Reviewerly/exHarmony huggingface dataset:
Decentralized News Publication Platform

Fake News has become a huge alarming issue since the previous few years.It can be used to influence people on any political, economical or social topics and change people’s thoughts on a particular subject. We’re using a blockchain based technique to overcome this problem. More specifically the proposed approach uses concepts of customized proof of authority and proof of truthfulness consensus algorithm serving as an incentive mechanism to determine the integrity of fake news. As Blockchain is a decentralized system no one will be able to tamper with the original news. Also, we are maintaining the reputation score of each organization. Due to fear of lowering credibility score, no one will produce fake news and the probability of fake news getting viral will be reduced. This platform which is a blockchain based Decentralized application can provide normal readers on the platform with a reliable way of verifying the content and the source by which it gets published. Our work demonstrates that the solutions proposed in this paper ensure data integrity, data security, data transparency, and data traceability by consideration of such a blockchain-based framework for tackling fake news. Key Words: Decentralized Applications, Decentralised Autonomous Organisation, Decentralized Exchange, Peer To Peer, Ethereum Virtual Machine
Designing IoT-based Smart Weather System to Promote Critical Thinking Skills

The role of education in promoting global warming awareness is important to enable students to understand and address the impact of global warming. The use of Internet of Things (IoT) with collaborative learning strategies can enhance students’ understanding of global warming. This study aimed to develop an IoT-based smart weather system enhancing the critical thinking skills of elementary students. It consists of weather-measuring sensors that capture data on temperature, humidity, air pressure, light intensity, and altitude. The data is stored in the Blynk cloud and displayed on smartphones. The IoT devices are placed in three different geographic locations. This paper presents the system design, including the system architecture and user interfaces. The data captured by the IoT sensors from the three measurement sites form the foundation to promote the development of collaborative learning. This result implies the need for teachers to creatively establish learning strategies in various subjects to improve students’ critical thinking skills.
A comprehensive analysis on single image-based deraining using generative adversarial network

Deraining is a process by which we can get a transparent image by removing raindrops from a rainy image. In the rainy time visibility of any scene decreases as vision property is affected by the rain. Recently generative adversarial network (GAN) is getting popular in the visual enhancement of hazy, dusty, and noisy images. It is essential to know the effectiveness of the diverse GAN algorithms in the natural rainy situations of different intensities. From this perspective, the present paper describes a comprehensive study on four single-image state-of-the-art GAN models, such as attentive GAN, cGAN, DHSGAN, and Cycle GAN for deraining. The experiment is done using the standard dataset consisting of real-world rainy images and the results are evaluated both objectively and subjectively. We have found somehow mixed results based on quantitative metrics and comparatively satisfactory results by the cGAN based on visual analysis.
Global Convergence of Over-parameterized Deep Equilibrium Models

A deep equilibrium model (DEQ) is implicitly defined through an equilibrium point of an infinite-depth weight-tied model with an input-injection. Instead of infinite computations, it solves an equilibrium point directly with root-finding and computes gradients with implicit differentiation. The training dynamics of over-parameterized DEQs are investigated in this study. By supposing a condition on the initial equilibrium point, we show that the unique equilibrium point always exists during the training process, and the gradient descent is proved to converge to a globally optimal solution at a linear convergence rate for the quadratic loss function. In order to show that the required initial condition is satisfied via mild over-parameterization, we perform a fine-grained analysis on random DEQs. We propose a novel probabilistic framework to overcome the technical difficulty in the non-asymptotic analysis of infinite-depth weight-tied models.
A New Technique to Accelerate the Learning Process in Agents based on Reinforcement Learning

The use of decentralized reinforcement learning (RL) in the context of multi-agent systems (MAS) poses some difficult problems.The speed of the learning process for example.Indeed, if the convergence of these algorithms has been widely studied and mathematically proven, they suffer from being very slow.In this context, we propose to use RL in MAS in an intelligent way to speed up the learning process in these systems.The idea is to consider the MAS as a new environment to be explored and the communication, between the agents, is limited to the exchange of knowledge about the environment.The last agent to explore the environment has to communicate the new knowledge to the other agents, and the latter have to build their knowledge bases taking into account this knowledge.To validate our method, we chose to evaluate it in a grid environment.Agents must exchange their tables (Qtables) to facilitate better exploration.The simulation results show that the proposed method accelerates the learning process.Moreover, it allows each agent to reach its goal independently.
[Reproducibility Report] Explainable Deep One-Class Classification

Fully Convolutional Data Description (FCDD), an explainable version of the Hypersphere Classifier (HSC), directly addresses image anomaly detection (AD) and pixel-wise AD without any post-hoc explainer methods. The authors claim that FCDD achieves results comparable with the state-of-the-art in sample-wise AD on Fashion-MNIST and CIFAR-10 and exceeds the state-of-the-art on the pixel-wise task on MVTec-AD. We reproduced the main results of the paper using the author's code with minor changes and provide runtime requirements to achieve if (CPU memory, GPU memory, and training time). We propose another analysis methodology using a critical difference diagram, and further investigate the test performance of the model during the training phase.
Integrasi Metode Webqual 4.0 dan Importance Performance Analysis (IPA) untuk Mengukur Kualitas Website Inlis Lite

Integrated Library System (Inlis Lite) is used to facilitate library performance in maximizing service and assist the Library in finding information. The problem on the Inlis Lite website is difficult to access. This study uses the Webqual 4.0 method which focuses on 3 variables namely (usability, information qualit and service interaction) and Importance Performance Analysis (IPA) method. The results of teh Inlis Lite website quality analysis have a conformity rate 88,71% which means that the service is still not satisactory. The average GAP of -0,46 means that the quality of the Inlis Lite website still does not meet user expections. There are 4 indicators that need to be improved quality, namely US5, US7, SIQ5, and SIQ6 which are in the first quadrant
The Effectiveness of Writing Descriptive Texts Using Mind Mapping Method by Online Learning in SMP Negeri 2 Tampaksiring

This research is entitled Analysis of The Effectiveness of Writing Descriptive Texts Using Mind Mapping Method by Online Learning in SMP Negeri 2 Tampaksiring.The purpose of this study is to emphasize the ability to write descriptive text as a whole by using the mind mapping method with online learning methods.This research was conducted at one of the junior high schools, SMP Negeri 2 Tampaksiring.The data collection technique that is used in this study is a technique of assigning tasks to two groups, the experimental group and the control group.The results of this study are the results of online learning research using image-assisted Mind Mapping techniques are in the very good category, as well as the results obtained with the n-gain test are in the high category.The results of the study using the Mind Mapping technique without the help of pictures were in the good category.Furthermore, the results obtained with the n-gain test are in the medium category.There is a significant difference using the image-assisted Mind Mapping technique with the image-assisted Mind Mapping technique on learning to write descriptive paragraphs.The conclusion of this study is that image-assisted Mind Mapping is more effective in learning to write descriptive paragraphs for 8th grade students of SMP Negeri 2 Tampaksiring.
Sentiment Analysis Methods using Lexicon Approach

Opinions plays an important role in our daily life. We collect opinion from various sources such as companions and are influenced what we think about that particular in various types of decision making process. Assessment is a review concerning some article or topic etc. On the development and appearance of web 2.0, there are various websites has expanded complex such as twitter, linkedIn facebook etc. Due to this development, it increases the mumber of users and their content on these plateforms. It is an examination of user’s feelings for some specific topic or product. It is monstrously helpful in web-based data checking since it permits to acquire knowledge for popular assessment on some specific subjects. In this study we have handles a complete outline of Lexicon method and it implementation, updation time to time. Numerous as of late proposed improvements, various challenges faced in sentiment analysis and different Sentiment analysis applications are introduced and explored in this study.
Peningkatan Hasil Belajar IPS dengan Metode Pembelajaran Snowball Throwing Di Sekolah Dasar

This research is motivated by the low learning outcomes of students on the subject matter of Social Sciences (IPS). The learning outcome is caused by the teachers only using conventional learning methods and the student being less involved in the learning process. Therefore, teachers need to change the way of learning by using appropriate learning methods so that they are not dull. One of the learning methods used is the Snowball Throwing learning method. Students must be more responsive to receiving messages from others and conveying them to their group friends. A pleasant learning atmosphere makes maximum learning outcomes. This study aims to determine the improvement of social studies learning outcomes with the Snowball Throwing learning method in elementary schools. The subjects in this study were fifth-grade students at SDN Belang for the 2021/2022 academic year, with 21 students consisting of 12 male students and nine female students. The method used in this research is Classroom Action Research (CAR) which is carried out in two cycles. Data to determine students' social studies learning outcomes were collected using test results in multiple-choice tests and analysis with percentages. Based on the data analysis, the number of students who finished studying in the pre-cycle was 12 people or 57.14%, after the first cycle, there were 16 people or 76.19%, the second cycle was 19 people or 90.48%. These data indicate that cooperative learning with the Snowball Throwing method can improve social studies learning outcomes in elementary schools.
Data Banzhaf: A Robust Data Valuation Framework for Machine Learning

Data valuation has wide use cases in machine learning, including improving data quality and creating economic incentives for data sharing. This paper studies the robustness of data valuation to noisy model performance scores. Particularly, we find that the inherent randomness of the widely used stochastic gradient descent can cause existing data value notions (e.g., the Shapley value and the Leave-one-out error) to produce inconsistent data value rankings across different runs. To address this challenge, we introduce the concept of safety margin, which measures the robustness of a data value notion. We show that the Banzhaf value, a famous value notion that originated from cooperative game theory literature, achieves the largest safety margin among all semivalues (a class of value notions that satisfy crucial properties entailed by ML applications and include the famous Shapley value and Leave-one-out error). We propose an algorithm to efficiently estimate the Banzhaf value based on the Maximum Sample Reuse (MSR) principle. Our evaluation demonstrates that the Banzhaf value outperforms the existing semivalue-based data value notions on several ML tasks such as learning with weighted samples and noisy label detection. Overall, our study suggests that when the underlying ML algorithm is stochastic, the Banzhaf value is a promising alternative to the other semivalue-based data value schemes given its computational advantage and ability to robustly differentiate data quality.
Speaker-conditioning Single-channel Target Speaker Extraction using Conformer-based Architectures

Target speaker extraction aims at extracting the target speaker from a mixture of multiple speakers exploiting auxiliary information about the target speaker. In this paper, we consider a complete time-domain target speaker extraction system consisting of a speaker embedder network and a speaker separator network which are jointly trained in an end-to-end learning process. We propose two different architectures for the speaker separator network which are based on the convolutional augmented transformer (conformer). The first architecture uses stacks of conformer and external feed-forward blocks (Conformer-FFN), while the second architecture uses stacks of temporal convolutional network (TCN) and conformer blocks (TCN-Conformer). Experimental results for 2-speaker mixtures, 3-speaker mixtures, and noisy mixtures of 2-speakers show that among the proposed separator networks, the TCN-Conformer significantly improves the target speaker extraction performance compared to the Conformer-FFN and a TCN-based baseline system.
The Effect of Paraphrasing Strategy on the Students’ Ability in Comprehending Narrative Text at the Eighth Grade of SMP Negeri 1 Mandrehe

Reading is one of English skills that should be mastered by students because throughreading, readers get important information, ideas or opinions of text they read about. But the fact,the students of SMP Negeri 1 Mandrehe at the eighth grade in 2015/2016 are not able to getinformation of narrative text. So, the researcher tries to apply Paraphrasing Strategy to investigateits significant effect on the students’ ability in comprehending narrative text. Paraphrasing Strategyis restating information in reading activity by finding the main ideas of paragraphs and by gettingthe specific facts of a text in own words. In conducting the research, the research uses quasiexperimental design. The subject of this study is the eighth grade of SMP Negeri 1 Mandrehe in2015/2016. The population of the research was consists of 103 students, the sample which consistsof 68 students by cluster sampling. The data collected both of groups’ pre test, the data werenormality and homogenous. The researcher did the treatment to the experimental group by usingParaphrasing Strategy. Based on the result of the data computation, it shown the mean score was76.61 stated good. In the control group, the researcher taught the students by using conventionalmathod. The result of post test was 61.47 stated adequate. Based on the result of hypothesis testingby using t-test, the researcher got tcount ≥ ttable (6.3347 ≥ 1.943 from the ttable with dk = 2(n-1) =2(34-1) = 66 and the significance level is 5% (∝= 0.05). Because ttableto dk 66 is not be found inthe critic distribution t of value table, so ttable is interpolated to dk 60 is 2.000 with ttable to dk 120is 1.9880 So, ttable = t1/2∝(dk) = t0.025 x 66 = 1.943. Ha is accepted and H0 is rejected. It can beconclude that there was a significant effect of Paraphrasing Strategy on the students’ ability incomprehending narrative text at the Eighth Grade of SMP Negeri 1 Mandrehe in 2015/2016. Baseon the analysis, the researcher suggest to the English teacher to use the strategy to teach thestudents. The strategy is Paraphrasing Strategy, it can solve the students problems, havefeedback,active and create the relation between teacher and student when teaching readingcomprehensionespecially in narrative text.
Mewujudkan Layanan Prima di Era Pandemi COVID-19 Melalui Pemanfaatan Fitur Booking Book

This study aims to find out how the level of satisfaction in the use and user feedback of the booking book feature service in the Syiah Kuala University Integrated Library Information System (UILIS) mobile library application during service restrictions as an effort to provide excellent service in the era of the COVID-19 pandemic. This research is quantitative because the data obtained are in the form of descriptive statistics and percentages. The method used is a survey, the sample in this study amounted to 65 people who were taken by random sampling. The data analysis technique used the descriptive analysis method, the data were analyzed by describing the picture and the results of the data that had been obtained. The results of the study indicate that the booking book feature is quite satisfactory for users, it can be seen from the level of utilization of the booking book feature. The development of the booking book feature has been to the lifestyle of today's society, which requires that the information sought can be found quickly and precisely. User feedback based on survey results shows that 75.69% of users agree that the booking book feature makes it very easy for them to get the books they need. Users also strongly agree that the booking feature is very useful and is a quick solution in getting the right collection service, with an average interpretation score of 82, 77%. The use of the USK Library's book booking feature is increasingly in demand to get books easily and save users' time. The results obtained are 72.61% of the booking book feature is quite satisfactory for users. The conclusion of this research is the USK Library still needs to improve the booking book feature service by making continuous improvements so that the utilization rate of the USK Library collection continues to increase.
Implementasi Algoritma Haversine Formula dan Location Based Service Pada Aplikasi Pencarian Lokasi Bird Contest Berbasis Android

At this time, the chirping bird competition has become so popular that it can be said to be a trend in Cibinong District. The number of enthusiastic chirping maniacs who have just entered this competition, not a few of the chirping maniacs do not know where the competition is taking place in Cibinong District. With the lack of information about the competition venue in Cibinong District. So a location search application was made using the Location Based Service method as the location of the user's point and the Haversine Formula Algorithm as a measure of the distance. From the measurement results of the haversine formula by comparing the application's haversine distance to the distance of google maps to get an average value of 0.039 kilometers.
MENINGKATKAN HASIL BELAJAR SISWA PADA KONSEP MODUS MELALUI METODE INQUIRY KELAS VI SD NEGERI TAMBAN BANGUN BARU 1 KECAMATAN TAMBAN oleh : Sri Mardiana

IMPROVING STUDENT LEARNING OUTCOMES ON THE CONCEPT OF MODUS THROUGH INQUIRY METHOD OF THE CLASS VI SD NEGERI TAMBAN BANGUN BARU 1ABSTRACTThis study aims to determine the learning outcomes of class VI students of SDN Tamban Baru Bangun 1 on the concept of modus (data that often appears) through the inquiry learning method. This research was conducted in two cycles according to the stages of action research, namely: planning, implementing actions, observing, and reflecting. This research was conducted from January to March 2020, at SDN Tamban Bangun Baru 1. The subjects in this study were grade VI students of SDN Tamban Bangun Baru 1 for the 2020/2021 academic year with a total of 13 students, consisting of 8 male students and 5 female students.Data collection techniques are using learning outcomes tests, observations, and questionnaires. Analysis of the data through the inquiry method which refers to the criteria for the level of student learning success, while the analysis of the results of the questionnaire refers to the scale of interpretation of student perceptions. The results showed that the inquiry method was effective in improving student learning outcomes individually and classically on the concept of mudus learning (data that often appears). By using two learning cycles, classical completeness in the first cycle of meeting 1 resulted in 42.30% and in the second cycle of meeting 2 the results increased to 95.38%. The average student learning achievement increased from 42.30 in the first cycle of meeting 1 to 95.38 in the second cycle of meeting 2. Students gave a positive response to contextual learning on the concept of mode learning (data that often appears).Keywords: Learning Outcomes, Concept Mode, Inquiry Method.
Robot Self-Calibration Using Actuated 3D Sensors

Both, robot and hand-eye calibration haven been object to research for decades. While current approaches manage to precisely and robustly identify the parameters of a robot's kinematic model, they still rely on external devices, such as calibration objects, markers and/or external sensors. Instead of trying to fit the recorded measurements to a model of a known object, this paper treats robot calibration as an offline SLAM problem, where scanning poses are linked to a fixed point in space by a moving kinematic chain. As such, the presented framework allows robot calibration using nothing but an arbitrary eye-in-hand depth sensor, thus enabling fully autonomous self-calibration without any external tools. My new approach is utilizes a modified version of the Iterative Closest Point algorithm to run bundle adjustment on multiple 3D recordings estimating the optimal parameters of the kinematic model. A detailed evaluation of the system is shown on a real robot with various attached 3D sensors. The presented results show that the system reaches precision comparable to a dedicated external tracking system at a fraction of its cost.