Reviewerly/exHarmony huggingface dataset:
MENINGKATKAN KEDISIPLINAN GURU SMP AWAL KARYA PEMBANGUNAN GALANG MELALUI PENERAPAN PENCATATAN PIKET

This research was conducted to implement strict and sustainable picket recording for the teachers of the SMP Awal Karya Pembangunan Galang, Deli Serdang Regency. This research is a school action research carried out for two cycles in the teachers of the SMP Awal Karya Pembangunan Galang in the 2018-2019 academic year. This research was conducted in two cycles, each cycle was conducted in one week. This research was conducted by observing the teacher's attendance at the first hour and the teacher's return at the last hour. The results of this study are: there is an increase in the discipline of the presence of teachers who enter at the first hour according to the schedule, and an increase in the discipline of teachers leaving the class at the last hour also according to the schedule
Group-Assign: Type Theoretic Framework for Human AI Orchestration

In today’s Information Age, we work under the constant drive to be more productive. Unsurprisingly, we progress towards being an AI-augmented workforce where we are augmented by AI assistants and collaborate with each other (and their AI assistants) at scale. In the context of humans, a human language suffices to describe and orchestrate our intents (and corresponding actions) with others. This, however, is clearly insufficient in the context of humans and machines. To achieve this, communication across a network of different humans and machines is crucial. With this objective, our research scope covers and presents a type theoretic framework and language built upon type theory (a branch of symbolic logic in mathematics), to enable the collaboration within a network of humans and AI assistants. While the idea of human-machine or human-computer collaboration is not new, to the best of our knowledge, we are one of the first to propose the use of type theory to orchestrate and describe human-machine collaboration. In our proposed work, we define a fundamental set of type theoretic rules and abstract functions Group and Assign to achieve the type theoretic description, composition and orchestration of intents and implementations for an AI-augmented workforce.
Positive Impact of Covid-19 Pandemic in Enhancing Digital Literacy Skills Among Library Professionals: A Study

The Corona virus pandemic has dramatically remodeled and transformed the education sector into a digital learning hub due to the closure of educational institutions globally. Possessing adequate digital literacy skills and embracing web-based techniques are the only means to ensure continuity in the process of teaching and learning. The purpose of this paper is to show the positive influence of Covid-19 pandemic in molding librarians into tech savvy library professionals in enhancing their digital knowledge and in upliftment of their IT skills. A structured online questionnaire using Google Forms was used to collect data from the librarians working in academic colleges across Goa. From the study it was found that Covid-19 pandemic period has played a positive role in uplifting the digital and technical knowledge of the library professionals, it has widened the use of various social media platforms in disseminating information to the patrons. The study highlighted that 75% of the librarians acquired digital literacy skills by taking part in the webinars on various topics. This paper also throws light on the importance of having knowledge of E-databases and E-resources in satisfying the needs of the users in the Covid-19 pandemic period.
The Use of Local Sensitive Hashing for E-learner Face Identification.

Because face can reveal so much hidden information, we need to interpret these data and benefit from them. Hence, our paper shows a new and productive facial image representation based on local sensitive hashing (LSH). This strategy makes it conceivable to recognize the students who pursue their preparation in our learning training; during every session, an image of the learner will be taken by the webcam to be compared to that already stored in the database. As soon as the learner is recognized, he/she must be arranged in the accordion to an appropriate profile that takes into consideration his/her weaknesses and strength, which is conducted with the help of the J48 as a predictive study. Furthermore, we utilize a light processing module on the client device with a compact code in order that we can have a lot of in formation transmission capable to send the component over the network and to have the option to record many photos in an enormous database in the cloud.
DATA CARVING LINEARLY FRAGMENTED JPEG USING FILE STRUCTURED BASED TECHNIQUE

Data carving is a robust technique that is used in the digital forensic investigation for data recovery. It is a file recovery technique that extract files based on the file format characteristic specifics and structure in which it can recover data without relying on metadata. Over the years, it has gathered the attention of researcher as it can overcome the shortcomings of the orthodox method of file recovery. However, many of the existing file carving tools were not specifically aimed and designed in consideration of fragmented file and fragmentation of a file can exist in different multitude of scenario. Thus, this paper proposes file carving tool that can recover linearly fragmented JPEG file using structured based technique where this technique utilizes the internal layout of the JPEG file with its elements such as header, footer, and the file size, to carve out non fragmented as well as linearly fragmented JPEG image. The proposed tool is tested and evaluated using Digital Forensic Research Workshop (DFRWS) 2006 challenge dataset where the proposed tool are able to carve out 8 JPEG images that are aligned with the project scope and the remaining unrecovered images are out of project scope where it is bi-fragmented or contained non-JPEG files in the fragmentation. Hence, the result shows that this tool has is capable of carving non-fragmented as well as linearly fragmented JPEG image and the objectives are achieved
Gauging the Acceptance of Contact Tracing Technology: An Empirical Study of Singapore Residents' Concerns and Trust in Information Sharing

In response to the COVID-19 pandemic, governments began implementing various forms of contact tracing technology. Singapore’s implementation of its contact tracing technology, TraceTogether, however, was met with significant concern by its population, with regard to privacy and data security. This concern did not fit with the general perception that Singaporeans have a high level of trust in its government. We explore this disconnect, using responses to our survey (conducted pre-COVID-19) in which we asked participants about their level of concern with the government and business collecting certain categories of personal data. The results show that respondents had less concern with the government as compared to a business collecting most forms of personal data. Nonetheless, they still had a moderately high level of concern about sharing such data with the government. We further found that income, education and perceived self-exposure to AI are associated with higher levels of concern with the government collecting personal data relevant to contact tracing, namely health history, location and social network friends’ information. This has implications for Singapore residents’ trust in government collecting data and hence the success of such projects, not just for contact tracing purposes but for other government-related data collection undertakings.
Pengaruh Pembelajaran Online terhadap Hasil Belajar Taruna Diploma III Teknik Bangunan dan Landasan Angkatan 4A dan 4B Semester II di Politeknik Penerbangan Surabaya

The purpose of e-learning is to increase the students' absorption of the material being taught, increase the active participation of students, improve their independent study skills, and improve the quality of learning materials. It is hoped that it can stimulate the growth of new students' innovations in accordance with their respective fields.In the midst of the Covid-19 pandemic, our education system must be ready to take the leap to transform online learning for all students / students / cadets and by all teachers and lecturers.Whereas all question items have a significance value of less than 0.05, so it is said that all questions posed to respondents are valid.The calculation results in the SPSS appendix show that the Cronbach's Alpha value is 0.917. This value is above 0.6, it can be said that the questionnaire in this study is reliable.The value of the correlation coefficient (R) is 0.975 or close to 1. This means that the relationship between the independent variables of online learning (X) and learning outcomes (Y) Cadets Diploma III of Building and Foundation Engineering Class 4A and 4B Semester II at Aviation Polytechnic of Surabaya is strong in the direction of . This means that if the free online learning variable (X) is increased, the dependent variable, namely the learning outcomes (Y) of the Cadets Diploma III in Building and Platform Engineering Class 4A and 4B Semester II at Aviation Polytechnic of Surabaya will also increase, and vice versa. The percentage of the influence of the independent variable on the dependent variable as shown by the coefficient of determination simultaneously (Rsquared¬) is 0.975 or 97.5%. This means that the ups and downs of the dependent variable, namely the learning outcomes (Y) of Cadets Diploma III in Building and Platform Engineering Class 4A and 4B Semester II at Aviation Polytechnic of Surabaya are influenced by free online learning (X) of 97.5% and the remaining 2.5 % influenced by other variables outside of this studyFor the free online learning variable (X), the t value obtained is 15.269 and the significance value is 0.000, this value is smaller than a = 0,05 so it means that the free online learning variable (X) has a significant effect on dependent variable learning outcomes (Y) Cadets Diploma III Building and Platform Engineering Batch 4A and 4B Semester II at Aviation Polytechnic of Surabaya
Short-term Photovoltaic Power Forecasting Based on Improved Firefly Algorithm to optimize support vector machine

With the current increasing demand in energy consumption, there is a huge increase of prominent energy problems that require us to imperatively seek for the new green energy sources. Photovoltaic power generation is one of the most feasible power generation methods due to its high cleanliness and static characteristics. This paper proposes a photoelectric power prediction method based on an improved firefly algorithm to optimize support vector machines (SVM) for short-term prediction. We effectively combine the regression support vector machine (SVR) with the modified firefly algorithm (MFFA) and use the firefly estimation method to determine the best fitness penalty factor c and kernel function g, so that the support vector machine can better predict the photovoltaic power. In order to make the firefly algorithm to optimize the support vector machine faster, we improved the firefly algorithm step factor a and introduced a weight coefficient π, Compared with conventional techniques, this method has better prediction results and prediction speed is also better than the traditional intelligent optimization models. Let's take the data from a photovoltaic base in the Desert Knowledge Australian Solar Energy Centre (DKASC) as an example.
A Low Power Architectural Framework for Automated Surveillance System with Low Bit Rate Transmission

Abstract The changed security scenario of the modern time has necessitated increased and sophisticated vigilance of the countries' borders. The technological challenges involved in accomplishing such feat of automated security system are many and require research at the components-and-algorithms as well as the architectural levels.  This paper proposes an architectural framework for automated video surveillance comprising a network of sensors and closed circuit television cameras as well as proposing algorithmic/component research of software and hardware for the core functioning of the framework, such as: communication protocols, object detection, data-integration, object identification, object tracking, video compression, threat identification, and alarm generation. In this paper, we are addressing some general topological and routing features that would be adopted in our system. There are two types of data with regard to data communication – video stream and object detection. The network is broken down into several disjoint, almost equal zones. A zone have one or more one cluster. A zone manager is chosen among the cluster heads depending on their relative residual energies. There are several levels of control that could be implemented with this arrangement with localized decision made, to get distributed effect at all levels. A cell tracks each target in its zone. If the target moves out of the range of a cell, the cell manager will send the target description to estimated next cell. The next cell starts tracking the target. If the estimated cell is wrongly chosen, corrections will be made by the cluster heads to get the new target-tracking. We also propose bitrate reduction algorithms to accommodate the limited bandwidth. One of the main feature of this paper is introducing a Low-Power Low-Bit rate video compression algorithm to accommodate the low power requirements at sensor nodes, and the low bit rate requirement for the communication protocol. We proposed two algorithms the ALBR and LPHSME. ALBR is addressing low bit rate required for sensors network with limited bandwidth which achieves a reduction in Average number of bits per Iframe by approximately 60% in case of low motion video sequences and 53% in case of fast motion video sequences . LPHSME addresses low power requirements of multi sensor network that has limited power batteries. The performance of the proposed LPHSME algorithm versus full search and three step search indicates  a reduction in motion estimation time by approximately 89% in case of low motion video sequences (e.g.,  Claire ) and 84% in case of fast motion video sequences. The reduced complexity of  LPHSME results in low power requirements.
Stopping the Press: New York Times Journalist Targeted by Saudi-linked Pegasus Spyware Operator

We thank Ben Hubbard for sharing his suspicious message with us, along with the many other journalists who have participated in our previous investigations. Special thanks to Sharly Chan, Miles Kenyon, and Adam Senft for copy editing and additional assistance.
An Introduction to Streaming Data

This chapter introduces you to streaming data, its various challenges, some of its real-world business applications, various windowing techniques, and the concepts of incremental and online learning algorithms. The chapter also introduces the scikit-multiflow framework in Python and some streaming data generators.
Can Robots replace Humans completely in the Workplaces

As we know now the world is filled with technology and AI (artificial intelligence) also with every electronic device there is information that is the internet. It’s all about the information here where the advanced users come which are known to be hackers worldwide. These hackers try to get information from a database of software where the personal information of a person will disclose all over the world.
Traffic Encryption: SSL/TLS

On today’s Internet, encryption is no longer optional. System administrators want security, users and customers demand privacy and confidentiality, governments and other authorities demand protection of privacy, and web browsers and search engines also insist on encryption.
The Politeness Concept of the Language Spoken by Women in Javanese Culture

This study critically examines the Politeness Concept of The Language Spoken by Women in Javanese Culture related to the realization or modesty of Javanese women in speaking with other people and what factors are behind this believed concept. The method used to study this topic is to use a description of the problem based on the concept of politeness from Foley, in the form of two types of politeness in general, namely positive and negative politeness. The results of this study generally describe Javanese women who more often use positive politeness strategies than negative politeness strategies when speaking. It also causes a woman to get closer to other women more quickly or with the opposite sex she has just met than men. Negative politeness strategies are mostly used by Javanese women in expressing apology. Secondly, in this study also identified factors underlying the concept of politeness, in these factors there are stereotypes in Javanese society which place women's gender as second sex after men and also the lack of confidence of women to express ideas or ideas as due to stereotypes in the community
UTILIZATION OF LEARNING MEDIA AND LEARNING MOTIVATION ON STUDENT LEARNING OUTCOMES OF SMP IN ASAHAN DISTRICT

This study was to determine the utiization of instructional media and learning motivation toward english learning outcomes. This research was conducted at the Junior High School Kisaran North Sumatera province with a sample of 28 students of class IX were obtained using the technique of multi-stage random sampling. The method used is the experimental design of treatment by level 2 x 2 with the dependent variable consists of local wisdom-based media and media-based presentation, moderator variables consist of high achievement and low achievement as well as the independent variable is the result of learning english . Collecting data using multiple-choice test instruments. Data analysis using descriptive and inferential statistics. Hypothesis testing is done by ANOVA two-lane after passing tests of normality and homogeneity. From the ANOVA calculation on the line between the two lanes of Learning Media (A) is known Fhitung> Ftabel (4.789> 4.260) so Ho rejected and declared there was significant difference in student learning outcomes were studied using local wisdom-based media with the use of media-based presentations. In line AxB interaction known Fhitung <F table (2.628 <4.260) so Ho accepted and declared there was no interaction effect of instructional media and learning motivation on student learning outcomes. Research results prove the use of Interactive media gives better results than the use of media-based presentation of the results of night grade students learn English. Keywords : Learningstudying english, Learining Motovation, interactive media, students Achievement
PENGARUH KOMPRES TEPID WATER SPONGE TERHADAP PENURUNAN SUHU TUBUH PADA ANAK YANG MENGALAMI HIPERTERMI DI RUANG MELUR RUMAH SAKIT UMUM DAERAH SIDIKALANG

ABSTRACT Â  A hyperthermia is an increase in body temperature that can occur that is Eƒ37,5Â°C.Â  compresses Tepid Water Sponge is the action by using a cloth or towel that has been dipped in warm water that is attached to certain parts so as to provide comfort and lower body temperature. This study aims to determine the effect of warm compress Tepid Water Sponge againt decreasing body temperature in hipertermia. The design of this research is Quasi eksperiment with one group pre post test design , with the number of respondents research six people. Technique of collecting data by using observation sheet. The results of this study indicate there is influence before and after given compresses Tepid Water Sponge . The assessment of the compressive Tepid Water Sponge therapeutic observation sheet is by the measurement of body temperature. If the body temperature decreases after a compress Tepid Water Sponge therapy effect. If the body temperature does not decrease/increase after a comress Tepid Water Sponge action the compress Tepid Water Sponge action has no effect. The results of this study into input for nursing services to deal with Hipertermia by providing compress Tepid Water Sponge . Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â  Keyword : Hipertermia, Compress Tepid Water Sponge, Decrease In Body Temperature
User Factor Adaptation for User Embedding via Multitask Learning

Language varies across users and their interested fields in social media data: words authored by a user across his/her interests may have different meanings (e.g., cool) or sentiments (e.g., fast). However, most of the existing methods to train user embeddings ignore the variations across user interests, such as product and movie categories (e.g., drama vs. action). In this study, we treat the user interest as domains and empirically examine how the user language can vary across the user factor in three English social media datasets. We then propose a user embedding model to account for the language variability of user interests via a multitask learning framework. The model learns user language and its variations without human supervision. While existing work mainly evaluated the user embedding by extrinsic tasks, we propose an intrinsic evaluation via clustering and evaluate user embeddings by an extrinsic task, text classification. The experiments on the three English-language social media datasets show that our proposed approach can generally outperform baselines via adapting the user factor.
DLRG@DravidianLangTech-EACL2021: Transformer based approachfor Offensive Language Identification on Code-Mixed Tamil

Internet advancements have made a huge impact on the communication pattern of people and their life style. People express their opinion on products, politics, movies etc. in social media. Even though, English is predominantly used, nowadays many people prefer to tweet in their native language and some- times by combining it with English. Sentiment analysis on such code-mixed tweets is challenging, due to large vocabulary, grammar and colloquial usage of many words. In this paper, the transformer based language model is applied to analyse the sentiment on Tanglish tweets, which is a combination of Tamil and English. This work has been submitted to the the shared task on DravidianLangTech- EACL2021. From the experimental results, it is shown that an F 1 score of 64% was achieved in detecting the hate speech in code-mixed Tamil-English tweets using bidirectional trans- former model.
HỆ THỐNG PHÂN PHỐI KHÓA LƯỢNG TỬ ĐA KÊNH TỪ VỆ TINH SỬ DỤNG SCM-WDM

Quantum key distribution (QKD is a solution capable of achieving unconditional security by applying the law of quantum mechanics to distribute a secure key between two legitimate parties in the presence of an eavesdropper. Using satellites to distribute quantum keys to ground stations over a free space optical (FSO) channel  is a promising solution in creating a global QKD network. However, due to the influence of the FSO channel, especially atmospheric disturbances, the secret key rate (SKR) of current QKD systems is limited. Therefore, this study proposes a model of multichannel QKD system based on wavelength division multiplexing (WDM) and subcarrier multiplexing (SCM) to increase the SKR. Based on theoretical analysis with the tools of mathematics and probability, the authors have developed formulas to calculate SKR and quantum bit error rate of the proposed system. Numerical results show that multichannel QKD systems allow for improved SKR compared to single-channel systems while still meeting QBER requirements.