Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of woman political participation in 2018 Elections and its comparison with elections of 2002, 2008 and 2013

Women’s political participation strengthens their political as well as their empowerment in other fields of life. The discourse of women’s political participation is a matter of concern in the academic circles across the world. The main aim of this study is to provide a complete analysis of changing orientation in the women politics of Charsadda, Khyber Pakhtunkhwa (KP), Pakistan. This study focuses on the effect of political reforms on women’s political participation in Pakistan. Furthermore, this study focuses on the effect of political reforms on women’s public and civic engagements which further contribute to their political participation. The main question that guides the study is that how can political participation of women transform the public sphere of KP, and how would then the transformed public sphere (i.e., the greater political participation of women) enhance democratic politics of KP? Feminist theories i.e., Liberal Feminist Theory and Radical Feminist Theories are used as theoretical framework in this study to examine the question of the effect of political reforms on women’s political participation. The study finds positive effects of the political reforms on women, like awareness about these reforms and civic engagements. The study recommends that women political participation could be enhanced by improving their level of education.
Bidirectional Transformations: A Cross-Discipline Perspective GRACE Meeting Notes, State of the Art, and Outlook

The GRACE International Meeting on Bidirectional Trans- formations was held in December 2008 near Tokyo, Japan. The meeting brought together researchers and practitioners from a variety of sub- disciplines of computer science to share research efforts and help create a new community. In this report, we survey the state of the art and summarize the technical presentations delivered at the meeting. We also describe some insights gathered from our discussions and introduce a new effort to establish a benchmark for bidirectional transformations.
Genetically Optimized Ensemble Classifiers for Multiclass Student Performance Prediction

: The knowledge obtained from data can be useful for the improvement of education systems, giving rise to a research space called Educational Data Mining (EDM). EDM covers the development of methods to explore information collected from educational environments, allowing to understand students more effectively and adequately, providing better educational benefits to them. Machine learning (ML) technologies are growing considerably in recent years. The field of data mining in education provides researchers and educators with metrics of success, failure, dropout, and more, allowing students to guess. The main reason for dropping out of school is not studying. Several researchers have proposed various educational data mining techniques to predict student performance and analyzed the techniques found in educational datasets. This paper proposes a student predictive model with the use of ensemble classifiers. Initially data is pre-processed and an analysis of the correlation between the entrance attributes was carried out to identify the existence of possible redundancies between them, resulting from a very high positive correlation. The filtered attribute is trained and tested with Boosting, Bagging and Random subspace classifiers. Further to improve the accuracy of predictive model genetic algorithm is applied on three classifiers. Genetic Algorithm is an approach used to find optimized solution to search problems and it intend to increase the probability of solving the problem. The process of optimization involves selection of the best option from the available set of options to achieve the desired goal. Selection is done such that the efficiency can be maximized and error can be minimized. An analysis of the correlation between the entrance attributes was carried out to identify the existence of possible redundancies between them, resulting from a very high positive correlation. There is significant improvement in classifier accuracy, when tested mathematic and Portuguese data i.e. 3 % and 11% respectively.
Two traditions of cognitive sociology: An analysis and assessment of their cognitive and methodological assumptions

Cognitive sociology has been split into cultural and interdisciplinary traditions that position themselves differently in relation to the cognitive sciences and make incompatible assumptions about cognition. This article provides an analysis and assessment of the cognitive and methodological assumptions of these two traditions from the perspective of the mechanistic theory of explanation. We argue that while the cultural tradition of cognitive sociology has provided important descriptions about how human cognition varies across cultural groups and historical periods, it has not opened up the black box of cognitive mechanisms that produce and sustain this variation. This means that its explanations for the described phenomena have remained weak. By contrast, the interdisciplinary tradition of cognitive sociology has sought to integrate cognitive scientific concepts and methods into explanatory research on how culture influences action and how culture is stored in memory. Although we grant that interdisciplinary cognitive sociologists have brought many fresh ideas, concepts and methods to cultural sociology from the cognitive sciences, they have not always clarified their assumptions about cognition and their models have
Verhulst mode for predicting foundation settlement

In present, the relation between foundation settlement and time always is set up by permeability-consolidation theory, but because there have many presumptive conditions and the factors acting on the permeability-consolidation, it is also very complicated, and the calculation result is always inconsistent with the observed value. By analyzing the process of the foundation settlement and characteristics of Verhulst mode, the foundation settlement of various periods after-construction can be predicted according to observed values in construction period by applying the Verhulst mode. The predicted example shows that the Verhulst mode is very effective and can be applied to the practice
Incorporating Photovoice Into a Community-Based Intervention With Latinx Families

Photovoice is a qualitative community-based participatory research (CBPR) method used by researchers and communities to inform policy and advocate for community change. Photovoice was piloted within an established community-based intervention, Your Family, Your Neighborhood (YFYN), within a predominantly Latinx community. YFYN is a dual-generation, evidence-based, manualized curriculum supporting and strengthening bonds between parents and their children while fostering neighborhood social cohesion among families living in low-income communities. The photovoice project was conducted with five families (n=20 participants) in English and Spanish. Participants guided the photovoice process to uncover complex community issues from their direct perspectives to accurately capture the challenges and strengths they encounter in their community. Community challenges identified by participants included the dumping of trash in their neighborhood, inadequate space for their children to play, and heavy traffic that impedes their ability to walk their children to school safely. Participants identified three main community strengths: the local park, the Boys & Girls Club, and personal connections with other YFYN family participants. When participants guide the photovoice process, it helps stakeholders understand and uncover complex issues from community members’ direct perspectives to capture the meaning of the issues accurately. Production of knowledge from the community rooted in their lived experience can help reshape the narrative of Latinx families living in low-income communities and allows for social workers to more adequately respond to their specific needs.
Know Sure Thing based Machine Learning Strategy for Predicting Stock Trading Signals

: Although some studies employed technical indicators as input to machine learning models to forecast stock trading signals, there was a noticeable gap between how technical analysts and machine learning professionals used technical indicators. Based on this finding, this study suggested a know sure thing based machine learning (KST-ML) technique for anticipating stock trading signals and compared its results to KST-based trading and Buy-Hold strategies. The main idea behind the KST-ML strategy is to learn and then predict stock trading signals from the relationship between KST indicators such that more accurate predictions can be made. The strategies were assessed based on their annual rate of return (ARR), Sharpe ratio (SR), and percentage of profitable trades executed. In addition, the proposed strategy's performance was compared to that of several intelligent stock trading strategies proposed in the literature. The proposed method clearly outperformed the other two strategies in terms of all three evaluation measures. With a 5.6 SR value, the strategy generated a 67.73% ARR and made 79.38% profitable trades. The results were much better than the results from the KST-based and the Buy-Hold strategies. Furthermore, we found that the annual returns generated by the KST-ML approach were significantly higher than those generated by other intelligent techniques reported in the literature.
Design is a Game: Developing Design Competence in a Game Setting

In this article we propose design games as a way of building design competence for design students as well as for practitioners. We report on four experiments in which game playing, game creation and game reflection has revealed a potential in developing design competence. We show how the use of games can contribute to talking about collaborative design processes, modelling design situations, exploring real life design and improving an existing design practice. Our findings are derived from both educational and industrial settings.
Essential oils of Lippia gracilis and Lippia sidoides chemotypes and their major compounds carvacrol and thymol: nanoemulsions and antifungal activity against Lasiodiplodia theobromae

The aim of this work was to evaluate the antifungal activity of essential oils (EOs) of Lippia gracilis and Lippia sidoides accessions, their major compounds and nanoemulsions. Nanoemulsions with 18% of EO or major compound were produced by spontaneous emulsification method. The EO of two L. gracilis accessions (LGRA-106 and LGRA-109) and two L. sidoides accessions (LSID-102 and LSID-104) were extracted by hydrodistillation and the major compounds thymol and carvacrol were purchased commercially. Antifungal activity was tested against Lasiodiplodia theobromae by calculating the percentage of inhibition of mycelial growth caused by different concentrations (0.1, 0.5, 1.0, 5.0, and 10.0 mL.L-1), in relation to the control. The EOs and their respective nanoemulsions presented as major compounds thymol (LGRA-106: 61.84% and Nano-106: 63.43%; LSID-102: 64.07% and Nano-102: 83.03%) or carvacrol (LGRA-109: 54.56% and Nano-109: 45.63%; LSID-104: 69.06% and Nano-104: 38.66%). Nano-104 presented 35.91% of an unidentified compound. The fungicidal activity of the EOs was similar to that of the major compounds, with a minimum fungicidal concentration of 1.0 mL.L-1 for LGRA-106, LSID-102 as well as for thymol, and 0.5 mL.L-1 for LGRA-109, LSID-104 as well as for carvacrol. The nanoemulsions were only able to reduce the mycelial growth of the fungus except for Nano-104 that exhibited fungicidal activity at the concentration of 10 ml.L-1. It was possible to observe that the EOs exhibited greater toxicity against L. theobromae than the nanoemulsions. These results can help in the development of products for the control of this important phytopathogen.
The Effect of Bridging Exercise to Improve Balance In Post Stroke Patients at Kartini Hospital Jepara

Stroke is a multi-factorial disease with various types of causes accompanied by major clinical manifestations and the main cause of disability and death in developing countries. Impaired standing balance in stroke patients is a very influential disorder and greatly disrupts the activities of post-stroke patients. With these problems, post-stroke patients have difficulty in carrying out independent activities so that they need a good balance. The body's ability to maintain balance or maintain a body of center is regulated by the higher central nervous system through the reception of non-impulse regulation. One of the interventions given is bridging exercise. This exercise was measured using the Berg Balance Scale (BBS) outcome measurement. The purpose of this study was to determine the effect of bridging exercise to improve the balance of post-stroke patients at the Kartini Jepara Hospital. The research method uses an experimental study with a single case report approach. The study was conducted at a hospital in Jepara City on a post-stroke SNH patient named Mr. S, 65 years old, Muslim and a carpenter. Based on the results of the pre-test and post-test scores, it can be concluded that Bridging Exercise has an effect on the balance of post-stroke patients.
The Impact of Reading for Pleasure - Examining the Role of Videos as a Tool for Improving Reading Comprehension

In this study we discuss the value of videos editing designed to enhance reading comprehension in students from the Faculty of Teacher Training of the University of Valencia. First, we present the role of reading for pleasure by summarizing research findings related with multimedia and reading comprehension. In the following part, we describe the methodology with 80 students from 3 different grades which participate in our study. Our results show the positive impact of creating videos in understanding the value of visual literacy in the classroom and the important role of reading for pleasure. Finally, we present the lack of mechanisms of digital video for some students without background knowledge in digital literacy and problem solving in technology.
Insider trading and informed trading patterns

This paper aims to examine how corporate insider trading influences trading patterns of foreign and institutional investors especially in firms with high discretionary accruals and low book-to-market ratios as proxies for information uncertainty. This study uses methods such as trading patterns of informed traders who are considered to gather more precise information before and after insider trading and tests how insider trading affects informed traders. The results of this study provide evidence that insider trading is likely to influence informed traders’ trading patterns. After controlling for firm-specific factors, this study finds that the event and the amount of insider trading affect significantly foreign and institutional trading patterns. Furthermore, the relation between informed trading and insider trading is more enhanced when firms have a high level of discretionary accruals and a low book-to-market ratio. Prior studies have focused on the association between abnormal returns of insider trading and types of insider information disseminated, while informed trading patterns and insider trading with information uncertainty have not been specifically considered. This study enables practitioners to interpret corporate insider trading with information uncertainty on informed trading patterns.
Professional Skills Development Affecting Organizational Learning and Corporate Performance: An Empirical Study in Thailand

This research aims to describe the factors and patterns of relationships involved in dominant professional skills development by focusing on social skills that influence organizational learning for business sustainability and operational efficiency enhancement. The research provides guidelines that hotel businesses in Phuket Province can use to implement strategies in a currently rapidly-changing and competitive environment. This study shows that professional and social skills influencing the organizational performance of the hotel businesses in Phuket include communication, leadership, problem solving, and teamwork skill. This analytical result is based on resource -based and service innovation theories and can be used to improve organizations operating performance.
The Patient Revolution: How Big Data and Analytics Are Transforming the Health Care Experience

In The Patient Revolution, author Krisa Tailor—a noted expert in health care innovation and management—explores, through the lens of design thinking, how information technology will take health care into the experience economy. In the experience economy, patients will shift to being empowered consumers who are active participants in their own care. Tailor explores this shift by creating a vision for a newly designed health care system that's focused on both sickness and wellness, and is driven by data and analytics. The new system seamlessly integrates health into our daily lives, and delivers care so uniquely personalized that no two people are provided identical treatments. Connected through data, everyone across the health care ecosystem, including clinicians, insurers, and researchers, will be able to meet individuals wherever they are in their health journey to reach the ultimate goal of keeping people healthy.
Preschoolers’ Sleep Problems and Peer Competence: The Mediating Effect of Emotion Regulation

Objectives: This study investigated the relationship between preschoolers’ sleep problems, emotion regulation, and peer competence. Specifically, this study examined the mediating role of emotion regulation in the relationship between sleep problems and peer competence in preschoolers.Methods: The study group consisted of 194 preschoolers, aged 4-5 years (84 boys, 110 girls). Their mothers responded to questionnaires on their preschool children’s sleep problems, emotion regulation, and peer competence. Data were analyzed using frequency analysis, descriptive statistics, and correlation analysis with SPSS 22.0. PROCESS macro version 3.4 (Hayes, 2017) was used to analyze the mediating effect.Results: First, preschoolers’ sleep problems had a negative effect on peer competence when emotion regulation was not considered as a mediator; that is, preschoolers who experienced frequent sleep problems showed low peer competence. Second, preschoolers’ sleep problems did not directly affect peer competence when emotion regulation was considered as a mediator. Preschoolers’ sleep problems had only an indirect effect on peer competence through emotion regulation. That is, preschoolers who experienced many sleep problems did not control their emotions well, leading to low peer competence.Conclusion: This study confirmed the importance of sleep by revealing how preschoolers’ sleep problems influence their socioemotional development. The results of this study suggest that preschoolers should have sufficient, high-quality sleep to function better socially and emotionally. Health and parenting educators can utilize these findings in developing and implementing parent education programs that emphasize the importance of building healthy sleep habits for preschoolers.
A Point Cloud-Based Feature Recognition and Path Planning Method

Based on the research background of in situ automatic ultrasonic phased array inspection of irregular porous castings, due to the limited in situ inspection stations, complex shape of irregular porous castings, and extreme multireflection structural features, it is necessary to identify the positioning inspection features among multiple features to be inspected and plan the optimal inspection path. This research is interested in the porous location recognition and its detection path planning of irregular porous castings. For this, a point cloud-based multifeature contour recognition and location algorithm were proposed to simultaneously extract and locate the hole feature and cylindrical feature from an irregular porous castings. Furthermore, a detection path planning method was put forward to search the shortest robot’s detection path based on the above acquired features by visual recognition and positioning technology. First, through the calibration of the industrial robot tool coordinate system and the internal and external parameters of the camera, the “EyeinHand” hand-eye conversion relationship was established. Second, the robot vision system collects the point cloud information of the area to be inspected and performs point cloud splicing, the accuracy of the original data, the removal of noise such as invalid points, outliers and internal noise points, on this basis, the boundary curve of the hole to be inspected was extracted, the cylindrical equation was fitted, its geometric center was calculated, and the central coordinates and axis direction of the contour of the hole to be inspected were obtained. Finally, all the detection paths were traversed through the multibranch tree to obtain the optimal detection path of the detection points of multiple targets. The experimental results show that the positioning accuracy of the feature of the hole to be inspected by the vision system is 0.107 mm, the aperture extraction accuracy is 0.002 mm, the cylinder fitting accuracy is 0.04 mm, and the calculation accuracy of the angle between the two axes is within 0.4. When the number of features to be inspected is different, the average moving distance can be saved by 10.7% by using the end effector after path optimization. The feasibility of in situ automatic ultrasonic phased array detection for irregular porous castings using by visual positioning is verified.
RANCANGAN SISTEM INFORMASI PENYEWAAN BUS DENGAN PENDEKATAN ELECTRONIC CUSTOMER RELATIONSHIP MANAGEMENT (E-CRM)

Perusahaan yang diteliti adalah perusahaan yang bergerak dalam bidang transportasi, melayani jasa angkutan darat baik penumpang maupun barang. Perusahaan tersebut mempunyai tagline “Journey with Pleasure” yang memiliki arti dimana pelanggan yang memanfaatkan jasa layanan kami akan merasakan kenyamanan, pelayanan dan mendapatkan kesan positif selama perjalanan. Masalah yang dihadapi perusahaan saat ini adalah kesulitan dalam mendapatkan pelanggan baru, belum ada informasi penyewaan bus secara online dan testimoni dari pelanggan terhadap pelayanan perusahaan. Tujuan penulisan ini untuk mengenalkan lebih luas profile perusahaan kepada masyarakat dengan dibuatkan sistem berbasis web dan pemberian pelayanan terbaik untuk mendapatkan kepuasan dan loyalitas pelanggan menggunakan pendekatan Electronik Customer Relationship Management (E-CRM). Dalam memodelkan kebutuhan sistem penulis menggunakan UML, database MYSQL dan untuk membuat aplikasi penulis menggunakan PHP. Hasil Akhir dari peneliitian ini yaitu akan dibuatkan website yang digunakan untuk penyewaan/revervasi Bus secara online, informasi ketersediaan bus, dan terdapat testimoni setelah menggunakan pelayanan dari perusahaan. Dengan adanya sistem tersebut diharapkan dapat membantu perusahaan dalam mendapatkan pelanggan baru dan mempertahankan pelanggan lama dengan adanya sistem online dan layanan kepuasan pelanggan yang dapat dilihat langsung masyarakat luas.