Reviewerly/exHarmony huggingface dataset:
Impact of Income Inequality on Economic Growth – Evidence from the Ten (10) Biggest Economies in Africa

Contributing to existing literature on the relationship between inequality and economic growth, this paper focused on the top ten biggest economies in Africa.There was positive correlation between income inequality and economic growth in the long term.Mean School Year and Gross Savings also regressed positively because it was established that a 1% increase in the number of years spent in school within these countries will causes the economy to grow about 214.76%, and 1% increase in gross savings pushes economic growth by 3.61% annually.Expectedly, unemployment had negative relationship with economic growth.A 1% decrease in unemployment rate within these countries will boost long term economic growth by 7.72%.Due to low educational standard, inadequate technological advancement, high unemployment rate and low human capital, gross capital formation had inverse relationship with economic growth in these countries.The paper recommended that Governments in these countries adopt strategies and approaches such as increase public spending and create employment opportunities, adopt new educational policy to increase the average school years with accompanying improvement in its quality.
SCHOOLOGY AND ITS CONTRIBUTION IN ENGLISH LEARNING

Education in Industrial Revolution 4.0 increases the demand of online learning. In this era almost all aspects of human’s life change into digital.  Education tries to find the alternative of traditional teaching and tries to more engage with digital world. Education needs a tool that can connect teacher and students inside and outside the class, a tool which is more familiar with the student’s life. Schoology is a kind of social networking Learning Management System that offers the easy access for student to connect with their lecturer and vice versa. They can learn the material from lecturer everywhere just by clicking on their mobile phone. The use of Schoology supports not only students but also the teacher in English learning. By the Schoology teacher can create paperless culture in education, give online assignments and online assessments to the students even connect in discussion with other lecture about certain topic.
KOLABORASI PENELITI DI ERA TEKNOLOGI INFORMASI DAN KOMUNIKASI

Advances in information and communication technology have an impact on the increasing number of scientific publications in the world. Scientific papers are indicators of a country's progress in the academic field. One strategy used to improve the quality of research is to collaborate with researchers. There is not much research that addresses the collaboration of researchers. This article provides an overview of the cooperation of researchers including the background of the partnership, as well as aspects that influence the teamwork of researchers, especially in the era of acceleration of information and communication technology. The method used is the study of literature. Reviews aim as the basis for assessing research productivity, especially in Indonesia.
Empirical study of Team Usability Testing: a laboratory experiment

Abstract The evaluation of groupware has a long history; several researchers have investigated this research area and made attempts to develop evaluation methods. This paper aims to make a contribution to this research topic by introducing a groupware evaluation method called Team Usability Testing. The goal of this method is to evaluate the usability of real-time distributed groupware. The Team Usability Test consists of a combination of questionnaires, on-screen behaviour recordings and interviews. The data analysis is based on the mechanics of collaboration theoretical framework and involves communication analysis, behaviour analysis, and analysis of post-experiment interviews. A laboratory experiment and a field study constitute the two main phases of the creation of the usability testing method. In this paper, the results of the laboratory experiment and its implications for the field study will be discussed. According to the results, the Team Usability Test is able to explore team-level usability problems and contextual problems. The paper ends with the discussion of future field research considerations related to the possible application of the Team Usability Test in real-life work settings.
Multi-input Laconic Function Evaluation

Recently, Quach, Wee and Wichs (FOCS 2018) proposed a new powerful cryptographic primitive called laconic function evaluation (LFE). Using an LFE scheme, Alice can compress a large circuit f into a small digest. Bob can encrypt some data x under this digest in a way that enables Alice to recover f(x) without learning anything else about Bob’s data. The laconic property requires that the size of the digest, the run-time of the encryption algorithm and the size of the ciphertext should be much smaller than the circuit-size of f. This new tool is motivated by an interesting application of “Bob-optimized” two-round secure two-party computation (2PC). In such a 2PC, Alice will get the final result thus the workload of Bob will be minimized. In this paper, we consider a “client-optimized” two-round secure multiparty computation, in which multiple clients provide inputs and enable a server to obtain final outputs while protecting privacy of each individual input. More importantly, we would also minimize the cost of each client. For this purpose, we propose multi-input laconic function evaluation (MI-LFE), and give a systematic study of it. It turns out that MI-LFE for general circuit is not easy. Specifically, we first show that the directly generalized version, i.e., the public-key MI-LFE implies virtual black-box obfuscation. Hence the public-key MI-LFE (for general circuits) is infeasible. This forces us to turn to secret key version of MI-LFE, in which encryption now needs to take a secret key. Next we show that secret-key MI-LFE also implies heavy cryptographic primitives including witness encryption for NP language and the indistinguishability obfuscation. On the positive side, we show that the secret-key MI-LFE can be constructed assuming indistinguishability obfuscation and learning with errors assumption. Our theoretical results suggest that we may have to explore relaxed versions of MI-LFE for meaningful new applications of “client-optimized” MPC and others.
Design and Analysis of Indoor Mobile Robot Positioning Technology

Abstract In the field of mobile robot technology research, positioning technology is one of the core technologies, so it has been widely concerned in the field of industry. Due to the limitation of space, indoor mobile robots often have a high demand for their own position confirmation in the process of operation. Therefore, exploration based on positioning technology is very important for the further development of indoor mobile robots. Based on the research on the positioning technology of wheeled indoor mobile robot, this paper will make an effective evaluation on the future development direction of indoor mobile robot technology.
STUDENTS’ PERCEPTION AND MOTIVATION TOWARD ENGLISH E-LEARNING DURING COVID-19 PANDEMIC (A STUDY AT THE TENTH GRADERS AT SMA N 1 SURUH IN THE ACADEMIC YEAR OF 2019/2020)

Mulyani, Sri. 2020. Students’ Perception and Motivation Toward English E-Learning during Covid-19 Pandemic (A Study at the Tenth Graders at SMA N 1 Suruh in the Academic Year of 2019/2020. A Graduating Paper, English Education Department of Teacher Training and Education Faculty at State Institute for Islamic Studies (IAIN) Salatiga.Counselor: Heru Saputra, S.Pd.I., M.A.This research aimed at knowing the students' perception towards English E-Learning during Covid-19 pandemic at SMA N 1 Suruh. This research generally answered two questions as follows: (1) What are students’ perceptions towards English E-Learning during Covid-19 pandemic? and (2) How arestudents’ motivation towards English E-Learning during Covid-19 pandemic? The data was collected through a questionnaire and interviews. There were 64 of tenth graders at SMA N 1 Suruh participated in this research. Since this research explored the students' perception and motivation which coming from the students' experiences during Covid-19 pandemic, descriptive research by using qualitative-quantitative techniques was considered as an appropriate approach as a type of research. The result of this research was presented descriptively in order to reveal the students' perception and motivation comprehensively. The research found E-learning gets positive perception because it is flexible and effective. Meanwhile, its flexibility makes some students motivated but some are being lazy in doing it and choose to procrastinate the assignments.Key Words: E-Learning; Perception; Motivation
Membership Inference Attacks against MemGuard : IEEE CNS 20 Poster

The membership inference attack makes it possible to extract participation information of the training dataset, which poses severe privacy threats to users. Most of existing solutions leverage differential privacy or regularization when training the target classifier, causing some accuracy drops. Recently, MemGuard, a defense with adding noise to each confidence score vector predicted by the target classifier has been proposed, instead of tampering the training process of the target classifier. The noise can turn score vector into an adversarial example that misleads the attacker's classifier. In this poster, we propose two novel attacks to foil the protection of MemGuard. We apply the knowledge distillation, which can improve the resilience to adversarial examples of our attack model, as our first attack. We also propose a resizing attack to denoise the adversarial example, as our second attack. The experimental results show the effectiveness of our two proposed attacks.
New Tools for Old Tasks: A Digital Approach to the Investigation of the Malay Language

Digital tools designed for linguistic analysis offer new ways of approaching old tasks, and they now routinely enable tasks which were formerly impossible. The work for this paper is based on MaLex, which is a collection of data tables and procedures designed to represent the intuitive knowledge of speakers of Malay, and provides the infrastructure for the solution of problems in linguistic analysis. This paper reports the use of the MaLex parser to investigate the adjectival system of Malay, including superlatives and the formation of manner adverbials. Although linguists have always been able to identify possible syntactic rules and try them out on small datasets, the automatic parser is able to extract examples from a large corpus, and it is much more effective than a linguist in ascertaining the ordering of rules, and tracing their interaction. Since the examples in this paper are also syntactic constituents, they are the appropriate units for translation, and in this case they are translated into English. The phonological component concatenates the phonological representations of constituents to form higher level structures, and an extension to Malex which is planned but not yet completed is intended to increase the range of waveform annotations that can be used as input for linguistic analysis. Malay is a suitable language for this research, because although it is under-investigated in relation to its importance as one of the main languages of ASEAN, it has extensive written records which make it possible to compile large corpora for research. A human linguist can get started on a very small amount of data, and the same is true of the approach pioneered by MaLex. For this reason, MaLex could prove to be a suitable model for the digital investigation of insufficiently researched languages.
Corporate Social Responsibility Practices: A Study on Foreign Commercial Banks in Bangladesh

Corporate Social Responsibility (CSR) is an important portion of an enterprise, bank or other industry.Corporate social responsibility increases the growth and success of a firm.Corporate Social Responsibility means responsibility for the people of the society about the country.The development of a society or a country happens only when the financial institutions like the bank of the country properly maintain their corporate social responsibility.Furthermore, there is a positive relationship between corporate social responsibility and customer perceptions towards the corporations.In our paper, we discussed the theoretical framework of the CSR.The theoretical framework includes bright sides of the CSR and limitations of the CSR.We also analyze 5 commercial banks Bank Al-Falah, Habib Bank Ltd., HSBC, Commercial Bank of Ceylon, and Standard Chartered Banks CSR contribution in corporate social responsibility.We compare their contribution in 2018 and 2019 year.We see that some areas of contribution decrease in 2019 as compared to 2018.There is no contribution to infrastructure development.At last, we recommend foreign commercial banks to increase CSR contribution in some specific areas.
STUDENTS’ DIFFICULTIES IN USING PERSONAL PRONOUNS IN WRITING RECOUNT TEXT

This study is aimed to investigate the students’ difficulties in using personal pronouns in writing recount text at grade eight of SMP Negeri 8 Pematangsiantar”. In this research, the problem is as follows: “What are the students’ difficulties in using personal pronouns in writing recount text at grade eight of SMP Negeri 8 Pematangsiantar?”. The objective is to find out the students’ difficulties in using personal pronouns at grade eight of SMP Negeri 8 Pematangsintar. To answer the problem above, the researcher intends to use the theories of Collins (2014), Siahaan (2007), Derewinka (1990), William (2005), Frank (1972). The methodology used in this research is the Qualitative research. The subject of this research is grade Eight of SMP Negeri 8 Pematangsiantar. The data collected by observation. After analyzing the data, the researchers found that there were three kinds of students’ difficulties in using personal pronouns in writing text, namely: Personal pronoun as subject (34%), personal pronouns as the object (24%), and personal pronoun as a possessive adjective (42%). It can be concluded that the students at grade eight of SMP Negeri 8 Pematangsiantar still have difficulties in using personal pronouns when they write a recount text based on their experience. The researchers suggest the students’ should memorize the kinds of personal pronouns so they can use it well.&#x0D;
An Evaluation of China’s Automated Scoring System Bingo English

The study evaluated the effectiveness of Bingo English, one of the representative automated essay scoring (AES) systems in China. 84 essays in an English test held in a Chinese university were collected as the research materials. All the essays were scored by both two trained and experienced human raters and Bingo English, and the linguistic features of them were also quantified in terms of complexity, accuracy, fluency (CAF), content quality, and organization. After examining the agreement between human scores and automated scores and the correlation of human and automated scores with the indicators of the essays&amp;rsquo; linguistic features, it was found that Bingo English scores could only reflect the essays&amp;rsquo; quality in a general way, and the use of it should be treated with caution.
From Quasi-Dominions to Progress Measures

In this paper we revisit the approaches to the solution of parity games based on progress measures and show how the notion of quasi dominions can be integrated with those approaches. The idea is that, while progress measure based techniques typically focus on one of the two players, little information is gathered on the other player during the solution process. Adding quasi dominions provides additional information on this player that can be leveraged to accelerate convergence to a progress measure. To accommodate quasi dominions, however, a non trivial refinement of the approach is necessary. In particular, we need to introduce a novel notion of measure and a new approach to prove correctness of the resulting solution technique.
Adversarial Curiosity

Model-based curiosity combines active learning approaches to optimal sampling with the information gain based incentives for exploration presented in the curiosity literature. Existing model-based curiosity methods look to approximate prediction uncertainty with approaches which struggle to scale to many prediction-planning pipelines used in robotics tasks. We address these scalability issues with an adversarial curiosity method minimizing a score given by a discriminator network. This discriminator is optimized jointly with a prediction model and enables our active learning approach to sample sequences of observations and actions which result in predictions considered the least realistic by the discriminator. We demonstrate progressively increasing advantages as compute is restricted of our adversarial curiosity approach over leading model-based exploration strategies in simulated environments. We further demonstrate the ability of our adversarial curiosity method to scale to a robotic manipulation prediction-planning pipeline where we improve sample efficiency and prediction performance for a domain transfer problem.
Informative Clusters for Multivariate Extremes.

Capturing the dependence structure of multivariate extreme data is a major challenge in many fields involving the management of risks that come from multiple sources, e.g., portfolio monitoring, environmental risk management, insurance and anomaly detection. The present paper develops a novel optimization-based approach called MEXICO, standing for Multivariate EXtreme Informative Clustering by Optimization. It aims at exhibiting a sparsity pattern within the dependence structure of extremes. This is achieved by estimating some disjoint clusters of features that tend to be large simultaneously through an optimization method on the probability simplex. This dimension reduction technique can be applied to statistical learning tasks such as feature clustering and anomaly detection. Numerical experiments provide strong empirical evidence of the relevance of our approach.
Syllogisms with Intermediate Quantifiers Solved in Marlo Logic Diagrams

In this article we propose diagrams with the ability to represent syllogisms that, in addition to the traditional quantifiers “all”, “some” and “none”, can represent the so-called intermediate quantifiers or probabilistic quantifiers “most”, “a few”, “half”, etc. The graphs contained in this paper have been developed based on the Marlo diagram, a tool for teaching logical reasoning that operates with propositional models that are constructed by quantifying the predicate in a way similar to Hamilton or Jevons in the 19th century. The quantification of the predicate allows us to represent the possibilities implicit in the premises, so that when the synthesis of the propositions is made later, the working memory can take these possibilities into account. In this way, we prevent our students from committing the persistent fallacies of denying the antecedent and affirming the consequent.
Design and implementation of proposed 320 bit RC6-cascaded encryption/decryption cores on altera FPGA

This paper attempts to build up a simple, strong and secure cryptographic algorithm. The result of such an attempt is “RC6-Cascade” which is 320-bits RC6 like block cipher. The key can be any length up to 256 bytes. It is a secret-key block cipher with precise characteristics of RC6 algorithm using another overall structure design. In RC6-Cascade, cascading of F-functions will be used instead of rounds. Moreover, the paper investigates a hardware design to efficiently implement the proposed RC6-Cascade block cipher core on field programmable gate array (FPGA). An efficient compact iterative architecture will be designed for the F-function of the above algorithm. The goal is to design a more secure algorithm and present a very fast encryption core for low cost and small size applications.
Performance Analysis of Convolutional Neural Networks on Embedded Systems

Machine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and complex-valued tensors and are tested using different inference engines. We conclude that the system must be tuned in a holistic way to achieve optimal efficiency.
Patentability of Artificial Intelligence in Europe : Is Artificial Intelligence Patentable According to the European Patent Convention and is the Current Legal Framework for Patents Suitable for Patenting Artificial Intelligence?

Patentability of Artificial Intelligence in Europe : Is Artificial Intelligence Patentable According to the European Patent Convention and is the Current Legal Framework for Patents Suitable for Patenting Artificial Intelligence?
Context Driven Bipolar Adjustment for Optimized Aspect Level Sentiment Analysis

World Wide Web provides numerous opinionated data that can influence users. Reviews on online data highly affect the user’s perception while buying a particular or related product from an online shopping site. The online review provided by a customer helps other customers to make up their decision regarding purchasing that item. Looking at the developer’s and producer’s perspective, the opinions of customers on their manufactured items is helpful in identifying deformities as well as scope for improving its quality. Equipped with all this information, the product can be developed and managed more efficiently. Along with the overall rating of the product, the feature-based rating will have a great impact on the decision-making process of the customer. In this paper, an optimized scheme of aspect level sentiment analysis is presented to analyze the online reviews of a product. Reviews ratings have been used for learning approach. Inherently biased reviews are considered to optimize the Aspect Level Sentiment Analysis. Bi-polar aspect level sentiment analysis model has been trained using multiple kernels of support vector machine to optimize the results. Lexicon based aspect level sentiment analysis is performed first and later on the basis of bipolar words adjustment, and its effect on results, aspect level sentiment analysis for efficient optimization has been performed. A Web Crawler is developed to extract data from Amazon. The results obtained outperformed traditional lexicon based Aspect Level Sentiment Analysis.
AFSKNN: Classification Method Based on K-Nearest Neighbors and Axiomatic Fuzzy Sets

The classification with both semantic description and accuracy performance is an appealing issue in the fields of pattern recognition and data mining. In this study, we make an attempt to design an interpretable classifier AFSKNN based on K-nearest neighbors (KNN) and Axiomatic fuzzy sets (AFS). The algorithm converts the learning data into a semantic description, followed by selecting k-neighborhood of test sample with the aid of the membership grade belonging to the training sample description. Some data sets from UCI machine learning repository are tested for comparing the results with KNN and AFS classifiers. The results demonstrate that the performance of AFS-KNN is satisfied in both interpretability and accuracy. Meanwhile, the classifier indicates a potential of acquiring knowledge by means of semantic description.