Reviewerly/exHarmony huggingface dataset:
Investigation of the Bitcoin Effects on the Country Revenues Via Virtual Tax Transactions for Purchasing Management

As a consensus network, Bitcoin enables new payment systems and money that are entirely digital or can be interpreted as a virtual currency that uses open source user-to-peer network systems for purchasing and sourcing management. It offers easier way of payment without the need for a bank account, credit card or intermediary. Bitcoin is cash stored in a computer that can be used to replace cash in an online sale transaction. Therefore, this study aims to investigate how to maximize the opportunities that allow Bitcoin in contributing for Indonesia tax revenue and also, the respond to the growing issues of virtual money transactions in the world. This study uses Literature study method based on some previous research and scientific journals that discuss about Bitcoin as a means of payment in sale and purchase transactions. The results of this study Bitcoin transaction tax still needs to be addressed is the absence of Legal Basis and legislation on legality of Bitcoin as a recognized payment instrument in Indonesia. This study can helps the Indonesian governments for creating a guidelines to adjust the regulation of virtual transactions for purchasing management, which have already been created and implemented in other countries and have a positive impact on the country's economy in addition to being one of the sources of increasing state tax revenues.
LibGuides: FAQs & Public Service Tips: Upcoming Events & Scheduling Space in Sims

Info and tips for helping Sims Library users. This may inform public service people about events in the building
LibGuides: Scholarly Activity Toolkit: Writing, Research & Publishing

This toolkit provides resources to help MAHEC users read, process, and produce scholarly activity.
Fidelity: Towards Measuring the Trustworthiness of Neural Network Classification

With the increasing performance of neural networks on many security-critical tasks, the security concerns of machine learning have become increasingly prominent. Recent studies have shown that neural networks are vulnerable to adversarial examples: carefully crafted inputs with negligible perturbations on legitimate samples could mislead a neural network to produce adversary-selected outputs while humans can still correctly classify them. Therefore, we need an additional measurement on the trustworthiness of the results of a machine learning model, especially in adversarial settings. In this paper, we analyse the root cause of adversarial examples, and propose a new property, namely fidelity, of machine learning models to describe the gap between what a model learns and the ground truth learned by humans. One of its benefits is detecting adversarial attacks. We formally define fidelity, and propose a novel approach to quantify it. We evaluate the quantification of fidelity in adversarial settings on two neural networks. The study shows that involving the fidelity enables a neural network system to detect adversarial examples with true positive rate 97.7%, and false positive rate 1.67% on a studied neural network.
THE INFLUENCE OF READING, MIND MAPPING, AND SHARING (RMS) LEARNING MODELS ON RESULTS OF LEARNING SCIENCE IN STUDENTS OF CLASS V SDN WERDOYO GROBOGAN

This research aims to determine whether there is an effect of the Reading, Mind Mapping and Sharing (RMS) learning model on the learning outcomes of Natural Sciences in students of Class V SDN Werdoyo, Godong, Grobogan. This type of research is a quasi experimental design in the form of nonequivalent control group design. The study population was all students at Class V SDN Werdoyo and students Class V at SDN 3 Latak. The sample amounted to 62 students. Data collection techniques with tests and  questionnaire. Hypothesis testing uses the t-test formula. The results showed that: RMS learning models affect the learning outcomes of  Natural Sciences in students of Class V SDN Werdoyo. This can be seen by the significant difference in the cognitive learning outcomes of science between the experimental group applying the RMS learning model and the control group with the learning that is usually done by the teacher, namely the conventional model. This is indicated by the value of sig t-test smaller than α. (0,000 <0.05). The average result of the post test score of the experimental group was 89.4 higher than the average result of the post test value of the control group that was 66.1.
Hedging Rule Discussions : A study on hedging and emoticons in an online board game discussion forum

In everyday language, people tend to speak in a non-committing fashion when making claims, either to save their own face or to save another person’s face. In linguistics, this is called hedging, wi ...
How to become a better reading: a handout for PAI's reading text practice

How to Become A Better Reader Reading helps us learn to think in the new language.It can help us build a better vocabulary as it also makes us more comfortable with written English. we can write better English if we feel comfortable with the language Reading may be the only way for us to use English if you live in a non-English-speaking country.This handout is taken from various sources of Reading Comprehension material that meets its competence in mastering English texts
Forensic Examination of Counterfeit Indian Currency based on Unique Obscure High Security Features in New Indian High Denomination Currency Note

Rampant cases related to circulation of fake currency notes have been reported worldwide. With the introduction of new banknotes (announced after demonetization) having advanced and exclusive security features, it is the need of the hour, especially for a forensic Scientists, to have an idea about these new features and the various methods to examine these features. Results presented in this paper are based on examination and comparison of original and suspected fake 2000 rupee Indian currency banknote utilizing physical examination methods and techniques such as physical, microscopic, digital image processing, etc. During the examination of original 2000 rupee banknote, it was found that some security features of this banknote are unique & exclusive and could not be forged by counterfeiters. Counterfeitercould only imitate most of the visual features of banknotes but some specific security features like OVI print, UV-fluorescent print, micro letters, etc. which are placed on all over the substrate of original banknote, could not be mimicked. However, imitation of the visual features, can at times deceives the public in general. The present case study presents a methodology which will be very useful and informative in assisting the forensic community in examination of fake currency banknotes and for future studies.
Analisis Kinerja Delay Scheduling Pada Hadoop Terhadap Karakteristik Job Fail Rate Untuk Pengiriman Dua Job Yang Berbeda

This research will compare two algorithms in the process of scheduling large-scale data that runs on VPS (Virtual Private Server) by utilizing an open source platform, Hadoop and Proxmox as a container for creating VPS. For the research method, it will use the FIFO algorithm and the delay scheduling algorithm, each of which will run on infrastructure that has been built previously. Of the three types of scenarios that are done by using two different types of jobs in job submission, it is obtained that the delay scheduling algorithm produces a smaller fail rate than the FIFO algorithm. This can occur because of the characteristics of the delay scheduling algorithm which is to improve job locality data but the more number of jobs the job fail rate performance will increase with the appearance of failures.
Retracted Article: Research on digital image wavelet transform filtering optimization processing method based on DSP Internet of Things

We, the Editor and Publisher of the International Journal of Computers and Applications, have retracted the following article which was part of the Special Issue on Advanced Security Techniques for Cloud Computing and Big Data - New Directions: Dahai Yu & Juan Zhu (2019) Research on digital image wavelet transform filtering optimization processing method based on DSP Internet of Things, International Journal of Computers and Applications, DOI: 10.1080/1206212X.2019.1706031 Since publication, it came to our attention that the articles published in this Special Issue were not reviewed fully in line with the journal's peer review standards and policy. We did not find any evidence of misconduct by the authors. However, in order to ensure full assessment has been conducted, we sought expert advice on the validity and quality of the published articles from independent peer reviewers. Following this post publication peer review, the Editor has determined that the articles do not meet the required scholarly standards to remain published in the journal, and therefore has taken the decision to retract. The concerns raised have been shared with the authors and they have been given the opportunity to respond. The authors have been informed about the retraction of the article. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.The retracted articles will remain online to maintain the scholarly record, but they will be digitally watermarked on each page as ‘Retracted’.
Teleportation via an Entangled Coherent Channel and Decoherence Effect on This Channel

We study an entangled two-mode coherent state within the framework of2×2-dimensional Hilbert space. We investigate the problem of quantum teleportation ofa superposition coherent state via an entangled coherent channel. By three differentmeasures with the titles ``minimum assured fidelity (MASF)”, ``average teleportationfidelity” and ``optimal fidelity (f)” we study the quality of this kind of teleportation.Decoherence properties of the entangled coherent state due to channel losses areanalysed. For a symmetric noise channel, the degradation of optimal fidelity and degreeof entanglement are calculated. Also by two different measures with the titles``concurrence” and ``entanglement of formation” we study the amount of entanglementof a decohered quantum channel and discuss its details. We demonstrate thatentanglement of the decohered entangled coherent state is reduced but not throughlylost. Finally we find that the optimal fidelity of the decohered entangled coherent state ismore than the classical limit and the decohered entangled coherent state may be usefulfor quantum teleportation.
Morphology based Character Recognition of Overlapped and Touched Objects

This paper presents an attempt made to recognize characters from English alphabets and numbers by first segmenting them using bounding box and then recognizing each character individually. Each character data set contains 26 alphabets. For connected characters morphological operations are used that process the image based on shapes. The input image is processed using morphological operations by applying a structuring element and creating an output image of the same size. For the purpose of character recognition template matching technique is used. The proposed system shows good recognition rates as compared to other similar schemes for character segmentation and recognition.
Rain Removal Using Guided Image Filtering For Surveillance Videos

The Intelligent Transportation System includes management of vehicle transportation. Video from surveillance cameras can be used for monitoring the number of vehicles and speed using digital image processing. However, in rainy conditions the monitoring process will be less accurate. So, removing rain noise is a solution that can be used. The method that will be presented in our paper is the method of rain removal using the low frequency and high frequency parts of the video frame. For each frame, low frequency as an image non-rain. Then, high frequency part as input from the guided filter, so we get a non-rain component from the high frequency part, and add a low frequency part is the restored frames. we also restore the nature of the background edge. The experiment will generate rain noise from videos without rain. The type of rain is heavy rain, moderate rain and light rain. The result of rain removal will be calculated image quality with a peak signal to noise ratio (PSNR). In addition, proper selection of radius and regulation parameters will reduce the rain effect more optimally. To be more detailed, we also test the performance of method on videos with static and moving foreground. The application of guided filter algorithm for three times, contained in preprocessing, filtering and recovering, can improve image quality.
A Design for Bidirectional Conversion between Blocks and Text for App Inventor

Blocks programming environments lower barriers to programming using visual code fragments that prevent syntactic and static semantic errors and reduce cognitive load. However, visual blocks notations can make programs more difficult to read, write, and share. Dual-mode environments that allow bidirectional conversion between isomorphic blocks and text representations can leverage the benefits of both modes. We are designing a dual-mode system for MIT App Inventor that supports textual representations for blocks, workspaces, screens, and whole projects. We present a preliminary design for Venbrace, a fully-braced textual syntax for App Inventor, based on a collection of design principles. Since a key principle is employing evidence-based programming language design, we will follow an iterative process that interleaves user studies with implementation. We describe planned user studies involving individuals of various levels of programming experience that test the usability of Venbrace and explore possible improvements.
Clustering of short sentences through representation of text data

Natural Language Processing has developed in the past few years very quickly.Numerous new applications emerged from new methods, notably involved bythe creation of the popular word embedding Word2V ...
Maximum Fault Tolerant Tile Mining Algorithm Based on Parallel PSO

The current maximum fault-tolerant tile mining has the following problems: 1) the mining speed is slow 2) the mining speed is greatly affected by the tolerance. To solve these problems, a maximum fault-tolerant tile-mining algorithm based on parallel PSO is proposed in this paper. PSO algorithm is used to find the maximum fault-tolerant tile quickly and accurately, and the Spark framework is combined to further improve the calculation speed. Compared with the maximum fault-tolerant tile mining algorithm of integer linear programming, experimental results are superior to traditional algorithms in speed and stability. Then the proposed algorithm was applied to wind power generation system, and the experiment outcome shows that the algorithm is accurate and eddective for the dateset of real system.
The Degree of Implementing Hoshin Kanri Methodology in Developing Quality of Culture at the Jordanian Secondary Schools

The study aimed to identify the degree of implementing Hoshin Kanri methodology in developing the quality of culture at the Jordanian secondary schools.The study sample consisted of (190) female and male secondary school principals.To achieve the study's objectives, a related questionnaire has been used.The results of the study showed that the degree of implementing Hoshin Kanri methodology in developing the quality of culture at the Jordanian secondary schools was moderate from the secondary school principals' point of view.In light of the results, the study recommends developing techniques to effectively advance the Hoshin Kanri implementation levels in Jordanian schools.
New Learning Architecture for Effective Interoperability of Learner’s Data Management

The Learners of the current generation have grown up with digital technologies. However, these new sets and ability to learn whenever wherever are highly appreciated by learners and educators. In the context of the learning analytics and adaptation, this evolution creates various challenges, such as the learner’s data tracking and interoperability between learning systems. In this paper we shortly describe the xAPI, compare it to its predecessor of learner profile standards interoperability and present our proposed architecture to provide an interoperable exchanged learner’s profile exploiting the features offered by xAPI. Furthermore, this solution offer adapted learning content to the learner according to his formal and informal activities, which are monitored via xAPI.
The Influence of Self-Imagery Training on the Visual Perception of Young Children at Environmental Risk

본 연구는 두 가지 목적을 가지고 실시되었다. 첫째, 국내 환경적 위험군 유아들에 대한 유아특수 교육적 지원 필요성에 대한 제기로서 이미 해외에서는 1970년 후반부터 빈곤, 가정폭력 등에 노출된 유아들을 환경적 위험군으로 분류하였고 유아기 단계에서부터 별도의 교육적 지원에 대한 고려를 하고 있다. 관련 문제에 대해 유아특수교육 차원의 관심을 제고 하는 것이 본 연구의 가장 큰 목적이다. 둘째, 환경적 위험군 유아들에 대한 지원 방법으로서 심상훈련이 향후 다양한 발달의 기제들과 연계 되는 시지각운동에 미치는 영향에 대한 분석이다. 본 연구는 양육자와 교육기관의 허락을 받은 후 2018년 8월부터 12월(일주일에 2회 총 30회기) 동안 서울과 경기북부 소재 유치원과 저소득 아이돌봄 서비스를 지원 받는 가정을 대상으로 직접 방문을 통해 실시되었다. 본 연구에서 실험도구로 적용된 SIT프로그램은 유아들의 심상훈련을 위해 특허출원(10-2011-0059853)된 도구이며 연구 참여 유아들의 시지각발달 정도는 K-DTVP-3를 이용해서 측정되었다. 본 연구의 결과를 요약하면 다음과 같다. 실험군과 대조군으로 참여한 유아들의 사전 시지각발달 검사 결과를 통해 두 집단의 동질성이 확보되었다. 둘째, 실험 종료 후 실시한 두 집단에 대한 사후 시지각발달 검사에서 실험군에 속한 유아들의 점수가 대조군에 속한 유아들보다 유의미하게 높은 것으로 보고되었다. 대응표본 검사를 통해 사전과 사후검사 점수를 비교한 결과, 실험군의 사후점수가 사전점수보다 유의미하게 높아졌으나 대조군의 사전과 사후검사 점수에서는 유의미한 차이가 나타나지 않았다. 본 연구를 통해 유아특수교육의 교육적 범위에 대한 재해석의 필요성이 제기 되었다. 또한, 유아특수교육 현장에 대한 직접적 교육적 지원뿐 아니라 잠재적 유아특수교육 대상자들을 위한 다양한 교육콘텐츠 개발과 적용의 중요성이 강조되었다.This study have been conducted with two aims. The first and main goal was to expand the understanding in young children at environmental risk. The second purpose was to investigate the effects of ‘Self-Imagery Training’ on the visual perception of young children from disadvantaged backgrounds as an educational contents for them. An experimental study was conducted for 12 weeks and an intervention program consisting of 30 sessions was provided. After defining the meaning of environmental risk with previous studies, 62 young children at environmental risk were selected and involved in this study, and they were assigned randomly into the experimental group(N=32) or the control group(N=30). The researchers measured the visual perception level of the participants before the experiment. SIT(patent for self-imagery training for young children application 10-2011-0059853)program was utilized for the experiment. The results of the study indicated a significant difference after the research treatment in general visual perception, visual-motor integration, and motor-reduced visual perception. However, there was not a significant difference between the pre and post-tests in the control group. This study suggest the important fact of considering young children at environmental risk as those for early childhood education and confirms the positive influence of imagery training and may have a positive impact on the development of young children. Moreover, pathways through which poverty influences learning experiences and intervention strategies to improve the home environments of young children are proposed.
Sensitive Personal Data Publication on Higher Education Information System Websites in Indonesia

Personal data described as any information that relates to an identifiable individual that is stored, maintained its truth, and is protected its confidentiality to prevent abuse by irresponsible parties. In this study, we analyzed the types of sensitive personal data published along with their distribution on the higher education institutions' information system websites. We also implemented data mining clustering analysis using the Expectation-Maximization method. As a result, from 72,522 instances that have been analyzed based on NIST criteria and Indonesian Regulation Number 23 of the year 2006, around 87.72% out of 189,358 obtained sensitive personal data were Critical personally identifiable information (PII), while the remaining 12.28% were Potential PII. Types of Critical PII published, including the place of birth, date of birth, home address, telephone number, email address, face photo, religion, and employee identification number. Meanwhile, the Potential PII including position, work location/unit, district area of residence, and age. Average clusters accuracy obtained using Expectation Maximization was 98.53%, with 1,682 incorrectly clustered instances. In the future, the used criteria for determining sensitive personal data could refer to local regulations so that the results and the recommendations obtained are more suitable to the territory where the study conducted.
Exploring players' user experience in a high-embodied virtual reality game.

In the virtual reality (VR) field, embodiment is a concept related to the degree that a player can naturally control an avatar in a virtual world. Prior studies demonstrated that when the effects of VR on players' cognition are evaluated, both the level of immersion and embodiment should be considered. However, few studies have explored the value of the embodiment dimension in assessing the effect of VR on players' user experience. This study aims to fill the gap and explore the characteristics of players' user experience in a high-embodied VR game. Sixty-seven gamers were quasirandomly assigned to either desktop or VR groups and played the same first-person shooter (FPS) game for 10 minute per person after a short training. The VR-version FPS game afforded participants the capability of gestures and physical movement like being in a real battlefield. Participants' in-game biometric data and post-game questionnaire data were collected and then analyzed. This study's results showed that the characteristics of players' user experience in a highembodied VR game condition can be summarized as achieving a significantly higher level of emotional arousal, more positive experience and attitude towards the video game than a traditional desktop condition. All the evidence demonstrated that the embodiment dimension is a critical factor that designers should consider when designing for effective games.
STO vs ICO: A Theory of Token Issues Under Moral Hazard and Demand Uncertainty

This paper considers a financing problem for an innovative firm that is considering launching a web-based platform. Our model is the first one that analyzes an entrepreneur's choice between security tokens (via a security token offering (STO)) and utility tokens (via initial coin offering (ICO)). The entrepreneur on one hand faces a large degree of demand uncertainty on his product and on the other hand has to deal with incentive problems of professional blockchain participants who contribute to the development and sales of the product. We argue that utility tokens with profit rights are a better option for the firm compared to straight utility tokens or security tokens because they help the firm better deal with both the moral hazard problems (via profit sharing incentives) and demand uncertainty (they help the firm learn the product demand). This finding is consistent with some recent evidence. The paper also generates new predictions that have not been tested so far.
Library Guides: Undergraduate Research Workshop Series at Berks: Research Freestyle

Workshop series to prepare for the HECBC Undergraduate Research & Creativity Conference (or any other conference)