Reviewerly/exHarmony huggingface dataset:
IMPLEMENTASI METODE UNIFIED APPROACH PADA SISTEM INFORMASI AKUNTANSI ARUS KAS KLINIK CITAMA

The Citama Clinic, the Pitara Branch, is a company in the field of health services, and the Citama Clinic, the Pitara branch, also provides health care facilities specifically to provide outpatient services. Where in this case makes the Citama clinic the Pitara branch have many purchase transactions every day and is accompanied by increased operational costs that support the company. While the recording of cash receipts and disbursements transactions is still simple, where cash flow data processing is still carried out using Microsoft Excel, and in storing data on computers it is vulnerable to security because it is not given a password on the document file. For this reason, the author tries to make research on the design of cash flow accounting information systems, the design of this information system is the right solution to solve the problems that exist at the Citama clinic of the Pitara branch, namely by using a Java-based program desktop, with this program the cashier and supervisors will be facilitated in the input and output process and the owner will easily observe the development and improvement of his company without the need for many documents that make data analysis difficult.
Bi-Directional Neighborhood-Aware Network for Entity Alignment in Knowledge Graphs

As an important research work in knowledge fusion, entity alignment can promote the sharing and integration of multi-source knowledge graphs. Recently, entity alignment based on graph neural networks has received a lot of attention for its ability to capture the topology of entities, but it ignores the noise in neighbor subgraphs and the impact of distant neighbors on central entities. In addition, the knowledge graph is a sparse structure, with the vast majority of entities obeying the long-tail effect.But existing works pay little attention to the alignment of long-tail entities. To address the above problems, this paper proposes an entity alignment approach, which aggregates bi-directional multi-hop neighbors to enrich the context of the central entity, and uses entity names to supply entities with less structural information. The feature fusion module can dynamically adjust weights for the significance of different features. Experimental results show that the overall performance of our model is superior than that of GNN-based methods.
Analysis of time-delay photonic reservoirs for neuromorphic computing

We numerically investigate time-delay photonic reservoirs to provide a deep understanding of their complex nonlinear dynamics, in connection to their memory and performance to solve machine learning problems. We explore the ability of such systems to tackle tasks with progressing difficulty towards optimized neuromorphic photonic applications.
Exception Handling

An exception is an error that occurs during execution of a program, sometimes called a runtime error. This could be a “file not found” error if you are trying to load a file that doesn’t exist, or a “type error” if you type text into a field when the program is expecting a number.
Enhanced Security in Supply Chain Management System Using AES and Md5 Algorithms

A supply chain is an order of activities engaged which circulates, assembles and handles the products to move the benefits from a dealer under the control of the last customer.It is an interconnected compound network controlled by supply and demand.Cyber security in SCM is one of the segment of its estimates of protection which primarily gives attention in managing the essential virtual protection which comprises of system software of information technology.In the existing system, cloud services must need extra applications and assistances to locate, govern and protect data which initiate extra supply chain contributors.The manufacturing process data will mislead the manufacturing process in this system based on errors which are done manually.To Store and Maintain data in a protected manner, most algorithms such as DES (Data Encryption Standard) algorithm has disadvantages and threats which seems to be an upper hand for the hackers who are working to steal the data all around.In this paper, for securing the private and secret data, we applied and executed AES (Advanced Encryption Standard) algorithm and MD5 (Message-Digest algorithm 5) in supply chain management.We apply PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyzes) approach in domain of supply chain management, data security, and cyber security to screen the various methods and algorithms which are published in various journal papers and to select a unique and best approach to be used in supply chain management and its security.This method is basically a kind of literature survey to select a best topic for doing a project or a research paper.
Chromatographic Study of Blue-Violet Tanzanite’s Color Appearance

Tanzanite is a blue-purple zoisite currently produced only in Tanzania. Tanzanite is loved by the public for its attractive blue-violet color. In this study, the color appearance of tanzanite will be studied chromatically using the CIE 1976 L*a*b* unified color space and the CIECAM16 color appearance model, respectively. The blue color of tanzanite is quantitatively characterized in CIE 1976 L*a*b* uniform color space using an X-Rite SP62 spectrophotometer. The tristimulus values XYZ of tanzanite’s color are input into the CIECAM16 forward model to calculate the color appearance parameters of tanzanite under different light sources, different illumination levels, and different surroundings. And the results show that D65 light source is more suitable for the display of tanzanite. The change in illumination will have a significant effect on Brightness (Q). Darkening of the surroundings will lead to an increase in the lightness of tanzanite. The blue-violet color of tanzanite has a better visual effect when observed in darker conditions.
Practical Research on Physical Problem Solving with Mathematical Graphical Models

There is the tightest relation between mathematics and physics among all disciplines.Specifically, mathematics can serve as an instrument to describe physical phenomena, while physical theory can be used to interpret mathematical laws.As a basic discipline of all natural disciplines, mathematics can provide operational tools, thinking methods, and process simplification approaches for the proposal and development of physical problems.The mathematical graphical model can effectively improve the efficiency of problem solving.This study is conducted based on the transfer theory.Besides, the methods and practice of physical problem solving with mathematical graphical models are analyzed from the perspective of specific examples in physics.
Age &amp; Gender Recognition Using Deep Learning

Human face image analysis is an important area of research in the science of computer vision. The human face conveys a wealth of information about their particular qualities. One of the most essential challenges in computer vision is recognising a person’s gender and age from a facial picture. The most significant characteristics derived from human faces are the eyes, nose, mouth, brows, and so on. These characteristics are employed in a variety of Human-Computer Interaction sectors, including security systems, judicial systems, transportation, medical, and many more. The first stage of age and gender recognition is detecting face from the inputted image. There are different techniques for face detection. The next stage is pre-processing where cropping and resizing of image for fast processing the last stage is feature extraction and classification by using deep convolution network. The various methods involved in these stages are studied and from the study building an Age and Gender Recognition System using deep learning.
Enhancing fourth-grade students’ writing skills through a problem-based learning module: A research and development

Writing is a necessary skill, especially for elementary school students, as it cannot be naturally gained. However, students in the Indonesian language classroom in elementary schools, struggle to learn how to write. Therefore, the purpose of this study was to develop a thematic module based on problem-based learning with the theme "Kayanya Negeriku" and investigate the feasibility of the teaching materials for this module to help elementary school students with their writing. Fourth-grade students from two elementary schools in rural areas in Lampung were the participants in this study, which used a research and development design based on the Borg and Gall's model. Data were collected using observation and a questionnaire. The collected data were analyzed descriptively. The findings indicate that the fourth-grade students found the problem-based learning module to be "extremely intriguing". The experimental class's pretest average for writing was 68.43, while the posttest average was 86.50. In the control class, the average pre-test score was 61.83, and the average post-test score was 78.16. Therefore, the average post-test score was higher in the experimental class than it was in the control class. The implications and suggestions for further investigation are also highlighted.
Exloratory Data Analysis Untuk Data Belanja Pelanggan dan Pendapatan Bisnis

A more quantifiable perspective is assuming the role of mechanistic management in an effort to enhance business based on its capacity to transform data into knowledge and insight. The industry has not completely supported its business strategy also with driven data. Using a transaction dataset taken from one of the Kaggle.com challenges, this experiment attempts to determine consumer spending patterns and Retail Fashion business revenues (H&amp;M Personalized Fashion Recommendations). The results of the experiment are the number of transactions based on customer age, the most sales product and one-time purchased item, and the type of product that generates the highest and smallest income. The approach employed is EDA using the Python language. In order for businesses to generate analytical findings that provide future perspectives and to help identify the gap by delivering analytical results in the form of suggestions that can be perpetuated, the findings of this experiment are intended to support the capabilities of simulation. The challenge in this experiment is the abundance of datasets, which necessitates a suitable operating environment.
Gated 3D-CNN for Action Recognition

Human action recognition is an active field in computer vision tasks. It is mostly based on the extensively developed image recognition algorithm using convolutional neural networks(CNNs) or recurrent neural networks (RNNs). Action recognition is considered as a more challenging task than image recognition as a video consists of an image sequence that changes in every frame, and the model has to deal with both spatial and temporal information simultaneously. Recently proposed methods using the two-stream fusion technique show good performance in such tasks. However, these methods are computationally expensive and are complex to build for learning spatio-temporal dependencies of the action. This paper proposes a simple yet efficient deep neural network architecture, Gated 3D-CNN, consisting of 3D convolutional layers and gating modules to act as an LSTM model for learning spatial and temporal dependencies and give attention to essential features. The proposed method first learns spatial and temporal features of actions through 3D-CNN. Then, the sigmoid gated 3D convolution layers of local and global gating help to locate attention to the essential features of the action. The proposed architecture is comparatively simpler to implement and gives a competitive performance on the UFC-101 dataset.
A Random Oracle for All of Us

We introduce the notion of a universal random oracle. Analogously to a classical random oracle it idealizes hash functions as random functions. However, as opposed to a classical random oracle which is created freshly and independently for each adversary, the universal random oracle should provide security of a cryptographic protocol against all adversaries simultaneously. This should even hold if the adversary now depends on the random function. This reflects better the idea that the strong hash functions like SHA-2 and SHA-3 are fixed before the adversary decides upon the attack strategy. Besides formalizing the notion of the universal random oracle model we show that the model is asymptotically equivalent to Unruh’s auxiliary-input random oracle model (Crypto 2007). In Unruh’s model the adversary receives some inefficiently computed information about the random oracle as extra input. Noteworthy, while security in the universal random oracle model implies security in the auxiliary-input random oracle model tightly, the converse implication introduces an inevitable security loss. This implies that the universal random oracle model provides stronger guarantees in terms of concrete security. Validating the model we finally show, via a direct proof with concrete security, that a universal random oracle is one-way.
YouTube as a Reinforcement Tool for Learning Differential Calculus

This work proposes utilizing a YouTube channel to reinforce previously covered contents in differential calculus units as part of the teaching–learning process and the application of technological and communication skills. YouTube is used as a resource to disseminate information in the learning process. The videos provide students with reference materials to review concepts, theories, and procedures. The YouTube platform can be an educational space for a large audience. Students use it frequently to reinforce content that may not have been understood in classes, review topics for retention, or complement previous knowledge. A keyword or subject search can access thousands of explanatory tutorials, which can be used, reused, shared, or transformed depending on the training needs. Thus, the necessity of incorporating and viewing YouTube as an educational tool arises. One can analyze its benefits and the utility offered to the students, teachers, and the educational institution as an open educational resource. Exploring the tools that technology provides and how the educational systems use them is a must in today’s times.
Simulation of fringe order of photoelastic samples based on Neural Network

The purpose of this paper is to solve the problem of traditional photoelastic fringe recognition and automatic grading through the BP artificial neural network. The nonlinear mapping relationship between the RGB value of each point on the photoelastic picture and the fringe order of the corresponding point is verified to resolve the problem. The simulation analysis is carried out by the BP neural network. The simulation analysis data shows that it has a favorable effect on fringes below grade 4.
CONTROLLED METHOD OF DETERMINE GOLD MINERALIZATION POTENTIALS IN AN UNEXPLOITED AREA; A CASE STUDY OF ITAGUNMODI AND OSU, SOUTHWESTERN, NIGERIA

The research was conducted to open up further unexploited areas for gold mineral exploitation in part of Ilesha schist belt using geological and geophysical approach. Itagunmodi was used as a control in order to determine the mineralization potentials of Osu as a case study. Both towns lie within Ilesha schist Belt, Southwestern Nigeria. The residual magnetic anomaly map of the study area revealed magnetic low in the two towns indicating the presence of geological structure serving as a conduit for mineralizing fluid. Airborne radiometry interpretation showed that both Itagunmodi and Osu are affected by hydrothermal alteration which is an indication of gold mineralization. Overall interpretation of aeromagnetic and airborne radiometry datasets show that hydrothermal alteration generally is associated with fault and shear zones in the study area. The isolated altered zones were subjected to further investigation by using six samples of stream sediment collected along Imo (Itagunmodi) and Olomumu (Osu) stream channels for the grain size and geochemical analyses. The results from the grain size analysis revealed that sediments in both areas are fine to medium grained, poorly sorted, fine to moderately fine skewed, which implied fluvial depositional settings, and revealed that the occurrences of gold mineralization in both areas are of secondary deposits (alluvial). The concentration of identified trace elements as related to their threshold values revealed similar contents of low to high concentrations in both areas. The results of the analyses observed in Itagunmodi are similar to that of Osu, which implies that Osu is also mineralized will gold deposit.
The Culture of Literacy Among Students of Islamic Education Program: A Case at a Private Islamic University

This study aims to determine the causes and obstacles faced by students of the Islamic Religious Education Study Program in carrying out literacy activities. This study used a qualitative descriptive approach, which provides an appropriate description or explanation that occurs in the field, with data collection methods namely observation, documentation and interviews. So that at the end of the study, it is expected to know the Literacy Culture of Students of the Islamic Religious Education Study Program which is useful as input for institutions/foundations as well as input for competent educators/lecturers. Based on the results of the study, it shows that the reading literacy culture among students is still very low, this is influenced by various factors. The first is the lack of awareness of students in obtaining books or not having books. Second, they prefer to hang out with friends by talking about things that are less likely to lead to learning on campus. Third, they prefer to play games and social networking than reading. Fourth, they are tired and unfocused because they have a side job to earn money for living. These factors arise from within students are generally due to laziness, lack of self-motivation. Although there have been efforts made by lecturers by giving lectures and the library to encourage students to practice a reading literacy culture. However, students themselves choose not to practice reading literacy culture. What is more important is how to optimize students who have a passion for reading and writing, which have added value as a source of information that can assist in carrying out the Tri Dharma of Higher Education.
Maximising Mobile Applications for Cost-effective Training in Africa: Evidence from an Empirical Investigation

This study examined the use of a mobile application to train facilitators of adult literacy with a view to exploring the possibility of providing cost-effective facilitator training, as against regular training programmes which incur several additional costs for venue, feeding, production of training manuals, honorarium, accommodation, subsistence allowance, among others. This has been a reason for which facilitator training has become a neglected field in most African countries, especially Nigeria. The study adopted the pretest-posttest control group, quasi-experimental design, and selected 66 adult literacy facilitators using a multi-stage sampling procedure. Two research questions were raised and analysed using frequency count, mean and standard deviation. Results revealed that it is cheaper to train using the mobile application compared to conventional face-to-face training method; and that participants in the experimental group who used the Mobile Training Application performed better than participants in the control group who went through the conventional training. Recommendations were made based on these findings that awareness could be created among adult literacy facilitators about this innovation of the mobile application for training. Also, the government, as well as other organisations interested in the training of facilitators, such as UNESCO, could be encouraged to adopt this cost-effective means to train facilitators of adult literacy in Nigeria and other African countries.
Application of Deep Learning Face-mask Detection Based on YOLOv5

Since the outbreak of coronavirus in 2019, people around the world have started to wear masks to avoid the further spread of the virus.In order to better control the epidemic, it is very necessary to supervise the wearing of masks.In this paper, a deep learning model based on yolov5 is established for mask recognition and detection, and the model is trained and tested through datasets.Finally, mask detection is carried out for people in images and videos using local computer equipment, and the best weight of training and the training accuracy of nearly 95% is obtained.This paper combines the algorithms of binary classification, convolutional neural network, and deep learning object detection to effectively and accurately train and test the model, which has a certain reference value.
ANALYSIS OF ARGUMENTATION WRITING ABILITY USING THE OBSERVATION MODEL IN HIGH SCHOOL STUDENTS IN THE 10th CLASS OF THE 2nd SEMESTER in the 2018/2019 ACADEMIC YEAR

Many people are fluent in speaking, but they are not able to express ideas in writing. Even if the speech experts are able to write down their ideas well, this usually happens after going through intensive training, both formally and informally. The ability to write is the result of a learning process and perseverance in practicing. The description in writing the argumentation from the students' observations is still not complete. To examine the ability to write arguments based on observations of high school students in the second semester of 10th class at SMA PGRI Talangpadang, the observation method was used, and sample testing with a population of students in the second semester of 10th class at SMA PGRI Talangpadang. Based on the results of the research data analysis that the author has done, the author can conclude that the average ability of students in the second semester of 10th class at SMA PGRI Talangpadang in 2018/2019 in writing arguments based on observations is quite good (65.25%).
PENGARUH MODEL PEMBELAJARAN BLENDED LEARNING TERHADAP HASIL BELAJAR PELAJARAN BAHASA INDONESIA SISWA KELAS 8 DI SMPN 1 PRINGSEWU

This study aims to determine the effect of the blended learning model on learning outcomes of Indonesian at SMPN 1 Pringsewu. The research method used is quasi-experimental, with a sample of 66 people divided into two classes, namely the experimental and control classes. The tools used are multiple choice tests and teacher observation forms. Before using the test instrument, the instrument has been tested for validity and reliability. Through the validity test of 50 questions, 37 valid questions were taken, but only 30 test questions were used, because to facilitate calculations, these questions already represented various indicators. The test results were tested statistically using the "t" test, based on the t_count value of 2.171 and t_table of 2.036, so that t_count &gt; t_table, which means Ho is rejected at the significance level = 0.05. Therefore, it can be concluded that Ha stated that the blended learning model had an effect on Indonesian language learning outcomes. This shows a significant effect on students' Indonesian learning outcomes.