Search results for: local learning resource

Authors: Maleh Yassine, Ezzati Abdellah

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Wireless Sensor Networks (WSNs) are currently used in different industrial and consumer applications, such as earth monitoring, health related applications, natural disaster prevention, and many other areas. Security is one of the major aspects of wireless sensor networks due to the resource limitations of sensor nodes. However, these networks are facing several threats that affect their functioning and their life. In this paper we present security attacks in wireless sensor networks, and we focus on a review and analysis of the recent Intrusion Detection schemes in WSNs.

Keywords: wireless sensor networks, security attack, denial of service, IDS, cluster-based model, signature based IDS, hybrid IDS

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Authors: Fangzheng Li, Xiong Li

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Significant differences in urban greening have occurred in Chinese cities, which accompanied with China's rapid urbanization. However, few studies focused on the spatial differentiation of urban greening in China with large amounts of data. The spatial differentiation pattern, spatial correlation characteristics and the distribution shape of urban green space ratio, urban green coverage rate and public green area per capita were calculated and analyzed, using Global and Local Moran's I using data from 289 cities in 2014. We employed Spatial Lag Model and Spatial Error Model to assess the impacts of urbanization process on urban greening of China. Then we used Geographically Weighted Regression to estimate the spatial variations of the impacts. The results showed: 1. a significant spatial dependence and heterogeneity existed in urban greening values, and the differentiation patterns were featured by the administrative grade and the spatial agglomeration simultaneously; 2. it revealed that urbanization has a negative correlation with urban greening in Chinese cities. Among the indices, the the proportion of secondary industry, urbanization rate, population and the scale of urban land use has significant negative correlation with the urban greening of China. Automobile density and per capita Gross Domestic Product has no significant impact. The results of GWR modeling showed that the relationship between urbanization and urban greening was not constant in space. Further, the local parameter estimates suggested significant spatial variation in the impacts of various urbanization factors on urban greening.

Keywords: China’s urbanization, geographically weighted regression, spatial differentiation pattern, urban greening

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: Kathaleeya Chanda

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The objectives of the research on the development of printed media for public relations of community products in Bang Khonthi District, Samut Songkram Province were to; 1) develop printed media for public relations of community products in Bang Khonthi District, Samut Songkram Province and 2) study the satisfaction towards the printed media for public relations of community products in Bang Khonthi District, Samut Songkram Province. The study was on the satisfaction focused on content, illustration, design, and quality. The sampling group of this study included 30 local community producers selected by probability sampling and simple random sampling. The research procedure consisted of 4 phases; 1) problem and situation study, 2) the development of printed media for public relations, 3) research tool development, and 4) data collection. Questionnaires to evaluate the satisfaction of local community producers towards the printed media for public relation were used to collect data which were analysed to find percentage, arithmetic means, and standard deviation. The results showed that the informants reported their satisfaction on 4 aspects as follows: 1) very high satisfaction on the content, 2) high satisfaction on the illustration, 3) very high satisfaction on the design, and 4) very high satisfaction on the product quality. This can be concluded that the developed printed media for public relations of community products can be used effectively with high satisfaction.

Keywords: printed media, public relations, community products in Bang Khonthi district, Samut Songkram Province

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: Robert Pocklington

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Most current language courses expect students to be ‘vocational’, sacrificing their free time in order to learn. However, pupils with a full-time job, or bringing up children, hardly have a spare moment. Others just need the language as a tool or a qualification, as if it were book-keeping or a driving license. Then there are children in unstructured families whose stressful life makes private study almost impossible. And the countless parents whose evenings and weekends have become a nightmare, trying to get the children to do their homework. There are many arguments against homework being a necessity (rather than an optional extra for more ambitious or dedicated students), making a clear case for teaching methods which facilitate full learning of the key content within the classroom. A methodology which could be described as Programmed Mastery Learning has been used at Fluency Language Academy (Spain) since 1992, to teach English to over 4000 pupils yearly, with a staff of around 100 teachers, barely requiring homework. The course is structured according to the tenets of Programmed Learning: small manageable teaching steps, immediate feedback, and constant successful activity. For the Mastery component (not stopping until everyone has learned), the memorisation and practice are entrusted to flashcard-based drilling in the classroom, leading all students to progress together and develop a permanently growing knowledge base. Vocabulary and expressions are memorised using flashcards as stimuli, obliging the brain to constantly recover words from the long-term memory and converting them into reflex knowledge, before they are deployed in sentence building. The use of grammar rules is practised with ‘cue’ flashcards: the brain refers consciously to the grammar rule each time it produces a phrase until it comes easily. This automation of lexicon and correct grammar use greatly facilitates all other language and conversational activities. The full B2 course consists of 48 units each of which takes a class an average of 17,5 hours to complete, allowing the vast majority of students to reach B2 level in 840 class hours, which is corroborated by an 85% pass-rate in the Cambridge University B2 exam (First Certificate). In the past, studying for qualifications was just one of many different options open to young people. Nowadays, youngsters need to stay at school and obtain qualifications in order to get any kind of job. There are many students in our classes who have little intrinsic interest in what they are studying; they just need the certificate. In these circumstances and with increasing government pressure to minimise failure, teachers can no longer think ‘If they don’t study, and fail, its their problem’. It is now becoming the teacher’s problem. Teachers are ever more in need of methods which make their pupils successful learners; this means assuring learning in the classroom. Furthermore, homework is arguably the main divider between successful middle-class schoolchildren and failing working-class children who drop out: if everything important is learned at school, the latter will have a much better chance, favouring inclusiveness in the language classroom.

Keywords: flashcard drilling, fluency method, mastery learning, programmed learning, teaching English as a foreign language

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Authors: Leandros A. Maglaras, Jianmin Jiang

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The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.

Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection

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Authors: Intan Azura Mokhtar, Yaacob Ibrahim

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In recent years, learning about sustainable development and sustainability has become an increasingly significant component in universities’ degree programmes and curricula. As the world comes together and races to fulfil the 17 United Nations’ sustainable development goals (SDGs) by the year 2030, our educational curricula and landscapes simultaneously evolve to integrate lessons and opportunities for sustainable development and sustainability to redefine our university education and set the trajectory for our young people to take the lead in co-creating solutions for a better world. In this paper, initiatives and projects that revolved around themes of sustainable development and sustainability in a young university in Singapore are discussed. These initiatives and projects were curated by a new centre in the university that focuses on community leadership, social innovation, and service learning and was led by the university’s academic staff. The university’s undergraduate students were also involved in these initiatives and projects and played an active role in reaching out to and engaging members of different segments of the community – to better understand their needs and concerns and to co-create with them relevant and sustainable solutions that generate positive social impact.

Keywords: singapore, sustainable development, sustainability, undergraduate education

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Authors: Dr. Luigi Iannacci

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This research critically explores the current educational landscape with respect to special education and dominant deficit/medical model discourses that continue to forward unresponsive problematic approaches to teaching students with disabilities. Asset-oriented perspectives and social/critical models of disability are defined and explicated in order to offer alternatives to these dominant discourses. To that end, a framework that draws on Brian Camborne’s conditions of learning and applications of his work in relation to instruction conceptualize learning conditions and their significance to students with special needs. Methodologically, the research is designed as Critical Narrative Inquiry (CNI). Critical incidents, interviews, documents, artefacts etc. are drawn on and narratively constructed to explore how disability is presently configured in language, discourses, pedagogies and interactions with students deemed disabled. This data was collected using ethnographic methods and as such, through participant-observer field work that occurred directly in classrooms. This narrative approach aims to make sense of complex classroom interactions and ways of reconceptualizing approaches to students with special needs. CNI is situated in the critical paradigm and primarily concerned with culture, language and participation as issues of power in need of critique with the intent of change in the direction of social justice. Research findings highlight the ways in which Cambourne’s learning conditions, such as demonstration, approximation, engagement, responsibility, immersion, expectation, employment (transfer, use), provide a clear understanding of what is central to and constitutes a responsive and inclusive this instructional frame. Examples of what each of these conditions look like in practice are therefore offered in order to concretely demonstrate the ways in which various pedagogical choices and questions can enable classroom spaces to be responsive to the assets and challenges students with special needs have and experience. These particular approaches are also illustrated through an exploration of multiliteracies theory and pedagogy and what this research and approach allows educators to draw on, facilitate and foster in terms of the ways in which students with special needs can make sense of and demonstrate their understanding of skills, content and knowledge. The contextual information, theory, research and instructional frame focused on throughout this inquiry ultimately demonstrate what inclusive classroom spaces and practice can look like. These perspectives and conceptualizations are in stark contrast to dominant deficit driven approaches that ensure current pedagogically impoverished teaching focused on narrow, limited and limiting understandings of special needs learners and their ways of knowing and acquiring/demonstrating knowledge.

Keywords: asset-oriented approach, social/critical model of disability, conditions for learning and teaching, students with special needs

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Authors: Kwanele Qonono

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Despite the significance and economic benefits of petrol stations in South Africa, these still pose a huge risk of fire and explosion threatening public safety. This research paper examines the extent to which land-use planning in Stellenbosch, South Africa, considers the fire risk posed by petrol stations and the implications for public safety as well as preparedness for large fires or explosions. To achieve this, the research identified the land-use types around petrol stations in Stellenbosch and determined the extent to which their locations comply with the local, national, and international land-use planning regulations. A mixed research method consisting of the collection and analysis of geospatial data and qualitative data was an applied method, where petrol stations within a six-kilometre radius of Stellenbosch’s town centre were utilised as study sites. The research examined the risk of fires/explosions at these petrol stations. The research investigated Stellenbosch Municipality’s institutional preparedness to respond in the event of a fire/explosion at these petrol stations. The research observed that siting of petrol stations does not comply with local, national, and international good practices, thus exposing the surrounding developments to fires and explosions. Land-use planning practice does not consider hazards created by petrol stations. Despite the potential for major fires at petrol stations, Stellenbosch Municipality’s level of preparedness to respond to petrol station fires appears low due to the prioritisation of more frequent events.

Keywords: petrol stations, technological hazard, drr, land-use planning, risk analysis

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Authors: Tendü H. Göktuğ, Gönül T. İçemer, Bülent Deniz

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National parks, which are rich in natural and cultural resources values are protected in the context of the idea to develop sustainability, are among the most important recreated areas demanding with each passing day. Increasing recreational use or unplanned use forms negatively affect the resource values and visitor satisfaction. The intent of national parks management is to protect the natural and cultural resource values and to provide the visitors with a quality of recreational experience, as well. In this context, the current studies to improve the appropriate tourism and recreation planning and visitor management, approach have focused on recreational carrying capacity analysis. The aim of this study is to analyze recreational carrying capacity of Çıralı Coast in the Bey Mountains Coastal National Park to compare the analyze results with the current usage format and to develop alternative management strategies. In the first phase of the study, the annual and daily visitations, geographic, bio-physical, and managerial characteristics of the park and the type of recreational usage and the recreational areas were analyzed. In addition to these, ecological observations were carried out in order to determine recreational-based pressures on the ecosystems. On-site questionnaires were administrated to a sample of 284 respondents in the August 2015 - 2016 to collect data concerning the demographics and visit characteristics. The second phase of the study, the coastal area separated into four different usage zones and the methodology proposed by Cifuentes (1992) was used for capacity analyses. This method supplies the calculation of physical, real and effective carrying capacities by using environmental, ecological, climatic and managerial parameters in a formulation. Expected numbers which estimated three levels of carrying capacities were compared to current numbers of national parks’ visitors. In the study, it was determined that the current recreational uses in the north of the beach were caused by ecological pressures, and the current numbers in the south of beach much more than estimated numbers of visitors. Based on these results management strategies were defined and the appropriate management tools were developed in accordance with these strategies. The authors are grateful for the financial support of this project by The Scientific and Technological Research Council of Turkey (No: 114O344)

Keywords: Çıralı Coast, national parks, recreational carrying capacity, visitor management

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Authors: Frappi Sofia, Nicolas Pilcher, Sander DenHaring, Royale Hardenstine, Luis Silva, Collin Williams, Mattie Rodrigue, Vincent Pieriborne, Mohammed Qurban, Carlos M. Duarte

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Nowadays, elasmobranch populations are disappearing at a dangerous rate, mainly due to overexploitation, extensive fisheries, as well as climate change. The decline of these species can trigger a cascade effect, which may eventually lead to detrimental impacts on local ecosystems. The Elasmobranch in the Red Sea is facing one of the highest risks of extinction, mainly due to unregulated fisheries activities. Thus, it is of paramount importance to assess their current distribution and unveil their environmental preferences in order to improve conservation measures. Important data have been collected throughout the whole red Sea during the Red Sea Decade Expedition (RSDE) to achieve this goal. Elasmobranch sightings were gathered through the use of submarines, remotely operated underwater vehicles (ROV), scuba diving operations, and helicopter surveys. Over a period of 5 months, we collected 891 sightings, 52 with submarines, 138 with the ROV, 67 with the scuba diving teams, and 634 from helicopters. In total, we observed 657 and 234 individuals from the superorder Batoidea and Selachimorpha, respectively. The most common shark encountered was Iago omanensis, a deep-water shark of the order Carcharhiniformes. To each sighting, data on temperature, salinity density, and dissolved oxygen were integrated to reveal favorable conditions for each species. Additionally, an extensive literature review on elasmobranch research in the Eastern Red Sea has been carried out in order to obtain more data on local populations and to be able to highlight patterns of their distribution.

Keywords: distribution, elasmobranchs, habitat, rays, red sea, sharks

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Authors: Jerzy Banski

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The basic aim of this study is to discuss and assess different classifications and research approaches to small towns that take their social and economic functions into account, as well as relations with surrounding areas. The subject literature typically includes three types of approaches to the classification of small towns: 1) the structural, 2) the location-related, and 3) the mixed. The structural approach allows for the grouping of towns from the point of view of the social, cultural and economic functions they discharge. The location-related approach draws on the idea of there being a continuum between the center and the periphery. A mixed classification making simultaneous use of the different approaches to research brings the most information to bear in regard to categories of the urban locality. Bearing in mind the approaches to classification, it is possible to propose a synthetic method for classifying small towns that takes account of economic structure, location and the relationship between the towns and their surroundings. In the case of economic structure, the small centers may be divided into two basic groups – those featuring a multi-branch structure and those that are specialized economically. A second element of the classification reflects the locations of urban centers. Two basic types can be identified – the small town within the range of impact of a large agglomeration, or else the town outside such areas, which is to say located peripherally. The third component of the classification arises out of small towns’ relations with their surroundings. In consequence, it is possible to indicate 8 types of small-town: from local centers enjoying good accessibility and a multi-branch economic structure to peripheral supra-local centers characterised by a specialized economic structure.

Keywords: small towns, classification, functional structure, localization

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Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

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This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Mohammed El Raey, Moustafa Osman Mohammed

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The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s System. Naturally exchange patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. The probabilistic risk assessment (PRA) technique is utilized to assess the safety of industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA- safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and ruler areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is also predicted the distribution schemes from the perspective of pollutants that considered multiple factors of multi-criteria analysis. The data extends input–output analysis to evaluate the spillover effect, and conducted Monte Carlo simulations and sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the biosphere and collective a composite index of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in artistic/ architectural perspective. The hypothesis is an attempt to unify analytic and analogical spatial structure for development urban environments using optimization software and applied as an example of integrated industrial structure where the process is based on engineering topology as optimization approach of systems ecology.

Keywords: spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology

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Authors: Slava Kalyuga, Sujanya Sombatteera

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In multimedia learning, written text is often transformed into spoken (narrated) text. This transient information may overwhelm limited processing capacity of working memory and inhibit learning instead of improving it. The paper reviews recent empirical studies in modality and verbal redundancy effects within a cognitive load framework and outlines conditions under which negative effects of transiency may occur. According to the modality effect, textual information accompanying pictures should be presented in an auditory rather than visual form in order to engage two available channels of working memory – auditory and visual - instead of only one of them. However, some studies failed to replicate the modality effect and found differences opposite to those expected. Also, according to the multimedia redundancy effect, the same information should not be presented simultaneously in different modalities to avoid unnecessary cognitive load imposed by the integration of redundant sources of information. However, a few studies failed to replicate the multimedia redundancy effect too. Transiency of information is used to explain these controversial results.

Keywords: cognitive load, transient information, modality effect, verbal redundancy effect

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Authors: V. V. Lakshmi, Y. V. S. Annapurna

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Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study. These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected.. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production

Keywords: Escherichia coli, Klebsiella sp, Uropathogens, Virulence features.

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Authors: Jureerat Buakaew

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The purpose of this research was to investigate Thai Muslims’ way of life through the way their clothes. The data of this qualitative research were collected from related documents and research reports, ancient cloths and clothing, and in-depth interviews with clothes owners and weavers. The research found that in the 18th century Thai Muslims in the three southern border provinces used many types of clothing in their life. At home women wore plain clothes. They used checked cloths to cover the upper part of their body from the breasts down to the waist. When going out, they used Lima cloth and So Kae with a piece of Pla-nging cloth as a head scarf. For men, they wore a checked sarong as a lower garment, and wore no upper garment. However, when going out, they wore Puyo Potong. In addition, Thai Muslims used cloths in various religious rites, namely, the rite of placing a baby in a cradle, the Masoyawi rite, the Nikah rite, and the burial rite. These types of cloths were related to the way of life of Thai Muslims from birth to death. They reflected the race, gender, age, social status, values, and beliefs in traditions that have been inherited. Practical Implication: Woven in these cloths are the lost local wisdom, and therefore, aesthetics on the cloths are like mirrors reflecting the background of people in this region that is fading away. These cloths are pages of a local history book that is of importance and value worth for preservation and publicity so that they are treasured. Government organizations can expand and materialize the knowledge received from the study in accordance with government policy in supporting the One Tambon, One Product project.

Keywords: way of life, rite of placing a baby in a cradle, Masoyawi rite, Thai Muslims

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Authors: Leah Burton, Sara Cumming, Julianne DiSanto

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Homelessness is a widespread and complex problem in Canada and around the globe. Many Canadians will face homelessness at least once in their lifetime, with several experiencing subsequent bouts or cyclical patterns of housing precarity. While a Housing First approach to homelessness is a long-standing and widely accepted best practice, it is also recognized that the acquisition of life skills is an effective way to reduce cycles of homelessness. Indeed, when individuals are provided with a range of life skills—such as (but not limited to) financial literacy, household management, interpersonal skills, critical thinking, and resource management—they are given the tools required to maintain long-term Housing for a lifetime; thus reducing a repetitive need for services. However, there is limited research regarding the best ways to teach life skills, a problem that has been further complicated in a post-pandemic world, where services are being delivered online or in a hybrid model of care. More than this, it is difficult to provide life skills on a large scale without losing a client-centered approach to services. This lack of client-centeredness is also seen in the lack of attention to culturally sensitive life skills, which consider the diverse needs of individuals and imbed equity, diversity, and inclusion (EDI) within the skills being taught. This study aims to fill these identified gaps in the literature by employing a community-engaged (CER) approach. Academic, government, funders, front-line staff, and clients at 15 not-for-profits from across the Greater Toronto Area in Ontario, Canada, collaborated to co-create a virtual, client-centric, EDI-informed life skill learning management system. A triangulation methodology was utilized for this research. An environmental scan was conducted for current best practices, and over 100 front-line staff (including workers, managers, and executive directors who work with homeless populations) participated in two separate Creative Problem Solving Sessions. Over 200 individuals with experience in homelessness completed quantitative and open-ended surveys. All sections of this research aimed to discover the areas of skills that individuals need to maintain Housing and to ascertain what a more client-driven EDI approach to life skills training should include. This presentation will showcase the findings on which life skills are deemed essential for homeless and precariously housed individuals.

Keywords: homelessness, housing first, life skills, community engaged research, client- centered

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Authors: Theoni Soublis

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The COVID-19 pandemic created a severe interruption in teaching and learning in K-12 schools. It is essential that educational researchers, teachers, and administrators understand the long term effects that COVID-19 had on a variety of stakeholders in education. This investigation aims to analyze the research since the beginning of the pandemic that focuses specifically on teacher retention, resilience, and training. The results of this investigation will help to inform future research in order to better understand how the institution of education can continue to be prepared and to better prepare for future significant shifts in the modalities of instruction. The results of this analysis will directly impact the field of education as it will broaden the scope of understanding regarding how COVID- 19 impacted teaching and learning. The themes that will emerge from the data analysis will directly inform policy makers, administrators, and researchers about how to best implement training and curriculum design in order to support teacher effectiveness this in the classroom. Educational researchers have written about how teacher morale plummeted and how many teachers reported early burnout and higher stress levels. Teachers’ stress and anxiety soared during the COVID-19 pandemic, but so has their resilience and dedication to the field of education. This research aims to understand how public-school teachers overcame teaching obstacles presented to them during COVID-19. Research has been conducted to identify a variety of information regarding the impact the pandemic has had on K-12 teachers, students, and families. This research aims to understand how teachers continued to pursue their teaching objectives without significant training of effective online instruction methods. Not many educators even heard of the video conferencing platform Zoom before the spring of 2020. Researchers are interested in understanding how teachers used their expertise, prior knowledge, and training to institute immediate and effective online learning environments, what types of relationships did teachers build with students while teaching 100% remotely, and how did relationships change with students while teaching remotely? Furthermore, did the teacher-student relationship propel teacher resolve to be successful while teaching during a pandemic. Recent world events have significantly impacted the field of public-school teaching. The pandemic forced teachers to shift their paradigm about how to maintain high academic expectations, meet state curriculum standards, and assess students learning gains to make data-informed decisions while simultaneously adapting modes of instruction through multiple outlets with little to no training on remote, synchronous, asynchronous, virtual, and hybrid teaching. While it would be very interesting to study how teaching positively impacted students learning during the pandemic, I am more interested in understanding how teaches stayed the course and maintained their mental health while dealing with the stress and pressure of teaching during COVID-19.

Keywords: teacher retention, COVID-19, teacher education, teacher moral

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Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

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Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

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Authors: Bryan Jefry Sabillon, Arlex Molina Cedillo

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Currently, the raise in the demand of electrical energy as a consequence of the development of technology and population growth, as well as some projections made by ‘La Agencia Internacional de la Energía’ (AIE) and research institutes, reveal alarming data about the expected raise of it in the next few decades. Because of this, something should be made to raise the awareness of the rational and efficient usage of this resource. Because of the global concern of providing electrical energy to isolated areas, projects consisting of energy generation using renewable resources are commonly carried out. On a socioeconomically and cultural point of view, it can be foreseen a positive impact that would result for the society to have this resource. This article is focused on the great potential that Honduras shows, as a country that is looking forward to produce renewable energy due to the crisis that it’s living nowadays. Because of this, we present a detailed research that exhibits the main necessities that the rural communities are facing today, to allay the negative aspects due to the scarcity of electrical energy. We also discuss which should be the type of electrical generation method to be used, according to the disposition, geography, climate, and of course the accessibility of each area. Honduras is actually in the process of developing new methods for the generation of energy; therefore, it is of our concern to talk about renewable energy, the exploitation of which is a global trend. Right now the countries’ main energetic generation methods are: hydrological, thermic, wind, biomass and photovoltaic (this is one of the main sources of clean electrical generation). The use of these resources was possible partially due to the studies made by the organizations that focus on electrical energy and its demand, such as ‘La Cooperación Alemana’ (GIZ), ‘La Secretaria de Energía y Recursos Naturales’ (SERNA), and ‘El Banco Centroamericano de Integración Económica’ (BCIE), which eased the complete guide that is to be used in the protocol to be followed to carry out the three stages of this type of projects: 1) Licences and Permitions, 2) Fincancial Aspects and 3) The inscription for the Protocol in Kyoto. This article pretends to take the reader through the necessary information (according to the difficult accessibility that each zone might present), about the best option of electrical generation in zones that are totally isolated from the net, pretending to use renewable resources to generate electrical energy. We finally conclude that the usage of hybrid systems of generation of energy for small remote communities brings about a positive impact, not only because of the fact of providing electrical energy but also because of the improvements in education, health, sustainable agriculture and livestock, and of course the advances in the generation of energy which is the main concern of this whole article.

Keywords: energy, isolated, renewable, accessibility

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Authors: M. Weller Jones, J. Moffat, J. Taylor, J. Hartland, M. Natarajan

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Background: Uganda’s teenage pregnancy rate remains a significant problem for female and maternal health in the country. Teenage pregnancy is linked to higher rates of maternal and neonatal mortality and morbidity, including preterm labour, obstructed labour, vesicovaginal fistulae, infections, and maternal mental health morbidity. In 2015, the National Strategy to End Child Marriage and Teenage Pregnancy was launched in Uganda. Research is needed so that the interventions in this Strategy can be effectively applied at a local level. This study at Kitovu and Villa Maria Hospitals, two local community hospitals near Masaka, Uganda, aimed to measure change in the local teenage pregnancy rate over the past 5 years; and to explore the awareness and attitudes of teenagers and healthcare professionals towards 1) teenage pregnancy and, 2) the challenges female adolescents still currently face. Method: Teenage delivery rate, type of delivery, incidence of complications in labour and neonatal and maternal outcomes were collected from the labour ward admission books, at both hospitals, for a six month time period in 2011 and 2016. At Kitovu Hospital, qualitative data regarding the experience of, and attitudes towards teenage pregnancy was collected from interviews conducted with 12 maternity staff members and with eight female teenagers, aged 16-19, who were pregnant or post-partum. Results: The proportion of total births to teenage mothers fell from 14% in 2011 to 7% in 2016 (Kitovu), but it remains higher in rural locations (19%, Villa Maria). Beliefs about exacerbating factors included: poor access to contraception; misconceptions that contraception is damaging to women’s health; failing sex education in schools; and poor awareness of national campaigns to reduce teenage pregnancy. Staff felt that the best way to tackle teenage pregnancy was to improve sex education in schools and to sensitise families to these issues. Six of the eight teenagers wanted more frequent sex education and easier, cheap access to contraception. Only one teenager saw positive consequences stating that teenage pregnancy would ‘avoid operations later in life.’ Discussion: Teenage pregnancy is a recognised problem and strategies in the Masaka region should focus on improving sex education in schools and initiating an organisation that educates and supplies free contraception to teenagers.

Keywords: adolescents, attitudes, teenage pregnancy, Uganda

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Authors: Mercedes Rodriguez Sanchez, Laura Luceño Casals

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With the rise of social media, creative people and brands everywhere are constantly generating content. The students with Bachelor's Degrees in Fashion Design use platforms such as Instagram or TikTok to look for inspiration and entertainment, as well as a way to develop their own ideas and share them with a wide audience. Information and Communications Technologies (ICT) have become a central aspect of higher education, virtually affecting every aspect of the student experience. Following the current trend, during the first semester of the second year, a collaborative project across two subjects –Design Management and History of Fashion Design– was implemented. After an introductory class focused on the relationship between fashion and cinema, as well as a brief history of 20th-century fashion, the students freely chose a work team and an iconic look from a movie costume. They researched the selected movie and its sociocultural context, analyzed the costume and the work of the designer, and studied the style, fashion magazines and most popular films of the time. Students then redesigned and recreated the costume, for which they were compelled to recycle the materials they had available at home as an unavoidable requirement of the activity. Once completed the garment, students delivered in-class, team-based presentations supported by the final design, a project summary poster and a making-of video, which served as a documentation tool of the costume design process. The methodologies used include Challenge-Based Learning (CBL), debates, Internet research, application of Information and Communications Technologies, and viewing clips of classic films, among others. After finishing the projects, students were asked to complete two electronic surveys to measure the acquisition of transversal and specific competencies of each subject. Results reveal that this activity helped the students' knowledge acquisition, a deeper understanding of both subjects and their skills development. The classroom dynamic changed. The multidisciplinary approach encouraged students to collaborate with their peers, while educators were better able to keep students' interest and promote an engaging learning process. As a result, the activity discussed in this paper confirmed the research hypothesis: it is positive to propose innovative teaching projects that combine academic research with playful learning environments.

Keywords: cinema, cooperative learning, fashion design, higher education, upcycling

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Authors: Cristina Chaminade, Mandar Kulkarni, Balaji Parthasarathy, Monica Plechero

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The characteristics of a regional innovation system (RIS) and the specificity of the knowledge base of an industry may contribute to create peculiar paths for innovation and development of firms’ geographic extended innovation networks. However, the relative empirical evidence in emerging economies remains underexplored. The paper aims to fill the research gap by means of some recent qualitative research conducted in 2016 in Beijing (China) and Bangalore (India). It analyzes cases studies of firms in the new media industry, a sector that merges different IT competences with competences from other knowledge domains and that is emerging in those RIS. The results show that while in Beijing the new media sector results to be more in line with the existing institutional setting and governmental goals aimed at targeting specific social aspects and social problems of the population, in Bangalore it remains a more spontaneous firms-led process. In Beijing what matters for the development of innovation networks is the governmental setting and the national and regional strategies to promote science and technology in this sector, internet and mass innovation. The peculiarities of recent governmental policies aligned to the domestic goals may provide good possibilities for start-ups to develop innovation networks. However, due to the specificities of those policies targeting the Chinese market, networking outside the domestic market are not so promoted. Moreover, while some institutional peculiarities, such as a culture of collaboration in the region, may be favorable for local networking, regulations related to Internet censorship may limit the use of global networks particularly when based on virtual spaces. Mainly firms with already some foreign experiences and contact take advantage of global networks. In Bangalore, the role of government in pushing networking for the new media industry at the present stage is quite absent at all geographical levels. Indeed there is no particular strategic planning or prioritizing in the region toward the new media industry, albeit one industrial organization has emerged to represent the animation industry interests. This results in a lack of initiatives for sustaining the integration of complementary knowledge into the local portfolio of IT specialization. Firms actually involved in the new media industry face institutional constrains related to a poor level of local trust and cooperation, something that does not allow for full exploitation of local linkages. Moreover, knowledge-provider organizations in Bangalore remain still a solid base for the IT domain, but not for other domains. Initiatives to link to international networks seem therefore more the result of individual entrepreneurial actions aimed at acquiring complementary knowledge and competencies from different domains and exploiting potentiality in different markets. From those cases, it emerges that role of government, soft institutions and organizations in the two RIS differ substantially in the creation of barriers and opportunities for the development of innovation networks and their specific aim.

Keywords: regional innovation system, emerging economies, innovation network, institutions, organizations, Bangalore, Beijing

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Authors: Maja S. Todorovic

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This paper aims to promote entrepreneurial storytelling by exploring new ideas and learning practices. An entrepreneur needs to be a ‘storyteller’, an ‘epic hero’, capable of offering an emotional connection to his audience, a character with whom audience can identify with, rejoice, suffer, celebrate, fail – simply experience everything. In other words, a successful entrepreneur is giving tangible experience through his business story and that’s what makes his story and business alive. Use of mythology, eulogy, metaphor, epic, fairytales and cartoons, permeated with humor and sudden twists is a winning recipe for a business story that captures attention. In the business case of the Greenesignit! Card game, (educational and brainstorming tool for development of sustainable products) we will demonstrate how an entrepreneur successfully used visual narrative to communicate his story and at the same time as a vehicle to transmute his message in learning tool and product development.

Keywords: animating narrative, entrepreneur, Greeneisgnit! card game, visual storytelling

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Authors: Runlian Miao, Wei Xie, Hong Zhang

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In China, Beijing-Tianjin-Hebei is regarded as a strategically important region because itenjoys highest development in economic development, opening up, innovative capacity and andpopulation. Integrated development of Beijing-Tianjin-Hebei region is increasingly emphasized by the government recently years. In 2014, it has ascended to one of the national great development strategies by Chinese central government. In 2015, Coordinated Development Planning Compendium for Beijing-Tianjin-Hebei Region was approved. Such decisions signify Beijing-Tianjin-Hebei region would lead innovation-driven economic development in China. As an essential factor to achieve national innovation-driven development and significant part of regional industry chain, the optimization of science and technology resources allocation will exert great influence to regional economic transformation and upgrading and innovation-driven development. However, unbalanced distribution, poor sharing of resources and existence of information isolated islands have contributed to different interior innovation capability, vitality and efficiency, which impeded innovation and growth of the whole region. Under such a background, to integrate and vitalize regional science and technology resources and then establish high-end, fast-responding and precise innovation service system basing on regional resources, would be of great significance for integrated development of Beijing-Tianjin-Hebei region and even handling of unbalanced and insufficient development problem in China. This research uses the method of literature review and field investigation and applies related theories prevailing home and abroad, centering service path of science and technology resources for innovation. Based on the status quo and problems of regional development of Beijing-Tianjin-Hebei, theoretically, the author proposed to combine regional economics and new economic geography to explore solution to problem of low resource allocation efficiency. Further, the author puts forward to applying digital map into resource management and building a platform for information co-building and sharing. At last, the author presents the thought to establish a specific service mode of ‘science and technology plus digital map plus intelligence research plus platform service’ and suggestion on co-building and sharing mechanism of 3 (Beijing, Tianjin and Hebei ) plus 11 (important cities in Hebei Province).

Keywords: Beijing-Tianjin-Hebei, science and technology resources, innovation service, digital platform

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Authors: Gikunda Aloise, Mjema Saida, Barasa Herbert, Wanyungu John, Kimani Maureen

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Background: Community Health Workforce (CHW) is health care providers at the community level (Level 1) and serves as a bridge between the community and the formal healthcare system. This human resource has enormous potential to extend healthcare services and ensures that the vulnerable, marginalized, and hard-to-reach populations have access to quality healthcare services at the community and primary health facility levels. However, these cadres are neither recognized, remunerated, nor in most instances, registered in a master list. Management and supervision of CHWs is not easy if their individual demographics, training capacity and incentives is not well documented through a centralized registry. Description: In February 2022, Amref supported the Kenya Ministry of Health in developing a community health workforce database called Community Health Workers Master List Registry (CHWML), which is hosted in Kenya Health Information System (KHIS) tracker. CHW registration exercise was through a sensitization meeting conducted by the County Community Health Focal Person for the Sub-County Community Health Focal Person and Community Health Assistants who uploaded information on individual demographics, training undertaken and incentives received by CHVs. Care was taken to ensure compliance with Kenyan laws on the availability and use of personal data as prescribed by the Data Protection Act, 2019 (DPA). Results and lessons learnt: By June 2022, 80,825 CHWs had been registered in the system; 78,174 (96%) CHVs and 2,636 (4%) CHAs. 25,235 (31%) are male, 55,505 (68%) are female & 85 (1%) are transgender. 39,979. (49%) had secondary education and 2500 (3%) had no formal education. Only 27 641 (34%) received a monthly stipend. 68,436 CHVs (85%) had undergone basic training. However, there is a need to validate the data to align with the current situation in the counties. Conclusions/Next steps: The use of CHWML will unlock opportunities for building more resilient and sustainable health systems and inform financial planning, resource allocation, capacity development, and quality service delivery. The MOH will update the CHWML guidelines in adherence to the data protection act which will inform standard procedures for maintaining, updating the registry and integrate Community Health Workforce registry with the HRH system.

Keywords: community health registry, community health volunteers (CHVs), community health workers masters list (CHWML), data protection act

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Authors: Chen Zhang, Nan Chen

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High-dimensional process monitoring becomes increasingly important in many application domains, where usually the process distribution is unknown and much more complicated than the normal distribution, and the between-stream correlation can not be neglected. However, since the process dimension is generally much bigger than the reference sample size, most traditional nonparametric multivariate control charts fail in high-dimensional cases due to the curse of dimensionality. Furthermore, when the process goes out of control, the influenced variables are quite sparse compared with the whole dimension, which increases the detection difficulty. Targeting at these issues, this paper proposes a new nonparametric monitoring scheme for high-dimensional processes. This scheme first projects the high-dimensional process into several subprocesses using random projections for dimension reduction. Then, for every subprocess with the dimension much smaller than the reference sample size, a local nonparametric control chart is constructed based on the spatial rank test to detect changes in this subprocess. Finally, the results of all the local charts are fused together for decision. Furthermore, after an out-of-control (OC) alarm is triggered, a diagnostic framework is proposed. using the square-root LASSO. Numerical studies demonstrate that the chart has satisfactory detection power for sparse OC changes and robust performance for non-normally distributed data, The diagnostic framework is also effective to identify truly changed variables. Finally, a real-data example is presented to demonstrate the application of the proposed method.

Keywords: random projection, high-dimensional process control, spatial rank, sequential change detection

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