Search results for: social learning

Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: I. O. Oladipo, Olusegun Adewale Ajayi, Omoniyi Oladipupo Adigun

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Information Communication Technology (ICT) have the potential to contribute to different facets of educational development and effective learning; expanding access, promoting efficiency, improve the quality of learning, enhancing the quality of teaching and provide important mechanism for the economic crisis. Considering the prevalence of unemployment among the higher institution graduates in this nation, in which much seems not to have been achieved in this direction. In view of this, the purpose of this study is to create an awareness and enlightenment of ICT for empowerment opportunities after school. A self-developed modified 4-likert scale questionnaire was used for data collection among Colleges of Education, Physical and Health Education students in Oyo State. Inferential statistical analysis of chi-square set at 0.05 alpha levels was used to analyze the stated hypotheses. The study concludes that awareness and enlightenment of ICT significantly influence empowerment opportunities and recommended that college of education students should be encouraged on the application of ICT for job opportunity after school.

Keywords: employment, empowerment, information communication technology, physical education

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Authors: Brian Fleischli, Shani Robins

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In recent years, the implementation of wisdom skills, including emotional intelligence, mindfulness, empathy, compassion, gratitude, realism (Cognitive-Behavioral Therapy), and humility, within K-12 educational settings has demonstrated significant benefits in reducing stress, anxiety, anger, and conflict among students. This study summarizes the findings of research conducted over several years, showcasing the positive outcomes associated with teaching these skills to elementary and high school students. Additionally, this overview includes an updated synthesis of current literature concerning the application and effectiveness of training these skill sets in K-12 schools. The research outcomes highlight substantial improvements in student well-being and behavior. Demonstrated with treatment group students exhibiting notable reductions in anger, anxiety, depression, and disruptive behaviors compared to control groups. For instance, fourth-grade students showed enhanced empathy, responsibility, and attention, particularly benefiting those with lower initial scores on these measures. Specific interaction effects suggest that older students and males particularly benefit from these interventions, showcasing the nuanced impact of wisdom skill training across different demographics. Furthermore, this presentation emphasizes the critical role of Social and Emotional Learning (SEL) programs in addressing the multifaceted challenges faced by children and adolescents, including mental health issues, academic performance, and social behaviors. The integration of wisdom skills into school curricula not only fosters individual growth and emotional regulation but also enhances overall school climate and academic achievement. In conclusion, the findings contribute to the growing body of empirical evidence supporting the efficacy of teaching wisdom skills in educational settings. The success of these interventions underscores the potential for widespread implementation of evidence-based programs to promote emotional well-being and academic success among students nationwide.

Keywords: wisdom skills, CBT, cognitive behavioral training, mindfulness, empathy, anxiety

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Authors: Behnam Habibi Dargah

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The economics of cost-benefit theory seeks to monitor claims and determine their final price. The cost of litigation is important because it is a measure of the efficiency of the justice system. From an economic point of view, the cost of litigation is considered to be the point of equilibrium of litigation, whereby litigation is regarded as a high-risk investment and is initiated when the costs are less than the probable and expected benefits. Costs are economically separated into private and social costs. Private cost includes material (direct and indirect) and spiritual costs. The social costs of litigation are also subsidized-centric due to the public and governmental nature of litigation and cover both types of bureaucratic bureaucracy and the costs of judicial misconduct. Macroeconomic policy in the economics of justice is the reverse engineering of controlling the social costs of litigation by employing selective litigation and working on the judicial culture to achieve rationality in the monopoly system. Procedures for controlling and managing court costs are also circumscribed to economic patterns in the field. Rational cost allocation model and cost transfer model. The rational allocation model deals with cost-tolerance systems, and the transfer model also considers three models of transferability, including legal, judicial and contractual transferability, which will be described and explored in the present article in a comparative manner.

Keywords: cost of litigation, economics of litigation, private cost, social cost, cost of litigation

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Authors: Annabel Burnley, Michelle St. Clair, Charlotte Dack, Yvonne Wren

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Children with Developmental Language Disorder (DLD) are well documented to experience social and emotional difficulties. Despite this, there is little consensus as to how these difficulties manifest, without which the ability to develop prevention initiatives is limited. An online survey was completed by 107 parents of either child with DLD (‘DLD sample’; n=57), or typically developing children (‘typical sample’; n=50), all aged 6-12 years old. Psychosocial symptom measures were used, alongside 11 psychosocial statements generated from previous qualitative work. Qualitative interviews were then held to understand the manifestation of key difficulties in more depth (n=4). The DLD sample scored significantly higher on all psychosocial statements than the typical sample. Experiencing anxiety (80.7%), requiring routine and sameness (75.4%) and struggling to regulate their emotions (75.4%) were the most common difficulties for a majority of children with DLD. For this DLD sample, family communication and coping styles were found not to contribute to the manifestation of these difficulties. Two separate mediation models were run to understand the role of other psychosocial difficulties in the manifestation of (1) anxiety and (2) social frustration. ‘Intolerance of uncertainty was found to strongly mediate the relationship between DLD diagnosis and symptoms of anxiety. Emotion regulation was found to moderately mediate the relationship between DLD diagnosis and social frustration. Parents appear to cope well with their children’s complex psychosocial needs, but further external intervention is needed. Intervention focussing on intolerance of uncertainty and emotion dysregulation may help the management of anxiety and social frustration. Further research is needed to understand the children’s routined behaviors.

Keywords: psychosocial difficulties, developmental language disorder, specific language impairment, parent, anxiety

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Authors: Naila Naseer

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Emotional Intelligence (EI) concept is not new yet unique and interesting. EI is a person’s ability to be aware of his/her own emotions and to manage, handle and communicate emotions with others effectively. The present study was conducted to assess the relationship between emotional intelligence and age of graduate level students at Allama Iqbal Open University (AIOU). Population consisted of Allama Iqbal Open University students (B.Ed 3rd Semester, Autumn 2007) from Rawalpindi and Islamabad regions. Total number of sample consisted of 469 participants was randomly drawn out by using table of random numbers. Bar-On EQ-i was administered on the participants through personal contact. The instrument was also validated through pilot study on a random sample of 50 participants (B.Ed students Spring 2006), who had completed their B.Ed degree successfully. Data was analyzed and tabulated in percentages, frequencies, mean, standard deviation, correlation, and scatter gram in SPSS (version 16.0 for windows). The results revealed that students with higher age group had scored low on the scale (Bar-On EQ-i). Moreover, the students in low age groups exhibited higher levels of EI as compared with old age students.

Keywords: emotional intelligence, age level, learning, emotion-related feelings

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Authors: Umamaheswari Shanmugam, Silvia Ronchi, Radu Vornicu

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that are able to use the large amount and variety of data generated during healthcare services every day. As we read the news, over 500 machine learning or other artificial intelligence medical devices have now received FDA clearance or approval, the first ones even preceding the year 2000. One of the big advantages of these new technologies is the ability to get experience and knowledge from real-world use and to continuously improve their performance. Healthcare systems and institutions can have a great benefit because the use of advanced technologies improves the same time efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and also to protect patients’ safety. The evolution and the continuous improvement of software used in healthcare must take into consideration the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device approval, but they are necessary to ensure performance, quality, and safety, and at the same time, they can be a business opportunity if the manufacturer is able to define in advance the appropriate regulatory strategy. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems.

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Authors: Syed Asif Hassan, Syed Atif Hassan

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Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

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Authors: Rania Sherif Abd El-Azim

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The role of corporate social responsibility (CSR) in business has evolved and led to an era where industry leaders can no longer overlook the importance of being participative corporate citizens. This is not only because of the media’s skeptical attitude toward whether or not companies’ CSR efforts are sincere but also due to key stakeholders’ ability to hold companies to a higher standard than ever before as companies can gain competitive advantage through CSR. These programs result in addressing global challenges, such as climate, and poverty, or simply improving employee retention, so it has become increasingly clear that CSR is not just the new trend for companies but a necessary tool that organizations must integrate into their overall business strategies to build a stronger reputation as well as to also increase credibility among their key audience and enhance customers’ willingness to repurchase, pay premium price and enhancing positive word of mouth. According to the literature review, the link between CSR and competitive advantage at the firm level has long been an important topic for both CSR researchers and practitioners. Thus CSR can play an important role in enhancing the firm's competitive advantage, which seems an attractive area to investigate specially in Egypt. So, this paper will investigate the role of corporate social responsibility in enhancing the firm competitive advantage.

Keywords: corporate social responsibility, competitive advantage, corporate reputation, customers' willingness to repurchase, willingness to pay premium price, positive word of mouth

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Authors: Heeyeul Kwon, Yongtae Park

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Despite the highly touted benefits, emerging technologies have unleashed pervasive concerns regarding unintended and unforeseen social impacts. Thus, those wishing to create safe and socially acceptable products need to identify such side effects and mitigate them prior to the market proliferation. Various methodologies in the field of technology assessment (TA), namely Delphi, impact assessment, and scenario planning, have been widely incorporated in such a circumstance. However, literatures face a major limitation in terms of sole reliance on participatory workshop activities. They unfortunately missed out the availability of a massive untapped data source of futuristic information flooding through the Internet. This research thus seeks to gain insights into utilization of futuristic data, future-oriented documents from the Internet, as a supplementary method to generate social impact scenarios whilst capturing perspectives of experts from a wide variety of disciplines. To this end, network analysis is conducted based on the social keywords extracted from the futuristic documents by text mining, which is then used as a guide to produce a comprehensive set of detailed scenarios. Our proposed approach facilitates harmonized depictions of possible hazardous consequences of emerging technologies and thereby makes decision makers more aware of, and responsive to, broad qualitative uncertainties.

Keywords: emerging technologies, futuristic data, scenario, text mining

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Authors: Jingwei Du

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The need of optimizing air conditioning systems for existing buildings calls for control methods designed with energy-efficiency as a primary goal. The majority of current control methods boil down to two categories: empirical and model-based. To be effective, the former heavily relies on engineering expertise and the latter requires extensive historical data. Reinforcement Learning (RL), on the other hand, is a model-free approach that explores the environment to obtain an optimal control strategy often referred to as “policy”. This research adopts Proximal Policy Optimization (PPO) to improve chiller plant control, and enable the RL agent to collaborate with experienced engineers. It exploits the fact that while the industry lacks historical data, abundant operational data is available and allows the agent to learn and evolve safely under human supervision. Thanks to the development of language models, renewed interest in RL has led to modern, online, policy-based RL algorithms such as the PPO. This research took inspiration from “alignment”, a process that utilizes human feedback to finetune the pretrained model in case of unsafe content. The methodology can be summarized into three steps. First, an initial policy model is generated based on minimal prior knowledge. Next, the prepared PPO agent is deployed so feedback from both critic model and human experts can be collected for future finetuning. Finally, the agent learns and adapts itself to the specific chiller plant, updates the policy model and is ready for the next iteration. Besides the proposed approach, this study also used traditional RL methods to optimize the same simulated chiller plants for comparison, and it turns out that the proposed method is safe and effective at the same time and needs less to no historical data to start up.

Keywords: chiller plant, control methods, energy efficiency, proximal policy optimization, reinforcement learning

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Authors: Jennifer Gallup, Joel Bocanegra, Greg Callan, Abigail Vaughn

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Students with disabilities (SWD) engaged in a distance summer program delivered over multiple virtual mediums that used gaming principles to teach and practice self-regulated learning (SRL) through the process of exploring possible jobs. Gaming quests were developed to explore jobs and teach transition skills. Students completed specially designed quests that taught and reinforced SRL and problem-solving through individual, group, and teacher-led experiences. SRL skills learned were reinforced through guided job explorations over the context of MinecraftEDU, zoom with experts in the career, collaborations with a team over Marco Polo, and Zoom. The quests were developed and laid out on an accessible web page, with active learning opportunities and feedback conducted within multiple virtual mediums including MinecraftEDU. Gaming mediums actively engage players in role-playing, problem-solving, critical thinking, and collaboration. Gaming has been used as a medium for education since the inception of formal education. Games, and specifically board games, are pre-historic, meaning we had board games before we had written language. Today, games are widely used in education, often as a reinforcer for behavior or for rewards for work completion. Games are not often used as a direct method of instruction and assessment; however, the inclusion of games as an assessment tool and as a form of instruction increases student engagement and participation. Games naturally include collaboration, problem-solving, and communication. Therefore, our summer program was developed using gaming principles and MinecraftEDU. This manuscript describes a virtual learning summer program called Virtual Academy New and Exciting Transitions (VAN) that was redesigned from a face-to-face setting to a completely online setting with a focus on SWD aged 14-21. The focus of VAN was to address transition planning needs such as problem-solving skills, self-regulation, interviewing, job exploration, and communication for transition-aged youth diagnosed with various disabilities (e.g., learning disabilities, attention-deficit hyperactivity disorder, intellectual disability, down syndrome, autism spectrum disorder).

Keywords: autism, disabilities, transition, summer program, gaming, simulations

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Authors: Sri Suryaningsum

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The achievement ‘Best Practice Model’ holds by the government on behalf of the success implementation corporate social responsibility program that held on PT. Kaltim Prima Coal which had operation located in the isolated district in Sanggata, it could be the reference for the other companies to improve the social welfare in surrounding area, especially for the companies that have operated in the isolated area in Indonesia. The rule of Kaltim Prima Coal as the catalyst in the development progress to push up the independence of district especially for the district which has located in surrounding mining operation from village level to the regency level, those programs had written in the 7 field program in Corporate Social Responsibility, it was doing by stakeholders. The stakeholders are village government, sub-district government, Regency and citizen. One of the best programs that implement at PT. Kaltim Prima Coal is Regarding Resettlement that was completed based on Asian Development Bank Resettlement Best Practice and International Financial Corporation Resettlement Action Plan. This program contributed on the resettlement residences to develop the isolated and the neglected district.

Keywords: CSR, isolated, neglected, poverty, mining industry

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Authors: Neda Jebellie

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New information and communication technologies (ICT) not only has revolutionized the world of communication but has also strongly impacted the state of international terrorism. Using the potential of social media, the new wave of terrorism easily can recruit new jihadi members, spread their violent ideology and garner financial support. IS (Islamic State) as the most dangerous terrorist group has already conquered a great deal of social media space and has deployed sophisticated web-based strategies to promote its extremist doctrine. In this respect the vastly popular social media are the perfect tools for IS to establish its virtual Caliphate (e-caliphate) and e-Ommah (e-citizen).Using social media to release violent videos of beheading journalists, burning their hostages alive and mass killing of prisoners are IS strategies to terrorize and subjugate its enemies. Several Twitter and Facebook accounts which are IS affiliations have targeted young generation of Muslims all around the world. In fact IS terrorists use modern resources of communication not only to share information and conduct operations but also justify their violent acts. The strict Wahhabi doctrine of ISIS is based on a fundamental interpretation of Islam in which religious war against non Muslims (Jihad) and killing infidels (Qatal) have been praised and recommended. Via social media IS disseminates its propaganda to inspire sympathizers across the globe. Combating this new wave of terrorism which is exploiting new communication technologies is the most significant challenge for authorities. Before the rise of internet and social media governments had to control only mosques and religious gathering such as Friday sermons(Jamaah Pray) to prevent spreading extremism among Muslims community in their country. ICT and new communication technologies have heighten the challenge of dealing with Islamic radicalism and have amplified its threat .According to the official reports even some of the governments such as UK have created a special force of Facebook warriors to engage in unconventional warfare in digital age. In compare with other terrorist groups, IS has effectively grasped social media potential. Their horrifying released videos on YouTube easily got viral and were re-twitted and shared by thousands of social media users. While some of the social media such as Twitter and Facebook have shut down many accounts alleged to IS but new ones create immediately so only blocking their websites and suspending their accounts cannot solve the problem as terrorists recreate new accounts. To combat cyber terrorism focusing on disseminating counter narrative strategies can be a solution. Creating websites and providing online materials to propagate peaceful and moderate interpretation of Islam can provide a cogent alternative to extremist views.

Keywords: IS-islamic state, cyber terrorism, social media, terrorism, information, communication technologies

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Authors: Nagore Guerra Bilbao, Clemente Lobato Fraile

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This paper outlines the design and development of the MENDEPRO questionnaire, designed to analyze mentoring performance within a professional development process carried out with professors at the University of the Basque Country, Spain. The study took into account the international research carried out over the past two decades into teachers' professional development, and was also based on a thorough review of the most common instruments used to identify and analyze mentoring styles, many of which fail to provide sufficient psychometric guarantees. The present study aimed to gather empirical data in order to verify the metric quality of the questionnaire developed. To this end, the process followed to validate the theoretical construct was as follows: The formulation of the items and indicators in accordance with the study variables; the analysis of the validity and reliability of the initial questionnaire; the review of the second version of the questionnaire and the definitive measurement instrument. Content was validated through the formal agreement and consensus of 12 university professor training experts. A reduced sample of professors who had participated in a lifelong learning program was then selected for a trial evaluation of the instrument developed. After the trial, 18 items were removed from the initial questionnaire. The final version of the instrument, comprising 33 items, was then administered to a sample group of 99 participants. The results revealed a five-dimensional structure matching theoretical expectations. Also, the reliability data for both the instrument as a whole (.98) and its various dimensions (between .91 and .97) were very high. The questionnaire was thus found to have satisfactory psychometric properties and can therefore be considered apt for studying the performance of mentoring in both induction programs for young professors and lifelong learning programs for senior faculty members.

Keywords: higher education, mentoring, professional development, university teaching

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.

Keywords: classification, CRISP-DM, machine learning, predictive quality, regression

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: Eman AbuKhousa, Marwan Z. Bataineh

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The 21^st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.

Keywords: clustering analysis, community of practice, data mining, higher education, new faculty challenges, social network, social influence, professional development

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Authors: John E. Boberg, Steven J. Bourgeois

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The decline in student engagement and motivation through the middle years is well documented and clearly associated with a decline in mathematics achievement that persists through high school. To combat this trend and, very often, to meet high-stakes accountability standards, a growing number of parents, teachers, and schools have implemented various methods to incentivize learning. However, according to Self-Determination Theory, forms of incentivized learning such as public praise, tangible rewards, or threats of punishment tend to undermine intrinsic motivation and learning. By focusing on external forms of motivation that thwart autonomy in children, adults also potentially threaten relatedness measures such as trust and emotional engagement. Furthermore, these controlling motivational techniques tend to promote shallow forms of cognitive engagement at the expense of more effective deep processing strategies. Therefore, any short-term gains in apparent engagement or test scores are overshadowed by long-term diminished motivation, resulting in inauthentic approaches to learning and lower achievement. The current study focuses on the relationships between student trust, engagement, and motivation during these crucial years as students transition from elementary to middle school. In order to test the effects of controlled motivational techniques on achievement in mathematics, this quantitative study was conducted on a convenience sample of 22 elementary and middle schools from a single public charter school district in the south-central United States. The study employed multi-source data from students (N = 1,054), parents (N = 7,166), and teachers (N = 356), along with student achievement data and contextual campus variables. Cross-sectional questionnaires were used to measure the students’ self-regulated learning, emotional and cognitive engagement, and trust in teachers. Parents responded to a single item on incentivizing the academic performance of their child, and teachers responded to a series of questions about their acceptance of various incentive strategies. Structural equation modeling (SEM) was used to evaluate model fit and analyze the direct and indirect effects of the predictor variables on achievement. Although a student’s trust in teacher positively predicted both emotional and cognitive engagement, none of these three predictors accounted for any variance in achievement in mathematics. The parents’ use of incentives, on the other hand, predicted a student’s perception of his or her controlled motivation, and these two variables had significant negative effects on achievement. While controlled motivation had the greatest effects on achievement, parental incentives demonstrated both direct and indirect effects on achievement through the students’ self-reported controlled motivation. Comparing upper elementary student data with middle-school student data revealed that controlling forms of motivation may be taking their toll on student trust and engagement over time. While parental incentives positively predicted both cognitive and emotional engagement in the younger sub-group, such forms of controlling motivation negatively predicted both trust in teachers and emotional engagement in the middle-school sub-group. These findings support the claims, posited by Self-Determination Theory, about the dangers of incentivizing learning. Short-term gains belie the underlying damage to motivational processes that lead to decreased intrinsic motivation and achievement. Such practices also appear to thwart basic human needs such as relatedness.

Keywords: controlled motivation, student engagement, incentivized learning, mathematics achievement, self-determination theory, student trust

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Authors: Andreia Osti

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The context experienced in the face of the COVID-19 pandemic substantially changed the way children communicate and the way literacy teaching was carried out. Officially, according to the Brazilian Institute of Geography and Statistics, children who should be literate were seriously impacted by the pandemic, and it was found that the number of illiterate children increased from 1.4 million, in 2019, to 2.4 million in 2021. In this context, this work presents partial results of an intervention project in which classroom monitoring of students in the literacy phase was carried out. Methodologically, pedagogical games were developed that work on specific reading and writing content, such as 1) games with direct regularities and; 2) Games with contextual regularities. The project involves the elaboration and production of games and their application by the classroom teacher. All work focused on literacy and improving understanding of grapheme and phoneme relationships among students, aiming to improve reading and writing comprehension levels. The project, still under development, is carried out in two schools and supports 60 students. The teachers participate in the research, as they apply the games produced at the university and monitor the children's learning process. The project is developed with financial support for research from FAPESP - in the public education improvement program – PROEDUCA. The initial results show that children are more involved in playful activities, that games provide better moments of interaction in the classroom and that they result in effective learning since they constitute a different way of approaching the content to be taught. It is noteworthy that the pedagogical games produced directly involve the teaching and learning processes of curricular components – in this case, reading and writing, which are basic components in elementary education and constitute teaching methodologies as specific and guided activities are planned in literacy methods. In this presentation, some of the materials developed will be shown, as well as the results of the assessments carried out with the students. In relation to the Sustainable Development objectives (SDGs) linked to this project, we have 4 – Quality Education, 10 – Reduction of inequalities. It is noteworthy that the research seeks to improve Public Education and promote the articulation between theory and practice in the educational context with a view to consolidating the tripod of teaching, research and university extension and promoting a humanized education.

Keywords: didactic, teaching, games, learning, literacy

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Authors: Jakub Stelina, Janina Ciechanowicz-McLean

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Fifty years of existence and development of international environmental law brought a deep disappointment with efficiency and effectiveness of traditional command and control mechanisms of environmental regulation. Agenda 21 agreed during the first Earth Summit in Rio de Janeiro 1992 was one of the first international documents, which explicitly underlined the importance of public participation in environmental protection. This participation includes also the initiatives undertaken by business corporations in the form of private environmental standards setting. Twenty years later during the Rio 20+ Earth Summit the private sector obligations undertaken during the negotiations have proven to be at least as important as the ones undertaken by the governments. The private sector has taken the leading role in environmental standard setting. Among the research methods used in the article two are crucial in the analysis. The comparative analysis of law is the instrument used in the article to analyse the practice of states and private business companies in the field of sustainable development. The article uses economic analysis of law to estimate the costs and benefits of Corporate Social Responsibility Projects in the field of environmental protection. The study is based on the four premises. First is the role of social dialogue, which is crucial for both Corporate Social Responsibility and modern environmental protection regulation. The Aarhus Convention creates a procedural environmental human right to participate in administrative procedures of law setting and environmental decisions making. The public participation in environmental impact assessment is nowadays a universal standard. Second argument is about the role of precaution as a principle of modern environmental regulation. This principle can be observed both in governmental regulatory undertakings and also private initiatives within the Corporate Social Responsibility environmental projects. Even in the jurisdictions which are relatively reluctant to use the principle of preventive action in environmental regulation, the companies often use this standard in their own private business standard setting initiatives. This is often due to the fact that soft law standards are used as the basis for private Corporate Social Responsibility regulatory initiatives. Third premise is about the role of ecological education in environmental protection. Many soft law instruments underline the importance of environmental education. Governments use environmental education only to the limited extent due to the costs of such projects and problems with effects assessment. Corporate Social Responsibility uses various means of ecological education as the basis of their actions in the field of environmental protection. Last but not least Sustainable development is a goal of both legal protection of the environment, and economic instruments of companies development. Modern environmental protection law uses to the increasing extent the Corporate Social Responsibility. This may be the consequence of the limits of hard law regulation. Corporate Social Responsibility is nowadays not only adapting to soft law regulation of environmental protection but also creates such standards by itself, showing new direction for development of international environmental law. Corporate Social Responsibility in environmental protection can be good investment in future development of the company.

Keywords: corporate social responsibility, environmental CSR, environmental justice, stakeholders dialogue

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Authors: Seyed Reza Naghibulsadat

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The nature of communication includes various forms of media productions, which include film and theater. In the current situation, since social networks have emerged, they have brought their own communication capabilities and have features that show speed, public access, lack of media organization and the production of extensive content, and the development of critical thinking; Also, they contain capabilities to develop access to all kinds of media productions, including movies and theater shows; Of course, this works differently in different conditions and communities. In terms of the scale of exploitation, the film has a more general audience, and the theater has a special audience. The film industry is more developed based on more modern technologies, but the theater, based on the older ways of communication, contains more intimate and emotional aspects. ; But in general, the main focus is the development of access to movies and theater shows, which is emphasized by those involved in this field due to the capabilities of social networks. In this research, we will look at these 2 areas and the relevant components for both areas through social networks and also the common points of both types of media production. The main goal of this research is to know the strengths and weaknesses of using social networks for the marketing of movies and theater shows and, at the same time are, also considered the opportunities and threats of this field. The attractions of these two types of media production, with the emergence of social networks, and the ability to change positions, can provide the opportunity to become a media with greater exploitation and higher profitability; But the main consideration is the opinions about these capabilities and the ability to use them for film and theater marketing. The main question of the research is, what are the marketing components for movies and theaters using social media capabilities? What are its strengths and weaknesses? And what opportunities and threats are facing this market? This research has been done with two methods SWOT and meta-analysis. Non-probability sampling has been used with purposeful technique. The results show that a recent approach is an approach based on eliminating threats and weaknesses and emphasizing strengths, and exploiting opportunities in the direction of developing film and theater marketing based on the capabilities of social networks within the framework of local cultural values and presenting achievements on an international scale or It is universal. This introduction leads to the introduction of authentic Iranian culture and foreign enthusiasts in the framework of movies and theater art. Therefore, for this issue, the model for using the capabilities of social networks for movie or theater marketing, according to the results obtained from Respondents, is a model based on SO strategies and, in other words, offensive strategies so that it can take advantage of the internal strengths and made maximum use of foreign situations and opportunities to develop the use of movies and theater performances.

Keywords: marketing, movies, theatrical show, social network potentials

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Authors: Zehra Sultan

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The study is based on the task-based language teaching approach which is found to be very effective in the EFL/ESL classroom. This approach engages learners to acquire the usage of authentic language skills by interacting with the real world through sequence of pedagogical tasks. The use of technology enhances the effectiveness of this approach. This study throws light on the historical background of TBLT and its efficacy in the EFL/ESL classroom. In addition, this study precisely talks about the implementation of this approach in the General Foundation Programme of Muscat College, Oman. It furnishes the list of the pedagogical tasks embedded in the language curriculum of General Foundation Programme (GFP) which are skillfully allied to the College Graduate Attributes. Moreover, the study also discusses the challenges pertaining to this approach from the point of view of teachers, students, and its classroom application. Additionally, the operational success of this methodology is gauged through formative assessments of the GFP, which is apparent in the students’ progress.

Keywords: task-based language teaching, authentic language, communicative approach, real world activities, ESL/EFL activities

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Authors: Helena Costa Oliveira, Carmem Oliveira, Rita Moutinho

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The Balanced Scorecard (BSC) is a continuous strategic monitoring model focused not only on financial issues but also on internal processes, patients/users, and learning and growth. Initially dedicated to business management, it currently serves organizations of other natures - such as hospitals. This paper presents a BSC designed for a Portuguese Acute Pain Unit (APU). This study is qualitative and based on the experience of collaborators at the APU. The management of APU is based on four perspectives – users, internal processes, learning and growth, and financial and legal. For each perspective, there were identified strategic objectives, critical factors, lead indicators and initiatives. The strategic map of the APU outlining sustained strategic relations among strategic objectives. This study contributes to the development of research in the health management area as it explores how organizational insufficiencies and inconsistencies in this particular case can be addressed, through the identification of critical factors, to clearly establish core outcomes and initiatives to set up.

Keywords: acute pain unit, balanced scorecard, hospital management, organizational performance, Portugal

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Authors: Z. Sun

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Health communication is essential in promoting healthy lifestyles, managing disease conditions, and eventually reducing health disparities. The key elements of successful health communication always include the development of communication strategies to engage people in thinking about their health, inform them about healthy choices, persuade them to adopt safe and healthy behaviours, and eventually achieve public health objectives. The use of 'Narrative' is recognised as a kind of health communication strategy to enhance personal and public health due to its potential persuasive effect in motivating and supporting individuals change their beliefs and behaviours by inviting them into a narrative world, breaking down their cognitive and emotional resistance and enhance their acceptance of the ideas portrayed in narratives. Meanwhile, the popularity of social media has provided a novel means of communication for both healthcare stakeholders, and a special group of active social media users (influencers) have started playing a pivotal role in providing health ‘solutions’. Such individuals are often referred to as ‘influencers’ because of their central position in the online communication system and the persuasive effect their actions may have on audiences. They may have established a positive rapport with their audience, earned trust and credibility in a specific area, and thus, their audience considers the information they delivered to be authentic and influential. To our best knowledge, to date, there is no published research that examines the effect of diabetes narratives presented by social media influencers and their impacts on health-related outcomes. The primary aim of this study is to investigate the diabetes narratives presented by social media influencers in the UK because of the new dimension they bring to health communication and the potential impact they may have on audiences' health outcomes. This study is situated within the interpretivist and narrative paradigms. A mixed methodology combining both quantitative and qualitative approaches has been adopted. Qualitative data has been derived to provide a better understanding of influencers’ personal experiences and how they construct meanings and make sense of their world, while quantitative data has been accumulated to identify key social media influencers in the UK and measure the impact of diabetes narratives on audiences. Twitter has been chosen as the social media platform to initially identify key influencers. Two groups of participants are the top 10 key social media influencers in the UK and 100 audiences of each influencer, which means a total of 1000 audiences have been invited. This paper is going to discuss, first of all, the background of the research under the context of health communication; Secondly, the necessity and contribution of this research; then, the major research questions being explored; and finally, the methods to be used.

Keywords: diabetes, health communication, narratives, social media influencers

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Authors: Chang Hung Chen

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Typically the Cause-Related Marketing (CRM) is effective for promoting products, and is also accepted as a role of communication tool for creating a positive image of the corporate. Today, companies are taking Corporate Social Responsibility (CSR) as core activities to build a goal of sustainable development. CRM is not a synonym of CSR. Actually, CRM is a part of CSR, or a type of marketing strategy in CSR framework. This article focuses on the relationship between CSR and CRM, and how the CRM improves the CSR performance of the corporate. The research was conducted through review of literature on the subject area.

Keywords: cause-related marketing, corporate social responsibility, corporate image, consumer behavior

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Authors: Nicole Nicholson, Anne Spillane

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The purpose of this quantitative, descriptive analysis was to determine the success of a post-graduate new teacher education program, designed to teach educators the knowledge and skills necessary to use technology in the classroom, improve the ability to communicate with stakeholders, and implement EBPs and UDL principles into instruction for students with ASD (Autism Spectrum Disorders ). The success of candidates (n=20) in the program provided evidence as to how candidates were effectively able to use technology to create meaningful learning opportunities and implement EBPs for individuals with ASD. ≥90% of participants achieved the following competencies: podcast creation; technology used to share information about assistive technology; and created a resource website on ASD (including information on EBPs, local and national support groups, ASD characteristics, and the latest research on ASD). 59% of students successfully created animation. Results of the analysis indicated that the teacher education program was successful in teaching candidates desired competencies during its first year of implementation.

Keywords: autism spectrum disorders, ASD, evidence based practices, EBP, universal design for learning, UDL

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Authors: Merey M. Sarsengeldin, Alexandr S. Kolokhmatov, Galiya Seidaliyeva, Alexandr Ozerov, Sanim T. Imatayeva

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This series of interdisciplinary studies is an attempt to investigate and develop a scalable model of fair socioeconomic relations on the base of blockchain using positive psychology techniques and Machine Learning algorithms for data analytics. In this particular study, we use hyperinteraction approach and intuition to investigate their influence on 'wisdom of crowds' via created mobile application which was created for the purpose of this research. Along with the public blockchain and private Decentralized Autonomous Organization (DAO) which were elaborated by us on the base of Ethereum blockchain, a model of fair financial relations of members of DAO was developed. We developed a smart contract, so-called, Fair Price Protocol and use it for implementation of model. The data obtained from mobile application was analyzed by ML algorithms. A model was tested on football matches.

Keywords: blockchain, Naïve Bayes algorithm, hyperinteraction, intuition, wisdom of crowd, decentralized autonomous organization

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Authors: Deepak Deshpande, Vikas Minchekar

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Day by day in modern India communal forces became stronger and stronger. Each and every caste group trying to show their strength through massive marches. Such kind of marches or ralliesruinous national integrity in India. To test this assumption present investigation has been carried out. This research was undertaken by using survey techniques. The study has been carried out in two phases. In the first stage, the students’ attitudes were collected while in the second phase the views of the members of the historical association were collected. The social dominance orientation scale and sources of social dominance inventory have been administered on 200 college students belonging to Maratha caste. Analyzed data revealed ahigh level of social dominance in Maratha caste students. Approximately, 80 percent students have reported that they have learned such dominance from the medieval history. The other sources disappear very less prominent. These results and present Indian social situation have been communicated with the members of the historical association of India. The majority members of this association agreed with this reality. The consensus also received on that Maratha caste person experiencing dominance due to the misinterpretation of the King Shivaji Empire; synchronize by politicians. The survey monkey app was used through electronic mail to collect the views on ‘The attitude towards the modification of curricula questionnaire’. The maximum number of members of the historical association agreed to employ to teach the medieval Indian history accordingly the secular perspectives.

Keywords: social dominance orientation, secular perceptive, national integrity, Maratha caste and medieval Indian history

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