Reviewerly/exHarmony huggingface dataset:
PERFORMANCE COMPARISON OF COMPUTER-BASED TEST AND PAPER-PENCIL TEST USING SUPPORT VECTOR MACHINE

The Joint Admissions and Matriculation Board (JAMB) have over the years been in the news over the use of Computer Based Test (CBT) mode over the Paper Pencil Test (PPT) mode for its Unified Tertiary Matriculation Examination (UTME). This study examines the two test modes, and also tries to ascertain which particular mode makes the unified tertiary matriculation examination more comfortable for the students in privileged environment and those in the rural areas. Predicting student performance can be useful to the managements in many contexts. The purpose of this research work is to do a performance evaluation of computer-based and paper-based version of Joint Admissions and Matriculation Board (JAMB) test data conducted in the previous year using a robust Support Vector Machine model. This work attempts to determine whether there is any difference in the performance of student when comparing CBT to identical PPT test mode and also investigate the levels of malpractices involved in both test mode. Experimental results demonstrated CBT has better predictive accuracy and root mean square error compared to PPT.
Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures

Deriving Optimal bounds on Sample Complexity of Latent Variable models is an active area of research. Recently such bounds were obtained for Mixture of Gaussians (Ashtiani et al., 2018), no such results are known for Ad-mixtures, a generalization of Mixture distributions. In this paper we show that O*(dk/m) samples are sufficient to learn each of k- topic vectors of LDA, a popular Ad-mixture model, with vocabulary size d and m 2 (1) words per document, to any constant error in L1 norm. The result is a corollary of the major contribution of this paper: The first sample complexity upper bound for the problem (introduced in (Bhattacharyya & Kannan, 2020)) of learning the vertices of a Latent k- Polytope in Rd, given perturbed points from it. The bound, O*(dk/I²), is optimal and linear in number of parameters. It applies to many stochastic models including a broad class Ad-mixtures. To demonstrate the generality of the approach we specialize the setting to Mixed Membership Stochastic Block Models(MMSB) and show for the first time that if an MMSB has k blocks, the sample complexity is O*(k2) under usual assumptions. Â© 2020 37th International Conference on Machine Learning, ICML 2020. All rights reserved.
An Analyzing on the Students Error in Using Conditional Sentence

In this study, the writer want to analyze the student error in using conditional sentence and involve all case in conditional sentence. The method of this research is error analysis. In this research, the researcher wishes to know how is the students of the second grade at Madrasah Tsanawiyah Muhammadiyah 04 Klamalu competence in using conditional sentence type III especially in tenses “simple past perfect tense and simple future perfect tense.” The researcher gave the test to the students without the treatment the researcher want to know just one the cause of errors about the use of conditional sentence type III “simple past perfect tense and simple future perfect tense.” The result showed that the causing error of the students in using conditional sentence are carelessness, first language using, translation, the facility of students learning like English book, the method of teaching and the students themselves. After the analysis kind of conditional sentence the writer to identification the kinds of error and persentage of students error, result of reserch are: omission the total error are 10 error, the persentage is 7, 04 %. Addition the total of error 14 error, the persentage is 9, 86%. Miss- ordering error is 80 error, the persentage is 56,34% and subtitution error is 38 error, the persentage is 26,76%. So the total of students error are 142 error and the persentage is 100%.
The Role of Factors in Enhancing the Practices of Knowledge Management in Public and Private Business Organizations in Jordan

In Organization Management, Knowledge Management emerges as a new discipline contributing to implementing organizational perpetual internal strength and external competitive edges. Our research aims to further explore the role of factors (trust, awareness, organizational culture and structure, and Information Technology) in emboldening the practices of Knowledge Management in private and public business enterprises in Jordan. 700 39-item questionnaires were used to inquire from respondents working in the Business Organization in Jordan. Multiple regression analyses were conducted to verify the research hypotheses. The results revealed the substantial positive impact of factors on practices of Knowledge Management as well as strongly agreeing with studies conducted beforehand in the literature; it was surmised that Information Technology (IT) had the highest impact on Knowledge Management practices. To achieve potential success in Knowledge Management practices, trust, awareness, organizational culture and structure, Information Technology should be given proper attention and care. With efficient factors, Organizations’ Knowledge Management practices will increase in terms of efficiently, allowing organizations to hone and maintain their competitive edge in the business organization.
Dissertation: “In the intersection of television and Twitter: Social television as a tool for interaction and participation in a media event”

This dissertation presents the phenomenon of social television by focusing on the interplay between the traditional broadcast media and the newer social media in the context of the FIFA World Cup. The aim of the study is to shed light on interactional practices that are generated in the intersection of television and Twitter. Through the lens of digital discourse and conversation analysis the study examines how the participation in a media event is constructed in live tweeting practices. The dissertation shows that social media have offered new ways of participating and enjoying television content but have not replaced the role of traditional television as a central medium for experiencing massive media events such as the FIFA World Cup.
Follow, select and assemble method FSAM for VE and re assembly

We modified the methods by Ballard et al. [1]. They sought to study eye-hand coordination strategies and created both a real world and a virtual model copying task consisting of three different areas: model, source, and workspace. Participants followed a pickup and place exercise and used a mouse to control stimuli presented on a computer monitor in the virtual task. We also considered the method presented by Hayhoe et al. [2] and Aivar et al. [3] who designed a similar model copying task in a 3D virtual environment. Stimuli were displayed in a head mounted display and participants held a motion sensor to select and move virtual objects in 3D space. Moreover, Aivar et al. [3] also included extra assembly pieces and a variation in the position of the assembly pieces located in the resource area.• It proposes an assembly task designed at a 1:1 scale for two environments, real and virtual environments.• It introduces a reading sequence for the model that is being replicated and it also introduces distractor assembly blocks with similar colors and shapes as the required assembly blocks, and a change in the location for all assembly blocks in the resource area.• It modifies the interaction for the VR environment by using hand gestures to select, move and position virtual assembly blocks. This was possible by incorporating a LEAP® motion controller which although it does not provide haptic feedback, it provides a virtual representation of the participant's hand. Our VE also includes visual and auditory feedback to guide depth perception and virtual control.The software used for this research study is available at: http://virtualete.com/research/fsam.php
Image Steganography Using Contrast Enhancement Technique

Traditional image steganography techniques leverage different kinds of data hiding schemes to hide secret data while preserving good image visual quality. The image quality is measured by its PSNR value, which is based on the mean square error between the stego image and the cover image. From the viewpoint of visual experience, the adjustments of gray level values on the high contrast portions and on the smooth portions make completely different effects. A slight change of gray level on the smooth region will be noticed and explained as a noise, while increasing the contrast of an image edge will lead to a more pleasant visual effect. In this paper, we propose a novel method of data hiding. The cover image is divided into small blocks and each block is analyzed to classify into smooth block or high contrast block. For each high contrast block, the secret data are appended in the way that the block contrast is further enhanced. On the other hand, only half amount of secret data are embedded into a smooth block. Experimental results show that our method provides satisfactory results.
On Some Aspects of Mathematical Education Content in the Conditions of the Digital Economy

Modern terms set for the education new challenges and for mathematical education in particular. It must give possibility of achievement the necessary level of mathematical knowledge to every student. In this connection the content of mathematical education should be decisive in the transition from competencies to computer competencies and to computer competencies that significantly improve eastern requirements in the digital economy
Sistem Pendukung Keputusan Penerimaan Programer Software House Menggunakan Metode Simple Additive Weighting (SAW)

Abstract— The software house business is one of the businesses that are developing in the 4.0 industrial revolution era, both globally and locally. There are many software houses that need programmers with various qualifications to be accepted as employees both contract and permanent employees. One of the problems that arises is the frequency of employees leaving (resigning) from the software house for various reasons such as meeting deadlines, difficulty in working in teams, and also limited ability of programmers (low-skilled). many components of test results to test the ability to make programs. This study aims to build a decision support system in the selection of software house employees who can rank the results of prospective applicants' tests quickly based on the weight of predetermined criteria. Decision support systems made in this study can process test score data, prospective programmer data, and criterion data. The software house programmer acceptance decision support system created in this study successfully implemented the SAW method and was able to display the results of the ranking ranking starting from the score with the highest value to the score with the lowest value. Keywords—: decision support systems; software house programmer acceptance; simpe additive weighting; SAW.
Behind the Mask – An Inquiry into the Shakespeare Authorship Question

There is at present no consensus concerning the true authorship of the monumental literature that we ascribe to “Shakespeare”. Orthodox scholarship attributes this corpus to a man who was born and who died in Stratford-Upon-Avon, who spelled his name William Shakspere (or variants thereof, almost all with a short “a”), who could not write his own name consistently, and who may have been illiterate – as were his parents and as were, essentially, his children. For these and other reasons, many alternative candidates have been proposed. At this date, the leading such candidate is Edward de Vere, 17th Earl of Oxford. We approach the Authorship issue from a scientific perspective. We frame the key question as that of Secrecy or No Secrecy. According to orthodox scholarship, the Authorship Issue does not involve considerations of secrecy. According to independent scholarship, considerations of secrecy are fundamental to the Authorship Issue. We follow the initiatives of Jonathan Bond, John Rollett, and David Roper, who all brought their considerable mathematical expertise to the challenge of identifying and deciphering cryptograms embodied in the Dedication of the Sonnets and in the Inscription on the “Shakespeare” Monument. We show that the combined statistical significance of the cryptograms is overwhelming: The probability that the evidence contained in the cryptograms has occurred by chance rather than by intent is less than one part in one million-billion. Hence the messages must be accepted as the intentional creations of the authors – Oxford (not Thomas Thorpe, as usually assumed) for the Dedication, and Ben Jonson for the Inscription. The cryptograms confirm the orthodox suspicion that the intended recipient of the Sonnets was Henry Wriothesley, 3rd Earl of Southampton (so also confirming the orthodox belief that Southampton was the “Fair Youth” of the Sonnets). These discoveries resolve some of the well-known outstanding puzzles concerning the Authorship Issue such as the Author’s familiarity with Europe and its languages (especially Italy), his intricate knowledge of the lives of monarchs and nobility, his detailed and highly accurate knowledge of the law, etc. (see Table 1). However, this change in perspective necessarily raises new questions that will call for new research.Keywords: Shakespeare, Edward de Vere, William Shakspere, cryptograms, Cardano Grille
Software Piracy in Nigeria

The enormity of software piracy varies in different countries and Nigeria is not an exception. Software piracy occurs in diverse forms such as soft lifting, hard disk loading, counterfeiting and unauthorized renting. Many reasons are behind software piracy. Software piracy has many negative economic consequences: Competition distorted by pirated software at the expense of local industries, loss of tax revenue and jobs because of the lack of a legitimate market, increase in cost recovery which, overall, affects social well-being of the citizenry. Findings have revealed that Nigeria has the highest case of software piracy, intellectual property theft and other sharp practices in the IT industry in Africa. Hence, this work investigates software piracy in Nigeria; revealing the concepts, causes, effects; and proffered solutions. We adopted the descriptive survey design. The research instrument used was online questionnaire with a sample size of 3270 people drawn from a population of respondents from the six (6) Geopolitical Zones of Nigeria. The results show that software piracy has statistically significant effect on the economy of Nigeria and that high standard of living is the biggest cause of software piracy in Nigeria.
ExTra: Transfer-guided Exploration

The sample efficiency and convergence time of a Reinforcement Learning (RL) algorithm depend heavily on the exploration method used by the agent. In thiswork, we formulate an exploration method that uses prior experiences of an agent at similar tasks in other environments for improving the efficiency of exploration in the current task-environment. We show that given an optimal policy in a related task-environment, its bisimulation distance from the current task-environment gives a lower bound on the optimal advantage of state-action pairs in the current task-environment.
Analysis of Geographical Information System (GIS) design aplication in the Fire Department of Depok City

Depok City is one of the cities that is vulnerable to fire disasters. The Depok City Fire Department feels the need for a system that can assist in the handling and management of fire disasters. This system must be the right system to solve existing problems. Researchers have created many new systems. One of them is Geographic Information System (GIS) is a special information system for managing data that has spatial information. This research purposes to analyze and design a Geographic Information System (GIS) aimed at assisting the Depok City Fire Department that is desktop-based using the waterfall method. With the application of this Geographic Information System (GIS) aims to help accelerate the processing of fire reports on decision making, presenting spatial and non-spatial data that is more organized and can be updated also makes it easier to find new locations of fire stations , hydrants, fire-prone points, and flood-prone points.
Modeling Five Sentence Quality Representations by Finding Latent Spaces Produced with Deep Long Short-Memory Models

We present a study in which we train neural models that approximate rules that assess the quality of English sentences. We modeled five rules using deep LSTMs trained over a dataset of sentences whose quality is evaluated under such rules. Preliminary results suggest the neural architecture can model such rules to high accuracy.
Revolution through Artificial Intelligence in Context to Financial Services

The human aspect of learning new things and the problem-solving in arising situations can now be done by the new age computers with machine intelligence known as “smart computers,” while, the machine intelligence also known as Artificial intelligence covers diversified fields, including medical, engineering, finance, etc. the potential of AI is still unknown as it is not completely explored, but there are expectations that it will change the way of machine operations and mark the beginning of the new modern era of humanity. While in the current age of technology, all the banks and non-banking financial companies rely heavily upon the internet and computers for providing financial services to their clients hence the introduction of AI in the financial service sector will be a game changer by facilitating innovation of new financial service products for the people. In recent times, PayPal, a company dealing with online funds transfer around the world, has used AI system for strengthening the cybersecurity for online transactions resulting more reliability of customers as well as adding more customers on the payment network [4]. Although AI offers some promising outcomes, but some key challenges, includes the need for high-end technology for the cost-effective integration of AI with financial services and while as lack of AI development at commercial scale and limited integration 88of AI in educational courses resulting a handful of people well qualified and experienced in the field of AI [5]. Also, lack of understanding about AI in the public domain will cause suspicions in the minds of governments posing risks of unhealthy government regulations in the future. Another problem relates to independent working processes of AI in the future leading to the complete loss of human control over AI and may even establish one AI bot to other AI Bot communication as a similar incident was observed in case of Facebook where two AI Bots start communicating in a language not understood by humans.
A Survey of Research on Retail Central Bank Digital Currency

This paper examines key considerations around central bank digital currency (CBDC) for use by the general public, based on a comprehensive review of recent research, central bank experiments, and ongoing discussions among stakeholders. It looks at the reasons why central banks are exploring retail CBDC issuance, policy and design considerations; legal, governance and regulatory perspectives; plus cybersecurity and other risk considerations. This paper makes a contribution to the CBDC literature by suggesting a structured framework to organize discussions on whether or not to issue CBDC, with an operational focus and a project management perspective.
Mitigating the Negative Side Effects of Reasoning with Imperfect Models: A Multi-Objective Approach

Agents often operate using imperfect models of the environment that ignore certain aspects of the real world. Reasoning with such models may lead to negative side effects (NSE) when satisfying the primary objective of the available model, which are inherently difficult to identify at design time. We examine how various forms of feedback can be used to learn a penalty function associated with NSE during execution. We formulate the problem of mitigating the impact of NSE as a multi-objective Markov decision process with lexicographic reward preferences and slack. Empirical evaluation of our approach on three domains shows that the proposed framework can successfully mitigate NSE.
Robust Algorithms Under Adversarial Injections

In this paper, we study streaming and online algorithms in the context of randomness in the input. For several problems, a random order of the input sequence - as opposed to the worst-case order - appears to be a necessary evil in order to prove satisfying guarantees. However, algorithmic techniques that work under this assumption tend to be vulnerable to even small changes in the distribution. For this reason, we propose a new adversarial injections model, in which the input is ordered randomly, but an adversary may inject misleading elements at arbitrary positions. We believe that studying algorithms under this much weaker assumption can lead to new insights and, in particular, more robust algorithms. We investigate two classical combinatorial-optimization problems in this model: Maximum matching and cardinality constrained monotone submodular function maximization. Our main technical contribution is a novel streaming algorithm for the latter that computes a 0.55-approximation. While the algorithm itself is clean and simple, an involved analysis shows that it emulates a subdivision of the input stream which can be used to greatly limit the power of the adversary.
Entity summarization with high readability and low redundancy

The development of the World Wide Web has triggered substantial growth of knowledge graphs (KG). Research into using KGs for intelligent applications has increased significantly. A KG describes facts about entities using RDF triples, and an entity description may contain a large number of triples. In applications where entity information is presented directly, entity summarization is required to prevent user information overload and to fit the presentation capacity. Here, the task is to select the most representative subset of triples from the rich entity description. In this paper, we propose an innovative entity summarization method, which we refer to as ESSTER, to generate summaries with both high readability and low redundancy. The proposed method combines structural and textual features. The importance of a triple is measured based on its structural features in the KG. The text readability of a triple is measured based on n-grams in a text corpus, and redundancy in a set of triples is measured by logical reasoning, numeric comparison, and text similarity. Entity summations is modeled and by combining these three measures and solved as a combinatorial optimization problem. We conducted experiments and compared the proposed method to six existing methods on two publicly available datasets of manually labeled summaries. Experimental results demonstrate that the proposed method achieves state of the art results.
OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task

In this paper, we demonstrate our machine translation system applied for the Chinese Japanese bidirectional translation task (aka.open domain translation task) for the IWSLT 2020 (Ansari et al., 2020).Our model is based on Transformer (Vaswani et al., 2017), with the help of many popular, widelyproved effective data preprocessing and augmentation methods.Experiments show that these methods can im prove the baseline model steadily and signifi cantly.