permit execution to be tuned to address the needs of specific gatherings or understudies.

Keywords: natural language processing, trainability, syntactic simplification tools, education

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Authors: Mohammad Idrees Yusofzai, Hirobata Yasuhiro, Matsuo Kojiro

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Kabul is the capital of Afghanistan. It is the focal point of educational, industrial, etc. of Afghanistan. Additionally, the population of Kabul has grown recently and will increase because of return of refugees and shifting of people from other province to Kabul city. However, this increase in population, the issues of urban congestion and other related problems of urban transportation in Kabul city arises. One of the problems is public transport (large buses) service and needs to be modified and enhanced especially large bus routes that are operating in each zone of the 22 zone of Kabul City. To achieve the above mentioned goal of improving public transport, Spatial Accessibility Analysis is one of the important attributes to assess the effectiveness of transportation system and urban transport policy of a city, because accessibility indicator as an alternative tool to support public policy that aims the reinforcement of sustainable urban space. The case study of this research compares the present model (present bus route) and the modified model of public transport. Furthermore, present model, the bus routes in most of the zones are active, however, with having low frequency and unpublished schedule, and accessibility result is analyzed in four cases, based on the variables of accessibility. Whereas in modified model all zones in Kabul is taken into consideration with having specified origin and high frequency. Indeed the number of frequencies is kept high; however, this number is based on the number of buses Millie Bus Enterprise Authority (MBEA) owns. The same approach of cases is applied in modified model to figure out the best accessibility for the modified model. Indeed, the modified model is having a positive impact in congestion level in Kabul city. Besides, analyses of person trip and trip distribution have been also analyzed because how people move in the study area by each mode of transportation. So, the general aims of this research are to assess the present movement of people, identify zones in need of public transport and assess equity level of accessibility in Kabul city. The framework of methodology used in this research is based on gravity analysis model of accessibility; besides, generalized cost (time) of travel and travel mode is calculated. The main data come from person trip survey, socio-economic characteristics, demographic data by Japan International Cooperation Agency, 2008, study of Kabul city and also from the previous researches on travel pattern and the remaining data regarding present bus line and routes have been from MBEA. In conclusion, this research explores zones where public transport accessibility level is high and where it is low. It was found that both models the downtown area or central zones of Kabul city is having high level accessibility. Besides, the present model is the most unfavorable compared with the modified model based on the accessibility analysis.

Keywords: accessibility, bus generalized cost, gravity model, public transportation network

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Authors: Joao Victor Borges Dos Santos, Thomas Richard, Yevhen Kovalyshen

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Down-the-hole (DTH) percussive drilling is an excavation method that is widely used in the mining industry due to its high efficiency in fragmenting hard rock formations. A DTH hammer system consists of a fluid driven (air or water) piston and a drill bit; the reciprocating movement of the piston transmits its kinetic energy to the drill bit by means of stress waves that propagate through the drill bit towards the rock formation. In the literature of percussive drilling, the existence of an optimum drilling state (Sweet Spot) is reported in some laboratory and field experimental studies. An optimum rate of penetration is achieved for a specific range of axial thrust (or weight-on-bit) beyond which the rate of penetration decreases. Several authors advance different explanations as possible root causes to the occurrence of the Sweet Spot, but a universal explanation or consensus does not exist yet. The experimental investigation in this work was initiated with drilling experiments conducted at a mining site. A full-scale drilling rig (equipped with a DTH hammer system) was instrumented with high precision sensors sampled at a very high sampling rate (kHz). Data was collected while two boreholes were being excavated, an in depth analysis of the recorded data confirmed that an optimum performance can be achieved for specific ranges of input thrust (weight-on-bit). The high sampling rate allowed to identify the bit penetration at each single impact (of the piston on the drill bit) as well as the impact frequency. These measurements provide a direct method to identify when the hammer does not fire, and drilling occurs without percussion, and the bit propagate the borehole by shearing the rock. The second stage of the experimental investigation was conducted in a laboratory environment with a custom-built equipment dubbed Woody. Woody allows the drilling of shallow holes few centimetres deep by successive discrete impacts from a piston. After each individual impact, the bit angular position is incremented by a fixed amount, the piston is moved back to its initial position at the top of the barrel, and the air pressure and thrust are set back to their pre-set values. The goal is to explore whether the observed optimum drilling state stems from the interaction between the drill bit and the rock (during impact) or governed by the overall system dynamics (between impacts). The experiments were conducted on samples of Calca Red, with a drill bit of 74 millimetres (outside diameter) and with weight-on-bit ranging from 0.3 kN to 3.7 kN. Results show that under the same piston impact energy and constant angular displacement of 15 degrees between impact, the average drill bit rate of penetration is independent of the weight-on-bit, which suggests that the sweet spot is not caused by intrinsic properties of the bit-rock interface.

Keywords: optimum drilling state, experimental investigation, field experiments, laboratory experiments, down-the-hole percussive drilling

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Authors: Promise Ekpo Osaine, Daniel Melesse

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Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.

Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score

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Authors: Engku Haliza Engku Ibrahim, Isarji Sarudin, Ainon Jariah Muhamad

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It is generally agreed that many factors contribute to one’s reading comprehension and there is consensus that vocabulary size one of the main factors. This study explores the relationship between second language learners’ vocabulary size and their reading comprehension scores. 130 Malay pre-university students of a public university participated in this study. They were students of an intensive English language programme doing preparatory English courses to pursue bachelors degree in English. A quantitative research method was employed based on the Vocabulary Levels Test by Nation (1990) and the reading comprehension score of the in-house English Proficiency Test. A review of the literature indicates that a somewhat positive correlation is to be expected though findings of this study can only be explicated once the final analysis has been carried out. This is an ongoing study and it is anticipated that results of this research will be finalized in the near future. The findings will help provide beneficial implications for the prediction of reading comprehension performance. It also has implications for the teaching of vocabulary in the ESL context. A better understanding of the relationship between vocabulary size and reading comprehension scores will enhance teachers’ and students’ awareness of the importance of vocabulary acquisition in the L2 classroom.

Keywords: vocabulary size, vocabulary learning, reading comprehension, ESL

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Authors: Muhammad Akram, Qamar Naseem, Imtiaz Ahmad

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The purpose of this study was to correlate students’ perceptions of teacher effectiveness with their academic achievement in English and Mathematics at the secondary level (grade 9th) based on five national professional standards for teacher evaluation in Pakistan (subject matter knowledge, instructional planning and strategies, assessment, learning environment, effective communication. A Students’ Perceptions of Teacher Effectiveness Questionnaire (SPTEQ) was developed by the researchers to collect data from 2009 students from forty public girls and boys high/ higher secondary schools in district Khanewal, Pakistan. The overall reliability of the SPTEQ was α=.86. The study found a significant positive relationship among all the five factors of teacher effectiveness construct. The study also showed significant, positive relationship between teacher effectiveness factors and students’ achievement in English and mathematics. No significant differences were found between male and female students’ perceptions about their English teacher effectiveness. The implications include students’ personal attachments with their teachers that might convince them to overrate their teachers.

Keywords: communication, students’ achievement, teacher effectiveness, teaching strategies, teaching strategies

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Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

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In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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Authors: Iván García-Magariño, Javier Bravo-Agapito, Marta López-Fernández

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Online judges have proven their utility in partial auto-evaluation of programming short exercises in the last decades. UnitJudge online judge has the advantage of facilitating the evaluation of separate units to provide more segregate and meaningful feedback to students in complex exercises and practices. This paper discusses the use of UnitUdge in advanced Java object-oriented programming exercises and web development practices. This later usage has been proposed by means of the Selenium Java library and classes to provide the web address. Consequently, UnitJudge is an online judge system that can be applied in several subjects, and therefore, many other students would take advantage of self-testing their exercises. This paper presents the experiments with a Java programming exercise for learning Java object-oriented classes with a generic type. Considering 10 students who voluntarily used UnitJudge, 80% successfully learned this concept, passing the judge exercise with correct results.

Keywords: online judges, programming skills, computer science education, auto-evaluation

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Authors: Samanta Kietytė

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The object of this study is the verbal derivatives stemming from the Lithuanian prefix per-. The prefix under examination can be classified as prepositional, having descended from the preposition per, thereby sharing the same prototypical meaning – denoting movement OVER. These frequently co-occur within sentences (1). The aim of this paper is to conduct a semantic analysis of the prefix per- and to propose a possible radial network of its meanings. In essence, the aim is to identify the interrelationships existing between its meanings. 1) Jis peršoko per tvorą/ 3SG.NOM.M jump.PST.3 over fence.ACC.SG. /ʻHe jumped over the fenceʼ. The foundation of this work lies in the methodological and theoretical framework of cognitive linguistics. The prototypical meaning of prefixes consistently embodies spatial dimensions that can be described through image schemas. This entails the identification of the trajectory, the landmark, and the relation between them in the situation described by the prefixed verb. The meanings of linguistic units are not perceived as arbitrary, but rather, they are interconnected through semantic motivation. According to this perspective, a singular meaning within linguistic units is considered as prototypical, while additional meanings are descended (not necessarily directly) from it. For example, one of the per- meanings TRANSFER (2) is derived from the prototypical meaning OVER. 2) Prašau persiųsti vadovo laišką man./ Ask.PRS.1 forward.INF manager.GEN.SG email.ACC.SG 1.SG.DAT/ ʻPlease forward the manager‘s email to meʼ. Certain semantic relations are explained by the conceptual metaphor and metonymy theory. For instances, when prefixed verb has a meaning WIN (3) it is related to the prototypical meaning. In this case, the prefixed verb describes situations of winning in various ways. In the prototypical meaning, the trajector moves higher than the landmark, and winning is metaphorically perceived as being higher. 3) Sūnus peraugo tėvą./ Son.NOM.SG outgrow.PST.3 father.ACC.SG/ ʻThe son has outgrown the fatherʼ. The data utilized for this study was collected from the 2014 grammatically annotated text "Lithuanian Web (LithuanianWaC v2)", consisting of 63,645,700 words. Given that the corpus is grammatically lemmatized, the list of the 793 items was obtained using the wordlist function and specifying that verbs starting with per were searched. The list included not only prefixed verbs but also other verbs whose roots have the same letter sequences as prefixes. Also, words with misspellings, without diacritical marks, and words listed for lemmatization errors were rejected, and a total of 475 derivatives were left for further analysis. The semantic analysis revealed that there are 12 distinct meanings of the prefix per-. The spatial meanings were extracted by determining what a trajector is, what a landmark is, and what the relation between them is. The connection between non-spatial meanings and spatial ones occurs through semantic motivation established by identifying elements that correspond to the trajector and landmark. The analysis reveals that there are no strict boundaries among these meanings, instead showing a continuum that encompasses a central core and a peripheral association with their internal structure, i.e., some derivatives are more prototypical of a particular meaning than others.

Keywords: word-formation, cognitive semantics, metaphor, radial networks, prototype theory, prefix

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Authors: Shaurya Chauhan, Sagar Gupta

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Prominent urbanizing centres across the globe like Delhi, Dhaka, or Manila have exhibited that development often faces a challenge in bridging the gap among the top-down collective requirements of the city and the bottom-up individual aspirations of the ever-diversifying population. When this exclusion is intertwined with rapid urbanization and diversifying urban demography: unplanned sprawl, poor planning, and low-density development emerge as automated responses. In parallel, new ideas and methods of densification and public participation are being widely adopted as sustainable alternatives for the future of urban development. This research advocates a collaborative design method for future development: one that allows rapid application with its prototypical nature and an inclusive approach with mediation between the 'user' and the 'urban', purely with the use of empirical tools. Building upon the concepts and principles of 'open-sourcing' in design, the research establishes a design framework that serves the current user requirements while allowing for future citizen-driven modifications. This is synthesized as a 3-tiered model: user needs – design ideology – adaptive details. The research culminates into a context-responsive 'open source project development framework' (hereinafter, referred to as OSPDF) that can be used for on-ground field applications. To bring forward specifics, the research looks at a 300-acre redevelopment in the core of a rapidly urbanizing city as a case encompassing extreme physical, demographic, and economic diversity. The suggestive measures also integrate the region’s cultural identity and social character with the diverse citizen aspirations, using architecture and urban design tools, and references from recognized literature. This framework, based on a vision – feedback – execution loop, is used for hypothetical development at the five prevalent scales in design: master planning, urban design, architecture, tectonics, and modularity, in a chronological manner. At each of these scales, the possible approaches and avenues for open- sourcing are identified and validated, through hit-and-trial, and subsequently recorded. The research attempts to re-calibrate the architectural design process and make it more responsive and people-centric. Analytical tools such as Space, Event, and Movement by Bernard Tschumi and Five-Point Mental Map by Kevin Lynch, among others, are deep rooted in the research process. Over the five-part OSPDF, a two-part subsidiary process is also suggested after each cycle of application, for a continued appraisal and refinement of the framework and urban fabric with time. The research is an exploration – of the possibilities for an architect – to adopt the new role of a 'mediator' in development of the contemporary urbanity.

Keywords: open source, public participation, urbanization, urban development

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, Rebecca K. Rossi, Yanmin Yuan, Xianpei Li

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The fiscal growth of any country hinges on the prudent administration of water resources. The river Yamuna and Ganga are measured as the life line of India as it affords the needs for life to endure. Earth observation over remote sensing images permits the precise description and identification of ingredients on the superficial from space and airborne platforms. Multiple and heterogeneous image sources are accessible for the same geographical section; multispectral, hyperspectral, radar, multitemporal, and multiangular images. In this paper, a taxonomical learning of the fluvial geomorphological features of river Yamuna and Ganga over doon valley using color fusion of multispectral remote sensing images was performed. Experimental results exhibited that the segmentation based colorization technique stranded on pattern recognition, and color mapping fashioned more colorful and truthful colorized images for geomorphological feature extraction.

Keywords: color fusion, geomorphology, fluvial processes, multispectral images, pattern recognition

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Authors: Mandayachepa C. Nyando, Lauren Suchman, Innocencia Mtalimanja, Address Malata, Tamanda Jumbe, Martha Kamanga, Peter Waiswa

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Background: Subcutaneous depot medroxyprogesterone acetate (DMPA-SC) is a new innovation in contraceptive methods that allow users to inject themselves with a hormonal contraceptive in their own homes. Self-injection (SI) of DMPA-SC has the potential to improve the accessibility of family planning to women who want it and who are capable of injecting themselves. Malawi started implementing this new innovation in 2018. SI was incorporated into the DMPA-SC delivery strategy from its outset. Methodology: This study involved two districts in Malawi where DMPA-SC SI was rolled out: Mulanje and Ntchisi. We used a qualitative cross-sectional study design where 60 in-depth interviews were conducted with women of reproductive age group stratified as 15-45 age band. These included women who were SI users, non-users, and any woman who was on any contraceptive methods. The women participants were tape-recorded, and data were transcribed and then analysed using Dedoose software, where themes were categorised into mother and child themes. Results: Women perceived DMPA SC SI as uniquely private, convenient, and less painful when self-injected. In terms of privacy, women in Mulanje and Ntchisi especially appreciated that self-injecting allowed them to use covertly from partners. Some men do not allow their spouses to use modern contraceptive methods; hence women prefer to use them covertly. “… but I first reach out to men because the strongest power is answered by men (MJ015).” In addition, women reported that SI offers privacy from family/community and less contact with healthcare providers. These aspects of privacy were especially valued in areas where there is a high degree of mistrust around family planning and among those who feel judged or antagonized purchasing contraception, such as young unmarried women. Women also valued the convenience SI provided in terms of their ability to save time by injecting themselves at home rather than visiting a healthcare provider and having more reliable access to contraception, particularly in the face of stockouts. SI allows for stocking up on doses to accommodate shifting work schedules in case of future stockouts or hard times, such as the period of COVID-19, where there was a limitation in the movement of the people. Conclusion: Our findings suggest that SI may meet the needs of many women in Malawi as long as the barriers are eliminated. The barriers women mentioned include fear of self-inject and proper storage of the DMPA SC SI, and these barriers can be eliminated by proper training. The findings also set the scene for policy revision and direction at a national level and integrate the approach with national family planning strategies in Malawi. Findings provide insights that may guide future implementation strategies, strengthen non-clinic family planning access programs and stimulate continued research.

Keywords: family planning, Malawi, Sayana press, self-injection

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Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

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The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

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Authors: Amanda Burrell, Tonia Gary, David Wright, Kumara Ward

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This paper explores the concept of academic identity as it relates to the lecture, in particular, the digitized lecture delivered to a camera, in the absence of a student audience. Many academics have the performance aspect of the role thrust upon them with little or no training. For the purpose of this study, we look at the performance of the academic identity and examine tailored film presence coaching for its contributions toward academic identity, specifically in relation to feelings of self-confidence and diminishment of discomfort or stage fright. The case is articulated through the lens of scholar-practitioners, using expert facilitated participatory action research. It demonstrates in our sample of experienced academics, all reported some feelings of uncertainty about presenting lectures to camera prior to coaching. We share how power poses and reframing fear, produced improvements in the ease and competency of all participants. We share exactly how this insight could be adapted for self-coaching by any academic when called to present to a camera and consider the relationship between this and academic identity.

Keywords: academic identity, digitized lecture, embodied learning, performance coaching

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Authors: Tinnaphop Sinsomboonthong

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The hashtag, #LoveWins, has been widely used for celebrating the victory of the LGBTQ movement since June 2015 when the US Supreme Court enacted the rights of same-sex marriage. Nowadays, the hashtag is generally used among active social media users in many countries, including Thailand. Amidst the political conflict between advocates of the junta-backed legislation related to same-sex marriage laws, known as ‘Thailand’s Civil Partnership Draft Bills,’ and its detractors, the hashtag becomes crucial for Thailand’s 2019 national election season and shortly afterward as it was one of the most crucial parts of a political campaign to rebrand many political parties’ image, create an LGBT-friendly atmosphere and neutralize the bi-polarized politics of the law. The use of the hashtag is, therefore, not just an online entertainment but a politico-discursive tool, used by many actors for many purposes. Behind the confrontation between supporters and opposers of the law, the hashtag is used by both sides to highlight the Western-centric normativity of homosexual love, closely associated with Eurocentric modernity and heteronormativity. As an online ethnographical study, this paper aims to analyze how #LoveWins is used among Thai social media users in late 2018 to mid-2019 and how it is signified by Thai social media users during the Drafted-Bills period and the 2019 national election. A number of preliminary surveys of data on Twitter were conducted in December 2018 and, more intensely, in January 2019. Later, the data survey was officially conducted twice during February and April 2019, while the data collection was done during May-June 2019. Only public posts on Twitter that include the hashtag, #LoveWins, or any hashtags quoting ‘love’ and ‘wins’ are the main targets of this research. As a result of this, the use of the hashtag can be categorized into three levels, including banal decoration, homosexual love celebration, and colonial discourse on homosexual love. Particularly in the third type of the use of the hashtag, discourse analysis is applied to reveal that this hashtag is closely associated with the discourse of development and modernity as most of the descriptive posts demonstrate aspirations to become more ‘developed and modernized’ like many Western countries and Taiwan, the LGBT capital in Asia. Thus, calls for the ‘right to homosexual love’ and the ‘right to same-sex marriage’ in Thailand are shaped and formulated within the discursive linkage between modernity, development, and love. Also, the use of #LoveWins can be considered as a de-queering process of love as only particular types of gender identity, sexual orientation, and relationships that reflect Eurocentric modernity and heteronormativity are acceptable and advocated. Due to this, more inclusive queer loves should be supported rather than a mere essentialist-traditionalist homosexual love. Homonormativity must be deconstructed, and love must no longer be reserved for only one particular type of relationship that is standardized from/by the West. It must become more inclusive.

Keywords: #LoveWins, homosexual love, LGBT rights, same-sex marriage

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