Reviewerly/exHarmony huggingface dataset:
Subsampling Bias and The Best-Discrepancy Systematic Cross Validation

Statistical machine learning models should be evaluated and validated before putting to work. Conventional k-fold Monte Carlo Cross-Validation (MCCV) procedure uses a pseudo-random sequence to partition instances into k subsets, which usually causes subsampling bias, inflates generalization errors and jeopardizes the reliability and effectiveness of cross-validation. Based on ordered systematic sampling theory in statistics and low-discrepancy sequence theory in number theory, we propose a new k-fold cross-validation procedure by replacing a pseudo-random sequence with a best-discrepancy sequence, which ensures low subsampling bias and leads to more precise Expected-Prediction-Error estimates. Experiments with 156 benchmark datasets and three classifiers (logistic regression, decision tree and naive bayes) show that in general, our cross-validation procedure can extrude subsampling bias in the MCCV by lowering the EPE around 7.18% and the variances around 26.73%. In comparison, the stratified MCCV can reduce the EPE and variances of the MCCV around 1.58% and 11.85% respectively. The Leave-One-Out (LOO) can lower the EPE around 2.50% but its variances are much higher than the any other CV procedure. The computational time of our cross-validation procedure is just 8.64% of the MCCV, 8.67% of the stratified MCCV and 16.72% of the LOO. Experiments also show that our approach is more beneficial for datasets characterized by relatively small size and large aspect ratio. This makes our approach particularly pertinent when solving bioscience classification problems. Our proposed systematic subsampling technique could be generalized to other machine learning algorithms that involve random subsampling mechanism.
Spectral Overlap and a Comparison of Parameter-Free, Dimensionality Reduction Quality Metrics

Nonlinear dimensionality reduction methods are a popular tool for data scientists and researchers to visualize complex, high dimensional data. However, while these methods continue to improve and grow in number, it is often difficult to evaluate the quality of a visualization due to a variety of factors such as lack of information about the intrinsic dimension of the data and additional tuning required for many evaluation metrics. In this paper, we seek to provide a systematic comparison of dimensionality reduction quality metrics using datasets where we know the ground truth manifold. We utilize each metric for hyperparameter optimization in popular dimensionality reduction methods used for visualization and provide quantitative metrics to objectively compare visualizations to their original manifold. In our results, we find a few methods that appear to consistently do well and propose the best performer as a benchmark for evaluating dimensionality reduction based visualizations.
Students’ Attitude towards the use of CBT for UTME in Rural Secondary Schools. A Case of Guyuk LGA of Adamawa State, Nigeria

This research investigated students' attitude towards the use of Computer Based Test (CBT) for Unified Tertiary Matriculation Examination (UTME) in rural secondary schools in Guyuk Local Government Area of Adamawa State.The population of the study comprises of 550 students in public schools who took 2018 UTME.This was randomly sampled from 5 selected public secondary schools in the study area.A five likert scale questionnaire comprises of 20 questions was used as instrument for data collection.Descriptive statistics was use to analyzed the data.The study revealed that most of the secondary schools in rural area do not have adequate facilities to teach and learn the use of computer and as a result it affected students' performance in 2018 CBT UTME.The study also revealed that CBT for UTME may hinder a brilliant candidate in the rural community, who has no computer knowledge, to gain admission into tertiary institutions in Nigeria.The study recommended that government should make more effort to support the teaching and learning of computer education in all secondary schools especially in the rural areas.The study also recommended that JAMB should make effort to open training CBT centers at the rural areas to enable candidates familiarize themselves with the use of computer and to curb posting candidates far from home because of insufficient computer centers.
IDENTIFIKASI MISKONSEPSI SISWA DENGAN MENGGUNAKAN METODE CERTAINTY OF RESPONSE INDEX (CRI) PADA MATERI PELAJARAN IPA

This study aims to reveal the misconceptions of students at the 46 Palembnag State Middle School in the Circulatory material. The type of research used in this study is descriptive quantitative. Sampling was ditermined by  stratified Purposive Sampling. The research instrument used in this study was the Essay Problem accompanied by a Certainty of response index (CRI) column. The result showed that the percentage of students who experienced misconceptions was 28.3% and the percentage was smaller than the percentage of students who did not know the concept. The most common misconceptions experienced by students are the determination of blood groups, the scheme of the human circulatory system and the disturbances that occur in the human circulatory system. Keywords: CRI, Misconception, Human Circulatory System
Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN

Mammographic mass detection and segmentation are usually performed as serial and separate tasks, with segmentation often only performed on manually confirmed true positive detections in previous studies. We propose a fully-integrated computer-aided detection (CAD) system for simultaneous mammographic mass detection and segmentation without user intervention. The proposed CAD only consists of a pseudo-color image generation and a mass detection-segmentation stage based on Mask R-CNN. Grayscale mammograms are transformed into pseudo-color images based on multi-scale morphological sifting where mass-like patterns are enhanced to improve the performance of Mask R-CNN. Transfer learning with the Mask R-CNN is then adopted to simultaneously detect and segment masses on the pseudo-color images. Evaluated on the public dataset INbreast, the method outperforms the state-of-the-art methods by achieving an average true positive rate of 0.90 at 0.9 false positive per image and an average Dice similarity index of 0.88 for mass segmentation.
Information-communication technologies as the instrument for improving the quality of the educational process

Now, different innovative technologies are used to improve the educational process through the presentation of a modern learning content, the quality monitoring and evaluation of learning results at the various stages, and also the creation of new organizational forms of learning, educational and scientific resources and electronic systems and their implementation in the process of students’ self-study and their classroom study. The transformation of the educational environment of the educational institutions by the use of special platforms is an important trend of the modern research. As the electronic educational resources supports different types of learning and research activities, such as theoretical material studies, the search for useful information, task solutions, testing, training, simulation, making experiments and others. Besides in the national strategy of education development takes place a defined course to improve the competitiveness and quality of education to ensure public high-level professionals in the current socio-economic conditions, and integration into the European and world educational space and precisely for this reason one of the main strategic directions of the national education system is the widespread integration of information technologies and innovative educational programs. The article is devoted to an analysis of the problems of modernization of the educational environment in the context of improving and quality control of information and communication technologies and innovative tools adoption into the educational process. Based on analysis of scientific researches in this field and according to the definition of quality of an educational process by UNESCO criteria, there was affected the question concerning monitoring systems of functioning of a higher educational institution as a unit that is its economic, administrative and educational guide. An analysis of impacts that must be factored now into our educational system is made. The most important indicators of information educational environment are considered. The main factors of the level of formation of educational-research environment have been given. The perspectives of using the electronic resources in the system of higher education are revealed
ENHANCING MENTORING BETWEEN ALUMNI AND STUDENTS AT MIDDLE EAST COLLEGE: AN ANDROID MOBILE APPLICATION USING DATA MINING TECHNIQUES

Graduates are a very important part of universities and colleges where graduates' participation can be considered common among universities and colleges these days. The idea of implementing a mobile application for alumni association is to associate all the alumni together with Middle East College and make the association more active and interactive through a high involvement. We are aware of the importance of graduate students where they can be considered as the key function for any university and any college. Furthermore, it is very important to utilize the power of the graduates. In this paper we propose a framework on how to building a mobile application for alumni association can enhance mentoring between alumni and students of Middle East College using data mining. It is not easy to apply data mining to enhance mentoring between alumni and current students. In the mobile application simple data mining algorithms are performed for more interactive between the alumni and current students.
String Sanitization: A Combinatorial Approach

String data are often disseminated to support applications such as location-based service provision or DNA sequence analysis. This dissemination, however, may expose sensitive patterns that model confidential knowledge (e.g., trips to mental health clinics from a string representing a user's location history). In this paper, we consider the problem of sanitizing a string by concealing the occurrences of sensitive patterns, while maintaining data utility. First, we propose a time-optimal algorithm, TFS-ALGO, to construct the shortest string preserving the order of appearance and the frequency of all non-sensitive patterns. Such a string allows accurately performing tasks based on the sequential nature and pattern frequencies of the string. Second, we propose a time-optimal algorithm, PFS-ALGO, which preserves a partial order of appearance of non-sensitive patterns but produces a much shorter string that can be analyzed more efficiently. The strings produced by either of these algorithms may reveal the location of sensitive patterns. In response, we propose a heuristic, MCSR-ALGO, which replaces letters in these strings with carefully selected letters, so that sensitive patterns are not reinstated and occurrences of spurious patterns are prevented. We implemented our sanitization approach that applies TFS-ALGO, PFS-ALGO and then MCSR-ALGO and experimentally show that it is effective and efficient.
PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS ANDROID PADA MATA PELAJARAN PENGENALAN MICRODOFT WORD DI LPK SHEZA PONTIANAK

The purpose of the study was to find out how the development of Android-based learning media for the LPK training and course institutions SHEZA, to find out the feasibility of Android-based learning media for LPK training institutions and SHEZA courses. Learning media is designed using the Pascal programming language with the application of Embacadero Delphi XE 8. The Android platform was chosen because all LPK Sheza students use an Android smartphone, the microsoft word learning media developed is an Android-based learning media. because Android-based devices have been widely used in communities from various circles. So that the use of mobile devices or smartphones among users is optimal especially for learning. The hope, this study can facilitate educators or students in particular to increase the spirit of learning and achieve its goals in learning. The study was conducted at LPK SHEZA. The type of research used is R &amp; D research. The research was conducted in two stages. The first stage for product development uses the ADDIE model and the second stage. Data collection techniques use measurement and direct communication. The data collection tool uses an interview guide and questionnaire. The results of the study are the development of Android-based learning media for LPK training institutions and SHEZA courses worthy of use.
Agent Based Asynchronous Training In Distributed Software Development

In the changing software development, training on tools and techniques are necessary for the developers for better quality. Global software development faces great challenge for employee training as project members are scattered geographically. Developers should aware of the custom and culture of co-developers to improve their social and interpersonal competencies such as negotiation, teamwork, conflict resolution, time management, leadership, and communication using common language. The paper discussed a framework for agent based training model that can simulate global software development from different cultures; allows learners to train asynchronously as the agents are always available, and permits to play different roles in the various stages of project development. The framework also provides effective client training on product and effective for the discussion between the client and the developer and thus reduces the effort. The model was evaluated with online geographically separated trainees and trainers and analysed the feedback.
Neural Network Verification for the Masses (of AI graduates)

Rapid development of AI applications has stimulated demand for, and has given rise to, the rapidly growing number and diversity of AI MSc degrees. AI and Robotics research communities, industries and students are becoming increasingly aware of the problems caused by unsafe or insecure AI applications. Among them, perhaps the most famous example is vulnerability of deep neural networks to ``adversarial attacks''. Owing to wide-spread use of neural networks in all areas of AI, this problem is seen as particularly acute and pervasive. Despite of the growing number of research papers about safety and security vulnerabilities of AI applications, there is a noticeable shortage of accessible tools, methods and teaching materials for incorporating verification into AI programs. LAIV -- the Lab for AI and Verification -- is a newly opened research lab at Heriot-Watt university that engages AI and Robotics MSc students in verification projects, as part of their MSc dissertation work. In this paper, we will report on successes and unexpected difficulties LAIV faces, many of which arise from limitations of existing programming languages used for verification. We will discuss future directions for incorporating verification into AI degrees.
Use of E-learning among Rural Youth of Udaipur District of Rajasthan

The advancement of internet technologies has been significantly observed in past decades and is proved most utilitarian in educational sector. Interaction with digitally delivered content, network-based services and tutoring support are the innovative approaches fore-learning. E-learning has the potential to improve the literacy rate in India especially in remote areas where situation is worse. The present study was undertaken with an objective to analyse the use of e-learning among the rural youth of Udaipur district of Rajasthan state. Sample of the study comprised of 140 rural youth (70 male and 70 female). Regarding use of e-learning tools, findings revealed that most of the respondents used internet (93.57%) and smart phones (92.86%) whereas more than half of the respondents (56.43%) used smart classroom. Other tools like personal computer, laptop, CD/DVD, audio videotape and interactive TV were used by 32.86- 47.86 per cent respondents. Various platforms such as YouTube, Gmail, Facebook, Instagram and Whatsapp were accessed for e-learning by the respondents. It was determined that half of the respondents (56.42%) were using e-learning tools to medium extent whereas 19.28 per cent were using them to high extent.
REVEALING PROCESS-BASED AND WRITERS’ CHOICE OF ACADEMIC ESSAY WRITING IN UNDERGRADUATE EFL LEARNERS

This research are to describe the process-based academic writing plays the role in essay creationin the argumentative essay from EFL learners; to describe the writer’s choice contributing in academic essay writing of EFL in undergraduate by using rhetorical patterns; and to describe the weaknesses and strengths of process-based and writer’s choice role; This research uses the descriptive qualitative. The data sources of this research are argumentative essays from ELTD, sixth semester in undergraduate IAIN SNJ Cirebon. The text was taken from the students who followed GBL lesson in previous semester. The instrument is the researchers theirself. The techniques of collecting data that is used by the researchers are questionnaire, interview transcript, audio recording and document. The result of this research is different with the previous research. In this research, the researcherss shows essay’s writing process in detail, contribution of rhetorical patterns in essay’s creation and how strength and weakness the process also the pattern in essay. To the role of process-based stages here are more than half of efforts in making essay, means certain stages are very useful to the students as the author here. The examples are pre writing, editing and revising, and responding. Then, the patterns help the students as the author to arrange their essay. Both are giving big contribution to communicate the text to the readers. This is such as using marker (Mk 1, Mk 2 and Mk 3) as the signal or bridge among the sentence or the paragraph. However, both of them still have their own to be applied to the EFL learners
PENGEMBANGAN WEBSITE PROGRAM STUDI DALAM UPAYA PENINGKATAN PELAYANAN AKADEMIK MAHASISWA PENDIDIKAN TEKNIK MESIN UNIVERSITAS SARJANAWIYATA TAMANSISWA

This research aims to develop a website product for the Mechanical Engineering Education Department that is suitable for academic service. It is very important to do in order to improve the service quality of the Mechanical Engineering Education Department to realize its vision and mission and also to give beneficial effect in improving the accreditation status of the department. The design of this research is Research and Development of 4D model. The steps of 4D model includes: define, design, develop, and disseminate. The define step aims to collect various information related to the product to develop. The design step aims to prepare the design of first product. The develop step aims to produce a suitable website. The disseminate step is the last step in developing the product. The subject of this research consisted of two parties; they are validator (website experts) who validated the website and students of the Mechanical Engineering Education Department of Sarjanawiyata Tamansiswa University. The instruments used to collect the research data are validation sheet of the suitability of website product and questionnaire for student satisfaction of academic service. The data analysis used descriptive quantitative and qualitative techniques. The Website of the Mechanical Engineering Education Department that has been developed is in good category, so it has been suitable for public access. The website can be accessed through: http://ptm.ustjogja.ac.id. The website gives students academic service satisfaction in a very good category.
Improvement in Sarf (Morphology) Competency through Gamification at Miri National Religious Secondary School (SMKAMi)

Learning through the gamification method can bring the students directly closer to real experience.Students have the opportunity to improve their ability to remember, increase sensitivity to interaction process and possess the capability to objectively analyse a situation.The purpose of this article is to introduce a type of gamification to strengthen Sarf (morphology), in addition to tracking improvement in Sarf competency after implementing the gamification method at Miri National Religious Secondary School (SMKAMi) in the 2017 Malaysian Certificate of Examination (SPM).This research uses a qualitative method and data was taken mainly from the Arabic Morphology Diagnostic Test (UDMA) and through the instrument of interview using WhatsApp application (voice message or voice recording).Two teachers were involved in the interview session: Head of Arabic Language Committee and an Arabic language teacher who teaches Form 5.The data obtained were transcribed in writing and descriptively analysed.Research findings show an improved achievement in Arabic language subject of the 2017 SPM by 1.09 with Average Grade of Subjects (GPMP) of 3.64 compared to 4.73 of the previous year.Research results show that the gamification method can resolve student weakness in Sarf, especially in remembering the verb and noun patterns and their derivatives, besides increasing student engagement, creating fun and fostering a positive attitude through game activity.The implications of this research will open the space for research on gamification designs appropriate for strengthening Nahu and Sarf with a high prospect for their application in the context of Arabic language education.
Organization of Simulated “Ground–Air” Radio Communication and Service Loud-Speaking Communication

Means of simulated voice communication (MSVC) are intended to simulate two-way radio communication between the AWS-C and AWSs of operating personnel through one of the selected radio channels, as well as for loud-speaking communication (LSC) between any ISS AWSs. To implement the ISS functionality, the MSRC and MSSC must provide the following:
Distilling with Residual Network for Single Image Super Resolution

Recently, the deep convolutional neural network (CNN) has made remarkable progress in single image super resolution(SISR). However, blindly using the residual structure and dense structure to extract features from LR images, can cause the network to be bloated and difficult to train. To address these problems, we propose a simple and efficient distilling with residual network(DRN) for SISR. In detail, we propose residual distilling block(RDB) containing two branches, while one branch performs a residual operation and the other branch distills effective information. To further improve efficiency, we design residual distilling group(RDG) by stacking some RDBs and one long skip connection, which can effectively extract local features and fuse them with global features. These efficient features beneficially contribute to image reconstruction. Experiments on benchmark datasets demonstrate that our DRN is superior to the state-of-the-art methods, specifically has a better trade-off between performance and model size.