Miracle-dz/UniFAR-FTUs huggingface dataset:
UPAYA PREVENTIF DALAM RANGKA PENGAWASAN TERHADAP APBD MELALUI PENJARINGAN ASPIRASI MASYARAKAT OLEH DPRD

Fungsi DPRD yaitu pembentukan perda, anggaran, dan pengawasan berdasarkan Undang-Undang Nomor 23 Tahun 2014 dengan menjaring aspirasi masyarakat. Banyaknya kasus korupsi dalam penyelewengan anggaran Pemerintah Daerah menunjukkan belum maksimalnya pengawasan oleh DPRD. Artikel ini bertujuan menganalisis bagaimana cara yang tepat penjaringan aspirasi masyarakat yang dapat dilakukan oleh DPRD sehingga menjadi upaya preventif dalam kerangka pengawasan terhadap APBD sesuai amanah Undang-Undang. Metode Penelitian yang digunakan yuridis normatif dengan statute approach dan conceptual approach. Hasil Penelitian yang dapat diambil adalah penjaringan aspirasi masyarakat dapat di awal sebelum pembahasan RAPBD maupun dalam pelaksanaan APBD. Cara yang dapat dilakukan yaitu dengan musrenbang (Musyawarah Perencanaan Pembangunan), maksimalisasi media online, media cetak, Focus Group Discussion, atau turun ke masyarakat secara langsung, menggunakan masa reses maupun mengoptimalkan peran dari lembaga institusi lokal non pemerintahan seperti Lembaga Swadaya Masyarakat, organisasi kemasyarakatan dan partai politik.
Analysis of the Tourism Demand for Iberian Ham Routes in Andalusia (Southern Spain): Tourist Profile

: Iberian/serrano ham is a food product with a long tradition in the Spanish diet that is increasingly demanded by national and international consumers. Spain has 5 protected designations of origin (PDO) and two protected geographical indications (PGI) that support the quality of this product, which is manufactured only in the Iberian Peninsula. Since 2013, and based on the culinary product of ham, public entities and some businessmen have been trying to promote tourism related to ham, similar to wine-based tourism. In this study, we attempt to understand the profile of a ham tourist in the three existing routes in Andalusia, as well as ham tourism’s potential demand through seasonal auto-regressive integrated moving average (SARIMA) models. The results show that the profile of a ham tourist is similar to that of other typologies such as a tourist of wine or oil, and the demand has slow growth due to the novelty of this new tourism offering. Thus, there is a need to design strategies that allow the development of ham tourism, which will lead to an increase of wealth via employment in the local community.
An ecological approach of autism spectrum disorders

Autism Spectrum Disorder (ASD) is one of the most researched topics in the last decades. The research led to a better understanding of the field and raised the number of children properly diagnosed. But also, the ASD became a social topic because it affects both families and society as a whole. In this paper, we propose an innovative ecological approach of ASD, based on a holistic approach of it. We recognize the fact that sectorial approaches, such as intervention in school, or family therapy are not sufficient to overcome the ASD. Instead, we propose an ecological model, in which the assessment and interventions are made at individual, family, school and societal level in order to structure a support network for the child and family.
Buying on rumors: how financial news flows affect the share price of Tesla

Purpose The purpose of this paper is to research how corporate communication regarding a specific corporate event (i.e. Tesla’s tweets about a new product) as well as the framing of both the event itself and the market reactions therewith in the news media influence the formation of the share price of the respective company over time. In so doing, the study provides insights into the nature of market-moving information and the role of financial news flows in shaping market reactions in today’s high-frequency news and information environment. Design/methodology/approach Using a multi-method case study approach, combining quantitative intraday event studies with a qualitative text analysis of financial online news and tweets by Elon Musk and Twitter, the authors shed light on the complex interaction between market events, financial information and stock market reactions. The analysis covers a period of four days, encompassing the announcement and introduction of the new battery pack for Model S and X by Tesla as well as the accompanying and follow-up reporting by the financial news media. Findings Findings show that market reactions are driven by business events and expectations among the market rather than the follow-up reporting by financial news media. Financial online news instead seems to heavily rely on Elon Musk’s attention-triggering news to sustain its 24-h airtime with a variety of reporting tools, keeping the highly demanded audience engaged. Eventually, Twitter accounts of media visible companies and personalities, such as Tesla and its CEO Elon Musk, have been found to be useful market information sources for day traders and shareholders to trade at a profit. Originality/value The study is a response to recent discussions about the legitimacy of Twitter communication by CEOs or representatives of listed companies. The findings show that Twitter communication needs to be well considered in light of strict market regulations (e.g. SEC in the USA) regarding insider-trading and the publication of market-relevant information. In addition, corporate financial communication should avoid impetuous communication via social media channels as this could have deterrent effects on the market valuation of a listed company.
Edge detection using parallel ant colony optimization with Hadoop MapReduce: implementation and scalability

The Ant Colony Optimization(ACO) is a popular optimization algorithm that finds use in multiple application areas. Though not among the common uses of this algorithm, edge detection in image analysis is a very functional application of this metaheuristic. To improve the edge detection capabilities, the inherent parallel nature of the ACO method can be combined with the distributed computing framework provided by the Hadoop/Map-Reduce infrastructure. The latter provides a simple, scalable and fault-tolerant distributed processing paradigm that has been popular in industry and the academic community. In this thesis, we explore the Elastic MapReduce service provided by Amazon Web Services to implement ACO algorithm for edge detection in images, and study its scalability and effectiveness by standard metrics. In addition, we demonstrate a filtering technique to reduce the noisy background of images to achieve significant improvement in the accuracy of edge detection.
Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledge discovery

Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS) has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI), machine learning (ML), and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community.
The study of brand extension among generation Y in the Indian market

Brand extensions are viewed as a strategy to expand the portfolio of a company and also for taking the advantage of an established name in the market. The study is aimed at understanding the variables which effect brand extensions. The study has proposed a framework for understanding brand extension and the impact of various variables on brand extension. The framework for the study is empirically tested with the help of structural equation modelling (SEM). Survey of 234 customers is done by using the brand Coca-Cola as a stimulus, and its brand extension Coca-Cola Zero which is a zero sugar variant. The study is based on generation Y customers in Indian market. It has identified that the effect of perceived risk, consumer innovativeness, parent brand reputation and perceived quality on brand extension was positive and significant.
Words for Sale: Early Modern Spanish Women’s Literary Economy

During the early modern period, most Spanish women understood writing as a means of entertainment or selfexpression, but a few seventeenthcentury female writers built a literary career that gave them prestige as well as financial or economic benefits. These women were proactive in the literary field: they wrote works that were of high commercial interest and could be sold to publishers, composed comedies that were purchased by impresarios to be staged in commercial theatres, received commissions from corporations, and wrote to please patrons who rewarded their work. Besides obtaining direct monetary gains, women writers applied the logic of profit: Luisa Sigea (c. 1522– 1560) – like other humanists in the first half of the sixteenth century – worked as Latin teacher or secretary for the Portuguese court. Others used literature for utilitarian reasons to promote themselves, their families or their convents. This chapter shows that although there were fewer of them and that they occupied weaker positions, Spanish women writers were active participants of the literary field like their male peers.
Exploring Servant Leadership in A Top-Down Environment

This study used both Greenleaf's (1977) theory of servant leadership and Spears’s (1995) ten characteristics of servant leadership to explore the concept in a topdown environment. The study proposed to answer the research question: To what extent, if any, is a mayor of a metropolitan area in the Northeast region of the USA displaying at work the ten characteristics of servant leadership as defined by Spears? This study used an exploratory single-case study design and purposeful sampling techniques. The methodology consisted of in-depth, semistructured, open-ended interview with leaders from the community and employees from each of the various departments throughout City Hall. The key finding of this study revealed that four of the ten servant leadership characteristics as defined by Spears were dominant characteristics with regard to the mayor’s leadership style: building community, commitment to the growth of people, empathy, and stewardship. The scope of this research was limited to the mayor of a metropolitan area in the Northeast region of the USA.
Capital inflows, manufacturing exports and economic growth in Nigeria: A threshold regression analysis

The study examined the optimal level of capital inflows for manufacturing exports and economic growth in Nigeria. Annual data from 1981-2017 on foreign direct investment (FDI), foreign portfolio investment (FPI), cross border borrowing CBB (components of capital inflows), financial sector development (FSD), real gross domestic product (RGDP) and manufacturing exports (MEX) were sourced from various issues of the Central Bank of Nigeria (CBN) Statistical Bulletin while data on gross capital formation (GCF) and human capital (HC) were sourced from World Bank Development Indicator (WDI) database. Data collected were analyzed using threshold regression econometric techniques. The results from the optimal level showed that capital inflows (CINF) threshold value of (25.55%) with coefficient of (9.94) annually is the optimal point of capital inflows for Nigeria and the threshold point for manufacturing exports indicates no capital inflows (CINF) threshold value for manufacturing exports in Nigeria. This study concludes that the optimal point of capital inflows for economic growth is 25.55%; any threshold level above this sustainable level, economic growth will be affected negatively in Nigeria but no capital inflows threshold point exist for manufacturing exports and therefore recommends that excessive capital inflows should be avoided in the country so that it does not make administration and management of monetary policy difficult, while the needed capital inflows should be well monitored and channeled into sectors (like manufacturing, agriculture, mining and quarrying etc.) that have absorptive capacity for them. Key words: Capital, inflows, export, growth, optimal, threshold.
Optical transmission testing based on asynchronous sampling techniques: images analysis containing chromatic dispersion using convolutional neural network

The article presents an image analysis method, obtained from an asynchronous delay tap sampling (ADTS) technique, which is used for simultaneous monitoring of various impairments occurring in the physical layer of the optical network. The ADTS method enables the visualization of the optical signal in the form of characteristics (so called phase portraits) that change their shape under the influence of impairments such as chromatic dispersion, polarization mode dispersion and ASE noise. Using this method, a simulation model was built with OptSim 4.0. After the simulation study, data were obtained in the form of images that were further analyzed using the convolutional neural network algorithm. The main goal of the study was to train a convolutional neural network to recognize the selected impairment (distortion); then to test its accuracy and estimate the impairment for the selected set of test images. The input data consisted of processed binary images in the form of two-dimensional matrices, with the position of the pixel. This article focuses only on the analysis of images containing chromatic dispersion.
Parents’ and Teachers’ Views on Digital Communication in Finland

Parents’ and teachers’ well-functioning communication supports their partnership and also benefits pupils’ well-being. Today, communication largely takes place using electronic tools. In the current study, Finnish parents’ (N = 1123) and teachers’ (N = 118) opinions on digital communication in urban and rural areas were studied by applying a new 14-item Digital Communication Scale (DCS) created for the purpose. The three-factor structured DCS was used to elucidate parents’ and teachers’ views on their partnership, feedback, and clarity of messaging. In contrast to some negative headlines and myths, the main finding of our study was overall satisfaction with digital communication, which was seen as supporting the parent-teacher partnership and providing valuable information on pupils’ development and their everyday issues. In particular, rural parents seemed satisfied with digital communication as a partnership-building tool. However, the view of parents was that they received less encouraging feedback about their children than teachers believed they had given. On the other hand, teachers experienced more ambiguity in digital communication than parents. This was more salient among urban teachers than among rural teachers. To summarize, rural parents and rural teachers saw digital communication as serving their collaboration better than did their urban peers. The results of the current study can be used for further development of parent-teacher communication in digital environments.
Secretary of State for Culture, Olympics, Media and Sport

The Secretary of State for Culture, Olympics, Media and Sport (previously Culture, Media and Sport) is a United Kingdom cabinet position with responsibility for the Department for Culture, Media and Sport. The role was created in 1992 by John Major as Secretary of State for National Heritage. The first to fill the role, David Mellor, dubbed it "Minister of Fun". The Cabinet of the United Kingdom is the collective decision-making body of Her Majesty's Government in the United Kingdom, composed of the Prime Minister and some 22 Cabinet Ministers, the most senior of the government ministers.
An Analysis of Selection Models For Non-ignorable Dropout: AnApplication to Multi-centre Trial Data

A common problem encountered in statistical analysis is that of missing data, which occurs when some variables have missing values in some units. The present paper deals with the analysis of longitudinal continuous measurements with incomplete data due to non-ignorable dropout. In repeated measurements data, as one solution to a problem, the selection model assumes a mechanism of outcome-dependent dropout and jointly both the measurement together with dropout process of repeated measures. We consider the construction of a particular type of selection model that uses a logistic regression model to describe the dependency of dropout indicators on the longitudinal measurement. We focus on the use of the Diggle-Kenward model as a tool for assessing the sensitivity of a selection model in terms of the modeling assumptions. Our main objective here is to investigate the influence on inference that might be exerted on the considered data by the dropout process. We restrict attention to a model for repeated Gaussian measures, subject to potentially non-random dropout. To investigate this, we carry out an application for analyzing incomplete longitudinal clinical trial with dropout by using a practical example in the form of a multi-center clinical trial data.
Contested and mistreated? Contested racial identities and unfair treatment due to race

ABSTRACT Race is a dynamic experience in which racial identities are not necessarily validated by outsiders, raising questions about how individuals experience racial bias. This raises questions about reports of racialized unfair treatment and how those who experience racial identity contestation, or when one identifies with a race they believe they are not seen as, experience unfair treatment. Drawing on data from the 2006–2010 Behavioural Risk Factor Surveillance System, this study examines the relationship between racial identity contestation and unfair treatment. This is explored in two distinct settings: at work and when seeking healthcare. The results suggest that identity contestation is associated with the likelihood of perceiving unfair treatment. Contestation is associated with a greater likelihood of reporting unfair treatment due to race for Whites but a lower likelihood of reporting unfair treatment for Latinx and Black individuals. This association is strongest for assessing unfair treatment in the workplace.
ORGANISATIONAL CLIMATE AND COMMITMENT: A SARAWAK VOCATIONAL COLLEGES’ TEACHERS PERSPECTIVE

The purpose of this study was to examine the relationship of organisational climate and commitment from the perspective of vocational colleges’ teachers in Sarawak, Malaysia. A total of six vocational colleges involving 691 teachers participated in this study. The Organisational Climate Index (OCI) and Organisational Commitment Questionnaire (OCQ) were used in measuring the relationship between the four dimensions in organisational climate, namely, collegial leadership, professional teacher behaviour, achievement press and institutional vulnerability and the teachers’ organisational commitment. The results of the statistical analysis indicated collegial leadership, professional teacher behaviour and achievement press showed significant positive relationships with teachers’ organisational commitment. However, institutional vulnerability was found to have no significant relationship with teachers’ organisational commitment. The multiple regression analysis revealed that the best predictor of teachers’ organisational commitment was professional teacher behaviour. Collegial leadership and achievement press were also found to be good predictors of teachers’ organisational commitment. This study contributed in enhancing a better understanding of the relationship between the organisational climate and teachers’ organisational commitment. Several recommendations were made for future research interests.
Long-Term Educational Consequences of Vocational Training in Colombia

Vocational training evaluations focus on trainees’ earnings. This focus may understate these programs’ benefits if training improves participants’ and relatives’ educational attainment. We use Colombian administrative data and a randomization design to examine the long-term employment and education impacts on trainees and their relatives. Eleven years after randomization, trainees increased higher education enrollments, and their relatives increased secondary school attainment. Training helped relax credit constraints for women, while improving field-specific knowledge for men. Including improved education impacts from training increases the program’s estimated internal rate of return from 22.2 percent to 24.1 percent for females and from 10.2 percent to 25.5 percent for males.
Atmospheric Environment and Quality of Life Information Extraction from Twitter with the Use of Self-Organizing Maps

The emergence of Web 2.0 technologies has changed dramatically not only the way users perceive the Internet and interact on it but also the way they influence a community and act in real life aspects. With the rapid rise in use and popularity of social media, people tend to share opinions and observations for almost any subject or event in their everyday life. Consequently, microblogging websites have become a rich data source for user-generated information. The leading opportunity is to take advantage of the wisdom of the crowd and to benefit from collective intelligence in any applicable domain. Towards this direction, we focus on the problem of mining and extracting knowledge from unstructured textual content, for the atmospheric environment domain and its effect to quality of life. As the main contribution, we propose a combined methodology of unsupervised learning methods for analyzing posts from Twitter and clustering textual data into concepts with semantically similar context. By applying Self-Organizing Maps and k-means clustering, we identify possible inter-relationships and patterns of words used in tweets that can form upper concepts of atmospheric and health related topics of discussion. We achieve to group together tweets, from more generic to more specific description levels of their content, according to the selected number of clusters. Strong clusters with significant semantic relatedness among their content are revealed, and hidden relations between concepts and their related semantics are acquired. The results highlight the potential use of social media text streams as a highly-valued supplement source of environmental information and situation awareness.