Reviewerly/exHarmony huggingface dataset:
Cluster Analysis for Identifying Obesity Subrouops in Health and Nutritional Status Survey Data

This study presents the discovery of meaningful patterns (groups) from the obese samples of health and nutritional survey data by applying various clustering techniques. Due to the mixed nature of the data (qualitative and quantitative variables) in the data set, the best-suited clustering techniques with appropriate dissimilarity metrics were chosen to interpret the meaningful results. The relationships between obesity and the lifestyle affecting factors like demography, socio-economic status, physical activity, and dietary behavior were assessed using four cluster techniques namely Two-Step clustering, Partition Around Medoids (PAM), Agglomerative Hierarchical clustering and, Kohonen Self Organizing Maps (SOMs). The solutions generated by these techniques were analyzed and validated by the help of cluster validity (CV) indices and later on their associations were determined with the obesity classes to discover the pattern from the obese sample. Two-Step clustering and hierarchical clustering outperformed the other applied techniques in identifying the subgroups based on the underlying hidden patterns in the data. Based on the CV indices values and the association analysis (obesity factor with the cluster solutions), two subgroups were generated and profiles of these groups have been reported. The first group belonged to the middle-aged individuals who seem to take care of their lifestyle while the other group belonged to young-aged individuals who in contrast to the first group presented a careless lifestyle factor (i.e., physical activity and dietary behavior). The salient features of these subgroups have been reported and can be proposed for the betterment in the health care industry. The research helped in identifying the interesting subsets/groups within survey data demonstrating similar characteristics and health status (i.e., prevalence of obesity with respect to lifestyle factors like physical activity, dietary behavior etc.) which will help to suggest appropriate measures/steps to be taken by the concerned departments to counter them and prevent in the population.
Intelligent Tutoring System Using Bayesian Network for Vocational High Schools in Indonesia

The lack of personal tutorials during school hours caused the learning approach at Vocational High Schools to be less optimal, and the student's competence is not achieved maximumly. Some computer-based self-learning systems have been developed as solutions to these problems. Unfortunately, the system's weakness is that learning does not pay attention to the diversity of students' abilities. Based on those, this research proposes an Intelligent Tutoring System (ITS) model using Bayesian Network at Vocational High Schools (SMK) to determine the level of students' abilities and teach skills competency materials based on each student's ability level. This is quantitative research with quasi-experimental using one group pretest-posttest design. The research participants were 69 students of the Computer and Network Engineering expertise program at SMK Negeri 4 Gowa and SMK Negeri 1 Gowa, South Sulawesi Province, Indonesia. The results showed significant differences in students' learning outcomes after the use of the proposed ITS; in other words, the proposed ITS was effective in increasing the skill competency of Vocational High School Students. The evaluation results showed that the created Bayesian Network model had a high level of accuracy, reaching 84%.
COVID-19 passes and public health law: Considerations for surveillance and social justice

Abstract The first panellist will focus on the jurists view on the legislative proposal on DCC, discuss proportionality of measure, incl. key considerations for DCC and PLF data combinations. A basic overview on the differences between vaccination, certificates, immunity passports and other passes, and the key characteristics of the DCC will be provided. Feasibility in terms of implementing acts across EU Member-States will be elaborated upon, incl. both potential expiry and revocation, as well as potential remedies in case of emerging issues, i.e., right to DCC, but no vaccine, strong contraindication against vaccination, known issues of reduced immunity despite vaccination, etc. Critical aspects with relevance for both the European and the global dimensions, i.e., GDPR and data transfer agreements, secondary use of health data, human-rights' issues, implications for vulnerable groups, etc., will also be discussed.
Research on the architectural design of the agricultural sightseeing tourist area

This paper combines the intelligent computer-assisted technology to carry out the architectural design and planning of the agricultural sightseeing area, and mainly plans the electricity consumption system of the agricultural sightseeing area to ensure that the agricultural sightseeing area can provide tourists with a good sightseeing experience at night. Moreover, this paper conducts an end-point analysis of the circuit system and analyzes multiple parameters, and combines the construction power demand of agricultural tourism areas to conduct power model analysis. The computer control system integrates various factor control methods, uses advanced control technology and control strategies, and fully considers the relationship between the control variables to realise the automation, intelligence and energy-saving regulation of the greenhouse environment of the agricultural sightseeing area. Finally, this paper takes the greenhouse system as an example to analyze the architectural planning. From the research point of view, it can be known that the architectural design method of agricultural sightseeing tourism area constructed in this paper has certain effects.
Blockchain Driven Access Control Mechanisms, Models and Frameworks: A Systematic Literature Review

Access control or authorization is referred to as the confinement of specific actions of an entity, thereby allowing them to be performed as per certain rules. Blockchain-driven access control mechanisms gained considerable attention directly after applications beyond the premise of cryptocurrency were found. However, there are no systematic efforts to analyze existing empirical evidence. To this end, we aim to synthesize litera- ture to understand the state-of-the-art blockchain driven access control mechanisms with respect to underlying platforms, utilized blockchain properties, nature of the mod- els and associated testbeds and tools. We conducted the review in a systematic way. Meta analysis and thematic synthesis were performed on the findings from relevant primary studies, in order to answer the framed research questions in perspective. We identified 76 relevant primary studies that passed the quality assessment. The problems targeted by relevant studies were single point of failure, security, and privacy, etc. The meta-analysis of the primary studies suggests the use of different blockchain platforms along with several application domains where different blockchain proprieties were utilized. In this paper, we present a systematic literature review of blockchain driven access control systems. In hindsight, we present a taxonomy of blockchain-driven access control systems to better understand the immense implications of this field spanning various application domains
Writing skills deficiency in English for specific purposes (Esp): English for computer science

English for Specific Purposes (ESP) taught at Higher Education Institution (HEI) is a kind of course for students majoring other than English. The descriptive research conducted in one of HEI in Pekanbaru, Riau, involved 65 students majoring in Computer Science of that institution. The data gathered by observation and interviews. This research aimed to find out what were the causes of students' weaknesses in English writing skills, for those were the primary problem that they have compared to other English skills. It was revealed those students had 1) low competence in General English (GE) based on CEFR, 2) had a problem with writing, even in their first language, 3) tendency in taking advantage of Google Translate without further checking, 4) lack of knowledge on lexical choice, sentence construction and the structure of writing, 5) limited practicing time and opportunity.
Revisiting Shallow Discourse Parsing in the PDTB-3: Handling Intra-sentential Implicits

In the PDTB-3, several thousand implicit discourse relations were newly annotated within individual sentences, adding to the over 15,000 implicit relations annotated across adjacent sentences in the PDTB-2.Given that the position of the arguments to these intra-sentential implicits is no longer as well-defined as with inter-sentential implicits, a discourse parser must identify both their location and their sense.That is the focus of the current work.The paper provides a comprehensive analysis of our results, showcasing model performance under different scenarios, pointing out limitations and noting future directions.
The Effect of the Role Playing Method on Reading Aloud Skills in Indonesian Class 1 Subjects at SD Negeri Condong Tasikmalaya

The background of this research is that the value of reading aloud skills in Indonesian class 1 subjects in elementary school is still low, it is necessary to update in improving student learning outcomes and teacher creativity in managing the learning process. This study aims to determine the effect of the Role Playing method on students' reading skills in Indonesian class I subjects at SD Negeri Condong Tasikmalaya. This research is a pre-experimental design type one-group pretest-posttest design. ). The subjects in this study were all 1st grade students at SDN Condong Tasikmalaya, totaling 36 students consisting of 14 girls and 22 boys. Based on the results of the calculation research and data analysis of the measurement results, it can be concluded that: The role playing method has a significant effect on improving students' reading skills at SDN Condong Tasikmalaya. This is indicated by the results of the initial test and the final test of reading aloud skills in the Indonesian language subject which has a greater and significant effect with the result of t arithmetic being greater than t table (6.90 &gt; 1.70) which means that the role playing method has a significant effect. significant effect on the aloud reading skills of the first grade Indonesian students at SDN Condong Tasikmalaya.
“Something Something Hota Hai!” An Explainable Approach towards Sentiment Analysis on Indian Code-Mixed Data

The increasing use of social media sites in countries like India has given rise to large volumes of code-mixed data.Sentiment analysis of this data can provide integral insights into people's perspectives and opinions.Codemixed data is often noisy in nature due to multiple spellings for the same word, lack of definite order of words in a sentence, and random abbreviations.Thus, working with codemixed data is more challenging than monolingual data.Interpreting a model's predictions allows us to determine the robustness of the model against different forms of noise.In this paper, we propose a methodology to integrate explainable approaches into code-mixed sentiment analysis.By interpreting the predictions of sentiment analysis models we evaluate how well the model is able to adapt to the implicit noises present in code-mixed data.
Dataset of Philippine Presidents’ Speeches from 1935 to 2016

Purpose–The dataset was collected to examine and identify possible key topicswithin these texts. Method–Data preparation such as data cleaning, transformation, tokenization, removal of stop wordsfrom both English and Filipino, and word stemmingwas employed in the datasetbefore feeding it to sentiment analysis and the LDA model.Results–The topmost occurring word within the dataset is "development" and there are three (3) likely topics from the speeches of Philippine presidents: economic development, enhancement of public services, and addressing challenges.Conclusion–The datasetwas ableto provide valuable insights contained among official documents. While the study showedthatpresidentshave used their annual address to express their visions for the country. It alsopresentedthat the presidents from 1935 to 2016 faced the same problems during their term.Recommendations–Future researchers may collect other speeches made by presidents during their term;combine them to the dataset used in this studyto furtherinvestigate these important textsby subjecting them to the same methodology used in this study.The dataset may be requested from the authors and it is recommended for further analysis. For example, determine how the speeches of the president reflect the preamble or foundations of the Philippine constitution.
PRESCHOOL PEDAGOGY CONFRONTED WITH THE CORONAVIRUS CHALLENGE

The current theoretical paper is a brief reflection with an analytical bias and a descriptive nature, aimed at registering the likely difficulties and presumed risk consequences for preschool children as a result of physical and social isolation in emergencies such as the Covid-19 pandemic. It applies to parents, students of pedagogical specialties, professionals in the field of education, and is a modest attempt to summarize the hypothetical adverse effects of the social recession in these days of a worldwide hardship. The view of these problems signals to the pedagogical specialists the negatives of the pandemic, unfolding the horizons of their timely preparation and readiness to deal with the influence of isolation on the socialization of children. At this stage, such a theoretical organization is devoid of pretensions to present the complexity of the problem, as well as to be comprehensive in reasoning, despite of a clear sense of the possibility for them to proliferate in a variety of directions, each of which deserves special attention and in-depth analysis.
Accurate Human Parsing Model by Edge Contour and Pose Feature

<p indent=0mm>To address the problem of low accuracy and precision of human parsing due to human pose, edge contour, complexity of clothing accessories and occlusions of human pose joints in dressing scenes, an accurate human parsing model with edge contour and pose features is proposed for dressed human. Firstly, the backbone network based on ResNet-101 is used to represent input human body images and extract the coarse parsing features. Secondly, the edge contour module combining the global and local features after upsampling is constructed to obtain the edge contour of human body. Then, the defined human pose loss function based on human pose is added into pose estimation module to acquire pose features. Finally, coarse parsing feature, edge contour and pose features are integrated into accuracy parsing module, and the accurate human parsing results are output by the combined function of structure loss function and human parsing loss function. The experimental results show that the proposed model can effectively improve 1.96% of mIoU and accuracy on human datasets with more accurate segmentation results for different poses and occlusions of the human body parts.
ITSM Strategy Using CSI on ITIL V.3 To Improve IT Services

The SIMBARU (Academic information System) has The obstacles that currently occur in the SIMBARU process is how to utilize an IT-based academic service system that is ready to run/use in the optimal time optimally, providing services with the right target, fast access that can provide satisfaction to users (user), as well as vision of mission and institutional business objectives can be realized. By using PDCA data analysis Method (Plan, Do, Check, and ACT), it is expected to design a SIP document (Service Improvement Plan) to improve the performance of SIMBARU. The design of SIP documents on SIMBARU can be done by using IT Infrastructure Library V. 3 by analyzing the condition of SIMBARU which then produce output in the form of SIP. Results of this research SIP designed in accordance with the knowledge gained from the results of the analysis, can be used as a strategy to improve IT services in college, which resulted in recommendation of improvement and output in the form of SIP. Repair and SIP recommendations are expected to be implemented to improve IT services, so that the IT service i.e. SIMBARU can help the academic staff in conducting academics in college.
The Effect of the Strategic Role of HR Department in Manufacturing on the Organizational Effectiveness through Education and Training Satisfaction

The purpose of this study is to find out the impact of the strategic role of the HR department in charge of human resource-related tasks, which is the subject of innovation to overcome the immediate crisis situation in the manufacturing industry, on the effectiveness of the organization through satisfaction with education and training.The result of this study is as follows: First, we verified that a strategic role of the HR department has a positive effect on education and training satisfaction.Second, the satisfaction level of education and training and the strategic role of the personnel department have a positive effect on job satisfaction among organizational effectiveness.Third, it was confirmed that education and training satisfaction was found to have a mediating effect in the relationship between HR department's strategic role and job satisfaction.We expect that the results of this study will serve as the basis for re-establishing the role of the HR department dedicated to human resources, which is the important factor not only for innovation but also for overcoming the crisis faced by SMEs and expand their authority and responsibility.The focus of this study is on manufacturing only.This industrial sector is currently facing a serious crisis due to fierce competition and rapidly changing economic environment, but it is better to expand its research focus to more diverse industrial areas.
Rethinking Denoised Auto-Encoding in Language Pre-Training

Pre-trained self-supervised models such as BERT have achieved striking success in learning sequence representations, especially for natural language processing.These models typically corrupt the given sequences with certain types of noise, such as masking, shuffling, or substitution, and then try to recover the original input.However, such pre-training approaches are prone to learning representations that are covariant with the noise, leading to the discrepancy between the pre-training and finetuning stage.To remedy this, we present Con-trAstive Pre-Training (CAPT) to learn noise invariant sequence representations.The proposed CAPT encourages the consistency between representations of the original sequence and its corrupted version via unsupervised instance-wise training signals.In this way, it not only alleviates the pretrain-finetune discrepancy induced by the noise of pre-training, but also aids the pre-trained model in better capturing global semantics of the input via more effective sentence-level supervision.Different from most prior work that focuses on a particular modality, comprehensive empirical evidence on 11 natural language understanding and cross-modal tasks illustrates that CAPT is applicable for both language and vision-language tasks, and obtains surprisingly consistent improvement, including 0.6% absolute gain on GLUE benchmarks and 0.8% absolute increment on NLVR 2 .
Embedded VR Video Image Control System in the Ideological and Political Teaching System Based on Artificial Intelligence

With the increasing development of multimedia teaching, the combination of virtual reality (VR) and video image control has very attractive development prospects in ideological and political teaching, for example, the use of virtual technology in games and so on. However, most virtual reality environments are currently built, and the functional development of artificial intelligence multimedia teaching systems is not comprehensive. An artificial intelligence VR video image control system is constructed for the multimedia teaching system. This article analyzes the development of artificial intelligence multimedia teaching systems and compares the detection performance and efficiency of traditional methods and artificial intelligence multimedia VR ideological and political teaching. Research shows that, in the use of VR to control the images of ideological and political teaching, the average accuracy of these ten video images is 75.68%. This shows that the video image classification and detection algorithm model based on artificial intelligence in this paper can extract deeper and more abstract features to classify the target. The artificial intelligence VR video image control algorithm constructed in this paper can reduce the maximum failure rate by 49.16%, 61.02%, and 66.94%, respectively. Compared with the traditional algorithm, the artificial intelligence VR video image control algorithm constructed in this paper can reduce the storage access delay time of 10 different video images by an average of 15.93%, can obtain about 9.37% performance optimization, and can reduce the video image control time by 7.28% and 10.63%, respectively. For pictures, the artificial intelligence VR video image control system in this article can increase the performance by up to 28.49%.
DIGITALIZACIJA I TRŽIŠTE RADA: RODNA PERSPEKTIVA

Digitalization is the latest phase of long-term transformation of work through technological innovations and implies intensive integration of digital technologies into work processes.In addition to increasing efficiency and productivity, digitalization also brings changes in organizational structures, work skills and ways of working.Central themes in this context are digital skills, job automation, as well as work on digital platforms.This paper analyses the gender perspective of digitalization in the field of work, which is one of the less researched topics.The analysis is based on official thematic reports on digitalization and gender equality in Serbia and the European Union.
A Dynamic Head Importance Computation Mechanism for Neural Machine Translation

Multiple parallel attention mechanisms that use multiple attention heads facilitate greater performance of the Transformer model for various applications e.g., Neural Machine Translation (NMT), text classification.In multi-head attention mechanism, different heads attend to different parts of the input.However, the limitation is that multiple heads might attend to the same part of the input, resulting in multiple heads being redundant.Thus, the model resources are under-utilized.One approach to avoid this is to prune least important heads based on certain importance score.In this work, we focus on designing a Dynamic Head Importance Computation Mechanism (DHICM) to dynamically calculate the importance of a head with respect to the input.Our insight is to design an additional attention layer together with multi-head attention, and utilize the outputs of the multi-head attention along with the input, to compute the importance for each head.Additionally, we add an extra loss function to prevent the model from assigning same score to all heads, to identify more important heads and improvise performance.We analyzed performance of DHICM for NMT with different languages.Experiments on different datasets show that DHICM outperforms traditional Transformer-based approach by large margin, especially, when less training data is available.