Reviewerly/exHarmony huggingface dataset:
Rancang Bangun Sistem Informasi Akuntansi Penerimaan Aliran Kas Distribusi Beras Miskin

In this globalization era, information technology is accelerates. Computers which are tools will create to take it easy of human work, when achieving progress both in the manufacture of hardware and software. Information system design is the best solution to solve problems that exist in this agency, and with a computerized system can achieve an effective and efficient activity in supporting activities in this agency. A computerized system is better than a manual system so that it runs more effectively and efficiently as well as a more conducive reception system compared to the previous system. This study uses quantitative methods and system development in the form of methods in analyzing the designed software. From the results of this study it is hoped that it can help the performance of village agencies starting from inputting data to distributing it to the community.
PICK AND PLACE ROBOT USING VACCUM GRIPPERS FOR UNEVEN SOLID OBJECTS

- To doing repeated works have become immense in today’s situation, like picking and placing objects from one place to another, have been a tiresome work, our work focuses on taking this job away from humans and handing it to a device which is capable of doing this job in an efficient way on its own. In this paper of two axis robotic arm with vacuum gripper focuses on doing the repeated tasks of picking and placing, so that it could easy the work of humans. We have used hydraulic plunger for robot arm and diaphragm pump for vacuum gripper.
Evolutionary approach in Assembler by Implementation of Neural Networks

A neural network is represented using the Assembler Encoding approach as a straightforward computer programme called the Assembler Encoding Programme. The goal of this programme is to create a Network Definition Matrix, which has all the data required to build a neural network. In order to create the programmes and subsequently the neural networks, evolutionary techniques are used.Finding the ideal number of neurons for a neural network is one of the difficulties in Assembler Encoding. The current implementation of Assembler Encoding relies on an inefficient and time-consuming way to deal with this issue. The report offers four other approaches to address this problem, though. Experiments were performed utilising a predator-prey problem to assess various solutions. The network's design, including the number of layers, the number of neurons in each layer, and the connections between neurons, is specified by the Assembler Encoding Programme. These rules are expressed in a low-level language that resembles machine code very closely.The Network Definition Matrix is produced by running the Assembler Encoding Programme, and it acts as a design for the neural network. Typically, the matrix contains data on the biases and weights of the connections between neurons.Thepaper track the Assembler Encoding Programmes are frequently improved and evolved using evolutionary techniques like genetic algorithms. The programmes are iteratively enhanced through evolutionary processes to create neural networks that display desirable behaviour for certain tasks or issues.
Feature Selection toEnhance Phishing Website Detection Based On URL Using Machine Learning Techniques

The detection of phishing websites based on machine learning has gained much attention due to its ability to detect newly generated phishing URLs. To detect phishing websites, most techniques combine URLs, web page content, and external features. However, the content of the web page and external features are time-consuming, require large computing power, and are not suitable for resource-constrained devices. To overcome this problem, this study applies feature selection techniques based on the URL to improve the detection process. The methodology for this study consists of seven stages, including data preparation, preprocessing, splitting the dataset into training and validation, feature selection, 10-fold cross-validation, validating the model, and finally performance evaluation. Two public datasets were used to validate the method. TreeSHAP and Information Gain were used to rank features and select the top 10, 15, and 20. These features are fed into three machine learning classifiers which are Naïve Bayes, Random Forest, and XGBoost. Their performance is evaluated based on accuracy, precision, and recall. As a result, the features ranked by TreeSHAP contributed most to improving detection accuracy. The highest accuracy of 98.59 percent was achieved by XGBoost for the first dataset with 15 features. For the second dataset, the highest accuracy is 90.21 percent using 20 features and Random Forest. As for Naïve Bayes, the highest accuracy recorded is 98.49 percent using the first dataset.
Performance Comparison of Deep Learning Algorithms in Twitter Bot Detection

Difficulty in detecting social media bots - software-controlled accounts that seem as human - has serious consequences. Bots have been used to affect the financial market, political elections, and spreading conspiracy theories. Most approaches detect bots at the account level by studying social media posts and using network structure, system dynamics, content analytics, etc. In this study, we compare the performance of the recurrent neural network (RNN), convolutional neural network (CNN), and feed forward neural network (FNN) in detecting Twitter bots by evaluating the textual content of 10,416,240 tweets from humans and bots. Deep learning models utilize sample data to gauge performance. The CNN model identified recent social bot samples most accurately (97.67 %). In comparison, the RNN model achieved great accuracy (97.04 %) with a longer training time. RNN and CNN algorithms perform well when compared to other deep learning classifiers.
Role of Singing Games in Character Formation among Pre-Primary School Children

The purpose of this study was to establish the influence of singing games on the moral development of pre-primary school children. Specifically, the study sought to find out the influence of singing games on character formation among pre-primary school children. The study employed a descriptive survey design. The target population was 2,446 respondents, constituting 2000 pre-primary school children, 230 teachers, 215 parents, and the Kisii South Sub-County ECDE Director. Krejcie and Morgan's (1970) table was used to obtain a sample of 331 respondents. Simple random sampling and purposive sampling were used. Questionnaires, interviews, and observation schedules were used as tools of data collection. Quantitative data were analysed using descriptive and inferential statistics, while qualitative data were coded and categorized through the identification of themes and patterns. The study found that most of the children who entirely and actively participated in singing games at school had a positive change in their moral development through character formation, with a correlation value of r=.260. These findings signified that for society to have morally upright children, there is a need for emphasis on more singing games by curriculum designers and educators for effective moral development. The findings will be useful to teachers, educational policymakers and practitioners, and educators in fine-tuning their pedagogical approaches, allocating teaching and learning resources, developing and designing the curriculum, and assessing the effectiveness of singing games on moral development. Finally, this study would help enhance the existing literature upon which potential researchers will base related work.
Exploring The Techniques and Applications of Hand Gesture Recognition for Human-Computer Interaction

Hand gesture controlled applications are software applications that are controlled by the user's hand movements. Hand gesture controlled applications have the potential to improve user experience by offering more intuitive and immersive ways to interact with system. Hand gesture controlled applications have a huge scope, including gaming, virtual reality, robotics, healthcare, and various other sectors. In this paper, we have combined several disparate end results of subsystems such as virtual mouse, contactless keyboard, finger counting, taking selfies, sign language, game, handling installed applications and volume control using computer vision. For implementation, we used the open-source software library OpenCV, mediapipe and pyautogui. Various hand gestures are assigned to launch and control different applications. These hand gestures are recognized using machine learning trained models, Euclidean distance formula and pixel positions. Overall, it allows humans to interact with computers through hand gestures rather than traditional input/output mechanisms such as the keyboard and mouse, improving accessibility. Key Words: Computer vision, OpenCV, hand gesture, machine learning, TensorFlow, pyautogui, mediapipe, virtual mouse, virtual keyboard, sign language, gaming.
PEMBELAJARAN FLIPPED CLASSROOM BERPENDEKATAN MATEMATIKA REALISTIK UNTUK MENDUKUNG LITERASI MATEMATIS SISWA

This study aims to determine the effectiveness of flipped classroom learning with a realistic mathematics approach to promote students' mathematical literacy. This research was a quasi-experimental study using posttest only non-equivalent control group design. The population of this research was all students of 10th grade in one of public senior higher school in Kendari, Indonesia. Two classes were chosen by purposive sampling as the samples of this study that is X-MIPA 1 as the experimental class and X-MIPA 2 as the control class. The instruments used in this study were a mathematical literacy test. The results of this study show that the flipped classroom learning with a realistic mathematics approach is effective to promote the achievement of students' mathematical literacy.
Cloud Security: Challenges and Future Scope

Now Cloud computing becomes so much popular coz satisfying business needs efficiently. Cloud features provide best lead to organizations to effectively access data and services with less cost over the internet. This also raise issues related with cloud security. This paper presents brief information regarding cloud computing security challenges. This information includes security mechanisms that should be consider for Cloud Service Models. This Work also focus on detail knowledge of security issues, threats which may use by attacker. It also explains cloud components levels threats and attack so more secure mechanism can identified for each component. This Paper introduced classification of Cloud security areas issues to develop secure Cloud Security services in future.
The impact of Foreign Direct Investment on poverty in Algeria 1990-2019

The research paper aimed to study the impact of Foreign Direct Investment (FDI) on Poverty in Algeria during the period 1990 to 2019, where the following variables were used: Foreign Direct Investment, Inflation Rate, Trade Openness rate and Per Capita GDP as an indicator for Poverty rate in Algeria. In the long term using the Auto-Regressive Distributed Lag (ARDL) model. The results the study concluded that foreign direct investment had a very weak positive and significant impact on poverty rates in Algeria during the study period
The impact of the use of the intranet network on the sharing of knowledge in the economic enterprise - a case study of the LafargeHolcim Cement Production Corporation - M'sila -

This research aims to study the role of the Intranet in the sharing of knowledge in the production of cement Lafarge Holcim-M'sila - Algeria. The main concepts related to the intranet and its uses in the organization were discussed and shared knowledge, objectives and obstacles.&#x0D; The descriptive approach was used and the survey was used as a basic tool for obtaining information and using a number of statistical methods to test the hypothesis of the study and analyze its results.&#x0D; A very low correlation was found between Intranet usage and the process of knowledge sharing by respondents, as well as the absence of an impact on the use of the Intranet to share the knowledge of the institution under study.&#x0D;
Introduction and Overview: Hybrid Metaheuristics in Structural Engineering—Including Machine Learning Applications

For the first chapter of the book entitled “Hybrid Metaheuristics in Structural Engineering—Including Machine Learning Applications”, an introduction and overview chapter is given. This chapter includes the importance of optimization in civil engineering as an introduction. Then, metaheuristics are defined as a general frame. Then, machine learning is mentioned. Finally, an overview of the content of the book was given.
Use of Internet of Things to Improve E-government Public Services

Internet of Things (IoT) technology is accelerating societal and lifestyle changes, yet its application in E-government public services remains inadequate.E-government public services have a direct impact on public life and development, and they reflect the government's governance capabilities.Technological improvement is critical to the development of E-government public services.In this paper, the technical characteristics and advantages of IoT technology applied to E-government public services are systematically outlined and analyzed.The technical challenges faced by the current development of E-government public services are examined, and how IoT technology can be leveraged to improve these services is explored.By integrating emerging technology applications, creating a data-driven environment and a distributed multicenter, opening up government-civilian interaction channels, and developing intelligent scene-based services, IoT is utilized to significantly enhance public service experiences and effectively improve public services.The utilization of IoT technology in E-government public services presents enormous potential, as it facilitates the advancement of such services and supports the transformation of governmental organizations and social governance models.This report offers guidance for policy makers, implementers, and IoT technology engineers on comprehending the implications of IoT technology in E-government public services.
High-Throughput Hardware Design for the AV1 Decoder Switchable Loop Restoration Filters

This paper presents a high-throughput hardware design for the Switchable Loop Restoration Filter (SLRF) of the AOM Video 1 (AV1) video format. This hardware includes the two filters defined at the AV1 SLRF: the Separable Symmetric Normalized Wiener Filter (SSNWF) and the Dual Self- Guided Filter (DSGF). The SLRF is the last step in the AV1 loop restoration filters, and it is used to attenuate blurring artifacts, improving the subjective video quality and the coding efficiency. The designed hardware targeted the AV1 decoderand is able to process up to 4K Ultra-High Definition (4K UHD) videos (with 3840x2160 pixels) at 60 frames per second (fps) in real-time. In order to cover different scenarios, two other target throughputs were also evaluated: 4K UHD at 30fps and Full HD (FHD) (with 1920x1080 pixels) at 30fps. The architectures were synthesized for standard cells using the 40 nm TSMC library. The SSNWF and DSGF architectures used 37.38 Kgates and 177.58 kgates in all evaluated scenarios. Depending on the evaluated scenario, the SSNWF power dissipation varied from 8.25mWto 26.95mWand the DSGF power varied from 57.19 mW to 115.02 mW. This is the first paper in the literature presenting a hardware design for the AV1 SLRF with its two filters.
Metaverse Magnifique: Making Meaningful Metaverses

Being immersive online and physically isolated during the COVID-19 pandemic may not be the future of the metaverse we anticipate.Therefore, the rising challenge of creating metaverses does not lie in what novel virtual experiences can be offered but in how to make the experience more meaningful to users.This involves creating an engaging environment for both physical and virtual social interactions and providing equity for a wide range of users.Metaverse Magnifique intends to explore the design of a meaningful metaverse beyond the computer screen.It investigates a combination of the best features of digital and physical environments with human interactions seamlessly conducted and transitioned between the two worlds while also inquiring a better understanding of the changing social norms from fundamental human activities.A series of experimental Protometaverse projects based on a critical review of the Metaverse typology are proposed then developed into small-scale designs to highlight a meaningful behavior, action, task, or activity.The projects are then coupled with a physical site and extended into a full-fledged metaverse project integrated within the city.The projects showcase meaningful experiences by translating visual and spatial elements then enabling AI assistive features for better communication or interpretation of subtle interaction nuances.
Exploring the Application of the Digital Gamification Mechanisms to the Experience of Physical Architectural Exhibitions

This study aims to respond to the 'human-centred' theme of digital heritage and visualisation by exploring a new approach to applying gamification mechanisms to design physical architectural exhibitions.This paper analyses the current exhibition's gamification design in three parts-core drivers, defining characteristics and development models.Then constructs a design model for "digital gamification".The history museum of Harbin Institute of Technology (Shenzhen) is selected as an example to conduct an empirical investigation.Finally, future experiments are proposed to evaluate the design process's effects on improving the platform's design.It is expected that the demonstration of this study will enrich the exploration of the application of the emerging design method of digital gamification mechanism in exhibition design.On the one hand, it attempts to construct the relationship between the influence of digital gamification mechanisms on the tangible and intangible information in the audience's cognitive space, thus providing new ideas for designing cultural experiences in future exhibition spaces.On the other hand, it gives new vitality to the exhibition design and enhances the audience's motivation to interact, which helps to expand cultural communication's influence.
Systematic Review of Organizing the Data Flow of Systems Using Building Information Modeling and Distributed Ledger Technology

As the digitalization in the architecture, engineering, and construction (AEC) industry has been rapidly progressing, building end users will require more coverage of quality data for their built environment.Despite its obvious need, it is seldom for the building information modeling (BIM) to be distributed for such broad use cases thus far.A potential reason for the situation is the lack of the public repository that can provide the adequate access control for various users.Distributed Ledger Technology (DLT), including blockchain, is one of the promising resolutions for the problem.Numbers of preceding proposals for DLT-based BIM repository systems (BIM-DLT system) have proved the utility to date.Understanding the statistical facts of their configurations will become a significant assistance to determine the plausible data distribution system, and thus, to strengthen the project information life cycle.This article aims to build a representative framework through the integrated literature review (ILR).The review results showed that the system's data flow was classified into two patterns.The judgment criteria for selecting the pattern of the system are expected to depend on the purpose of system implementation, and the purpose of automation through smart contracts is more important than the oracle problem.
ANALYSIS OF STUDENTS’ ERRORS IN WRITING RECOUNT TEXT

This research aims to find out the grammatical errors and the dominant error written by the tenth-grade students of SMA Karuna Dipa Palu in the academic year 2021/2022 in writing recount text. The researchers used the descriptive qualitative design. The subject of this research was all the tenth-grade students of SMA Karuna Dipa Palu which consisted of 32 students. In collecting the data, the researchers used test as the instrument. The researchers analyzed the data by using error analysis. The result of the research showed that the students made 412 errors in their recount texts which are classified into: simple past tense (34.7%), preposition (6.1%), pronoun (3.9%), spelling (10.7%), and punctuation (44.7%). The dominant error is punctuation. The dominant errors occurred because the students pay less attention to the use of good and correct punctuation. They are apathetic to the use of punctuation.
USING FLASHCARDS TO INCREASE STUDENTS’ VOCABULARY

The objective of this research is to find out if using flashcards can increase students’ vocabulary of grade VIII students at SMPN 4 Tanantovea Donggala. The researcher used quasi-experimental design with two classes, experimental class consisted of 24 students and control class consisted of 20 students, experimental class and control class. The selected through total sampling technique. In collecting data, the researcher administered pretest and posttest to both the experimental class and control class. The data were analyzed statistically in order to find out the significant difference of students’ achievement before and after treatments.Using 0.05 level of significance and 42 degree of freedom (df), the researcher found that the value of t-table was 2.019, which was lower than the of t-counted (4.65. It means that the hypothesis is accepted. In other words, using flashcards can increase students’ vocabulary.
Evaluation of Radar Health Status Based on Fuzzy Comprehensive Evaluation of Cloud Mode

Health status assessment is the core of radar health management. In this paper, a radar health status index system is established according to national standards and actual conditions, and radar health status levels are divided. The problem uses the trapezoidal cloud model to determine the membership function, which reduces the subjectivity in the evaluation and avoids the problem of too absolute demarcation in the evaluation.
USE OF DICTOGLOSS TECHNIQUE TO IMPROVE STUDENTS’ WRITING SKILL

The objective of this research is to find out if applying Dictogloss technique can improve writing skills of eighth-grade students. The researcher applied pre-experimental research design. One hundred and thirty seven students of SMPN 5 Palu took part in this research, and class VIII A which consisted of 23 students were selected samples of the research. The data were collected using a test administered twice; it was in the form of a pre-test and a post-test. The data were analyzed statistically. The results of the data analysis showed that the t-counted value (15.3) was higher than that of the t-table (1.717) by applying a significance level of 0.05 with a degree of freedom (df) 22(n-1). This means that the hypothesis is accepted. In other words, applying Dictogloss technique can improve writing skills of eighth-grade students of SMPN 5 Palu.