Search results for: online learning/teaching

Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Hela Ghali, Sihem Ben Fredj, Mohamed Ben Rejeb, Sawssen Layouni, Salwa Khefacha, Lamine Dhidah, Houyem Said Laatiri

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Background: Antimicrobial resistance is a growing threat to public health and motivates to improve prevention and control programs both at international (WHO) and national levels. Despite their low pathogenicity, vancomycin-resistant enterococci (VRE) are common nosocomial pathogens in several countries. The high potential for transmission of VRE between patients and the threat to send its resistance genes to other bacteria such as staphylococcus aureus already resistant to meticilin, justify strict control measures. Indeed, in Europe, the proportion of Enterococcus faecium responsible for invasive infections, varies from 1% to 35% in 2011 and less than 5% were resistant to vancomycin. In addition, it represents the second cause of urinary tract and wound infections and the third cause of nosocomial bacteremia in the United States. The nosocomial outbreaks of VRE have been mainly described in intensive care services, hematology-oncology and haemodialysis. An epidemic of VRE has affected our hospital and the objective of this work is to describe the measures put in place. Materials/Methods: Following the alert given by the service of plastic surgery concerning a patient carrier of VRE, a team of the prevention and healthcare security service (doctor + technician) made an investigation. A review of files was conducted to draw the synoptic table and the table of cases. Results: By contacting the microbiology laboratory, we have identified four other cases of VRE and who were hospitalized in Medical resuscitation department (2 cases, one of them was transferred to the Physical rehabilitation department), and Nephrology department (2 cases). The visit has allowed to detect several malfunctions in professional practice. A crisis cell has allowed to validate, coordinate and implement control measures following the recommendations of the Technical Center of nosocomial infections. In fact, the process was to technically isolate cases in their sector of hospitalization, to restrict the use of antibiotics, to strength measures of basic hygiene, and to make a screening by rectal swab for both cases and contacts (other patients and health staff). These measures have helped to control the situation and no other case has been reported for a month. 2 new cases have been detected in the intensive care unit after a month. However, these are short-term strategies, and other measures in the medium and long term should be taken into account in order to face similar outbreaks. Conclusion: The efforts to control the outbreak were not efficient since 2 new cases have been reported after a month. Therefore, a continuous monitoring in order to detect new cases earlier is crucial to minimize the dissemination of VRE.

Keywords: hospitals, nosocomial infection, outbreak, vancomycin-resistant enterococci

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Authors: Mokhlisur Rahman

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Consumers have developed a sense of responsibility in the past decade, reflecting on their purchasing behavior after viewing an advertisement. Consumers tend to buy ideal products that enable them to be judged by their close network in the opinion world. In such value considerations, any information that feeds consumers' desire for social status helps, which becomes capital for educating consumers on the importance of purchasing green products for manufacturing companies. Companies' effort in manufacturing green products to get high conversion demands a good deal of promotion with quality information and engaging representation. Additionally, converting people from traditional to eco-friendly products requires innovative alternatives to replace the existing product. Considering consumers' understanding of products and their purchasing behavior, it becomes essential for the brands to know the extent to which consumers' level of awareness of the ecosystem is to make them more responsive to green products. Another is brand image plays a vital role in consumers' perception regarding the credibility of the claim regarding the product. Brand image is a significant positive influence on the younger generation, and younger generations tend to engage more in pro-environmental behavior, including purchasing sustainable products. For example, Adidas senses the necessity of satisfying consumers with something that brings more profits and serves the planet. Several of their eco-friendly products are already in the market, and one is UltraBOOST DNA parley, made from 3D-printed recycled ocean waste. As a big brand image, Adidas has leveraged an interest among the younger generation by incorporating sustainability into its advertising. Therefore, influential brands' effort in the sustainable revolution through engaging advertisement makes it more prominent by educating consumers about the reason behind launching the product. This study investigates younger consumers' attitudes toward sustainability, brand recognition, exposure to green advertising, willingness to receive more green advertising, purchasing green products, and motivation. The study conducts a market experiment by creating two video advertisements: a sustainable product video advertisement and a non-sustainable product video advertisement. Both the videos have similar content design and the same length of 2 minutes, but the messages are different based on the identical product type college bags. The first video advertisement promotes eco-friendly college bags made from biodegradable raw materials, and the second promotes non-sustainable college bags made from plastics. After viewing the videos, consumers make purchasing decisions and complete an online survey to collect their attitudes toward sustainable products. The study finds the importance of a sense of responsibility to the consumers for climate change issues. Also, it empowers people to take a step, even small, and increases environmental awareness. This study provides companies with the knowledge to participate in sustainable product launches by collecting consumers' perceptions and attitudes toward green products. Also, it shows how important it is to build a brand's image for the younger generation.

Keywords: brand-image, environment, green-advertising, sustainability, younger-consumer

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Authors: Emilie Zimet

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During networking and NCCD moderation meetings, best practices for identifying students who require Literacy Intervention are often discussed. Once these students are identified, consideration is given to the most effective process for prioritising those who have the greatest need for Literacy Support and the allocation of resources, tracking of intervention effectiveness and communicating with teachers/external providers/parents. Through a workshop, the group will investigate best practices to identify students who require literacy support and strategies to communicate and track their progress. In groups, participants will examine what they do in their settings and then compare with other models, including the researcher’s model, to decide the most effective path to identification and communication. Participants will complete a worksheet at the beginning of the session to deeply consider their current approaches. The participants will be asked to critically analyse their own identification processes for Literacy Intervention, ensuring students are not overlooked if they fall into the borderline category. A cut-off for students to access intervention will be considered so as not to place strain on already stretched resources along with the most effective allocation of resources. Furthermore, communicating learning needs and differentiation strategies to staff is paramount to the success of an intervention, and participants will look at the frequency of communication to share such strategies and updates. At the end of the session, the group will look at creating or evolving models that allow for best practices for the identification and communication of Literacy Interventions. The proposed outcome for this research is to develop a model of identification of students requiring Literacy Intervention that incorporates the allocation of resources and communication to key stakeholders. This will be done by pooling information and discussing a variety of models used in the participant's school settings.

Keywords: identification, student selection, communication, special education, school policy, planning for intervention

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Authors: Sumedha Weerasekara, Morgan Miles, Mark Morrison, Branka Krivokapic-Skoko

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This paper is aimed at exploring the interrelationships among entrepreneurial ecosystem factors and entrepreneurial cognition in regional and metropolitan ecosystems. Entrepreneurial ecosystem factors examined include: culture, infrastructure, access to finance, informal networks, support services, access to universities, and the depth and breadth of the talent pool. Using a multivariate approach we explore the impact of these ecosystem factors or elements on entrepreneurial cognition. In doing so, the existing body of knowledge from the literature on entrepreneurial ecosystem and cognition have been blended to explore the relationship between entrepreneurial ecosystem factors and cognition in a way not hitherto investigated. The concept of the entrepreneurial ecosystem has received increased attention as governments, universities and communities have started to recognize the potential of integrated policies, structures, programs and processes that foster entrepreneurship activities by supporting innovation, productivity and employment growth. The notion of entrepreneurial ecosystems has evolved and grown with the advancement of theoretical research and empirical studies. Importance of incorporating external factors like culture, political environment, and the economic environment within a single framework will enhance the capacity of examining the whole systems functionality to better understand the interaction of the entrepreneurial actors and factors within a single framework. The literature on clusters underplays the role of entrepreneurs and entrepreneurial management in creating and co-creating organizations, markets, and supporting ecosystems. Entrepreneurs are only one actor following a limited set of roles and dependent upon many other factors to thrive. As a consequence, entrepreneurs and relevant authorities should be aware of the other actors and factors with which they engage and rely, and make strategic choices to achieve both self and also collective objectives. The study uses stratified random sampling method to collect survey data from 12 different regions in regional and metropolitan regions of NSW, Australia. A questionnaire was administered online among 512 Small and medium enterprise owners operating their business in selected 12 regions in NSW, Australia. Data were analyzed using descriptive analyzing techniques and partial least squares - structural equation modeling. The findings show that even though there is a significant relationship between each and every entrepreneurial ecosystem factors, there is a weak relationship between most entrepreneurial ecosystem factors and entrepreneurial cognition. In the metropolitan context, the availability of finance and informal networks have the largest impact on entrepreneurial cognition while culture, infrastructure, and support services having the smallest impact and the talent pool and universities having a moderate impact on entrepreneurial cognition. Interestingly, in a regional context, culture, availability of finance, and the talent pool have the highest impact on entrepreneurial cognition, while informal networks having the smallest impact and the remaining factors – infrastructure, universities, and support services have a moderate impact on entrepreneurial cognition. These findings suggest the need for a location-specific strategy for supporting the development of entrepreneurial cognition.

Keywords: academic achievement, colour response card, feedback

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Authors: Abdul Rahmat

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Community-based education in the economic empowerment of the family is an attempt to accelerate human development index (HDI) Dumbo Kingdom District of Gorontalo economics (purchasing power) program developed in this activity is the manufacture of functional skills shredded fish, fish balls, fish nuggets, chips anchovies, and corn sticks fish. The target audience of this activity is fishing se mothers subdistrict Dumbo Kingdom include Talumolo Village, Village Botu, Kampung Bugis Village, Village North and Sub Leato South Leato that each village is represented by 20 participants so totaling 100 participants. Time activities beginning in October s/d November 2014 held once a week on every Saturday at 9.00 s/d 13:00/14:00. From the results of the learning process of testing the skills of functional skills of making shredded fish, fish balls, fish nuggets, chips anchovies, fish and corn sticks residents have additional knowledge and experience are: 1) Order the concept include: nutrient content, processing food with fish raw materials , variations in taste, packaging, pricing and marketing sales. 2) Products made: in accordance with the wishes of the residents learned that estimated Eligible selling, product packaging logo creation, preparation and realization of the establishment of Business Study Group (KBU) and pioneered the marketing network with restaurant, store / shop staple food vendors that are around CLC.

Keywords: community development, functional skills, gender, HDI

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Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

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Authors: Camille Charlebois-Plante, Marie-Ève Bourassa, Gaelle Dumel, Meriem Sabir, Louis De Beaumont

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To the extent of our knowledge, there has been little interest in the chronic effects of mild traumatic brain injury (mTBI) on cognition during normal aging. This is rather surprising considering the impacts on daily and social functioning. In addition, sustaining a mTBI during late adulthood may increase the effect of normal biological aging in individuals who consider themselves normal and healthy. The objective of this study was to characterize the persistent neuropsychological repercussions of mTBI sustained during late adulthood, on average 12 months prior to testing. To this end, 35 mTBI patients and 42 controls between the ages of 50 and 69 completed an exhaustive neuropsychological assessment lasting three hours. All mTBI patients were asymptomatic and all participants had a score ≥ 27 at the MoCA. The evaluation consisted of 20 standardized neuropsychological tests measuring memory, attention, executive and language functions, as well as information processing speed. Performance on tests of visual (Brief Visuospatial Memory Test Revised) and verbal memory (Rey Auditory Verbal Learning Test and WMS-IV Logical Memory subtest), lexical access (Boston Naming Test) and response inhibition (Stroop) revealed to be significantly lower in the mTBI group. These findings suggest that a mTBI sustained during late adulthood induces lasting effects on cognitive function. Episodic memory and executive functions seem to be particularly vulnerable to enduring mTBI effects.

Keywords: cognitive function, late adulthood, mild traumatic brain injury, neuropsychology

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Authors: Laura Seppälä, Ana Nuutinen

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Environmental concerns are increasing the interest in the potential uses of natural dyes. Natural dyes are more safe and environmentally friendly option than synthetic dyes. However, one must be also cautious with natural dyes, because, for example, some dyestuff such as plants or mushrooms, as well as some mordants are poisonous. By natural dyes we mean dyes that are derived from plants, fungi, bark, lichens, algae, insects, and minerals. Different plant parts, such as stems, leaves, flowers, roots, bark, berries, fruits, and cones, can be utilized for textile dyeing and printing, pigment manufacture, and other processes depending on the season. They may be utilized to produce distinctive colour tones that are challenging to do with synthetic dyes. This adds value to textiles and makes them stand out. Synthetic dyes quickly replaced natural dyes, after being developed in the middle of the 19th century, but natural dyes have remained the dyeing method of crafters until recently. This research examines the commercial solutions for natural dyes in many parts of the world, such as Europe, the United States, South America, Africa, Asia, New Zealand, and Australia. This study aims to determine the commercial status of natural dyes. Each continent has its own traditions and specific dyestuffs. The availability of natural dyes can vary depending on several aspects, including plant species, temperature, and harvesting techniques, which poses a challenge to the work of designers and crafters. While certain plants may only provide dyes during specific seasons, others may do so continuously. To find the ideal time to collect natural dyes, it is critical to research various plant species and their harvesting techniques. Furthermore, to guarantee the quality and colour of the dye, plant material must be handled and processed properly. This research was conducted via an internet search, and results were searched systematically for commercial stakeholders in the field. The research question looked at commercial players in the field of natural dyes. This qualitative case study interpreted the data using thematic analysis. Each webpage was screenshotted and analyzed in reflection on to research question. Online content analysis means systematically coding and analyzing qualitative data. The most evident result was that the natural dyes interest in different parts of the World. There are clothing collections dyed with natural dyes, dyestuff stores, and courses for natural dyeing. This article presents the designers who work with natural dyes and actors who are involved with the natural dye industry. Several websites emphasized the safety and environmental benefits of natural dyes. Many of them included eye-catching images of textiles dyed naturally, and the colours of such dyes are thought to be attractive since they are beautiful and natural hues. The search did not find big-scale industrial solutions for natural dyes, but there were several instances of dyeing with natural dyes. Understanding the players, designers, and stakeholders in the natural dye business is the purpose of this article. The comprehension of the current state of the art illustrates the direction that the natural dye business is currently taking.

Keywords: commercial solutions, environmental issues, key stakeholders, natural dyes, sustainability, textile dyeing

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Authors: Sukjai Charoensuk, Penphan Pitaksongkram, Michael Christopher

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Preliminary evidences supported the effectiveness of mindfulness-based interventions in reducing symptoms associated with a variety of medical and psychological conditions. However, the measurements of mindfulness are questionable since they have not been developed based-on Buddhist experiences. The purpose of this qualitative study was to describe meaning and cultivating factors of mindfulness as experienced by Thai females who practice Dhamma. Participants were purposively selected to include 2 groups of Thai females who practice Dhamma. The first group consisted of 6 female Buddhist monks, and the second group consisted of 7 female who practice Dhamma without ordaining. Data were collected using in-depth interview. The instruments used were demographic data questionnaire and guideline for in-depth interview developed by researchers. Content analysis was employed to analyze the data. The results revealed that Thai women who practice Dhamma described their experience in 2 themes, which were meaning and cultivating factors of mindfulness. The meaning composed of 4 categories; 1) Being Present, 2) Self-awareness, 3) Contemplation, and 4) Neutral. The cultivating factors of mindfulness composed of 2 categories; In-personal factors and Ex-personal factors. The In-personal cultivating factors included 4 sub-categories; Faith and Love, the Five Precepts, Sound body, and Practice. The Ex-personal cultivating factors included 2 sub-categories; Serenity, and Learning. These findings increase understanding about meaning of mindfulness and its cultivating factors. These could be used as a guideline to promote mental health and develop nursing interventions using mindfulness based, as well as, develop the instrument for assessing mindfulness in Thai context.

Keywords: cultivating factor, meaning of mindfulness, practice Dhamma, Thai women

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

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Authors: Ayush Aditya

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In today's digitised world, the extent of an individual’s social involvement is largely determined by their interaction over the internet. The Internet has emerged as a primary source of information consumption and a reliable medium for receiving updates on everyday activities. Owing to this change in the information consumption pattern, the internet has also emerged as a hotbed of misinformation. Experts are of the view that media literacy has emerged as one of the most effective strategies for addressing the issue of misinformation. This paper aims to study the evolution of the Kerala government's media literacy policy, its implementation strategy, challenges and opportunities. The objective of this paper is to create a conceptual framework containing details of the implementation strategy based on the Kerala model. Extensive secondary research of literature, newspaper articles, and other online sources was carried out to locate the timeline of this policy. This was followed by semi-structured interview discussions with government officials from Kerala to trace the origin and evolution of this policy. Preliminary findings based on the collected data suggest that this policy is a case of policy by chance, as the officer who headed this policy during the state level implementation was the one who has already piloted a media literacy program in a district called Kannur as the district collector. Through this paper, an attempt is made to trace the history of the media literacy policy starting from the Kannur intervention in 2018, which was started to address the issue of vaccine hesitancy around measles rubella(MR) vaccination. If not for the vaccine hesitancy, this program would not have been rolled out in Kannur. Interviews with government officials suggest that when authorities decided to take up this initiative in 2020, a huge amount of misinformation emerging during the COVID-19 pandemic was the trigger. There was misinformation regarding government orders, healthcare facilities, vaccination, and lockdown regulations, which affected everyone, unlike the case of Kannur, where it was only a certain age group of kids. As a solution to this problem, the state government decided to create a media literacy curriculum to be taught in all government schools of the state starting from standard 8 till graduation. This was a tricky task, as a new course had to be immediately introduced in the school curriculum amid all the disruptions in the education system caused by the pandemic. It was revealed during the interview that in the case of the state-wide implementation, every step involved multiple checks and balances, unlike the earlier program where stakeholders were roped-in as and when the need emerged. On the pedagogy, while the training during the pilot could be managed through PowerPoint presentation, designing a state-wide curriculum involved multiple iterations and expert approvals. The reason for this is COVID-19 related misinformation has lost its significance. In the next phase of the research, an attempt will be made to compare other aspects of the pilot implementation with the state-wide implementation.

Keywords: media literacy, digital media literacy, curriculum based media literacy intervention, misinformation

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Authors: Eugene Mashapa

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The age of information has witnessed countless unprecedented technological developments, which signal the articulation of succinct technological capabilities that can match these cutting-edge technological trends. These changes have impacted patterns in the production, distribution, and consumption of media content, a space that the Film and Publication Board (FPB) is concerned with. Consequently, the FPB is keen to understand the nature and impact of these technological changes on media content regulation. This exploratory study sought to investigate how content regulators in high and middle-income economies have adapted to the changes in this space, seeking insights into innovations, technological and operational, that facilitate continued relevance during this fast-changing environment. The study is aimed at developing recommendations that could assist and inform the organisation in regulating media content as it evolves. Thus, the overall research strategy in this analysis is applied research, and the analytical model adopted is a mixed research design guided by both qualitative and quantitative research instruments. It was revealed in the study that the FPB was significantly impacted by the unprecedented technological advancements in the media regulation space. Additionally, there exists a need for the FPB to understand the current and future penetrations of 4IR technology in the industry and its impact on media governance and policy implementation. This will range from reskilling officials to align with the technological skills to developing technological innovations as well as adopting co-regulatory or self-regulatory arrangements together with content distributors, where more content is distributed in higher volumes and with increased frequency. Importantly, initiating an interactive learning process for both FPB employees and the general public can assist the regulator and improve FPB’s operational efficiency and effectiveness.

Keywords: media, regulation, technology, film and publications board

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Authors: Laura Mendez

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Tribunals for the prosecution of crimes against humanity have been implemented in recent history via international intervention or imposed by one side of the conflict, as in the cases of Rwanda, Iraq, Argentina, and Chile. However, the creation of a criminal tribunal as the result of a peace agreement between formerly warring parties has been unique to the Colombian peace process. As such, the Colombian Jurisdiction for Peace (SJP), or JEP for its Spanish acronym, is viewed as a site of social contestation where actors shape its design and implementation. This study contributes to the literature of transitional justice by analyzing how the framing of the creation of the Colombian tribunal reveals the parties' interests. The analysis frames the interests of the power-brokers, i.e., the government and the Revolutionary Armed Forces of Colombia (FARC), and the victims in light of the tribunal’s functions. The purpose of this analysis is to understand how the interests of the parties are embedded in the designing of the SJP. This paper argues that the creation of the SJP rests on restorative justice, for which the victim, not the perpetrator, is at the center of prosecution. The SJP’s approach to justice moves from prosecution as punishment to prosecution as sanctions. SJP’s alternative sanctions focused on truth, reparation, and restoration are designed to humanize both the victim and the perpetrator in order to achieve reconciliation. The findings also show that requiring the perpetrator to perform labor to repair the victim as an alternative form of sanction aims to foster relations of reintegration and social learning between victims and perpetrators.

Keywords: transitional justice mechanisms, criminal tribunals, Colombia, Colombian Jurisdiction for Peace, JEP

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Authors: Shirley S. Ho, Alisius X. L. D. Leong, Jiemin Looi, Agnes S. F. Chuah

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Nuclear energy is a contentious technology that has attracted much public debate over the years. The prominence of nuclear energy in Southeast Asia (SEA) has burgeoned due to the surge of interest and plans for nuclear development in the region. Understanding public perceptions of nuclear energy in SEA is pertinent given the limited number of studies conducted. In particular, five SEA nations – Singapore, Malaysia, Indonesia, Thailand, and Vietnam are of immediate interest as that they are amongst the most economically developed or developing nations in the SEA region. High energy demands from economic development in these nations have led to considerations of adopting nuclear energy as an alternative source of energy. This study aims to explore whether differences in the nuclear developmental stage in each country affects public perceptions of nuclear energy. In addition, this study seeks to find out about the type and importance of communication credibility as a judgement heuristic in facilitating message acceptance across these five countries. Credibility of a communication channel is a crucial component influencing public perception, acceptance, and attitudes towards nuclear energy. Aside from simply identifying the frequently used communication channels, it is of greater significance to understand public perception of source and media credibility. Given the lack of studies conducted in SEA, this exploratory study adopts a qualitative approach to elicit a spectrum of opinions and insights regarding the key communication aspects influencing public perceptions of nuclear energy. Specifically, the capitals of each of the abovementioned countries - Kuala Lumpur, Bangkok, and Hanoi - were selected, with the exception of Singapore, an island city-state, and Yogyakarta, the most populous island of Indonesia to better understand public perception towards nuclear energy. Focus group discussions were utilized as the mode of data collection to elicit a wide variety of viewpoints held by the participants, which is well-suited for exploratory research. In total, 156 participants took part in the 13 focus group discussions. The participants were either local citizens or permanent residents aged between 18 and 69 years old. Each of the focus groups consists of 8-10 participants, including both male and female participants. The transcripts from each focus group were analysed using NVivo 10, and the text was organised according to the emerging themes or categories. The general public in all the countries was familiar but had no in-depth knowledge with nuclear energy. Four dimensions of nuclear energy communication were identified based on the focus group discussions: communication channels, perceived credibility of sources, circumstances for discussion, and discussion style. The first dimension, communication channels refers to the medium through which participants receive information about nuclear energy. Four types of media emerged from the discussions. They included online and social media, broadcast media, print media, and word-of- mouth (WOM). Collectively, across all five countries, participants were found to engage in different types of knowledge acquisition and information seeking behavior depending on the communication channels used.

Keywords: nuclear energy, public perception, communication, Southeast Asia, source credibility

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Authors: Tavee Cheausuwantavee

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: COVID-19 pandemic significantly has impacted everyone’s life. Persons with disabilities (PWDs) in Thailand have been also effected by COVID-19 situation in many aspects of their lives, while there have been no more appropriate services of the government and providers. Research projects had been only focused on health precaution and protection. Rapid need assessments on populations and vulnerable groups were limited and conducted via social media and an online survey. However, little is known about the real problems and needs of Thai PWDs during the COVID-19 pandemic for an effective plan and integral services for those PWDs. Therefore, this study aims to explore the diverse problems and needs of Thai PWDs in the COVID -19 pandemic. Results from the study can be used by the government and other stakeholders for further effective services. Methods: This study was used a mixed-method design that consisted of both quantitative and qualitative measures. In terms of the quantitative approach, there were 744 PWDs and caregivers of all types of PWDs selected by proportional multistage stratified random sampling according to their disability classification and geographic location. Questionnaires with 59 items regarding participant characteristics, problems, and needs in health, education, employment, and other social inclusion, were distributed to all participants and some caregivers completed questionnaires when PWDs were not able to due to limited communication and/or literacy skills. Completed questionnaires were analyzed by descriptive statistics. For qualitative design, 62 key informants who were PWDs or caregivers were selected by purposive sampling. Ten focus groups, each consisting of 5-6 participants and 7 in-depth interviews from all the groups identified above, were conducted by researchers across five regions. Focus group and in-depth interview guidelines with 6 items regarding problems and needs in health, education, employment, other social inclusion, and their coping during COVID -19 pandemic. Data were analyzed using a modification of thematic content analysis. Results: Both quantitative and qualitative studies showed that PWDs and their caregivers had significant problems and needs all aspects of their life, including income and employment opportunity, daily living and social inclusion, health, and education, respectively. These problems and needs were related to each other, forming a vicious cycle. Participants also learned from negative pandemic to more positive life aspects, including their health protection, financial plan, family cohesion, and virtual technology literacy and innovation. Conclusion and implications: There have been challenges facing all life aspects of PWDs in Thailand during the COVID -19 pandemic, particularly incomes and daily living. All challenges have been the vicious cycle and complicated. There have been also a positive lesson learned of participants from the pandemic. Recommendations for government and stakeholders in the COVID-19 pandemic for PWDs are the following. First, the health protection strategy and policy of PWDs should be promoted together with other quality of life development including income generation, education and social inclusion. Second, virtual technology and alternative innovation should be enhanced for proactive service providers. Third, accessible information during the pandemic for all PWDs must be concerned. Forth, lesson learned from the pandemic should be shared and disseminated for crisis preparation and a positive mindset in the disruptive world.

Keywords: challenge, COVID-19, disability, Thailand

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Authors: Javed Mallick

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In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

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Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

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Authors: Nongcebo Ngcobo

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This research explores the importance of including a multitude of voices in the cultural heritage narrative, particularly in South Africa. The Mashishing project is an extension of and builds on the existing ‘Biesje Poort project’ which is a rock art project that was funded by the National Heritage Council in 2010 - 2013. Hence, the Mashishing marking memories project applies comparable Biesje Poort project objectives, though in a different geographical area. The wider project objectives are to transfer skills, promote social cohesion and empowerment, and lastly to add to the knowledge base of the Mashishing region and the repository of the local museum in the Lydenburg museum. This study is located in the Mashishing area, in Mpumalanga, South Africa. In this area, there were no present multi-vocal heritage projects. This research assesses the Mashishing marking memories project through the culture-centered approach for communication for social change, which examines the impact that the diverse participants have on the operations of the Mashishing project and also investigates whether the culturally diverse participants facilitates or hinders effective participation within the project. Key findings of this research uncovered the significance of participation and diverse voices in the cultural heritage field. Furthermore, this study highlights how unequal power relations affect effective participation. As a result, this study encourages the importance of bringing the researcher and the participant in a safe space to facilitate mutual learning. It also encourages an exchange of roles, where the researcher shifts from being an authoritarian figure to being in the role of a listener.

Keywords: culture, heritage, participation, social change

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Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

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A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

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Authors: Mehdi Soula, Yosra Mani, Estelle Saras, Antoine Drapeau, Raoudha Grami, Mahjoub Aouni, Jean-Yves Madec, Marisa Haenni, Wejdene Mansour

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Multi-resistance to antibiotics in gram-negative bacilli and particularly in enterobacteriaceae, has become frequent in hospitals in Tunisia. However, data on antibiotic resistant bacteria in aquatic products are scarce. The aims of this study are to estimate the proportion of ESBL- and carbapenemase-producing Enterobacterales in seafood (clams and fish) in Tunisia and to molecularly characterize the collected isolates. Two types of seafood were sampled in unrelated markets in four different regions in Tunisia (641 pieces of farmed fish and 1075 mediterranean clams divided into 215 pools, and each pool contained 5 pieces). Once purchased, all samples were incubated in tubes containing peptone salt broth for 24 to 48h at 37°C. After incubation, overnight cultures were isolated on selective MacConkey agar plates supplemented with either imipenem or cefotaxime, identified using API20E test strips (bioMérieux, Marcy-l’Étoile, France) and confirmed by Maldi-TOF MS. Antimicrobial susceptibility was determined by the disk diffusion method on Mueller-Hinton agar plates and results were interpreted according to CA-SFM 2021. ESBL-producing Enterobacterales were detected using the Double Disc Synergy Test (DDST). Carbapenem-resistance was detected using an ertapenem disk and was respectively confirmed using the ROSCO KPC/MBL and OXA-48 Confirm Kit (ROSCO Diagnostica, Taastrup, Denmark). DNA was extracted using a NucleoSpin Microbial DNA extraction kit (Macherey-Nagel, Hoerdt, France), according to the manufacturer’s instructions. Resistance genes were determined using the CGE online tools. The replicon content and plasmid formula were identified from the WGS data using PlasmidFinder 2.0.1 and pMLST 2.0. From farmed fishes, nine ESBL-producing strains (9/641, 1.4%) were isolated, which were identified as E. coli (n=6) and K. pneumoniae (n=3). Among the 215 pools of 5 clams analyzed, 18 ESBL-producing isolates were identified, including 14 E. coli and 4 K. pneumoniae. A low isolation rate of ESBL-producing Enterobacterales was detected 1.6% (18/1075) in clam pools. In fish, the ESBL phenotype was due to the presence of the blaCTX-M-15 gene in all nine isolates, but no carbapenemase gene was identified. In clams, the predominant ESBL phenotype was blaCTX-M-1 (n=6/18). blaCPE (NDM1, OXA48) was detected only in 3 isolates ‘K. pneumoniae isolates’. Replicon typing on the strains carring the ESBL and carbapenemase gene revelead that the major type plasmid carried ESBL were IncF (42.3%) [n=11/26]. In all, our results suggest that seafood can be a reservoir of multi-drug resistant bacteria, most probably of human origin but also by the selection pressure of antibiotic. Our findings raise concerns that seafood bought for consumption may serve as potential reservoirs of AMR genes and pose serious threat to public health.

Keywords: BLSE, carbapenemase, enterobacterales, tunisian seafood

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Authors: Haidy Weliam Megaly Gouda

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Dermatology is often a neglected specialty in low-resource settings despite the high morbidity associated with skin disease. This becomes even more significant when associated with HIV infection, as dermatological conditions are more common and aggressive in HIV-positive patients. African countries have the highest HIV infection rates, and skin conditions are frequently misdiagnosed and mismanaged because of a lack of dermatological training and educational material. The frequent lack of diagnostic tests in the African setting renders basic clinical skills all the more vital. This project aimed to improve the diagnosis and treatment of skin disease in the HIV population in a district hospital in Malawi. A basic dermatological clinical tool was developed and produced in collaboration with local staff and based on available literature and data collected from clinics. The aim was to improve diagnostic accuracy and provide guidance for the treatment of skin disease in HIV-positive patients. A literature search within Embassy, Medline and Google Scholar was performed and supplemented through data obtained from attending 5 Antiretroviral clinics. From the literature, conditions were selected for inclusion in the resource if they were described as specific, more prevalent, or extensive in the HIV population or have more adverse outcomes if they develop in HIV patients. Resource-appropriate treatment options were decided using Malawian Ministry of Health guidelines and textbooks specific to African dermatology. After the collection of data and discussion with local clinical and pharmacy staff, a list of 15 skin conditions was included, and a booklet was created using the simple layout of a picture, a diagnostic description of the disease and treatment options. Clinical photographs were collected from local clinics (with full consent of the patient) or from the book ‘Common Skin Diseases in Africa’ (permission granted if fully acknowledged and used in a not-for-profit capacity). This tool was evaluated by the local staff alongside an educational teaching session on skin disease. This project aimed to reduce uncertainty in diagnosis and provide guidance for appropriate treatment in HIV patients by gathering information into one practical and manageable resource. To further this project, we hope to review the effectiveness of the tool in practice.

Keywords: prevalence and pattern of skin diseases, impact on quality of life, rural Nepal, interventions, quality switched ruby laser, skin color river blindness, clinical signs, circularity index, grey level run length matrix, grey level co-occurrence matrix, local binary pattern, object detection, ring detection, shape identification

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Authors: Shitu Sani

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The paper is advanced on the historical background of the effects of excess work load on lecturers in higher institutions of learning which will assess the socio-economic and psychological disposition of lecturers in the realm of quality production. The paper further discusses the significant roles played by excess work load in general transformation of higher education, which will give the management and stake holders input for successful development of higher education. Even though all forms of work and organizational procedures are potential source of stress and stressors. In higher institution of leaning, lecturers perform many responsibilities such as lecturing, carrying out research and engaging in community services. If these multiple roles could not be handle property it would have result in stress which may have negative impact on job performance, and it’s relation with instructional technology. A sample 191 lecturers were randomly selected from the higher institutions in the northern west zone in Nigerian using two instruments i.e. work load stress management question and job performance Approval, data were collected on lecturers of socio-economic and physiological stress and job performances. Findings of the study shows that lecture experienced excess work load in academic activities. Lecturer’s job performance was negatively influences by socio-economic and psychological work stress. Among the recommendation made were the need for organizing regular induction courses for lecturers on stress, and enhance interpersonal relations among the lecturers as well as provision of electronic public address system to reduce the stress.

Keywords: effect, excess, lecturers, workload

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Authors: Michel Patiño-Sáenz, Martín Haissiner, Jorge Martínez-Cotrina, Daniel Pastor, Hernando Santamaría-García, Maria-Alejandra Tangarife, Agustin Ibáñez, Sandra Baez

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It has been shown that gruesome descriptions of harm can increase the punishment given to a transgressor. This biasing effect is mediated by negative emotions, which are elicited upon the presentation of gruesome descriptions. However, there is a lack of studies inquiring the influence of such descriptions on moral decision-making in people involved in the criminal justice system. Such populations are of special interest since they have experience dealing with gruesome evidence, but also formal education on how to assess evidence and gauge the appropriate punishment according to the law. Likewise, they are expected to be objective and rational when performing their duty, because their decisions can impact profoundly people`s lives. Considering these antecedents, the objective of this study was to explore the influence gruesome written descriptions on moral decision-making in this group of people. To that end, we recruited attorneys, judges and public prosecutors (Criminal justice group, CJ, n=30) whose field of specialty is criminal law. In addition, we included a control group of people who did not have a formal education in law (n=30), but who were paired in age and years of education with the CJ group. All participants completed an online, Spanish-adapted version of a moral decision-making task, which was previously reported in the literature and also standardized and validated in the Latin-American context. A series of text-based stories describing two characters, one inflicting harm on the other, were presented to participants. Transgressor's intentionality (accidental vs. intentional harm) and language (gruesome vs. plain) used to describe harm were manipulated employing a within-subjects and a between-subjects design, respectively. After reading each story, participants were asked to rate (a) the harmful action's moral adequacy, (b) the amount of punishment deserving the transgressor and (c) how damaging was his behavior. Results showed main effects of group, intentionality and type of language on all dependent measures. In both groups, intentional harmful actions were rated as significantly less morally adequate, were punished more severely and were deemed as more damaging. Moreover, control subjects deemed more damaging and punished more severely any type of action than the CJ group. In addition, there was an interaction between intentionality and group. People in the control group rated harmful actions as less morally adequate than the CJ group, but only when the action was accidental. Also, there was an interaction between intentionality and language on punishment ratings. Controls punished more when harm was described using gruesome language. However, that was not the case of people in the CJ group, who assigned the same amount of punishment in both conditions. In conclusion, participants with job experience in the criminal justice system or criminal law differ in the way they make moral decisions. Particularly, it seems that they are less sensitive to the biasing effect of gruesome evidence, which is probably explained by their formal education or their experience in dealing with such evidence. Nonetheless, more studies are needed to determine the impact this phenomenon has on the fulfillment of their duty.

Keywords: criminal justice system, emotions, gruesome descriptions, intentionality, moral decision-making

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Authors: Pawel Martynowicz

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Vibrations are a crucial problem for slender structures such as towers, masts, chimneys, wind turbines, bridges, high buildings, etc., that is why most of them are equipped with vibration attenuation or fatigue reduction solutions. In this work, a slender structure (i.e., wind turbine tower-nacelle model) equipped with nonlinear, semiactive tuned vibration absorber(s) is analyzed. For this study purposes, magnetorheological (MR) dampers are used as semiactive actuators. Several optimal-based approaches to structural vibration attenuation are investigated against the standard ‘ground-hook’ law and passive tuned vibration absorber(s) implementations. The common approach to optimal control of nonlinear systems is offline computation of the optimal solution, however, so determined open loop control suffers from lack of robustness to uncertainties (e.g., unmodelled dynamics, perturbations of external forces or initial conditions), and thus perturbation control techniques are often used. However, proper linearization may be an issue for highly nonlinear systems with implicit relations between state, co-state, and control. The main contribution of the author is the development as well as numerical and experimental verification of the Pontriagin maximum-principle-based vibration control concepts that produce directly actuator control input (not the demanded force), thus force tracking algorithm that results in control inaccuracy is entirely omitted. These concepts, including one-step optimal control, quasi-optimal control, and optimal-based modified ‘ground-hook’ law, can be directly implemented in online and real-time feedback control for periodic (or semi-periodic) disturbances with invariant or time-varying parameters, as well as for non-periodic, transient or random disturbances, what is a limitation for some other known solutions. No offline calculation, excitations/disturbances assumption or vibration frequency determination is necessary, moreover, all of the nonlinear actuator (MR damper) force constraints, i.e., no active forces, lower and upper saturation limits, hysteresis-type dynamics, etc., are embedded in the control technique, thus the solution is optimal or suboptimal for the assumed actuator, respecting its limitations. Depending on the selected method variant, a moderate or decisive reduction in the computational load is possible compared to other methods of nonlinear optimal control, while assuring the quality and robustness of the vibration reduction system, as well as considering multi-pronged operational aspects, such as possible minimization of the amplitude of the deflection and acceleration of the vibrating structure, its potential and/or kinetic energy, required actuator force, control input (e.g. electric current in the MR damper coil) and/or stroke amplitude. The developed solutions are characterized by high vibration reduction efficiency – the obtained maximum values of the dynamic amplification factor are close to 2.0, while for the best of the passive systems, these values exceed 3.5.

Keywords: magnetorheological damper, nonlinear tuned vibration absorber, optimal control, real-time structural vibration attenuation, wind turbines

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Authors: Daniel Pinheiro Da Silva Junior, Aline Paes, Daniel De Oliveira, Christiano Lacerda Ghuerren, Marcio Duran

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The Courts of Accounts are institutions responsible for overseeing and point out irregularities of Public Administration expenses. They have a high demand for processes to be analyzed, whose decisions must be grounded on severity laws. Despite the existing large amount of processes, there are several cases reporting similar subjects. Thus, previous decisions on already analyzed processes can be a precedent for current processes that refer to similar topics. Identifying similar topics is an open, yet essential task for identifying similarities between several processes. Since the actual amount of topics is considerably large, it is tedious and error-prone to identify topics using a pure manual approach. This paper presents a tool based on Machine Learning and Natural Language Processing to assists in building a labeled dataset. The tool relies on Topic Modelling with Latent Dirichlet Allocation to find the topics underlying a document followed by Jensen Shannon distance metric to generate a probability of similarity between documents pairs. Furthermore, in a case study with a corpus of decisions of the Rio de Janeiro State Court of Accounts, it was noted that data pre-processing plays an essential role in modeling relevant topics. Also, the combination of topic modeling and a calculated distance metric over document represented among generated topics has been proved useful in helping to construct a labeled base of similar and non-similar document pairs.

Keywords: courts of accounts, data labelling, document similarity, topic modeling

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Authors: Renata Roma, Christine Tardif-Williams

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Engaging in daily walks with a dog (f.e. Canis lupus familiaris) during the COVID-19 pandemic may be linked to feelings of greater social-connectedness and global self-worth, and lower stress after controlling for mental health issues, lack of physical contact with others, and other stressors associated with the current pandemic. Therefore, maintaining a routine of dog walking might mitigate the effects of stressors experienced during the pandemic and promote well-being. However, many dog owners do not walk their dogs for many reasons, which are related to the owner’s and the dog’s personalities. Note that the consistency of certain personality characteristics among dogs demonstrates that it is possible to accurately measure different dimensions of personality in both dogs and their human counterparts. In addition, behavioural ratings (e.g., the dog personality questionnaire - DPQ) are reliable tools to assess the dog’s personality. Clarifying the relevance of personality factors in the context of young adult-dog relationships can shed light on interactional aspects that can potentially foster protective behaviours and promote well-being among young adults during the pandemic. This study examines if and how nine combinations of dog- and young adult-related personality characteristics (e.g., neuroticism-fearfulness) can amplify the influence of personality factors in the context of dog walking during the COVID-19 pandemic. Responses to an online large-scale survey among 440 (389 females; 47 males; 4 nonbinaries, Mage=20.7, SD= 2.13 range=17-25) young adults living with a dog in Canada were analyzed using structural equation modeling (SEM). As extraversion, conscientiousness, and neuroticism, measured through the five-factor model (FFM) inventory, are related to maintaining a routine of physical activities, these dimensions were selected for this analysis. Following an approach successfully adopted in the field of dog-human interactions, the FFM was used as the organizing framework to measure and compare the human’s and the dog’s personality in the context of dog walking. The dog-related personality dimensions activity/excitability, responsiveness to training, and fearful were correlated dimensions captured through DPQ and were added to the analysis. Two questions were used to assess dog walking. The actor-partner interdependence model (APIM) was used to check if the young adult’s responses about the dog were biased; no significant bias was observed. Activity/excitability and responsiveness to training in dogs were greatly associated with dog walking. For young adults, high scores in conscientiousness and extraversion predicted more walks with the dog. Conversely, higher scores in neuroticism predicted less engagement in dog walking. For participants high in conscientiousness, the dog’s responsiveness to training (standardized=0.14, p=0.02) and the dog’s activity/excitability (standardized=0.15, p=0.00) levels moderated dog walking behaviours by promoting more daily walks. These results suggest that some combinations in young adult and dog personality characteristics are associated with greater synergy in the young adult-dog dyad that might amplify the impact of personality factors on young adults’ dog-walking routines. These results can inform programs designed to promote the mental and physical health of young adults during the Covid-19 pandemic by highlighting the impact of synergy and reciprocity in personality characteristics between young adults and dogs.

Keywords: Covid-19 pandemic, dog walking, personality, structural equation modeling, well-being

Procedia PDF Downloads 104