Reviewerly/exHarmony huggingface dataset:
Dual Axis Solar Power Tracking System

In the current world, electrical energy has surpassed all other important resources. However, it still hasn't been able to reach every corner of the globe, mainly rural places. Energy production has also come under threat from the quick depletion of fossil fuels and greenhouse gas emissions. As a result, finding other methods of energy generation is crucial. Solar energy is the greatest underutilized renewable energy source and has the potential to meet all of our energy needs entirely. Using solar photovoltaic panels allows for easy exercise. However, it has been noted that the majority of solar panels are positioned at fixed angles. The solar tracking device is used to keep the solar panel towards the sun throughout the day in order to capture as much incident solar energy as possible, increasing the system's performance ratio. The Dual Axis Solar Power Tracker, which combines software programming for the microcontroller unit with hardware design and implementation, can be used to accomplish this. To move two DC gear motors, which spin the solar panel in two axes, the system used an ATmega328P microcontroller. The microprocessor estimates rotating speed based on data collected from four light sensing sensors that are placed strategically close to a solar panel. As a result, solar panels are able to provide more output power.
Construction of Lahure Culture in Nepali Literature

The Gurkha and lahure with identical sense has gained their name and fame in western discourse. After the Anglo-Gorkha war fought in 1814-16 A. D., the hill-people of Nepal joined in British and Indian army forces and were referred to as ‘Gorkhas’ or ‘Goorkhali’or 'lahure'. The British rulers referred to them as ‘Gurkhas’ and British construction of lahure culture brought a division between lahure and non-lahure in Nepali society. It reveals that the practice of Gurkha as a product of western imperialism is still in use. The orientalist martial discourse dominates the historiography of Gurkhas. This article uses Lionel Caplan's theory that deals with the Gurkhas in the context of the western military imagination. The recruitment in military force accepted the Gurkha culture and turned their mythological character into reality to a considerable increase in Gurkha recruitment. The fact that Nepali writers and singers raised the different voices to accept and oppose the reality of lahure culture.
The Impact of Education System on Economic Growth: An Empirical Evidence from Developing Economy

The role of education in economic growth levies a massive impact on the economic growth of developing countries. This study has investigated the outcome of the education system on economic growth in the context of Pakistan. This study has also considered the literacy rate, labour force, consumer price index and unemployment for analyzing their shade on the growth of our country. The gross domestic products of the country have shown dependency in our model. In the light of regression analysis, results are helpful for a literature review that illustrates that role of education positively affects the growth of a country and freedom of economy is a sophisticated way to check the prominence of the growth of the economy.
IMPLEMENTATION OF WEIGHTED PRODUCT METHOD IN DETERMINING SELECTION THE BEST MUSIC STREAMING SERVICE APPLICATION

At this time, the music streaming service is a platform that is often easily found on every device, either through downloads from the Playstore and Appstore or the default application from the device itself. Many companies in the world are competing to create platforms and applications that provide the most complete songs. For example, several well-known music streaming service applications in Indonesia have their own innovations and characteristics, such as Spotify, Joox, Youtube Music, Apple Music, SoundCloud, and so on. This causes users to have difficulties because of several considerations in deciding how to use the application according to their needs. This study aims to assist in providing solutions to music streaming service subscribers by recommending several music streaming service applications according to the ranking results, which are the best choice for the user version of the application through a Decision Support System using the Weighted Product method based on 5 criteria: subscription rates, available features, streaming quality, music, application design, and application efficiency. The final result of this study is the ranking of applications that have the highest score in accordance with the criteria provided, namely that in first place with a value of 0.415 is Spotify as a recommendation for the best music streaming service application, and Apple Music ranks last out of the 6 alternatives that have been provided.
DrunkChain: Blockchain-Based IoT System for Preventing Drunk Driving-Related Traffic Accidents

Traffic accidents present significant risks to human life, leading to a high number of fatalities and injuries. According to the World Health Organization’s 2022 worldwide status report on road safety, there were 27,582 deaths linked to traffic-related events, including 4448 fatalities at the collision scenes. Drunk driving is one of the leading causes contributing to the rising count of deadly accidents. Current methods to assess driver alcohol consumption are vulnerable to network risks, such as data corruption, identity theft, and man-in-the-middle attacks. In addition, these systems are subject to security restrictions that have been largely overlooked in earlier research focused on driver information. This study intends to develop a platform that combines the Internet of Things (IoT) with blockchain technology in order to address these concerns and improve the security of user data. In this work, we present a device- and blockchain-based dashboard solution for a centralized police monitoring account. The equipment is responsible for determining the driver’s impairment level by monitoring the driver’s blood alcohol concentration (BAC) and the stability of the vehicle. At predetermined times, integrated blockchain transactions are executed, transmitting data straight to the central police account. This eliminates the need for a central server, ensuring the immutability of data and the existence of blockchain transactions that are independent of any central authority. Our system delivers scalability, compatibility, and faster execution times by adopting this approach. Through comparative research, we have identified a significant increase in the need for security measures in relevant scenarios, highlighting the importance of our suggested model.
Digital Platforms with the Ups and Downs in the Metaverse Era

The arrival of the metaverse era, the birth and development of digital currency, and the creation and improvement of the blockchain platform. How does the cryptocurrency sector in the financial markets attract more and more investors? Is it a risk or an opportunity? Digital currency is the product of The Times, keeping pace with The Times is the trend of social development, and seeking advantages and avoiding disadvantages is a necessary condition for operation. This paper through the definition of the metauniverse, the rise of the metauniverse era and unknown, cryptocurrency types, judgment and analysis, digital platform trading and loopholes, analyzes the cause of the virtual currency market instability, as a rational investor, under the premise of self-financing, should be in this field of what financial theory can be as profitable as much as possible. How does FSV stand out, how does it operate, and what is its potential? It also describes the Kepler market for the recent hacking attack and the reasons for the birth of blockchain.
Comparative analysis of Indonesian news validity detection accuracy using machine learning

Hoax news prediction is required to anticipate the growth of hoax news in social media. This study aimed to determine the best model for predicting whether the news is a hoax or valid based on the dataset taken from Kaggle.com. This study used several data prediction methods: Support Vector Machine (SVM), Random Forest, Logistic Regression, and Naïve Bayes. After the research processes and data testing, the results showed that the best model for predicting hoax news was SVM, which had the highest accuracy, precision, and recall score of the others.
Markov Chain Monte Carlo Sampling

The EM algorithm is suitable for topic models whose parameters and latent variables are distinguished. However, the approximate inference is usually applied in practice for fully Bayesian models whose parameters are treated as random variables. This chapter discusses an essential type of approximate inference: Markov chain Monte Carlo (MCMC) sampling.
A PROTOTYPE OF DIGITAL LIBRARY APPLICATION USING MICROFRAMEWORK FLASK

Covid-19 encourages the use of Digital Library sources. especially for students who are completing college assignments, students who are preparing their final project, lecturer in compling teaching material, including researchers. On the other hand, technology has developed rapidly. Technological developments have changed the pattern of human life and changed the business models of various organizations in order to survive in this digital era. However, there are still many organizations have not optimized the use of technology. One example is a university that does not yet have a Digital Library. This prompted the research team to conduct research on how to build a Digital Library. This study uses the Extreme programming (XP) software development method. This study aims to design a Digital Library prototype using a Microframework Flask. This research is expected to be a reference or model in developing digital libraries.
COMPARISON OF EIGENFACE AND FISHERFACE METHODS FOR FACE RECOGNITION

Abstract— Biometric information systems have been widely used in the fields of government, shopping centers, education and even security, which offer biological authentication so that the system can recognize its users more quickly. The parts of the human body are identified by a biometric system that has unique and specific characteristics, one of which is the face. Adjustment of facial image deals with objects that are never the same, due to the parts that can change. These changes are caused by facial expressions, light intensity, shooting angle, or changes in facial accessories. With this, the same object with several differences must be recognized as the same object. In this study, the data used were 388 face images and the sata test consisted of 30 face images. Before the face is tested, preprocessing and feature extraction are carried out using the Haar Cascade Classifier and then detected using Eigenface and Fisherface. Based on the research results, the Fisherface method is an algorithm that is accurate and efficient compared to the Eigenface algorithm. The Fisherface algorithm has an accuracy of 88%. while the Eigenface method has an accuracy rate of 76%.&#x0D; Keywords – Haar Cascade Classifier, Eigenface, Fisherface,.
Using Mixed Reality for Iterative Sketching and Prototyping in Product Design

Abstract: Mixed reality (MR) integrates virtual objects and environments with the real-world using sensors, cameras, and displays. Unlike virtual reality, which is completely immersive, MR allows users to interact with virtual objects while still being aware of the physical environment. This technology can be applied to education, healthcare, entertainment, and product design. MR can simulate user experiences, allowing designers to test the usability and functionality of their designs before they are manufactured. In education, MR provides immersive learning experiences that allow students to explore and interact with virtual objects in a real-world context. For example, MR can create interactive educational simulations that enable students to explore complex scientific concepts or historical events. In healthcare, MR simulates medical procedures, allowing medical professionals to practice and improve their skills in a safe and controlled environment. MR can also be used for patient education, allowing patients to visualize and better understand medical conditions and procedures. Overall, MR offers a unique opportunity to integrate virtual and real-world environments, providing a powerful tool for various industries. A visual interface is a computerized representation of a user interface that may or may not correspond to the physical interface controller. Virtual interface designs are static in nature, representing signals used to connect design modules and physical products. With the advent of the internet and its technologies, newer possibilities for remote access to technology have emerged, such as the concept of virtual reality. Virtual reality uses graphical displays to represent objects or scenes in three dimensions, making it easier for users to visualize real-world objects, scenes, or processes. This technology combines visual representations of 3D elements and objects, such as polygons and surfaces, to create a computer-generated scene that resembles a real environment. This scene is known as virtual reality, and it is often projected as what is popularly known as a "virtual world.
English Students' Perception Toward E-Learning during COVID-19 in University Level at Surabaya

In COVID-19 pandemic, many activities cannot be carried out as normal, especially in the field of education. Therefore, the government has determined that offline learning is temporarily suspended and learning is carried out online. However, E-learning has many conveniences, there are also obstacles that give rise to various student perceptions. The purpose of this study was to describe student perceptions of E-learning during the COVID-19 period at the university level in Surabaya. This research method uses descriptive qualitative research. The informants in this study were 17 English students in the year 2020 from classes A, B, and E, at PGRI Adi Buana University, Surabaya. Data collection techniques used in this study were questionnaires and interviews. The analytical technique used is the descriptive analysis technique. The results of the study revealed that most of the students had negative perceptions at first. This is due to constraints in infrastructure and connectivity such as poor internet, limited internet data and lack of suitable devices. Students have difficulty understanding the material because unstable connections affect their understanding of the material. In addition, not all lecturers have a good strategy for teaching using E-Learning, and some students feel bored. One of the students also felt stressed with homework. In addition, they have difficulty communicating with their friends and lecturers. Overall, students consider E-learning effective during the pandemic because it is able to overcome obstacles such as connectivity problems, operate LMS (Zoom Meeting, Google Meet, Virlenda) and also all applications (Kahoot, WordWall).
How to choose the best promotion strategies for increasing prospective students: The role of risk management factors

X University is one of the private universities located in the East Java province. To retain prospective students and encourage them to register, informational media through promotion is necessary. To determine the best promotion strategy, student profile data is utilized. The accumulated student profile data must be processed through data mining. In this research, the K-means method is used for data mining. The K-means measurement results are divided into three groups: Cluster 1 includes P1, P7, and P8; Cluster 2 includes P2 and P9; and Cluster 3 includes P3, P4, P5, P6, and P10. The risk management process is carried out in three stages: risk identification, risk assessment, and risk mitigation. The results of the risk identification phase showed that there were 15 risk variables. The risk assessment phase revealed two very high category risks, two high category risks, four medium category risks, and seven low category risks. Following the advice of X University, risk mitigation activities were selected for the very high and high-category risk variables. The results of this research are expected to contribute to an increase in the number of students at X University in the future.
Efforts to Improve the Ability to Recognize Letters Through Alphabet Mini Book Media in Pembina II Public Kindergarten in Surabaya

This study aims to improve children's ability to recognize letters through the alphabet mini book media. This research is a classroom action research conducted in 3 cycles. The subjects in this study were students in class A3 of TK Negeri Pembina II Surabaya, totaling 20 children consisting of 11 boys and 9 girls. Methods of data collection using observation and documentation. Data analysis technique uses simple descriptive statistics. The results showed that the ability to recognize children's letters increased, namely on the indicator mentioning the name of the letter in cycle 1 by 50 Percent, cycle 2 by 70 Percent, and cycle 3 by 85 Percent, the indicator mentioned the initial letter of the picture in cycle 1 by 35 Percent, cycle 2 by 65 Percent, and cycle 3 by 85 Percent, as well as indicators of writing letters in cycle 1 by 30 Percent, cycle 2 by 50 Percent, and cycle 3 by 80 Percent. Based on these results it can be concluded that the alphabet mini book media can improve the ability to recognize letters in children aged 4-5 years.
Kecemasan Dalam Novel Dangdut Karya Putu Wijaya (Kajian Psikopragmatik)

This study aims to find out anxiety in the Dangdut novel. This study uses physcopragmatic studies to reveal anxiety in the novel. The research approach used is qualitative. The data analysis technique used hermeneutic and heuristic methods. The results show that there are anxiety such as: Assertive Realistics Anxiety and Assertive Neurotics Anxiety. Assertive Realistics Anxiety is an anxiety represents the speechform that occurs in realistics anxiety symptoms. It is reflects characters experienced anxiety based on struggle for something. Something that is meant can be a a realistics problem. Assertive Neurotic Anxiety refers to conflicted and emotional characters that lead to an inability to control themselves. Characters who experience these symptoms will appear frustrated, nervous, and unable to control their behavior.
Modeling Price-Aware Session-Based Recommendation Based on Graph Neural Network

Session-based Recommendation (SBR) aims to accurately recommend a list of items to users based on anonymous historical session sequences. Existing methods for SBR suffer from several limitations: SBR based on Graph Neural Network often has information loss when constructing session graphs; Inadequate consideration is given to influencing factors, such as item price, and users’ dynamic interest evolution is not taken into account. A new session recommendation model called Price-aware Session-based Recommendation (PASBR) is proposed to address these limitations. PASBR constructs session graphs by information lossless approaches to fully encode the original session information, then introduces item price as a new factor and models users’ price tolerance for various items to influence users’ preferences. In addition, PASBR proposes a new method to encode user intent at the item category level and tries to capture the dynamic interest of users over time. Finally, PASBR fuses the multi-perspective features to generate the global representation of users and make a prediction. Specifically, the intent, the short-term and long-term interests, and the dynamic interests of a user are combined. Experiments on two real-world datasets show that PASBR can outperform representative baselines for SBR.
An Efficient Encrypted Speech Retrieval Based on Unsupervised Hashing and B+ Tree Dynamic Index

Existing speech retrieval systems are frequently confronted with expanding volumes of speech data. The dynamic updating strategy applied to construct the index can timely process to add or remove unnecessary speech data to meet users’ real-time retrieval requirements. This study proposes an efficient method for retrieving encryption speech, using unsupervised deep hashing and B+ tree dynamic index, which avoid privacy leakage of speech data and enhance the accuracy and efficiency of retrieval. The cloud’s encryption speech library is constructed by using the multi-threaded Dijk-Gentry-Halevi-Vaikuntanathan (DGHV) Fully Homomorphic Encryption (FHE) technique, which encrypts the original speech. In addition, this research employs Residual Neural Network18-Gated Recurrent Unit (ResNet18-GRU), which is used to learn the compact binary hash codes, store binary hash codes in the designed B+ tree index table, and create a mapping relation of one to one between the binary hash codes and the corresponding encrypted speech. External B+ tree index technology is applied to achieve dynamic index updating of the B+ tree index table, thereby satisfying users’ needs for real-time retrieval. The experimental results on THCHS-30 and TIMIT showed that the retrieval accuracy of the proposed method is more than 95.84% compared to the existing unsupervised hashing methods. The retrieval efficiency is greatly improved. Compared to the method of using hash index tables, and the speech data’s security is effectively guaranteed.
KAJIAN PEMANFAATAN MEDIA PEMBELAJARAN LEAFLET TERHADAP PENINGKATAN HASIL BELAJAR PESERTA DIDIK

&lt;p&gt;&lt;em&gt;Learning media is an important element in the learning process. Innovative learning certainly greatly affects students interest and motivation in learning. One of the learning media that can be used is leaflet. Leaflet is printed media in the form of sheets (folded), equipped with picture and contains a summary of material related to a subject. This research is a research that aims to examine the results of the analysis of the use of leaflet in the learning process from the result of various tests that have been carried out previosly. This research is also used to find out how the influence of the use of the leaflet media on student learning outcomes. This research was conducted using a meta-analysis method, riviewing library sources such as articles, theses and related journals. Based on the results of the analysis of the research that has been done by the researcher, it shows that this leaflet-based learning media has a high effect on increasing students understanding and activity in learning. The increase in student learning activities also has an impact outcomes in the learning process.&lt;/em&gt;&lt;/p&gt;
Event-Based Camera Tracker by ∇<sub> <i>t</i> </sub>NeRF

When a camera travels across a 3D world, only a fraction of pixel value changes; an event-based camera observes the change as sparse events. How can we utilize sparse events for efficient recovery of the camera pose? We show that we can recover the camera pose by minimizing the error between sparse events and the temporal gradient of the scene represented as a neural radiance field (NeRF). To enable the computation of the temporal gradient of the scene, we augment NeRF’s camera pose as a time function. When the input pose to the NeRF coincides with the actual pose, the output of the temporal gradient of NeRF equals the observed intensity changes on the event’s points. Using this principle, we propose an event-based camera pose tracking framework called TeGRA which realizes the pose update by using the sparse event’s observation. To the best of our knowledge, this is the first camera pose estimation algorithm using the scene’s implicit representation and the sparse intensity change from events.