Reviewerly/exHarmony huggingface dataset:
ANALYSIS ON THE IMPORTANT VALUE OF ARCHAEOLOGICAL RESOURCES AT THE LAMLAGANG SITE, BANDA RAYA DISTRICT, BANDA ACEH

This article is entitled "Analysis on the Importance of Archaeological Resources at the Lamlagang Site, Banda Raya District, Banda Aceh". Banda Aceh is one of the areas in Aceh which is famous for the remains of Islamic archaeology. An example of Islamic archaeological heritage is the Lamlagang Site. Inside the Lamlagang Site, there are locations of Raja Reubah and Raja Jalil Tomb. The two tomb complexes need to be preserved based on the important values ​​contained in the site. The problems to be studied in this paper are related to the important values ​​contained in the Lamlagang Site. The method used in this study is a qualitative analysis method. The process stages in the research are: The data collection stage consists of direct observation, interviews and documentation. And the last stage is the data analysis stage consisting of Artifact analysis, Analysis of the significance of the observed object (significance assessment), and Stakeholder analysis. From the results of this study, it is found that the Lamlagang Site has several important values, namely 1. Important historical values, 2. Important cultural values ​​which include: Art, Social, Public. 3. The Importance of Religion, 4. The Importance of Science, and 5. The Importance of Education. The existence of important values ​​at the Lamlagang Site will be one of the foundations in the pattern of preserving archaeological resources at the Lamlagang Site.
Peran Orang Tua terhadap Hasil Belajar Siswa di Masa Pandemi Covid-19 dalam Pembelajaran Matematika Berbasis Online

One of the problems faced by children at school while studying at home is about learning mathematics which is carried out online. The purpose of this study was to determine the role and influence of the role of parents on learning outcomes in online learning during the Covid-19 pandemic. The population in this study were SMP/MTs students, parents, students, and mathematics teachers. The research subjects were 5 students, 5 students' parents, and 1 mathematics teacher. When viewed from each role, S-1 parents do not meet 1 sub-indicator, the score for the role of parents as teachers is 80%, S-2 and S-3 parents get a maximum score of 100%, S-4 parents do not meet 2 sub-indicators so that the score is 60%, S-5 parents get the lowest score of 20% because they only meet 1 sub-indicator. The role of parents as motivators for S-1, S-3, and S-4 parents got the maximum score because they had fulfilled all the sub-indicators, S-2 and S-5 parents got the same score of 70%, because they did not meet the sub-indicators. indicator. The role of parents as facilitators and directors, all parents scored 100% because all indicators were met by all parents. Therefore, the role of parents affects learning outcomes.
Mobile School Canteen Food Ordering System

Food ordering has been familiar nowadays. Everyone is very concerned about time and the necessities of life such as food. The food ordering application helps people to get their food easily and save lots of time. Most of the existing food ordering applications only focused on registered restaurants or food providers based on the specific location. However, there is no special food ordering application that focused on food ordering for school students and canteen food provider in Malaysia. Even though many food ordering applications are available to be used, the most apparent drawback to food ordering applications is that students are unable to use them during breaks at the school. Due to this problem, a mobile application named as Mobile School Canteen Food Ordering System is proposed as an alternative to the school students in selecting and ordering the food offered by the school canteen food provider. In addition, with the implementation of collaborative filtering technique, this system offered one additional function that will recommend the user on healthy meal that the children should consume according to the provided criteria such as foods that contain allergens. This project will benefit many students especially in primary schools whereas 75% of the respondents have agreed that the system is effective in choosing foods easily, facilitate and save their time to get food during breaks.
Food Runner Mobile Application for UiTM Tapah Students

Food delivery service is an uprising service that were used worldwide. It can be used in few platforms such as mobile apps or a website. It usually involves 3 types of users which are the customer, the rider, and the restaurant. It also brings a lot of benefit in an individual daily life. If people had no time to prepare their meal, or stuck in a back-to-back meeting session, food delivery service is an option to fix their meal break. However, food delivery service is only available in a busy and high-density household area in Malaysia. This project proposed a UiTM Tapah EAT mobile application for UiTM Tapah Students, a food delivery service that can be used in an Android smartphone as a mobile app and able to receive notification of order status in real-time. Since Tapah is a small town placed in Perak, it also holds a university that occupied with about 2,000 students at one time. These students have few limitations of buying meal outside of the university or they are too busy with their schedule. This project uses Android Studio, an Integrated Development Environment (IDE) for Android app development to design the pages using XML and develop the functions of the mobile app using Java language. Besides, this project also used Firebase, a mobile and web application developments platform that helps in storing the data in real-time. Once the development process complete, this project was tested with functionality test that list all the functions available in the app to be evaluated accordingly. The results of the experiment show that all functions in the app successfully executed including the notification system between two end-users, the customer and the runner.
Identity-Preserving Pose-Robust Face Hallucination Through Face Subspace Prior

Over the past few decades, numerous attempts have been made to address the problem of recovering a high-resolution (HR) facial image from its corresponding low-resolution (LR) counterpart, a task commonly referred to as face hallucination. Despite the impressive performance achieved by position-patch and deep learning-based methods, most of these techniques are still unable to recover identity-specific features of faces. The former group of algorithms often produces blurry and oversmoothed outputs particularly in the presence of higher levels of degradation, whereas the latter generates faces which sometimes by no means resemble the individuals in the input images. In this paper, a novel face super-resolution approach will be introduced, in which the hallucinated face is forced to lie in a subspace spanned by the available training faces. Therefore, in contrast to the majority of existing face hallucination techniques and thanks to this &lt;i&gt;face subspace prior&lt;/i&gt;, the reconstruction is performed in favor of recovering person-specific facial features, rather than merely increasing image quantitative scores. Furthermore, inspired by recent advances in the area of 3D face reconstruction, an efficient 3D dictionary alignment scheme is also presented, through which the algorithm becomes capable of dealing with low-resolution faces taken in uncontrolled conditions. In extensive experiments carried out on several well-known face datasets, the proposed algorithm shows remarkable performance by generating detailed and close to ground truth results which outperform the state-of-the-art face hallucination algorithms by significant margins both in quantitative and qualitative evaluations.
Proposed Solutions to Enhance Lecturers’s Adaptation to E-learning in the Context of COVID-19 Pandemic (A Case Study at the VNU University of Social Sciences and Humanities – Vietnam National University, Hanoi)

Since March 2020, due to the outbreak of the COVID-19 pandemic, to continue students’ education while controlling the spread of COVID-19, the higher education system has been required to switch from face-to-face learning model to a virtual one. In Vietnam, although e-learning has already been introduced, it has been actively adopted since the COVID-19 pandemic occurred. The transition to e-learning in the context of the COVID-19 outbreak while lacking preparation for this teaching mode has put lecturers and students in a passive position with many difficulties. This article presents the situation of virtual learning adoption and implementation by lecturers at the University of Social Sciences and Humanities (Vietnam National University, Hanoi) in recent years and their associated challenges. Based on the situation analysis, this article suggests a number of potential solutions to enhance the adaptability of lecturers and improve the effectiveness of e-learning. These solutions will contribute to the better preparation of lecturers and educational administrators for immediate and effective responses to similar adverse events in the future, from that ensure the quality of higher education.&#x0D; Keywords:&#x0D; Solution, adaptation; lecturer, e-learning; COVID-19 pandemic.&#x0D; &#x0D; &#x0D;
History and current state of books in Braille in Ukraine and abroad

The article raises the issue of perception of information by visually impaired people. The history of the search for ways of writing and reading for the blind in a broad chronological section — from the IV century to the period of the invention of L. Braille.&#x0D; It is noted that by the XIX century blind people did not have much choice of profession, were distant from the world of books and mostly made brushes or baskets. For a long time, mankind has experimented with many methods that would help people with special needs to read and write, but many of them proved unviable because they were only a relief version of printed letters. In contrast, the Braille system has become effective, because it is based on a rational sequence of signs intended for the fingertips, not the eyes.&#x0D; It is emphasized that using the Braille alphabet, visually impaired people have access to a wide range of materials for reading and early education, which is vital for knowledge, literacy and employment. Thanks to this system, people can work, pursue hobbies and develop in every way.
Evidence of dynamical transition and maximum predictability of air temperature, relative humidity and dew point temperature

Monitoring and predicting the climatic phenomenon are the major global concern because of its devasting effects on people's lives and their environments. As a result of this, there is a need to understand the natural processes that control the dynamic evolution of the climatic phenomenon. Air temperature and relative humidity data collected from Nsukka station by the Centre for Atmospheric Research (CAR), measured in 5 minutes time steps from 1st January till 31st December, 2012 have been analysed. Dew point temperature was calculated from the actual readings of air temperature and relative humidity using appropriate empirical relation. In this paper, Average Mutual Information (AMI), False Nearest Neighbour (FNN) and Lyapunov Exponent methods were used to study changes and transitions in the dynamics of these meteorological parameters or temporal deviations from their overall dynamical regimes. The results show that the dynamic model needed to describe the data has 4-5 dimensions for air temperature, 4-6 for relative humidity and 4-5 for dew point temperature. Positive and negative Lyapunov exponents were observed in the air temperature, relative humidity and dew point temperature time series. This indicates that there exists periodicity inherent in the chaotic behaviour of these meteorological time series, causing a transition from chaoticity (positive Lyapunov exponent) to periodicity (negative Lyapunov exponent) and thereafter to chaoticity (positive Lyapunov exponent). The results, therefore, provide additional information about the climate transitions, maximum predictability and also, for formulating a weather prediction model.
Clustering of Electricity Usage Using K-Means Method

The electricity usage in the buildings depends on all activities related to using any electrical devices in the buildings. More electrical devices in the building used, the more electrical energy will be used as well. Using excessive electrical energy can cause the waste of electrical energy in buildings. The waste of electrical energy also can happen at the campus. The campus has some needs for electricity energy in working hours even outside working hours. As a result, the logistics team can not determine the regulation of using electrical energy on campus and can causes the overuse of electricity and the swelling of the electricity bill. Therefore, to solve this problem it needs a system that can clustering data that results in excessive power usage or not. Then the logistics team can do something about how to prevent the overuse of electricity and the swelling of the electricity bill. This paper will be using K-Means Clustering to cluster data regarding how long the time it takes that using any electricity in the building. The results clustered data then will be searched for the accuracy value using the Davies Boulden Index method. The accuracy that has been obtained is 0,83 and the data that has been clustered into 3, which is low usage, medium usage, and high usage. This paper will focus on making the K-Means clustering system required by theuser.
Research of Natural Scene Text Recognition Algorithm Based on OCR

RNN and strengthen the semantic information of the context, BLSTM is used to replace the RNN model for label prediction, and then the CTC algorithm is used to complete the transcription and output the final recognition result. Experimental results show that the improved CRNN text recognition algorithm has an accuracy rate of 96.6%, which is 1% higher than the basic CRNN text recognition algorithm, and this end-to-end network structure design also greatly shortens the text recognition time.
Pengembangan E-Modul pada Proses Pembelajaran Instalasi Penerangan Listrik

This research is motivated by the lack of learning materials provided by the teacher as a guide for students in learning which results in a lack of student initiative to learn independently. Coupled with the policy for online learning during the COVID-19 pandemic, learning in schools is not optimal. This study aims to produce a valid and practical E-Module for Electrical Lighting Installation learning at SMK Negeri 2 Payakumbuh. This study uses research and development methods with a 4D development model. The subjects of this study were students of class XI TITL SMK N 2 Payakumbuh who were registered in the first semester of the 2021/2022 academic year. Based on the results of the study, the validity of the media was obtained with a valid category and material validation was obtained with a valid category. The practicality test with teacher respondents got results in the practical category and respondents from class XI TITL SMK N 2 Payakumbuh stated that the E-Module learning of Electrical Lighting Installation was categorized as very practical. So it can be concluded that the E-Module of Electrical Lighting Installation produced is valid and practical to use in the learning process at school.
Clustering of seismicity in the Indonesian Region for the 2018-2020 Period using the DBSCAN Algorithm

Indonesia is located at the confluence of 3 large, active plates that are constantly moving. Therefore, Indonesia is one of the countries that has a high level of seismicity risk. This study aims to classify seismicity data in the Indonesian region based on coordinate data which contains variable data on frequency of occurrence, depth, and strength of seismicity. Seismicity data was obtained from the BMKG official website using data for the period 2018 to 2020. The clustering technique used was the DBSCAN algorithm. This algorithm requires epsilon and MinPts input parameters. The results of the cluster formed will then be validated using silhouette coefficients. Based on the coordinate data, 4 clusters were formed with 4 disturbances. Based on the characteristic data, 3 clusters were formed with 5 disturbances. The silhouette coefficient obtained was 0.35 for coordinate data and 0.39 for characteristic data. This research is useful for increasing the use value of abundant seismicity information and can be used as an effort to mitigate seismicity natural disasters.
Wearable Motion Capture: Reconstructing and Predicting 3D Human Poses from Wearable Sensors

Identifying 3D human walking poses in unconstrained environments has many applications such as enabling prosthetists and clinicians to access the amputees’ walking functions outside clinics and helping amputees obtain an optimal walking condition with predictive control. Thus, we propose the wearable motion capture problem of reconstructing and predicting 3D human poses from the wearable IMU sensors and wearable cameras. To solve this challenging problem, we introduce a novel Attention-Oriented Recurrent Neural Network (AttRNet) that contains a sensor-wise attention-oriented recurrent encoder, a reconstruction module, and a dynamic temporal attention-oriented recurrent decoder, to reconstruct the current pose and predict the future poses. To evaluate our approach, we collected a new WearableMotionCapture dataset using wearable IMUs and wearable video cameras, along with the musculoskeletal joint angle ground truth. The proposed AttRNet shows high accuracy on theWearableMotionCapture dataset, and it also outperforms the current best methods on two public pose prediction datasets with IMU-only data: DIP-IMU and TotalCaputre. The source codes and the new dataset will be publicly available on https://github.com/MoniruzzamanMd/Wearable-Motion-Capture.&lt;br&gt;
UNDIKSHA VIRTUAL ASSISTANT (SHAVIRA): INTEGRATION FREQUENCY ASKED QUESTION WITH RASA FRAMEWORK

Nowadays, the implementation of chatbots in information systems is getting popular to increase user experience. In our previous research, we developed Undiksha Virtual Assistant (Shavira). Shavira is a knowledge management system (KMS) as Frequency Asked Question (FAQ) system to facilitate users to get an answer about their questions. The challenge on the existing Shavira system is that the users must open a website and type queries to get a list of answers. The text query must match with the keyword in systems. To address this problem and to avoid cognitive load, in this research we implemented a chatbot in Shavira. The purpose of the chatbot implementation in Shavira is to make information easier to be accessed and to increase user experience. The users can ask a question in natural language and get an answer immediately on their chat application such as: Telegram, Facebook, or Messenger. We used Rasa Framework as a chatbot engine in Shavira. Rasa Framework is an open-source virtual assistant engine based on artificial intelligence. The challenge in conducting this research is in integrating the existing FAQ system with Rasa Framework. This research consists of four phases, they are: adaptation data structure in the existing FAQ with data structure requested by Rasa framework, data integration and mapper, and evaluation. The result of this research is a new Shavira that is integrated with a chatbot and can be accessed from chat applications such as Telegram. We evaluated the accuracy of Shavira powered by Rasa Framework with ten topics about academic information. The results showed that the accuracy of Shavira is 90%. We also evaluated the usability of Shavira with Software Usability Scale (SUS) Questionnaire. The usability evaluation showed that Shavira satisfied users with value 81 (threshold 68) and categorized Excellent, Acceptable and Prometer.
User Experience Analysis of E-Learning UIN Malang with User Experience Questionnaire (UEQ) Method: Case Study of Students of Library and Information Science Departmen

Abstract-The rapid advancement of information technology has an impact on all aspects of human life. In the field of education, this can be seen through the number of universities that use E-Learning (Electronic Learning) as an alternative media of learning between lecturers and students, especially during this pandemic, where learning is done by online. One of the universities that utilizes E-Learning as media of learning is UIN Malang. Even though it is used as an alternative media of learning, there is still some troubles that experienced by students. According to a survey we conducted on students from the Department of Library and Information Science of UIN Malang, it was found that the use of E-Learning that owned by the campus was still low. The data shows that 53% of the 60 respondents do not use the application frequently. This study use a quantitative typeof research with asurvey approach. The population in this study is the students of Library and Information Science Department. The sample is part of the entire population that can represent the entire population. To determine the size of the sample to be taken, we used the Slovin formula with a confidence value of 90% and a tolerance value of 10%. In addition, based on a survey conducted using the User Experience Questionnaire (UEQ) method, it was found that in terms of attractiveness, perspicuity, efficiency, dependability, stimulation and novelty, are in a bad position. From the explanation above, it can be concluded that, E-Learning UIN Malang is still not optimally used and still needs a lot of development.
A novel Adam approach related to Decoupled Weight Decay (AdamL)

The use of optimizers makes it possible to reduce losses during the learning process of a neural network. Currently there are some types of optimizers whose effectiveness has already been proven, an example of this is Adam. Adam is an extension to Stochastic Gradient Decent that makes use of Momentum and Adaptive Learning to converge faster. An interesting alternative to complement the Adam’s work is the addition of weight decay. This is done to decouple the weight decay from the gradient-based update. Some attempts have been developed previously, however its correct operation has not been keenly proven. In this work, a weight decay decoupling alternative is presented and acutely analyzed. The algorithm’s convergence is mathematically verified and its operation too through the use of a Convolutional Encoder-Decoder network and the application of strategies for error reduction. The AdamL operation is verified by the achievement of a proper Temperature Forecast with a percentage error lower than 4.5%. It can be seen too that the forecast error deepens around noon but it does not exceed 1.47°C.
Local Coordination in Multi-Agent Reinforcement Learning

This paper studies cooperative multi-agent reinforcement learning problems where agents pursue a common goal through their cooperation. Because each agent needs to act individually on the basis on its local observation, the difficulty of learning depends on to what extent information can be exchanged among agents. We extend value-decomposition networks (VDN), a framework requiring the least communication, by allowing information exchange within a local group and present residual group VDN (RGV). We empirically show that the performance of RGV is better than VDN and other state-of-the-art methods in the predator-prey game. Also, on three tasks in the StarCraft Multi-Agent Challenge, RGV showed comparable performance with more sophisticated methods utilizing more information or communication. Therefore, our RGV is an alternative method worth further research.