Miracle-dz/UniFAR-FTUs huggingface dataset:
Three Main Components for Ulul Albab Teachers’ Professional Development Programme Theory

The role of teachers as purveyors of knowledge and values is crucial to improve the quality of educational processes which leads to the excellence outcomes. The quality of education directly needs the teachers to play their roles. Therefore, the curriculum of education and preparation of teachers should be considered as the central and most crucial in the reconstruction of any educational system. In the context of Ulul Albab, objectives, mission and vision have been drawn up beautifully to achieve the aim of having a generation who is able to use their mind and heart to understand the essence of life based on strong foundation of Al-Quran epistemology. It is therefore, the students of Ulul Albab program that need to be educated, guided, facilitated, and monitored properly to prepare them as Ulul Albab generation. Hence, teachers are expected to play their role as a group who will be responsible to assist these students. This research has been concerned on teachers of the Ulul Albab program as the key implementer of Ulul Albab curriculum. The purpose of this research is to examine the components of professional development (PD) theory for teachers of Ulul Albab program regardless of field of expertise, religious or academic. Six experts and prominence in various fields have been interviewed from purposeful sampling method, in order to investigate the relevancy of developing teachers’ professional development for Ulul Albab teachers. Open coding grounded theory approach by using Qualitative Data Analysis (QDA) Software Atlas ti has been chosen to analyse the data, whereby, the theory develops from the data as it is collected and analysed inductively. In-depth interview method has been using for collecting data and the recorded interviews were transcribed verbatim. The findings have shown that there are three main components; the Input, the Process/Mechanism and the Outcome in which several elements have been drawn up from the findings such as the selection of the right teachers, teachers’ training (preservice and in-service) model, and the nature of Ulul Albab teachers. Each component that represents every element in the findings will be treated as the foundation in developing Ulul Albab Teachers’ Professional Development Programme Theory. From the discussion, the experts collaboratively agree International Journal of Academic Research in Business and Social Sciences Vol. 8 , No. 10, Oct. 2018, E-ISSN: 2222-6990 © 2018 HRMARS 1007 that teachers’ professional development is necessary to prepare teachers with certain characteristics. In a nutshell, it is crucial to train the teachers with a systematic and dynamic professional development according to the concept of Ulul Albab, for the sake of moulding future generation that would be the frontliner of Muslim civilization in the country.
IoT Energy Storage - A Forecast

Abstract Exponential growth in computing, wireless communication, and energy storage efficiency is key to allowing smaller and scalable IoT solutions. These advancements have made it possible to power devices from energy harvesters (EH) and explore other energy storage solutions that can increase the lifetime and robustness of IoT devices. We summarize current trends and limits for the current paradigm as the basis of our forecast. The trend shows that conventional ceramic capacitors are sufficient for energy storage for today’s EH powered wireless IoT devices and that in the future, IoT devices can either perform more advanced tasks with their current volume or be shrunk in size.
Classifiers for Concept-drifting Data Streams: Evaluating Things That Really Matter

When evaluating the performance of a classifier for concept-drifting data streams, two factors are crucial: prediction accuracy and the ability to adapt. The first factor could be analyzed by a simple error-rate, which can be calculated using a holdout test set, chunks of examples, or incrementally after each example [1]. More recently, Gama [2] proposed prequential accuracy as a means of evaluating data stream classifiers and enhancing drift detection methods. For imbalanced data streams, Bifet and Frank [3] proposed the use of the Kappa statistic with a sliding window to assess the classifier’s predictive abilities. However, all of the aforementioned measures, when averaged over an entire stream, loose information about the classifier’s reactions to drifts. For example, an algorithm which has very high accuracy in periods of concept stability, but drastically looses on accuracy when drifts occur can still be characterized by higher overall accuracy than an algorithm which has lower accuracy between drifts, but reacts very well to changes. If we want our algorithm to react quickly to, e.g., market changes, we should choose the second algorithm, but to do so we would have to analyze the entire graphical plot of the classifier’s prequential accuracy, which cannot be easily automated and requires user interaction. To evaluate the second factor, the ability to adapt, separate methods are needed. Some researchers evaluate the classifier’s ability to adapt by comparing drift reaction times [4]. It is important to notice that in order to calculate reaction times, usually a human expert needs to determine moments when drifts start and stop. To automate the assessment of adaptability, Shaker and Hullermeier [5] proposed an approach, called recovery analysis, which uses synthetic datasets to calculate a classifier’s reaction time. A different evaluation method, which uses artificially generated datasets was proposed by Zliobaite [6]. The author put forward three controlled permutation techniques that create datasets which can help inform about the robustness of a classifier to variations in changes. However, approaches such as [5], which calculate absolute or relative drift reaction times, require external knowledge about drifts in real streams or the use of synthetic datasets and, therefore can only be used offline. Furthermore, reaction times are always calculated separately from accuracy which makes choosing the best
Social competence of bilingual and monolingual native English speaking preschoolers: a comparison of parent and teacher perspectives

ABSTRACT Effective peer interaction is fundamental to social development, cognitive development, and academic success. Young children’s early exposure to and development of social competence begins in the home and is further developed upon entry into early childhood programmes. In the United States, where early childhood programmes serve increasingly diverse families, discrepancies between families and teachers in relation to the social competencies valued may exist. This study compares parent and teacher perspectives of children’s social competence (i.e. social skills and problem behaviours) and whether similarities and differences in perspectives are associated with children’s classification as an emergent bilingual or monolingual native English speaker. Findings indicate statistically significant differences in parent and teacher ratings on the empathy, externalizing, and hyperactivity subscales for bilingual children and on the empathy, self-control, internalizing, externalizing, and hyperactivity subscales for monolingual English-speaking children. Recommendations for future research are discussed.
Specificity in English for Academic Purposes (EAP): A Corpus Analysis of Lexical Bundles in Academic Writing

The issue of specificity in English for Academic Purposes (EAP) settings has always challenged linguists and instructors in the field to take a stance on how language should be perceived, that is whether language forms and features are transferable across different academic disciplines or are specific to particular disciplines. This study intends to take this debate a step further by employing a corpus-driven method in identifying a type of phraseological sequence, namely lexical bundles in a corpus of journal articles in the field of International Business Management (IBM). The lexical bundles were compared with those compiled by Simpson-Vlach and Ellis (2010) in their study of Academic Formulas List (AFL) to determine the specificity of the lexical bundles identified in this study. Following frequency-based approach, the corpus tool, Collocate 1.0 was used to extract three- to five-word sequences. These word sequences were manually filtered to exclude irrelevant and meaningless combinations. The qualified lexical bundles were compiled and compared with lexical bundles in AFL (Simpson-Vlach and Ellis 2010) using log-likelihood test. The findings show that three-word lexical bundles are the most common types of lexical bundles in IBM corpus. The comparison reveals that lexical bundles in IBM corpus are relatively specific as compared with lexical bundles in AFL. A discipline-specific approach to the teaching and learning of lexical bundles in EAP settings is therefore advocated to enhance EAP syllabuses and instruction. Keywords: EAP; phraseological sequences; lexical bundles; frequency-based; discipline-specific
Different Approaches for Face Authentication as Part of a Multimodal Biometrics System

This paper describes different approaches for the face authentication from the features and classification abilities point of view. Authors compare two types of features - Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) including their combination. These parameters are classified using Multilayer Neural Network (MLNN) and Support Vector Machines (SVM). Face authentication consists of several steps. The first step contains Viola-Jones algorithm for face detection. Authors resize the detected face for a fixed vector and afterwards, it is converted into grayscale. Next, feature extraction with a simple Min-Max normalization is applied. Obtained parameters are evaluated by classifiers and for each detected face, authors get posterior probability as the output of the classifier. Different approaches for face authentication are compared with each other using False Acceptance Rate (FAR), False Rejection Rate (FRR), Equal Error Rate (EER), Receiver Operating Characteristic (ROC) and Detection Error Tradeoff (DET) curves. The results are verified with AR Face Database and elaborated in a feature extraction and classifier design point of view. Best results were achieved by HOG feature for SVM classifier. Detailed results are listed in the text below.
A Simplified Approach to Calibrating 14C Dates

We propose a simplified approach to the calibration of radiocarbon dates. We use splines through the tree-ring data as calibration curves, thereby eliminating a large part of the statistical scatter of the actual data points. To express the age range, we transform the ± 1 σ and ± 2 σ values of the BP age to calendar dates and interpret them as the 68% and 95% confidence intervals. This approach bypasses the conceptual problems of the transfer of individual probability values from the radiocarbon to the calendar age. We have adapted software to make this calibration possible.
Improving the Performance of the Distributed File System through Anticipated Parallel Processing

In the emerging Big Data scenario, distributed File systems (DFSs) are used for storing and accessing information in a scalable manner. Many cloud computing systems use DFS as the main storage component. The Big Data applications de-ployed in cloud computing systems more frequently perform read operations and less frequently the write operations. So, improving the performance of read access has become an im-portant research issue in DFS. In the literature, many client side caching with appropriate pre fetching techniques are proposed for improving the performance read access in the DFS. A speculation-based approach which uses client side caching is also proposed in the literature for improving the performance of read access in the DFS. In this paper, we have proposed a new read algorithm for the DFS based on anticipated parallel processing. We have evaluated the per- formance of the proposed algorithm using mathematical and simulation methods and the results indicate that the pro-posed algorithm performs better than the speculation-based algorithm proposed in the literature.
Palmer Luckey and the rise of contemporary virtual reality

Despite a lack of consumer interest as recently as 2012, virtual reality (VR) technologies entered the mainstream in 2014 backed by multinational corporations, including Facebook and Google. At the heart of this transition is Palmer Luckey, founder of Oculus and purported ‘face’ of VR. This article develops a case study centred on Palmer Luckey to examine the rise of contemporary VR within the overlapping, contemporaneous contexts of video game culture and the misogynistic gamergate movement. As gamergate expanded its scope with far-right political fervour, Luckey’s political ambitions also expanded in scope. I argue that Luckey’s promotion under the banner of ‘progress’ serves to reify White, male systems of power that are both established and contested within cultures of technological development.
Solving for Pattern: An Ecological Approach to Reshape the Human Building Instinct

The human species’ adaptive advantage is driven by its ability to build new material structures and artefacts. Engineering is the modern manifestation of this building instinct, and its advent has made the construction and use of technologies the central pattern of human life. In parallel, efficiency, the overarching narrative driving technology and related life practices, has pervaded most occupations as a value, forming a cultural backdrop that implicitly guides decisions and behaviour. We examine the process through which this backdrop has developed, and argue that it emerged through the constant presence and use of built artefacts and structures, which function as manifestations of the engineering value of efficiency. The constant presence and use of built structures leads to the slow percolation of their building values into society, forming a cultural narrative that emphasises efficiency. This narrative then feeds back, to further reinforce efficiency-driven engineering processes. This loop creates a runaway building system that is highly resistant to change, even when faced with the prospect of the species going extinct. Any effort towards sustainability can be successful only when this all-pervading – and hence invisible – building loop is made explicit, and compensated for, through a counter-loop where building manifests sustainable engineering values. As a first step in revealing this structure, we characterise the emergence of the efficiency value as a cultural narrative, and analyse its wide-ranging environmental effects. We then present the design principle of ‘Solving for Pattern’ (SfP) as an illustrative contrast case. SfP, first articulated by Wendell Berry, focuses on interconnectedness and flourishing of all species as central design principles. We argue that these ecological principles can be extended to engineering, and can thus support the development of a robust operational-level building movement that manifests value systems oriented towards sustainability. To ground this proposal in actual practice, we outline two case studies of technology design that illustrates SfP. We also discuss three cases that illustrate SfP at a larger scale, and examine how these extend existing design approaches such as systems engineering. We conclude with a proposal to include SfP in engineering education curricula, to facilitate a faster cultural shift towards flourishing, which is required given the limited time window available to move to sustainable building practices.
HAP: Building Pipelines with Heterogeneous Data and Hive

The increasing number of available datasets gives opportunities to build large and complex applications which aggregate results coming from several sources. These emerging usecases require new systems where combinations of heterogeneous sources are both allowed and efficient. To tackle these challenges, we provide a simple high-level set of primitives – called HAP – to easily describe processing chains. These descriptions are then compiled into optimized SQL queries executed by Hive.
Electronic Health Record in Bolivia and ICT: A Perspective for Latin America

The emergence of new technologies in society through its application to many areas and very diverse realities is a clear element in the time in which we live. The health sector has been unable to escape this reality and has been renovated many of its traditional structures with new options brought by the application of information technology and communication (ICT) in areas such as management and hospital administration. This paper focuses on analyzing from the point of view of medical diagnosis the importance of electronic medical records as a unifying element of the information essential for this type of diagnosis, and the use of artificial intelligence techniques in this field. To this end the current situation of electronic medical records is analyzed in a country like Bolivia exhaustively analyzing three of the most important health centers. Is used for this unstructured interview experts on the subject reflect the current status of electronic medical records from the point of view of protection of the right to privacy of individuals and will serve as a model for development, not only in Bolivia but also in other Latin American countries.
Academic Success Indicators Associated with Immediate Postsecondary Enrollment

The primary aim of this study was to examine the predictive relationship between human capital academic success indicators and student enrollment or non-enrollment in a postsecondary institution or program. For this study, the researcher analyzed academic records, demographic information, and National Student Clearinghouse (NSC) reports from two comprehensive high schools in one school district to address the research question. A direct logistic regression was used to examine the predictors that influenced the decision of high school graduates from the class of 2017 to enroll in a two-year college, technical college, four-year college, or non-enrollment immediately after graduation from high school. Three predictor variables contributed to the odds of increasing postsecondary enrollment: high school attended, cumulative GPA, and math credit above Algebra Two; and one predictor variable contributed to decreasing the odds of postsecondary enrollment: FAFSA completion. This study yielded postsecondary enrollment information for one local school district that can lead to promising school district policy and practice changes which may enable educators in their assistance and guidance of students toward immediate post-high school plans.
A Content Analysis of Media Information Exposure on Tourism Destination Image

This study examines the issue of the formation of destination image through the analysis of the specific tourism discourse. It is the linguistic variety of English used in tourism which was written by tourists on websites imaging the destination of the Campuhan Ridge. The study focuses on the way tourism discourse contributes to convey an image of a destination using the approach of media exposure theory. Referring to previous scientific studies, tourism destination image have been shaped through the mediation between tourists’ mental constructs and web-based tourism discourse. Using a theory of information media exposure and an approach of linguistic study, samples of texts from websites were examined and analyzed using qualitative content analysis. Results show that linguistic features seen from lexical and phrasal choices were used together with functional attributes, psychological attributes, Psychological-holistic impressions, and Common-Unique dimension when tourists describing about tourism destination image.
Visual analytics of location-based social networks for decision support

Chae, Junghoon Ph.D., Purdue University, December 2016. Visual Analytics of Locationbased Social Networks for Decision Support. Major Professor: David S. Ebert. Recent advances in technology have enabled people to add location information to social networks called Location-Based Social Networks (LBSNs) where people share their communication and whereabouts not only in their daily lives, but also during abnormal situations, such as crisis events. However, since the volume of the data exceeds the boundaries of human analytical capabilities, it is almost impossible to perform a straightforward qualitative analysis of the data. The emerging field of visual analytics has been introduced to tackle such challenges by integrating the approaches from statistical data analysis and human computer interaction into highly interactive visual environments. Based on the idea of visual analytics, this research contributes the techniques of knowledge discovery in social media data for providing comprehensive situational awareness. We extract valuable hidden information from the huge volume of unstructured social media data and model the extracted information for visualizing meaningful information along with user-centered interactive interfaces. We develop visual analytics techniques and systems for spatial decision support through coupling modeling of spatiotemporal social media data, with scalable and interactive visual environments. These systems allow analysts to detect and examine abnormal events within social media data by integrating automated analytical techniques and visual methods. We provide comprehensive analysis of public behavior response in disaster events through exploring and examining the spatial and temporal distribution of LBSNs. We also propose a trajectory-based visual analytics of LBSNs for anomalous human movement analysis during crises by incorporating a novel classification technique. Finally, we introduce a visual analytics approach for forecasting the overall flow of human crowds.
Catalogue of WEB Data Services on Global Trade

This document is a catalogue of WEB services providing data on global trade. It updates to March 2010 the first edition published in 2007. Each service is described in the catalogue according to a form specifying data fields, geographical coverage, temporal span, search criteria and reporting facilities on data records. The information has been derived from WEB sites, email contacts with service providers, trial runs, and interviews with users. Services listed herein offer data on imports and exports on all types of commodities over the last decade. The use of the data is generic: they can support studies related to trade in diverse domains and applications. Trade data described in this catalogue have a regulatory origin because they stem from declarations made by importers and exporters to customs authorities. The data are collected at national level, processed, and released for public access under formats respecting national provisions on data confidentiality. Trade data are released in transactional or statistical format and may have a national or multinational scope. Services on trade transactions are run by companies and are accessible after the payment of subscription fees. Services on statistical data (obtained by aggregating transactions) often have a multi-national scope and are provided for free access by international and governmental organizations, and statistical offices, or as pay services by companies. This catalogue has been compiled as part of the activities on nuclear trade information analysis within the action IANUS (Information Analysis for Nuclear Security, action nr. 53104 of JRC IPSC FP7).