Search results for: learning program

Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

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Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

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Authors: Jin-Hee Ahn, Seok-Hyeon Jeon, Young-Bin Lee, Min-Gyun Ha, Yu-Chan Hong

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Corrosion durability of steel bridges can be generally affected by atmospheric environments of bridge installation, since corrosion problem is related to environmental factors such as humidity, temperature, airborne salt, chemical components as SO₂, chlorides, etc. Thus, atmospheric environment condition should be measured to estimate corrosion condition of steel bridges as well as measurement of actual corrosion damage of structural members of steel bridge. Even in the same atmospheric environment, the corrosion environment may be different depending on the installation direction of structural members. In this study, therefore, atmospheric corrosion monitoring was conducted using atmospheric corrosion monitoring sensor, hygrometer, thermometer and airborne salt collection device to examine the corrosion durability of steel bridges. As a target steel bridge for corrosion durability monitoring, a cable-stayed bridge with truss steel members was selected. This cable-stayed bridge was located on the coast to connect the islands with the islands. Especially, atmospheric corrosion monitoring was carried out depending on structural direction of a cable-stayed bridge with truss type girders since it consists of structural members with various directions. For atmospheric corrosion monitoring, daily average electricity (corrosion current) was measured at each monitoring members to evaluate corrosion environments and corrosion level depending on structural members with various direction which have different corrosion environment in the same installed area. To compare corrosion durability connected with monitoring data depending on corrosion monitoring members, monitoring steel plate was additionally installed in same monitoring members. Monitoring steel plates of carbon steel was fabricated with dimension of 60mm width and 3mm thickness. And its surface was cleaned for removing rust on the surface by blasting, and its weight was measured before its installation on each structural members. After a 3 month exposure period on real atmospheric corrosion environment at bridge, surface condition of atmospheric corrosion monitoring sensors and monitoring steel plates were observed for corrosion damage. When severe deterioration of atmospheric corrosion monitoring sensors or corrosion damage of monitoring steel plates were found, they were replaced or collected. From 3month exposure tests in the actual steel bridge with various structural member with various direction, the rust on the surface of monitoring steel plate was found, and the difference in the corrosion rate was found depending on the direction of structural member from their visual inspection. And daily average electricity (corrosion current) was changed depending on the direction of structural member. However, it is difficult to identify the relative differences in corrosion durability of steel structural members using short-term monitoring results. After long exposure tests in this corrosion environments, it can be clearly evaluated the difference in corrosion durability depending on installed conditions of steel bridges. Acknowledgements: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03028755).

Keywords: corrosion, atmospheric environments, steel bridge, monitoring

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Authors: Akano Benedict Ubawuike

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This study investigated the effects of pre-laboratory discussion on physics students’ acquisition of science process skills. The study design was quasi-experimental and purposive sampling technique was applied in selecting two schools in Kontagora Town for the research based on the availability of a good physics laboratory. Intact classes already grouped by the school for the sake of small laboratory space and equipment, comprising Thirty (30) students, 15 for experimental group in School A and 15 for control in school B were the subjects for the research. The instrument used for data collection was the lesson prepared for pre – practical discussion and researcher made Science Process Skill Test (SPST ) and two (2) research questions, and two (2) research hypotheses were developed to guide the study. The data collected were analyzed using means and t-Test statistics at 0.05 level of significance. The study revealed that pre-laboratory discussion was found to be more efficacious in enhancing students’ acquisition of science process skills. It also revealed that gender, had no significant effect on students’ acquisition of science process skills. Based on the findings, it was recommended among others that teachers should encourage students to develop interest in practical activities by engaging them in pre-laboratory discussion and providing instructional materials that will challenge them to be actively involved during practical lessons. It is also recommended that Ministries of Education and professional organizations like Science Teachers' Association of Nigeria (STAN) should organize workshops, seminars and conferences for physics teachers and Physics concepts should be taught with practical activity so that the students will do science instead of learning about science.

Keywords: physics, laboratory, discussion, students, acquisition, science process skills

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Authors: Yi-Hsiu Lai

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The present study aimed to elucidate the lexical-semantic processing for Chinese as second language (CSL) learners. Twenty L1 speakers of Chinese and twenty CSL learners in Taiwan participated in a picture naming task and a category fluency task. Based on their Chinese proficiency levels, these CSL learners were further divided into two sub-groups: ten CSL learners of elementary Chinese proficiency level and ten CSL learners of intermediate Chinese proficiency level. Instruments for the naming task were sixty black-and-white pictures: thirty-five object pictures and twenty-five action pictures. Object pictures were divided into two categories: living objects and non-living objects. Action pictures were composed of two categories: action verbs and process verbs. As in the naming task, the category fluency task consisted of two semantic categories – objects (i.e., living and non-living objects) and actions (i.e., action and process verbs). Participants were asked to report as many items within a category as possible in one minute. Oral productions were tape-recorded and transcribed for further analysis. Both error types and error frequency were calculated. Statistical analysis was further conducted to examine these error types and frequency made by CSL learners. Additionally, category effects, pictorial effects and L2 proficiency were discussed. Findings in the present study helped characterize the lexical-semantic process of Chinese naming in CSL learners of different Chinese proficiency levels and made contributions to Chinese vocabulary teaching and learning in the future.

Keywords: lexical-semantic processing, Mandarin Chinese, naming, category effects

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Authors: Alireza Barari, Ahmad Abdi

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Regular body trainings cause adaption in various system in body. One of the important effect of body training is its effect on immune system. It seems that cytokines usually release after long period exercises or some exercises which cause skeletal muscular damages. If some of the cytokines which cause responses such as inflammation of cells in skeletal muscles, with manipulating of training program, it can be avoided or limited from those exercises which induct cytokines release. Ginger plant is a kind of medicinal plants which is known as a anti inflammation plant. This plant is as most precedence medicinal plants in medicine science especially in inflammation cure. The aim of the present study was the effect of selected resistance training and consumption of ginger extract on IL-1α and TNFα untrained young women. The population includes young women interested in participating in the study with the average of 30±2 years old from Abbas Abad city among which 32 participants were chosen randomly and divided into 4 four groups, resistance training (R), resistance training and ginger consumption(RG), Ginger consumption(G)and Control group(C). The training groups performed circuit resistance training at the intensity of 65-75% one repeat maximum, 3 days a week for 6 weeks. Besides resistance training, subjects were given either ginseng (5 mg/kg per day) or placebo. Prior to and 48 hours after interventions body composition was measured and blood samples were taken in order to assess serum levels of IL-1α and TNFα. Plasma levels of cytokines were measured with commercially available ELISA Kits.IL-1α kit and TNFα kit were used in this research. To demonstrate the effectiveness of the independent variable and the comparison between groups, t-test and ANOVA were used. To determine differences between the groups, the Scheffe test was used that showed significant changes in any of the variables. we observed that circuit resistance training in R and RG groups can significant decreased in weight and body mass index in untrained females (p<0.05). The results showed a significant decreased in the mean level of IL-1α levels before and after the training period in G group (p=0.046) and RG group (p=0.022). Comparison between groups also showed there was significant difference between groups R-RG and RG-C. Intergroup comparison results showed that the mean levels of TNFα before and after the training in group G (p=0.044) and RG (p=0.037), significantly decreased. Comparison between groups also showed there was significant difference between groups R–RG , R-G ,RG-C and G-C. The research shows that circuit resistance training with reducing overload method results in systemic inflammation had significant effect on IL-1α levels and TNFα. Of course, Ginger can counteract the negative effects of resistance training exercise on immune function and stability of the mast cell membrane. Considerable evidence supported the anti-inflammatory properties of ginger for several constituents, especially gingerols, shogaols, paradols, and zingerones, through decreased cytokine gene TNF α and IL-1Α expression and inhibition of cyclooxygenase 1 and 2. These established biological actions suggest that ingested ginger could block the increase in IL-1α.

Keywords: resistance training, ginger, IL-1α , TNFα

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Authors: Uzma Rashid, Mommnah Asad

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As more and more people fall victim to the intolerance that has become a plague globally, academicians are faced with the herculean task of sowing the roots for more tolerant individuals. Being the multilayered task that it is, promoting an acceptance of diversity and pushing an agenda to push back hate requires efforts on multiple levels. Not only does the curriculum need to be in line with such goals, but teachers also need to be trained to cater to the sensitivities surrounding conversations of tolerance and diversity. In addition, institutional support needs to be there to provide conducive conditions for a diversity driven learning process to take place. In reality, teachers have to struggle with forwarding ideas about diversity and tolerance which do not sound particularly risky to be shared but given the current socio-political and religious milieu, can put the teacher in a difficult position and can make the task exponentially challenging. This paper is based on an auto-ethnographic account of teaching undergraduate and graduate courses at a private university in Pakistan. These courses were aimed at teaching tolerance to adult learners through classes focused on key notions pertaining to religion, culture, gender, and society. Authors’ classroom experiences with the students in these courses indicate a marked heightening of religious sensitivities that can potentially threaten a teacher’s life chances and become a hindrance in deep, meaningful conversations, thus lending a superficiality to the whole endeavor. The paper will discuss in detail the challenges that this teacher dealt with in the process, how those were addressed, and locate them in the larger picture of how tolerance can be materialized in current times in the universities in Pakistan and in similar contexts elsewhere.

Keywords: tolerance, diversity, gender, Pakistani Universities

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Authors: Fatemah Al-Baroud, Sudharani Shreenivas Kshatriya

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Kuwait Oil Company (KOC) is one of the companies for gas & oil production in Kuwait. The oil and gas industry is truly global; with operations conducted in every corner of the globe, the global community will rely heavily on oil and gas supplies. KOC has made many commitments to protect all due to KOC’s operations and operational releases. As per KOC’s strategy, the substantial increase in production activities will bring many challenges in managing various environmental hazards and stresses in the company. In order to handle those environmental challenges, the need of implementing effectively the health, safety, and environmental management system (HSEMS) is significant. And by implementing the HSEMS system properly, the environmental aspects of the activities, products, and services were identified, evaluated, and controlled in order to (i) Comply with local regulatory and other obligatory requirements; (ii) Comply with company policy and business requirements; and (iii) Reduce adverse environmental impact, including adverse impact to company reputation. Assessments for the Jurassic Production Facilities are being carried out as a part of the KOC HSEMS procedural requirement and monitoring the implementation of the relevant HSEMS procedures in the facilities. The assessments have been done by conducting series of theme audits using KOC’s audit protocol at JPFs. The objectives of the audits are to evaluate the compliance of the facilities towards the implementation of environmental procedures and the status of the KEPA requirement at all JPFs. The list of the facilities that were covered during the theme audit program are the following: (1) Jurassic Production Facility (JPF) – Sabriya (2) Jurassic Production Facility (JPF) – East Raudhatian (3) Jurassic Production Facility (JPF) – West Raudhatian (4)Early Production Facility (EPF 50). The auditing process comprehensively focuses on the application of KOC HSE MS procedures at JPFs and their ability to reduce the resultant negative impacts on the environment from the operations. Number of findings and observations were noted and highlighted in the audit reports and sent to all concerned controlling teams. The results of these audits indicated that the facilities, in general view, were in line with KOC HSE Procedures, and there were commitments in documenting all the HSE issues in the right records and plans. Further, implemented several control measures at JPFs that minimized/reduced the environmental impact, such as SRU were installed for sulphur recovery. Future scope and monitoring audit after a sufficient period of time will be carried out in conjunction with the controlling teams in order to verify the current status of the recommendations and evaluate the contractors' performance towards the required actions in preserving the environment.

Keywords: assessment of the environmental compliance, environmental and social impact assessment, kuwait environment public authority regulations, health, safety and environment management procedures, jurassic production facilities

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Authors: Fernando Cabo Aseguinolaza, Víctor Bouzas Blanco, Alberto Martí Ezpeleta

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Santiago de Compostela became a stable object of literary representation during the period between 1840 and 1915, approximately. This study offers a partial cartographical look at this process, suggesting that a cultural space like Compostela’s becoming an object of literary representation paralleled the first stages of its becoming a tourist destination. We use maps as a method of analysis to show the interaction between a corpus of novels and the emerging tradition of tourist guides on Compostela during the selected period. Often, the novels constitute ways to present a city to the outside, marking it for the gaze of others, as guidebooks do. That leads us to examine the ways of constructing and rendering communicable the local in other contexts. For that matter, we should also acknowledge the fact that a good number of the narratives in the corpus evoke the representation of the city through the figure of one who comes from elsewhere: a traveler, a student or a professor. The guidebooks coincide in this with the emerging fiction, of which the mimesis of a city is a key characteristic. The local cannot define itself except through a process of symbolic negotiation, in which recognition and self-recognition play important roles. Cartography shows some of the forms that these processes of symbolic representation take through the treatment of space. The research uses GIS to find significant models of representation. We used the program ArcGIS for the mapping, defining the databases starting from an adapted version of the methodology applied by Barbara Piatti and Lorenz Hurni’s team at the University of Zurich. First, we designed maps that emphasize the peripheral position of Compostela from a historical and institutional perspective using elements found in the texts of our corpus (novels and tourist guides). Second, other maps delve into the parallels between recurring techniques in the fictional texts and characteristic devices of the guidebooks (sketching itineraries and the selection of zones and indexicalization), like a foreigner’s visit guided by someone who knows the city or the description of one’s first entrance into the city’s premises. Last, we offer a cartography that demonstrates the connection between the best known of the novels in our corpus (Alejandro Pérez Lugín’s 1915 novel La casa de la Troya) and the first attempt to create package tourist tours with Galicia as a destination, in a joint venture of Galician and British business owners, in the years immediately preceding the Great War. Literary cartography becomes a crucial instrument for digging deeply into the methods of cultural production of places. Through maps, the interaction between discursive forms seemingly so far removed from each other as novels and tourist guides becomes obvious and suggests the need to go deeper into a complex process through which a city like Compostela becomes visible on the contemporary cultural horizon.

Keywords: compostela, literary geography, literary cartography, tourism

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Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: Gysele Lima Ricci, Jose Miguel Rodriguez Anton

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Companies in the tourism sector need to achieve competitive advantages for their survival in the market. In this way, the models based on association, cooperation, complementarity, distribution, exchange and mutual assistance arise as a possibility of organizational development, taking as reference the concept of networks. Many companies seek to partner in local networks as clusters to act together and associate. The main objective of the present research is to identify the specificities of management and the practices of cooperation in the tourist destination of São Paulo - Brazil, and to propose a new management model with possible cluster of tourism. The empirical analysis was carried out in three phases. As a first phase, a research was made by the companies, associations and tourism organizations existing in São Paulo, analyzing the characteristics of their business. In the second phase, the management specificities and cooperation practice used in the tourist destination. And in the third phase, identifying the possible strengths and weaknesses that potential or potential tourist cluster could have, proposing the development of the management model of the same adapted to the needs of the companies, associations and organizations. As a main result, it has been identified that companies, associations and organizations could be looking for synergies with each other and collaborate through a Hiperred organizational structure, in which they share their knowledge, try to make the most of the collaboration and to benefit from three concepts: flexibility, learning and collaboration. Finally, it is concluded that, the proposed tourism cluster management model is viable for the development of tourism destinations because it makes it possible to strategically address agents which are responsible for public policies, as well as public and private companies and organizations in their strategies competitiveness and cooperation.

Keywords: cluster, management model, networks, tourism sector

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Authors: Siripen Yiamjanya, Kevin Wongleedee

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This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: decision making, destination choice, international tourist, pull factor, push factor, Thailand, travel motivation

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Authors: T. Lazzarini, M. Imbiki, P. E. Sutter, G. Borragan

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While several strategies, such as the development of more efficient appliances, the financing of insulation programs or the rolling out of smart meters represent promising tools to reduce future energy consumption, their implementation relies on people’s decisions-actions. Likewise, engaging with consumers to reshape their behavior has shown to be another important way to reduce energy usage. For these reasons, integrating the human factor in the energy transition has become a major objective for researchers and policymakers. Digital education programs based on tangible and gamified user interfaces have become a new tool with potential effects to reduce energy consumption4. The B2020 program, developed by the firm “Économie d’Énergie SAS”, proposes a digital platform to encourage pro-environmental behavior change among employees and citizens. The platform integrates 160 eco-behaviors to help saving energy and water and reducing waste and CO2 emissions. A total of 13,146 citizens have used the tool so far to declare the range of eco-behaviors they adopt in their daily lives. The present work seeks to build on this database to identify the potential impact of adopted energy-saving behaviors (n=62) to reduce the use of energy in buildings. To this end, behaviors were classified into three categories regarding the nature of its implementation (Eco-habits: e.g., turning-off the light, Eco-actions: e.g., installing low carbon technology such as led light-bulbs and Home-Refurbishments: e.g., such as wall-insulation or double-glazed energy efficient windows). General Linear Models (GLM) disclosed the existence of a significantly higher frequency of Eco-habits when compared to the number of home-refurbishments realized by the platform users. While this might be explained in part by the high financial costs that are associated with home renovation works, it also contrasts with the up to three times larger energy-savings that can be accomplished by these means. Furthermore, multiple regression models failed to disclose the expected relationship between energy-savings and frequency of adopted eco behaviors, suggesting that energy-related practices are not necessarily driven by the correspondent energy-savings. Finally, our results also suggested that people adopting more Eco-habits and Eco-actions were more likely to engage in Home-Refurbishments. Altogether, these results fit well with a growing body of scientific research, showing that energy-related practices do not necessarily maximize utility, as postulated by traditional economic models, and suggest that other variables might be triggering them. Promoting home refurbishments could benefit from the adoption of complementary energy-saving habits and actions.

Keywords: energy-saving behavior, human performance, behavioral change, energy efficiency

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: D. Shamatov

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Becoming a teacher is a journey with significant learning experiences. Exploring teachers’ lives and experiences can provide much-needed insights into the multiple realities of teaching. Teachers’ stories through qualitative narrative studies help understand and appreciate the complexities of the socio-political, economic and practical realities facing teachers. Events and experiences, both past and present, that take place at home, school, and in the broader social sphere help to shape these teachers’ lives and careers. Researchers and educators share the responsibility of listening to these teachers’ stories and life experiences and being sensitive to their voices in order to develop effective models for teacher development. A better understanding of how teachers learn to become teachers can help teacher educators prepare more effective teacher education programs. This paper is based on qualitative research which includes individual and focus group interviews, as well as auto-biography stories of Master of Science in School Leadership students at Graduate School of Education of Nazarbayev University. Twenty five MSc students from across Kazakhstan reflected on their professional journey and wrote their professional autobiographies as teachers. Their autobiographies capture the richness of their experiences and beliefs as a teacher, but also serve as window to understand broader socio-economic and political contexts where these teachers live and work. The study also provides an understanding of the systemic and socio-economic challenges of teachers in the context of post-Soviet Kazakhstan. It helps the reader better understand how wider societal forces interact and frame the development of teachers. The paper presents the findings from these stories of MSc students and offers some practical and policy implications for teacher preparation and teacher development.

Keywords: becoming a teacher, Kazakhstan, teacher stories, teacher development

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Authors: Robert Ogbanje Okwori

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The paper explained the causes low students’ access to university education in Nigeria and how it can be remedied. It is discovered that low students’ access to university education in Nigeria is evident despite these number of universities in the country. In 2006/2007 academic session, 806,089 sat for Joint Unified Matriculation Board Examination (JAMB) into Nigerian universities and only 123,626 (15.3%) were admitted while 2011/2012 academic session, a total of 1,493,604 candidates sat for Joint Unified Matriculation Board Examination (JAMB) into Nigerian universities and only 65,073 (43.57%) were admitted. This necessitates for the research. Therefore, the study posed the following research questions. What are causes of low students’ access to university education in Nigeria? What are the challenges of students’ access to university education in Nigeria? How can students’ access to university education in Nigeria be improved? Sample survey research design was adopted for the study. A structured questionnaire was used to gather data for the study. Six hundred and eighty (680) respondents which comprised of 100 level university students; JAMB Officers and University administrators (Vice Chancellors, Registrars and Admission Officers) were used for the study. Stratified random sampling was applied for adequate representation of respondents from universities in the six geopolitical zones of Nigeria. Mean was used to answer research questions while Kuder-Richardson formula 20 was used to check the internal consistency of the instrument. The correlation coefficient of the instrument was 0.87. The major findings include the carrying capacity of each university contributes to low students’ access to university education and academic staff were inadequate. From the analysis of the study, it is concluded that the rate of access to university education is low, therefore, every university should establish distance learning programme to reduce university admission crisis. The training infrastructure in the universities should be improved upon by the owners to increase the carrying capacity of each university.

Keywords: access, causes, low, university

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Authors: Kalangi Rodrigo

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The term Neuroecology elucidates the study of customizable variation in cognition and the brain. Subject marked the birth since 1980s, when researches began to apply methods of comparative evolutionary biology to cognitive processes and the underlying neural mechanisms of cognition. In Archaeology and Anthropology, we observe behaviors such as social learning skills, innovative feeding and foraging, tool use and social manipulation to determine the cognitive processes of ancient mankind. Depending on the brainstem size was used as a control variable, and phylogeny was controlled using independent contrasts. Both disciplines need to enriched with comparative literature and neurological experimental, behavioral studies among tribal peoples as well as primate groups which will lead the research to a potential end. Neuroecology examines the relations between ecological selection pressure and mankind or sex differences in cognition and the brain. The goal of neuroecology is to understand how natural law acts on perception and its neural apparatus. Furthermore, neuroecology will eventually lead both principal disciplines to Ethology, where human behaviors and social management studies from a biological perspective. It can be either ethnoarchaeological or prehistoric. Archaeology should adopt general approach of neuroecology, phylogenetic comparative methods can be used in the field, and new findings on the cognitive mechanisms and brain structures involved mating systems, social organization, communication and foraging. The contribution of neuroecology to archaeology and anthropology is the information it provides on the selective pressures that have influenced the evolution of cognition and brain structure of the mankind. It will shed a new light to the path of evolutionary studies including behavioral ecology, primate archaeology and cognitive archaeology.

Keywords: Neuroecology, Archaeology, Brain Evolution, Cognitive Archaeology

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Barbora Svechova, Monika Licbinska

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Geochemical modeling of mineralogical changes of various materials in contact with an aqueous solution is an important tool for predicting the processes and development of given materials at the site. The modeling focused on the mutual interaction of groundwater at the contact with the rock mass and its subsequent influence on concrete structures. The studied locality is located in Slovakia in the area of the Liptov Basin, which is a significant inter-mountain lowland, which is bordered on the north and south by the core mountains belt of the Tatras, where in the center the crystalline rises to the surface accompanied by Mesozoic cover. Groundwater in the area is bound to structures with complicated geological structures. From the hydrogeological point of view, it is an environment with a crack-fracture character. The area is characterized by a shallow surface circulation of groundwater without a significant collector structure, and from a chemical point of view, groundwater in the area has been classified as calcium bicarbonate with a high content of CO2 and SO4 ions. According to the European standard EN 206-1, these are waters with medium aggression towards the concrete. Three rock samples were taken from the area. Based on petrographic and mineralogical research, they were evaluated as calcareous shale, micritic limestone and crystalline shale. These three rock samples were placed in demineralized water for one month and the change in the chemical composition of the water was monitored. During the solution-rock interaction there was an increase in the concentrations of all major ions, except nitrates. There was an increase in concentration after a week, but at the end of the experiment, the concentration was lower than the initial value. Another experiment was the interaction of groundwater from the studied locality with a concrete structure. The concrete sample was also left in the water for 1 month. The results of the experiment confirmed the assumption of a reduction in the concentrations of calcium and bicarbonate ions in water due to the precipitation of amorphous forms of CaCO3 on the surface of the sample.Vice versa, it was surprising to increase the concentration of sulphates, sodium, iron and aluminum due to the leaching of concrete. Chemical analyzes from these experiments were performed in the PHREEQc program, which calculated the probability of the formation of amorphous forms of minerals. From the results of chemical analyses and hydrochemical modeling of water collected in situ and water from experiments, it was found: groundwater at the site is unsaturated and shows moderate aggression towards reinforced concrete structures according to EN 206-1a, which will affect the homogeneity and integrity of concrete structures; from the rocks in the given area, Ca, Na, Fe, HCO3 and SO4. Unsaturated waters will dissolve everything as soon as they come into contact with the solid matrix. The speed of this process then depends on the physicochemical parameters of the environment (T, ORP, p, n, water retention time in the environment, etc.).

Keywords: geochemical modeling, concrete , dissolution , PHREEQc

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Magdalena Grudzińska

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Passive systems allow solar radiation to be converted into thermal energy thanks to appropriate building construction. Greenhouse systems are particularly worth attention, due to the low costs of their realization and strong architectural appeal. The paper discusses the energy effects of using passive greenhouse systems, such as glazed balconies, in an example residential building. The research was carried out for five localities in Poland, belonging to climatic zones different in terms of external air temperature and insolation: Koszalin, Poznań, Lublin, Białystok and Zakopane The analysed apartment had a floor area of approximately 74 m² Three thermal zones were distinguished in the flat - the balcony, the room adjacent to it, and the remaining space, for which various internal conditions were defined. Calculations of the energy demand were made using the dynamic simulation program, based on the control volume method. The climatic data were represented by Typical Meteorological Years, prepared on the basis of source data collected from 1971 to 2000. In each locality, the introduction of a passive greenhouse system led to a lower demand for heating in the apartment, and the shortening of the heating season. The smallest effectiveness of passive solar energy systems was noted in Białystok. Demand for heating was reduced there by 14.5% and the heating season remained the longest, due to low temperatures of external air and small sums of solar radiation intensity. In Zakopane, energy savings came to 21% and the heating season was reduced to 107 days, thanks to the greatest insolation during winter. The introduction of greenhouse systems caused an increase in cooling demand in the warmer part of the year, but total energy demand declined in each of the discussed places. However, potential energy savings are smaller if the building's annual life cycle is taken into consideration, and amount from 5.6% up to 14%. Koszalin and Zakopane are localities in which the greenhouse system allows the best energy results to be achieved. It should be emphasized that favourable conditions for introducing greenhouse systems are connected with different climatic conditions. In the seaside area (Koszalin) they result from high temperatures in the heating season and the smallest insolation in the summer period, while in the mountainous area (Zakopane) they result from high insolation in the winter and low temperatures in the summer. In the region of middle and middle-eastern Poland active systems (such as solar energy collectors or photovoltaic panels) could be more beneficial, due to high insolation during summer. It is assessed that passive systems do not eliminate the need for traditional heating in Poland. They can, however, substantially contribute to lower use of non-renewable fuels and the shortening of the heating season. The calculations showed diversification in the effectiveness of greenhouse systems resulting from climatic conditions, and allowed to identify areas which are the most suitable for the passive use of solar radiation.

Keywords: solar energy, passive greenhouse systems, glazed balconies, climatic conditions

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Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway networks play a vital role in post-disaster recovery for disaster-damaged areas. Damaged bridges in such networks can disrupt the recovery activities by impeding the transportation of people, cargo, and reconstruction resources. Therefore, rapid restoration of damaged bridges is of paramount importance to long-term disaster recovery. In the post-disaster recovery phase, the key to restoration scheduling for a highway network is prioritization of bridge-repair tasks. Resilience is widely used as a measure of the ability to recover with which a network can return to its pre-disaster level of functionality. In practice, highways will be temporarily blocked during the downtime of bridge restoration, leading to the decrease of highway-network functionality. The failure to take downtime effects into account can lead to overestimation of network resilience. Additionally, post-disaster recovery of highway networks is generally divided into emergency bridge repair (EBR) in the response phase and long-term bridge repair (LBR) in the recovery phase, and both of EBR and LBR are different in terms of restoration objectives, restoration duration, budget, etc. Distinguish these two phases are important to precisely quantify highway network resilience and generate suitable restoration schedules for highway networks in the recovery phase. To address the above issues, this study proposes a novel resilience quantification method for the optimization of long-term bridge repair schedules (LBRS) taking into account the impact of EBR activities and restoration downtime on a highway network’s functionality. A time-dependent integer program with recursive functions is formulated for optimally scheduling LBR activities. Moreover, since uncertainty always exists in the LBRS problem, this paper extends the optimization model from the deterministic case to the stochastic case. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. The proposed methods are tested using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that, in this case, neglecting the bridge restoration downtime can lead to approximately 15% overestimation of highway network resilience. Moreover, accounting for the impact of EBR on network functionality can help to generate a more specific and reasonable LBRS. The theoretical and practical values are as follows. First, the proposed network recovery curve contributes to comprehensive quantification of highway network resilience by accounting for the impact of both restoration downtime and EBR activities on the recovery curves. Moreover, this study can improve the highway network resilience from the organizational dimension by providing bridge managers with optimal LBR strategies.

Keywords: disaster management, highway network, long-term bridge repair schedule, resilience, restoration downtime

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Authors: Martina Dickson, Lilly Tennant

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The young Emirati female university students of today are the first generation of women in the UAE for whom higher education as become not only a possibility, but almost an expectation. Young women in the UAE today make up around 77% of students in higher education institutes in the country. However, the societal expectations placed upon these women in terms of early marriage, child-bearing and rearing are similar to those placed upon their mothers and grandmothers in a time where women were not expected to go to university. A large proportion of female university students in the UAE are mothers of young children, or become mothers whilst at the university. This creates a challenging situation for young student mothers, where two weeks’ maternity leave is typical across institutions. The context of this study is in one such institution in the UAE. We have employed a mixed method approach to gathering interview data from twenty mothers, and survey data from over one hundred mothers. The main findings indicate that mothers have strong desires for their institution to support them more, for example by the provision of nursery facilities and resting areas for new mothers, and giving them greater flexibility over course selections and schedules including the provision of online learning. However, the majority felt supported on a personal level by their tutors. The major challenges which they identified in returning to college after only two weeks’ leave included the inevitable health and lack of sleep issues when caring for a newborn, struggling to catch up with missed college work and handling their course load. We also explored the women's’ home support systems which were provided from a variety of extended family, spouses and paid domestic help.

Keywords: student mothers, challenges, supports, United Arab Emirates

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Authors: Dali Gaganidze, Ekaterine Abashidze

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Potato is one of the main agricultural crops in Georgia. Georgia produces early and late potato varieties in almost all regions. In traditional potato growing regions (Svaneti, Samckhet javaheti and Tsalka), the yield is higher than 30-35 t/ha. Among the plant pests that limit potato production and quality, the potato cyst nematodes (PCN) are harmful around the world. Yield losses caused by PCN are estimated up to 30%. Rout surveys conducted in two geographically distinct regions of Georgia producing potatoes - Samtskhe - Javakheti and Svaneti revealed potato cyst nematode Globodera rostochiensi. The aim of the study was the Phylogenetic analyses of Globodera rostochiensi revealed in Georgia by the amplification and sequencing of 28S gen in the D3 region and intergenic ITS1-15.8S-ITS2 region. Identification of all the samples from the two Globodera populations (Samtskhe - Javakheti and Svaneti), i.e., G. rostochiensis (20 isolates) were confirmed by conventional multiplex PCR with ITS 5 universal and PITSp4, PITSr3 specific primers of the cyst nematodes’ (G. pallida, G. rostochiensis). The size of PCR fragment 434 bp confirms that PCN samples from two populations, Samtskhe- Javakheti and Svaneti, belong to G. rostochiensi . The ITS1–5.8S-ITS2 regions were amplified using prime pairs: rDNA1 ( 5’ -TTGATTACGTCCCTGCCCTTT-3’ and rDNA2( 5’ TTTCACTCGCCGTTACTAAGG-3’), D3 expansion regions were amplified using primer pairs: D3A (5’ GACCCCTCTTGAAACACGGA-3’) and D3B (5’-TCGGAAGGAACCAGCTACTA-3’. PCR products of each region were cleaned up and sequenced using an ABI 3500xL Genetic Analyzer. Obtained sequencing results were analyzed by computer program BLASTN (https://blast.ncbi.nlm.nih.gov/Blast.cg). Phylogenetic analyses to resolve the relationships between the isolates were conducted in MEGA7 using both distance- and character-based methods. Based on analysis of G.rostochiensis isolate`s D3 expansion regions are grouped in three major clades (A, B and C) on the phylogenetic tree. Clade A is divided into three subclades; clade C is divided into two subclades. Isolates from the Samtckhet-javakheti population are in subclade 1 of clade A and isolates in subclade 1 of clade C. Isolates) from Svaneti populations are in subclade 2 of clade A and in clad B. In Clade C, subclade two is presented by three isolates from Svaneti and by one isolate (GL17) from Samckhet-Javakheti. . Based on analysis of G.rostochiensis isolate`s ITS1–5.8S-ITS2 regions are grouped in two main clades, the first contained 20 Georgian isolates of Globodera rostochiensis from Svaneti . The second clade contained 15 isolates of Globodera rostochiensis from Samckhet javakheti. Our investigation showed of high genetic variation of D3 and ITS1–5.8S-ITS2 region of rDNA of the isolates of G. rostochiensis from different geographic origins (Svameti, Samckhet-Javakheti) of Georgia. Acknowledgement: The research has been supported by the Shota Rustaveli National Scientific Foundation of Georgia : Project # FR17_235

Keywords: globodera rostochiensi, PCR, phylogenetic tree, sequencing

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Authors: Broto Seno

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This study aims to describe and examine more in the implementation of educational partnerships for undergraduate students at Yogyakarta State University (YSU), which is more focused on educational partnerships abroad. This study used descriptive qualitative approach. The study subjects consisted of a vice-rector, two staff education partnerships, four vice-dean, nine undergraduate students and three foreign students. Techniques of data collection using interviews and document review. Validity test of the data source using triangulation. Data analysis using flow models Miles and Huberman, namely data reduction, data display, and conclusion. Results of this study showed that the implementation of educational partnerships abroad for undergraduate students at YSU meets six of the nine indicators of the success of strategic partnerships. Six indicators are long-term, strategic, mutual trust, sustainable competitive advantages, mutual benefit for all the partners, and the separate and positive impact. The indicator has not been achieved is cooperative development, successful, and world class / best practice. These results were obtained based on the discussion of the four formulation of the problem, namely: 1) Implementation and development of educational partnerships abroad has been running good enough, but not maximized. 2) Benefits of the implementation of educational partnerships abroad is providing learning experiences for students, institutions of experience in comparison to each faculty, and improving the network of educational partnerships for YSU toward World Class University. 3) The sustainability of educational partnerships abroad is pursuing a strategy of development through improved management of the partnership. 4) Supporting factors of educational partnerships abroad is the support of YSU, YSU’s partner and society. Inhibiting factors of educational partnerships abroad is not running optimally management.

Keywords: partnership, education, YSU, institutions and faculties

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Authors: Tom Wanyama

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We have developed a weight-based parts inventory monitoring system utilizing the Industrial Internet of Things (IIoT) to enhance operational efficiencies in manufacturing. The system addresses various challenges, including eliminating downtimes caused by stock-outs, preventing human errors in parts delivery and product assembly, and minimizing motion waste by reducing unnecessary worker movements. The system incorporates custom QR codes for simplified inventory tracking and retrieval processes. The generated data serves a dual purpose by enabling real-time optimization of parts flow within manufacturing facilities and facilitating retroactive optimization of stock levels for informed decision-making in inventory management. The pilot implementation at SEPT Learning Factory successfully eradicated data entry errors, optimized parts delivery, and minimized workstation downtimes, resulting in a remarkable increase of over 10% in overall equipment efficiency across all workstations. Leveraging the IIoT features, the system seamlessly integrates information into the process control system, contributing to the enhancement of product quality. This approach underscores the importance of effective tracking of parts inventory in manufacturing to achieve transparency, improved inventory control, and overall profitability. In the broader context, our inventory monitoring system aligns with the evolving focus on optimizing supply chains and maintaining well-managed warehouses to ensure maximum efficiency in the manufacturing industry.

Keywords: industrial Internet of things, industrial systems integration, inventory monitoring, inventory control in manufacturing

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Authors: Abeer Alhazmi

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Introduction: Clinical education is considered a significant part of the learning process for nurses and nursing students. However, recruiting high- caliber individuals to train them to be tomorrow’s educators/teachers has been a recurrent challenge. One of the troubling challenges in this field is the absent of proper training programmes to train educators to be future education professionals and leaders. Aim: To explore the impact of a stage 1 and stage 2 clinical instructor courses on developing leadership skills for nurses as educators.Theoretical Framework: Informed by a symbolic interactionist framework, this research explored the Impact of stage 1 and stage 2 clinical instructor courses on nurses' knowledge, attitudes, and leadership skills. Method: Using Glaserian grounded theory method the data were derived from 3 focus groups and 15 in-depth interviews with nurse educators/clinical instructors and nurses who attended stage 1 and stage 2 clinical instructor courses at King Abdu-Aziz University Hospital (KAUH). Findings: The findings of the research are represented in the core category exploring new identity as educator and its two constituent categories Accepting change, and constructing educator identity. The core and sub- categories were generated through a theoretical exploration of the development of educator’s identity throughout stage 1 and stage 2 clinical instructor courses. Conclusion: The social identity of the nurse educators was developed and changed during and after attending stage 1 and stage 2 clinical instructor courses. In light of an increased understanding of the development process of educators identity and role, the research presents implications and recommendations that may contribute to the development of nursing educators in general and in Saudi Arabia in specific.

Keywords: clinical instructor course, educators, identity work, clinical nursing

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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Authors: Fouzia Khanam, Tridib Chowdhury, Belal Hossain, Sajedur Rahman, Mahfuzar Rahman

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Introduction: Over the last decades, the world has achieved a noticeable success in preventing malaria. Nevertheless, malaria, a vector-borne infectious disease, remains a major public health burden globally as well as in Bangladesh. To achieve the goal of eliminating malaria, BRAC, a leading organization of Bangladesh in collaboration with government, is distributing free LLIN to the 13 endemic districts of the country. The study was conducted with the aim of assessing the gap between coverage, access, and utilization of LLIN among the people of the 13 malaria endemic districts of Bangladesh. Methods: This baseline study employed a community cross-sectional design triangulated with qualitative methods to measure households’ ownership, access and use of 13 endemic districts. A multistage cluster random sampling was employed for the quantitative part and for qualitative part a purposive sampling strategy was done. Thus present analysis included 2640 households encompassing a total of 14475 populations. Data were collected using a pre-tested structured questionnaire through one on one face-to-face interview with respondents. All analyses were performed using STATA (Version 13.0). For the qualitative part participant observation, in-depth interview, focus group discussion, key informant interview and informal interview was done to gather the contextual data. Findings: According to our study, 99.8% of households possessed at least one-bed net in both study areas. 77.4% households possessed at least two LLIN and 43.2% households had access to LLIN for all the members. So the gap between coverage and access is 34%. 91.8% people in the 13 districts and 95.1% in Chittagong Hill Tracts areas reported having had slept under a bed net the night before interviewed. And despite the relatively low access, in 77.8% of households, all the members were used the LLIN the previous night. This higher utilization compared to access might be due to the increased awareness among the community people regarding LLIN uses. However, among those people with sufficient access to LLIN, 6% of them still did not use the LLIN which reflects the behavioral failure that needs to be addressed. The major reasons for not using LLIN, identified by both qualitative and quantitative findings, were insufficient access, sleeping or living outside the home, migration, perceived low efficacy of LLIN, fear of physical side effects or feeling uncomfortable. Conclusion: Given that LLIN access and use was a bit short of the targets, it conveys important messages to the malaria control program. Targeting specific population segments and groups for achieving expected LLIN coverage is very crucial. And also, addressing behavior failure by well-designed behavioral change interventions is mandatory.

Keywords: long lasting insecticide net, malaria, malaria control programme, World Health Organisation

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Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

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This research was conducted in the Mae Sot Watershed whereas located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urbanized in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recently years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood event in 2013 as the worst studied case for those all communities in this municipality. Moreover, other problems are also faced in this watershed such shortage water supply for domestic consumption and agriculture utilizations including deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of appropriated application of some short period rainfall forecasting model as the aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in short period of 7 - 10 days in advance during rainy season instead of real time record. The IDV product can be present in advance period of rainfall with time step of 3 - 6 hours was introduced to the communities. The result can be used to input to either the hydrologic modeling system model (HEC-HMS) or the soil water assessment tool model (SWAT) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfied. The result of IDV’s rainfall forecast data was compared to observed data and found fair. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: global rainfall, flood forecast, hydrologic modeling system, river analysis system

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Physiological changes during pregnancy, such as alterations in the circulatory, respiratory, and musculoskeletal systems, can negatively impact daily physical activity. This reduced activity is often associated with an increased risk of adverse maternal health outcomes, particularly gestational diabetes mellitus (GDM) and excessive weight gain. This meta-analysis aims to evaluate the effectiveness of structured physical exercise interventions during pregnancy in reducing the risk of GDM and managing maternal weight gain. A comprehensive search was conducted across six major databases: PubMed, Cochrane Library, EMBASE, Web of Science, ScienceDirect, and ClinicalTrials.gov, covering the period from database inception until 2023. Randomized controlled trials (RCTs) that explored the effects of physical exercise programs on pregnant women with low physical activity levels were included. The search was performed using EndNote and results were managed using RevMan (Review Manager) for meta-analysis. RCTs involving healthy pregnant women with low levels of physical activity or sedentary lifestyles were selected. These RCTs must have incorporated structured exercise programs during pregnancy and reported on outcomes related to GDM and maternal weight gain. From an initial pool of 5,112 articles, 65 RCTs (involving 11,400 pregnant women) met the inclusion criteria. Data extraction was performed, followed by a quality assessment of the selected studies using the Cochrane Risk of Bias tool. The meta-analysis was conducted using RevMan software, where pooled relative risks (RR) and weighted mean differences (WMD) were calculated using a random-effects model to address heterogeneity across studies. Sensitivity analyses, subgroup analyses (based on factors such as exercise intensity, duration, and pregnancy stage), and publication bias assessments were also conducted. Structured physical exercise during pregnancy led to a significant reduction in the risk of developing GDM (RR = 0.68; P < 0.001), particularly when the exercise program was performed throughout the pregnancy (RR = 0.62; P = 0.035). In addition, maternal weight gain was significantly reduced (WMD = −1.18 kg; 95% CI −1.54 to −0.85; P < 0.001). There were no significant adverse effects reported for either the mother or the neonate, confirming that exercise interventions are safe for both. This meta-analysis highlights the positive impact of regular moderate physical activity during pregnancy in reducing the risk of GDM and managing maternal weight gain. These findings suggest that physical exercise should be encouraged as a routine part of prenatal care. However, more research is required to refine exercise recommendations and determine the most effective interventions based on individual risk factors and pregnancy stages.

Keywords: gestational diabetes, maternal weight management, meta-analysis, randomized controlled trials

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