Reviewerly/exHarmony huggingface dataset:
IMPLEMENTASI DIGITAL SIGNATURE ALGORITHM (DSA) MENGGUNAKAN SECURE HASH ALGORITHM-256 (SHA-256) PADA MEDIA GAMBAR

With the development of technology, documents not only produced in printed form but also produced in digital form, especially image documents. The advantage of digital documents is that they are easier and more efficient to use but digital documents are also easy to fake. To overcome this, a digital document security technique is needed, that is the document is digitally signed. This study aims to explain the process of implementing Digital Signature Algorithm by using the Secure Hash Algorithm-256 as hash function on image file and designing digital signature programs.The results of this study indicate that the Digital Signature Algorithm (DSA) using the Secure Hash Algorithm-256 hash function can’t only be implemented in text messages, but can be implemented in image file by the method of image conversion to ASCII images. DSA can also be programmed using the Python programming language to facilitate the generation and authentication of signatures.
Voice shift in the translation from Dutch into Indonesian

This article discusses voice shift in the translation of academic texts from Dutch into Indonesian. The data used involve ten articles taken from the proceedings of Dutch Study Congresses in Indonesia published in 2010 and 2015. A total number of 3,085 clauses were analysed using the mixed method. The result shows that, of all clauses with verbal predicates, nearly 15.06% of clauses with agentive voice shift to patientive and 14.8% of clauses with patientive voice shift to agentive. The causes of voice shift are related to lexical and grammatical levels. However, most voice shift is triggered by preserving word order which is heavily related to information flow on the textual level. Voice shift leads to shifts nuances in meaning, but not the core meaning. Textual meaning is preserved. Therefore, voice shift is caused by efforts to attain a textual equivalence.
Financial Literacy Education Through Fiqh Mu’āmalāt Learning Based on Kitab Kuning

This research used R&D approach 4D model goals to gain the design for a learning program to guide students in pondok pesantren on achieving financial literacy throught fiqh mu’āmalāt learning that is based on kitab kuning that validated by experts and practitioners and reliability counted based on test.
Analysis of Factors of Employee Work Satisfaction At The Office Of The Management Casablanca Est To Residences.

Employees are the most critical resources to drive the organization. Hence employee satisfaction is important to the company. This research uncovers the factors of employee work satisfaction in the apartment Casablanca east to residences. For this, data collection is done by means of a questionnaire on 111 workers in management apartment. Samples were taken using formulas Slovin. Testing the quality of data in this research was done using validity and reliability. Subsequently, data was subject to factor analysis. It is known that through factoring, it can be reduced to five factors that are significant - personnel management ( 0,600 > 0,5 ), facilities employees (0,565 > 0,5 ), of managerial capabilities ( 0,520 > 0,5 ), employment regulation (0,627 > 0,5), secure (0,565 > 0,5 ). Hence employee satisfaction is very predominant with personnel management related to trust, attention to employees, equal treatment, variation work, conducive environment, a superior respect subordinate, communication, and awards
A Survey on the Application of Educational Lighting Board as an Educational Aid Tool of Occupational Health Students

A Survey on the Application of Educational Lighting Board as an Educational Aid Tool of Occupational Health Students
A StyleMap-Based Generator for Real-Time Image Projection and Local Editing

Generative adversarial networks (GANs) have been successful in synthesizing and manipulating synthetic but realistic images from latent vectors. However, it is still challenging for GANs to manipulate real images, especially in real-time. State-of-the-art GAN-based methods for editing real images suffer from time-consuming operations in projecting real images to latent vectors. Alternatively, an encoder can be trained to embed real images to the latent space instantly, but it loses details drastically. We propose StyleMapGAN, which adopts a novel representation of latent space, called stylemap, incorporating spatial dimensions into embedding. Because each spatial location in the stylemap contributes to its corresponding region of the generated images, the real-time projection through the encoder becomes accurate as well as editing real images becomes spatially controllable. Experimental results demonstrate that our method significantly outperforms state-of-the-art models in various image manipulation tasks such as local editing and image interpolation. Especially, detailed comparisons show that our local editing method successfully reflects not only the color and texture but also the shape of a reference image while preserving untargeted regions.
English Teacher’s Strategies To Cope With The Problems In Applying Online Learning At Al-Firdaus Islamic Elementary School

This study aims to find the English teacher's strategy to overcome the problems that occur in online learning at Al-Firdaus Islamic Elementary School. The subject of the study is all English teachers at Al-Firdaus Islamic Elementary School. This study uses a qualitative method. Qualitative data is obtained through observation and interview. The data is analyzed using the following steps: data reduction, data presentation and making conclusion. The study find problems faced by the English teachers in applying online learning process, that is the limited time, internet connection, and students difficulties to understand the materials in online learning. The researcher also find the strategies used to cope with the problems that is dealing with the limited time. The teachers apply two strategies; giving more assignment, separatin the meeting into two (for boys and gilrs). To overcome the internet connection, the school improves the internet connection system. While for overcoming the students' difficulty in understanding the materials, the teachers apply personal approach.
Enhancing Students’ Pronunciation Accuracy through Speechnotes Application at MAN 1 Semarang

Automatic Speech Recognition or ASR is used as a part of CAPT or computer-assisted pronunciation training application to improve learners’ foreign language in pronunciation. However, nowadays there are many application which adopted ASR technology which one of those is Speechnotes application. Speechnotes application is WellSource creation to make the user recognize their speech accuracy and Speechnotes also used as part of MALL or Moblie Assisted Learning Language. Therefore, this study aimed to enhance students’ pronunciation accuracy by using Speechnotes application through classroom action research which were done in three cycles, which every cycle consisted of planning, action, observation, and reflection. The participant were students of XI-1 IPS of MAN 1 Semarang. The data were collected from students result of pronunciation’ recording activity by using Speechnotes in every cycle, pre-test, a questionnaire of students’ response, field-note to observe students’ response, and interview. The instrument had been analysed by using SPSS, which to describe the statistics, sample test, independent simple t-test, validity dan reliability. The result after doing three cycles, students’ pronunciation got significant in making  mistake precentage. The first cycle got 15.29% mistake words which including homophone and difficult words such as weight, niche and bony. The second cycle got 5.81% mistake words and the last cycle got 2.39% mistake words which in every cycle, the homophones words still could not be interpreted. By filling the questionnaire and interview, 66.3% students agreed  to use Speech--notes can improve their pronunciation and students’ confidence during learning in the class. Keywords: Enhancing, Pronunciation, Automatic Speech Recognition (ASR), technology, Speechnotes application
RESPON SISWA TERHADAP MODEL THINK TALK WRITE BERBANTUAN MEDIA IKLAN DALAM PEMBELAJARAN MENULIS TEKS PERSUASI DI SMP

This research is motivated by the difficulties experienced by students in writing persuasion text essay in midlle School . The facts in the field state that students are difficult to get ideas, develop ideas and apply language rules that should be in the text of persuasion. Therefore the researcher tries to apply the Think Talk Write (TTW) learning model with the help of advertising medias to overcome the problem. The formulation of the problem in this study is how are students' responses to learning to write persuasion text using the think talk write model assisted by advertising media ?. The method used in this research is descriptive qualitative and the instruments used are questionnaires. Based on data processing in this study there were 89.5% of responses that stated positive. Thus, learning to write persuasive texts with the model of think talk write assisted by advertising media in class VIII F, SMP received very good responses.
LibGuides: So You Want to Be a Writer?: Teen Writing Guide: Writing Resources

A writing guide for teens aimed at writers of any skill level, from those who are just getting started on their writing journey to those who have been writing for some time.
TELL ME: Design of an Intelligence-Empowered Recommendation System

With the advances in science and technology, the life becomes smarter and more convenient. In recent years, the Artificial intelligence (AI) is a popular topic. AI can be used in many areas such as healthcare, Automotive, Finance, etc. For instance, the smart phone could be a multi-function entity such as voice connecting, data storing, information displaying, etc. These are expected to provide more significant and precise function for each user based on personal requirement. This study, with the concern on high-quality service provision, seeks for the possibility in developing location-based service(s) based on the concept of anticipatory computing. We attempt to achieve the concept of request-free and realize the scenario of ‘act before you act.’ Hence, three main portions will be discussed.
Технологии использования образовательного портала Гродненского государственного университета имени Янки Купалы для реализации проектного метода и практико-ориентированного подхода в преподавании

The experience of teaching university disciplines “Cryptographic Methods” and “Information Resources” using the project method and practice-oriented approach in teaching is analyzed; the opinion of students about online learning is studied. The author describes test work with the elements “Seminar” and “Wiki” of the educational portal of Yanka Kupala State University of Grodno in order to improve the quality of teaching university disciplines in digital format
Lighting up the Dark Web

Profound web content can’t be recorded via web index, for example, Google, Yahoo and Bing, and darknet exists in the profound web. Dim web has been deliberately covered up and it isn’t open through standard program. Profound web can be gotten to by any individual who has The Onion Router (TOR) program. TOR is a virtual and scrambled passage which enables individuals to conceal their character and system traffic, and enable them to utilize web namelessly. The dull web is for all intents and purposes online market for anything, including however not restricted to drugs, weapons, Visa information, produced records, procure administrations for homicide, opiates and foul erotic entertainment and so on,. As a result of these reasons, it is hard for law authorization offices or advanced scientific experts to pinpoint the cause of traffic, area or responsibility for PC or individual on the dull net.
Användarupplevelser i administrativa system

It is nowadays almost a given when developing graphical interfaces to allocate resources for designing and creating a great user experience for the users. This however has not yet found its way int ...
Research Guides: Library Guide to SIP Research: Literature Review

Each SIP is unique. These resources and suggestions do not replace guidance given by departments or advisors.
The Effects of Electronic Alert Letters in the Time of COVID-19

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Copy DOI
Analisis Kesalahan Berbahasa pada Tabloid Kontan dalam Kolom Bisnis Edisi Juni-September 2019

This study has two objectives, (1) to describe and explain the form of languageerrors in the Kontan Tabloid in the June-September 2019 Edition Businesscolumn. (2) to describe and explain the analysis of the forms of language errors inthe KontanTabloid in the June-September 2019 Edition Business column. Thisresearch is a qualitative descriptive study. The data source in this study is theJune-September 2019 edition of the Cash Tabloid. The data are in the form oflanguage errors in the Kontan Tabloid in the June-September 2019 EditionBusiness column. Data collection techniques in this study are to use the refermethod and follow up using the record method. Data analysis techniques usingthe method of matching and agitating. The results of research on language erroranalysis in the Cash Tabloid in the business column can be divided into fourforms of error. (1) Errors in the phonology field consist of phoneme removalerrors, phoneme changes, addition of vowel or consonant phonemes, and italics.(2) Mistakes in the field of morphology consist of word order, derivation, diction,contamination, and pleonasm (3) syntactic field errors related, for example with(1) non-standard structured sentences, (2) ambiguous sentences, (3) unclearsentences , (4) improper diction in forming sentences, (5) sentence contamination,(6) coherence, (7) redundant use of words, (8) improper absorption words informing sentences, and (9) logic and (4) Semantic field errors related to wordmeanings.
Text-To-Speech (TTS) Conversion System for Gujarati Language

Text-to-speech (TTS) conversion system enables user to enter text in Gujarati language and as an output it generates the equivalent sound. This type of system will be greatly useful for illiterate and vision-impaired people to hear and understand the content. TTS systems are still suffering from the problem of producing emotional speech like that of human being. Scientists are trying to give emotions and feelings to it. This shows that research work can be done to enhance the efficiency of TTS system. There are TTS systems that are under development for many languages other than Gujarati language. So, we are proposing the TTS system, which will work on Gujarati language. The input of our desired system is typed or scanned Gujarati text and equivalent Gujarati speech with smooth flow will be generated as an output. We are trying to add a new feature through which we can hear our own voice by superimposing our own voice frequency on the pre-recorded synthesized speech, so that we can listen to any text in our own voice. This paper starts with the introduction to the fundamental concepts of TTS synthesis. So, it will be useful for the readers who are less familiar in this area of research.
Fraunhofer IAIS at FinCausal 2020, Tasks 1 & 2: Using Ensemble Methods and Sequence Tagging to Detect Causality in Financial Documents

The FinCausal 2020 shared task aims to detect causality on financial news and identify those parts of the causal sentences related to the underlying cause and effect. We apply ensemble-based and sequence tagging methods for identifying causality, and extracting causal subsequences. Our models yield promising results on both sub-tasks, with the prospect of further improvement given more time and computing resources. With respect to task 1, we achieved an F1 score of 0.9429 on the evaluation data, and a corresponding ranking of 12/14. For task 2, we were ranked 6/10, with an F1 score of 0.76 and an ExactMatch score of 0.1912.
Archives: Features without a business plan

Language archives effectively achieve their stated goal of long-term data storage, but they often fail to meet the needs of both community member users and also researcher users. We present the mismatch between the services offered by ‘language archives’ and the jobs to be done by both segments of archive service consumers as a business model mismatch. We present this mismatch as a business risk which mitigates against the mission of archives. Finally, we discuss some technical innovations which would bring workflow revisions and ease consumer friction, but we hold that this is ultimately a business model problem and not a technological problem, because an organization’s business plan is what drives it choice of technological deployment.
Incorporating Terminology Constraints in Automatic Post-Editing.

Users of machine translation (MT) may want to ensure the use of specific lexical terminologies. While there exist techniques for incorporating terminology constraints during inference for MT, current APE approaches cannot ensure that they will appear in the final translation. In this paper, we present both autoregressive and non-autoregressive models for lexically constrained APE, demonstrating that our approach enables preservation of 95% of the terminologies and also improves translation quality on English-German benchmarks. Even when applied to lexically constrained MT output, our approach is able to improve preservation of the terminologies. However, we show that our models do not learn to copy constraints systematically and suggest a simple data augmentation technique that leads to improved performance and robustness.
Implementasi Algoritma K-Medoids Untuk Mengelompokkan Limbah Pabrik Yang Berbahaya (Studi Kasus: PT.Indowastek)

Waste is waste material resulting from human activities that has no economic value. Waste has types, namely: liquid waste, gas waste, solid waste, and hazardous waste, where the most dangerous waste for humans is hazardous waste. Data mining is the process of recognizing an interesting knowledge of the amount of data in the database and so that a pattern is obtained that has a method, one of the K-Medoids algorithms. The result of this research is where a hazardous factory waste can be grouped into harmful wastes in the company PT. Indowastek with the K-Medoids algorithm, if the company has no problem determining these wastes with this algorithm makes it easier for PT Indowastek. Keywords : K-Medoids Algorithm, Data Mining, Waste, Hazardous
Female Student Participation in Software Engineering Projects: Opportunities to Model Project Evaluation and to Improve Early Prediction of Teamwork Failure

Software engineering project is the preferred mean to measure competency and practical skills among learners in IT-fields.This study investigates the opportunities to model software engineering project final evaluation and improve early prediction of academic software engineering project failure by considering female student participation as a teamwork member, regardless of being a teamwork leader or a teamwork regular member.Four distinct arrangements of software engineering development teamwork are advised and studied.Those arrangements range from female-less participation teamwork to female-dominated participation teamwork.Machine learning techniques are leveraged to build prediction models.Teams are evaluated from two distinct perspectives.First, software products submitted at the end of each project life cycle milestone, namely product perspective.Second, the degree of obeying the good practices of software engineering project development, namely process perspective.Results reveal significant differences due to female student participation.Arrangement of female-less participation attains the worst modeling and prediction performance compared to the other arrangements of female student participation.
Social media - Facebook, Twitter, Instagram and YouTube

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Detecting changes in web applications

As the availability and popularity of the Internet continues to grow, the trend ofproviding global access to business resources and services online is an efficient andprofitable way for organizatio ...
Multi-task Learning for Automated Essay Scoring with Sentiment Analysis

Automated Essay Scoring (AES) is a process that aims to alleviate the workload of graders and improve the feedback cycle in educational systems. Multi-task learning models, one of the deep learning techniques that have recently been applied to many NLP tasks, demonstrate the vast potential for AES. In this work, we present an approach for combining two tasks, sentiment analysis, and AES by utilizing multi-task learning. The model is based on a hierarchical neural network that learns to predict a holistic score at the document-level along with sentiment classes at the word-level and sentence-level. The sentiment features extracted from opinion expressions can enhance a vanilla holistic essay scoring, which mainly focuses on lexicon and text semantics. Our approach demonstrates that sentiment features are beneficial for some essay prompts, and the performance is competitive to other deep learning models on the Automated StudentAssessment Prize (ASAP) benchmark. TheQuadratic Weighted Kappa (QWK) is used to measure the agreement between the human grader’s score and the model’s prediction. Ourmodel produces a QWK of 0.763.
Feature Selection Using Multiple Kernel Learning Methods

Picture denoising is a significant pre-preparing step in picture investigation. Different denoising calculations, for example, BM3D, PCD, and K = SVD, get momentous impacts. As of late, a profound denoising auto-encoder has been proposed and indicated amazing execution contrasted with customary picture denoising calculations. Right now, study the factual highlights of reestablished picture residuals created by denoising auto-encoders and suggest an improved preparing misfortune work for denoising auto-encoders dependent on method commotion and entropy augmentation guideline, with leftover insights as imperative conditions. We contrast it and regular denoising calculations including unique denoising auto-encoders, BM3D, complete variety (TV) minimization, and non-neighborhood mean (NLM) calculations. Trials show that the improved denoising auto-encoders present less non-existent curios and are more heartiness than other cutting edge denoising strategies in both PSNR and SSIM lists, particularly under low SNR. Picture denoising is a significant pre-preparing step in clinical picture investigation. Various calculations have been proposed in recent decades with fluctuating denoising exhibitions. All the more as of late, having beated every single traditional technique, profound learning-based models have indicated an extraordinary guarantee. These strategies are anyway restricted for the necessity of enormous preparing test size and high computational expenses. Right now show that utilizing little example size, denoising auto-encoders built utilizing convolutional layers can be utilized for proficient denoising of clinical pictures.