Reviewerly/exHarmony huggingface dataset:
Neural Networks and Adapted Optimal Transport

Within Data Science scenario both Machine Learning (ML) and Neural Networks (NNs) are widely used for a plethora of applications, spanning from engineering to biology, from finance to medicine. Meanwhile, the pure analytical analysis of related models used often lacks of detailed description. Trying to close this gap, during recent years the theory of Optimal Transport start becoming more a more popular within the Data Science arena, since it allows for efficient and scalable solutions about what can be broadly referred as Artificial Intelligence tasks, particularly by using approximate solvers through linear programming. More precisely, let us recall that both in ML and statistics, minimizing an objective function over the space of probability measures is fundamental problem. Along this line, the training of a Neural Network through Stochastic Gradient Descent has been shown to be equivalent to a gradient flow in Wasserstein space. Moreover, in many applications, it is crucial to consider the causal structure of the data generating process. In view of providing a possibly unifying as well as efficient approach to latter questions, we consider the Adapted Optimal Transport (AOT) method which allows to incorporate causality constraints into the optimization of the Wasserstein distance. AOT is particularly useful when dealing with laws of stochastic processes, being exploitable to encode an adapted (non-anticipative) constraint into the allocation of mass of the classical OT problem. Accordingly, we provide an in depth exploration of the connections between supervised learning and AOT, providing theoretical insights into the benefits of including causality constraints for developing more robust, scalable and accurate algorithms, while maintainig their computational efforts at minimum possible levels.
Writing Letters Training in Lumbung Baca Luwungragi Village

Community service activity is training in writing correspondence on contextual or real life. The team carried out the movement in the Lumbung Baca village of Luwungragi district of Bulakamba Brebes. The first part is the trainee's initial understanding of correspondence in a contextual approach, then the second part trainee's final experience and skills in writing the letter. This initial understanding is using questionnaires given to trainees. Then the trainees responded to the question to the questionnaire. The questionnaire contains about the knowledge of writing correspondence in contextual or real life. The understanding consists of definitions, objectives, functions, classifications, forms, and types of everyday letters. The student of Universitas Muhadi Setiabudi can show trainee in the following table. Thus, correspondence writing training in a real-life context can explain the trainees writing letters in Luwungragi village. In addition to learning, trainees also gain skills in writing letters for the results of writing a letter because of the devotion report attachment.
Utilization of Used Bulbs as Learning Media Innovations to Improve Visual/Spatial Intelligence in Early Childhood

This Community Service Implementation Activity aims to introduce to early childhood children in Kasih Ibu schools the use of Waste / Used Materials that can be used as a medium for learning in class and as a medium for recognizing colors and reading so that children are more interested in participating in learning activities in class. With learning media with the bulbs used by early childhood , they are provoked and moved to be more willing to know about how to analyze colors and how to read easily. This stage in Devotion is the first one we make observations to the Kasih Ibu school, this observation is used as a reference to find out the actual conditions in the field directly. The second stage is the introduction of learning media that utilizes the media of the former bulb, the third stage is evaluation and monitoring, and the last stage is the results and conclusion. We hope that after carrying out this community service activity, we can increase the interest in learning in mother-love schools so that children in their learning activities are more active, happy, and able to receive material and explanations well and maximally.
Public Speaking Training at SMKN 1 Slawi

One element most important from life socializing is interacting with other people. A person's verbal ability becomes very important because talking to other people will knowing ability someone and can rate it or know with term Public speaking. The phenomenon that happened Moment this many held open Public speaking training for general or organized by the agency or school. Public speaking training shows existence needs will reference base for understanding basics speaking in front of general like at the start of the heyday rhetoric. The UPS Tegal Service Team scheduled the implementation of public speaking training at SMKN 1 Slawi as a form of Devotion To the Community. Destination holding is to improve the skills and abilities of students/participants in public speaking so that they can be applied in life daily or later in the world of work. Implementation use method lecture ( gift ) materials and training directly (workshop), with target participants SMKN 1 Slawi students as many as 50 participants. mplementation condwas ucted two-dayday implementations. Output from devotion to Public this is mass media publication or rise journal devotion UPS Tegal community.
Study of Students’ Perception on Using Facebook for Communication

The research was aimed to find out students’ perception towards the use of Facebook for written communication outside of the classroom tenuously. The research was conducted in a descriptive quantitative study that was accomplished at the Eleventh grade students of Multimedia program major at SMK Negeri 6 Pontianak. The survey questionnaire was administered to the 50 participants throughout Google Form to collect the data accessibly. The result elucidated that the ground of Facebook had positively reinforced students (96%) to communicate in the English language within solitary and intercommunication state. Accordingly, the finding in the research presented that 80% of students agreed that Facebook is easy and pleasing to communicate in English autonomously. Further, 88% of students agreed that Facebook personal chat is the most used feature to communicate in English conveniently. Additionally, 66% of students agreed that Facebook allowed them to utilize English for written communication. In sum, the students were agreed on Facebook as a helpful platform for communication. It was shown in 50% students disagreed that they feel less embarrassed to communicate in English on Facebook as a challenge. Hence, students’ personal interest on Facebook can be channeled to communicate in English collaboratively. It is suggested that the use of Facebook for communication in English language considerably set the tool to encourage school integration of the educational technologically external environment.
Designing Transactional Conversation Videos as Supplementary Materials to Support Teaching English Speaking Skill

This research was aimed at designing transactional conversation videos as supplementary materials to support teaching English speaking skills. This research is a design and development research adopted from the ADDIE model. The respondents of this research were the second semester students of English Education Study Program (EESP) Universitas Tanjungpura. This research was done by three phases of the ADDIE approach, which is ADD. In the Analyze phase, the researcher observed the students’ and the teacher’s needs and the syllabus applied. In the Design phase, the researcher observed examples of good product videos, theories, and references for making the video. In the Develop phase, the researcher used Adobe Premier Pro to develop learning videos for the students. It was found that the design of the product was successfully integrated with the syllabus and met the criteria of success in product validation. The result of validation showed that the applied video with the Student’s book was helpful for the students to support them in learning to speak for Transactional Functions.
Teacher`s Challenges and Efforts in Teaching English Vocabulary for Deaf Students

The present study was conducted in order to find out the challenges faced by non-certified special education English teacher in teaching English vocabulary for deaf students and the teacher`s efforts to face those challenges. This was a case study design which used qualitative method as the methodology. The data were taken from the interview and observations of the non-certified special education English teacher who taught English at the X grade of SMALB-B Dharma Asih Pontianak. The result of the study showed that there were several challenges such as students` misinterpretation of words from teacher`s similar lip movements, students` less attention, delivering the meaning of the words, students` lack of articulation, comprehension, and remembering English vocabulary, little experiences of the teacher in using sign language, and the needs of repetition. There were also several efforts to face those challenges such as providing different English vocabulary in each meeting, using picture as a media, using sign language as an alternative communication, drilling, and waving either patting on deaf students` shoulder to get their attention.
Implementation of Read, Encode, Annotate, adn Ponder (REAP) Strategy To Improve Students’ Reading Comprehension

This research aims to improve students’ reading comprehension of narrative text by using Read, Encode, Annotate, and Ponder (REAP) strategy. This research is a classroom action research which was conducted in three cycles. The participants of this research are the teacher and the students in class X IIS 4 of SMA Negeri 1 Kayan Hulu.The study showed that the use of REAP strategy gave significant improvement in students’ reading comprehension of narrative text. Before implementing the strategy, the students’ understanding of the text were not well structured because they could not comprehend the text or story clearly. They were not motivated to read and comprehend the text. The students’ problems solved when the researcher implemented REAP strategy for teaching and learning. REAP strategy gave an active process of reading which can help students to construct their greater understanding about the text. It was shown by students’ enthusiasm to pay attention in doing every activity during teaching and learning process used REAP strategy. Furthermore, the students showed motivation and enthusiasm during the learning phase of teaching. In conclusion, the use of REAP strategy could enhance students’ reading comprehension of narrative text.
Browser-in-the-Middle - Evaluation of a modern approach to phishing

This paper examines the phishing technique Browser-in-the-Middle and its practical implications in the context of logins protected by multi-factor authentication. We implement and analyze Browser-in-the-Middle (BitM) attacks, evaluate them and discuss suitable measures for mitigation. To facilitate a thorough analysis, we implement two variants of BitM by using two different technology stacks and compare them to a conventional phishing system based on a proxy. To evaluate BitM attacks, we test our implementations on a number of popular websites. Our results show that in practice BitM attacks are currently highly capable of stealing login information protected by more than one factor, since the difficulty to detect such an attack appears to be greater when using BitM than comparable techniques. Therefore, we propose a new entry for BitM in the Common Attack Patterns Enumeration and Classification (CAPEC). The high effectiveness of the attack technique is limited by mitigation methods such as the use of resistant factors for two-sided authentication. We conclude that BitM attacks can potentially be used for highly effective targeted phishing, but they are unlikely to scale well enough for large-scale phishing attacks aiming at a broad variety of users.
Science in Quarantine: Experimenting From Home. An Interactive Walkthrough of Science Experiments at Home.

“Science in Quarantine: Experimenting from Home” is an interactive, take-home style packet composed of different science experiments that can be done with common materials found around the house. The project features a culmination of 11 different science experiments and is geared towards students at the intermediate- and middle-school levels of education. All the experiments have been thoroughly designed and tested in such a way which enables the student to have an easy time navigating which experiment appeals to them, as well as the actual performance of the experiment of interest. Experiments within this project aim to cover multiple aspects of science, including chemistry, biology, physics, and psychology. Past the title page, the experiments begin. They do not have to be done in any order and students can choose which experiment to try based on personal interest or which materials are readily available. As a project which originated during a global pandemic, the goal is to bring science home for students who may have been in the classroom less this academic year.
Deep Learning Approach for Suspicious Activity Detection from Surveillance Video

Abstract: In today's uncertain world, video surveillance plays a vital role in maintaining indoor and outdoor security. Video surveillance system components such as behaviour detection, behaviour understanding, and normal or suspicious activity classification can be used for real-time applications. This article uses a hierarchical approach to detect various suspicious activities such as loitering, fainting, and trespassing. This approach is based on motion properties between different objects. First, various suspicious activities are defined using a semantic approach. Object detection is then performed by background subtraction. Detected objects are classified as live (human) or non-live (bag). These objects need to be tracked and this is done using correlation techniques. Finally, motion features and temporal information are used to classify events as normal or suspicious. A semantics-based approach is used, resulting in low computational complexity and high efficiency of the approach.
Quantum Circuit Implementation and Resource Analysis of LBlock and LiCi

Due to Grover's algorithm, any exhaustive search attack of block ciphers can achieve a quadratic speed-up. To implement Grover,s exhaustive search and accurately estimate the required resources, one needs to implement the target ciphers as quantum circuits. Recently, there has been increasing interest in quantum circuits implementing lightweight ciphers. In this paper we present the quantum implementations and resource estimates of the lightweight ciphers LBlock and LiCi. We optimize the quantum circuit implementations in the number of gates, required qubits and the circuit depth, and simulate the quantum circuits on ProjectQ. Furthermore, based on the quantum implementations, we analyze the resources required for exhaustive key search attacks of LBlock and LiCi with Grover's algorithm. Finally, we compare the resources for implementing LBlock and LiCi with those of other lightweight ciphers.
Quantum MAC: Genuine Entanglement Access Control via Many-Body Dicke States

Multipartite entanglement plays a crucial role for the design of the Quantum Internet, due to its peculiarities with no classical counterpart. Yet, for entanglement-based quantum networks, a key open issue is constituted by the lack of an effective entanglement access control (EAC) strategy for properly handling and coordinating the quantum nodes in accessing the entangled resource. In this paper, we design a quantum-genuine entanglement access control (EAC) to solve the contention problem arising in accessing a multipartite entangled resource. The proposed quantum-genuine EAC is able to: i) fairly select a subset of nodes granted with the access to the contended resource; ii) preserve the privacy and anonymity of the identities of the selected nodes; iii) avoid to delegate the signaling arising with entanglement access control to the classical network. We also conduct a theoretical analysis of noise effects on the proposed EAC. This theoretical analysis is able to catch the complex noise effects on the EAC through meaningful parameters.
Development of Android-based Edutainment game on Numerical Ability

Learning mathematic cannot be separated from the mathematical symbol and a numerical skill, which is required as ability to perform calculation and related matters with the numbers. This research is aimed to improve the numerical ability of students. The method used was based on Borg and call, which consisted of ten main stages involved. The first research result is the validation of android-based mobile games edutainment, that is, the average value of the three experts is 78.33% with valid criteria. Then the average validation results of the android mobile game test questions based on edutainment is 77.77% with valid criteria. The second is the value of simplicity, seen from the value of the questionnaire which was filled in by all fresh graduates which was accumulated so that a percentage of 85.84% was obtained with very practical criteria. Furthermore, the effectiveness is seen from the increase in scores workmanship of fresh graduate pretest and posttest which is calculated by the formula T test results obtained by increasing the pretest posttest score then ability numerical increase so that it is categorized as effective. Thus it is concluded that the development of android mobile games is based on edutainment on numerical ability is categorized valid, practical, and effective for used&#x0D;
Analysis of the Naïve Bayes Method for Determining Social Assistance Eligibility Public

Economic needs are community needs that are used to meet daily needs. Therefore, economic needs are very important for the life of every society. There is a gap in the economic needs of the community, the government created a social assistance program which is assistance provided to the community in the form of cash or non-cash. The help is made for welfare society from inequality, especially economic inequality. So researchers will carry out a data classification of people who are eligible for social assistance. The classification will be carried out using the Naïve Bayes method. The Naïve Bayes method is a simple classification method for calculating the probability of a combination of certain data. The data to be used by researchers is community data as much as 62 community data. research done by using the Naïve Bayes method aims to classify community data that is feasible to forget social assistance. The first stage of this classification is the process of collecting community data and determining community data that will be used as a filtered sample cleaned, furthermore preprocessing data and then designing the Naïve Bayes Algorithm model. The results of data classification using the Naïve Bayes method show that the number of people who are eligible for social assistance is 14 community data and people who are not eligible for social assistance are 48 community data. These results can be a reference for determining the eligibility of the community to receive social assistance.
Detect Fake Reviews Using Random Forest and Support Vector Machine

With the rapid development of e-commerce, which makes it possible to buy and sell products and services online, customers are increasingly using these online shop sites to fulfill their needs. After purchase, customers write reviews about their personal experiences, feelings and emotions. Reviews of a product are the main source of information for customers to make decisions to buy or not a product. However, reviews that should be one piece of information that can be trusted by customers can actually be manipulated by the owner of the seller. Where sellers can spam reviews to increase their product ratings or bring down their competitors. Therefore this study discusses detecting fake reviews on productreviews on Tokopedia. Where the method used is the distribution post tagging feature to perform detection. By using the post tagging feature method the distribution got 856 fake reviews and 4478 genuine reviews. In the fake reviews, there were 628 reviews written with the aim of increasing product sales or brand names from store owners, while there were 228 reviews aimed at dropping their competitors or competitors. Furthermore, the classification is carried out using the random forest algorithm model and the support vector machine. By dividing the dataset for training data by 80% while 20% for data testing. Here it is known that the support vector machine gets much higher accuracy than the random forest. The support vector machine gets an accuracy of 98% while the random forest gets an accuracy of 60%
Classification of Positive and Negative Sentiments Using the K-Nearest Neighbor Algorithm on iQIYI Aplication

In the current state of the Covid pandemic, the government has implemented restrictions on community activities or PPKM, which has an impact on the number of cinemas in the country temporarily closed to reduce the spread of the virus. The number of films that have been postponed for release due to this outbreak and also the decreasing use of VCDs / DVDs have made movie streaming applications begin to be favored by the public, one of which is the iQIYI movie streaming application. iQIYI is a movie streaming app launched in April 2010, so that users can know that the iQIYI application is considered good is to do a sentiment classification on the application. Therefore, this study aims to implement sentiment classification in review data using the K-Nearest Neighbor (K-NN) algorithm. K-NN itself is an algorithm that functions to classify data based on its learning data (train data sets). The data used is iQIYI user reviews as many as 400 review data, the first stage carried out is the data cleaning process or Pre-Processing, the next step is to design a K-NN algorithm model in RapidMiner Studio software to process sentiment classification. The test results using 400 review data using the K-NN algorithm obtained an Accuracy value of 99.50% then a Precision value of 100% and a Recall value of 99.44%. Which means that this study managed to get the best and best algortima in classifying positive reviews and negative reviews against the iQIYI application.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
Application Of The C4.5 Algorithm to Determine Security Guard Work Schedules

All agencies, companies, and public spaces must employ security guards to maintain security. The problem with the security guard's schedule is that there is an imbalance in disciplinary issues, poor performance because there is no seniority that is emulated so that the guard is not optimal which results in the problem of losing employee items, working time is not according to the rules and there is a vacancy in personnel due to personnel not coming to work, suing With the existence of a policy in the placement and distribution of the right employee work schedule, it is hoped that it can synergize all elements in the institution so that the quantity and quality of the security guard's work can increase and be completed on time. One of the techniques in data mining is classification. By applying classification techniques to security guard data and work schedules, the Decision Tree method and C4.5 algorithm are developed. The results of data processing form the root node of the gender tree as the root, that those who get schedule A are men while those who get schedule B with high school and junior level education are women, besides that they get schedule A. The accuracy of all classifications of the correct number is 61, 53%.