Reviewerly/exHarmony huggingface dataset:
Faktor-Faktor yang Memengaruhi Keputusan Pembelian Buku pada Mahasiswa

&lt;p&gt;&lt;em&gt;Publishers and bookstores decline&lt;/em&gt;&lt;em&gt;d&lt;/em&gt;&lt;em&gt; in book sales from 2013 to 2020. &lt;/em&gt;&lt;em&gt;The&lt;/em&gt;&lt;em&gt; study &lt;/em&gt;&lt;em&gt;aimed &lt;/em&gt;&lt;em&gt;to find out factors that caused book sales decline&lt;/em&gt;&lt;em&gt;d and &lt;/em&gt;&lt;em&gt;students&lt;/em&gt;&lt;em&gt; &lt;/em&gt;&lt;em&gt;influenc&lt;/em&gt;&lt;em&gt;ing factors&lt;/em&gt;&lt;em&gt; in buying books. There are various factors that influenc&lt;/em&gt;&lt;em&gt;ing&lt;/em&gt;&lt;em&gt; the decision to purchase books,&lt;/em&gt;&lt;em&gt; i.e&lt;/em&gt;&lt;em&gt; price, product, location, promotion, lifestyle, word of mouth technology, and information.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This study use&lt;/em&gt;&lt;em&gt;d&lt;/em&gt;&lt;em&gt; 205 respondents who are students of IPB University. &lt;/em&gt;&lt;em&gt;The data collection technique used is&lt;/em&gt;&lt;em&gt; Probability sampling, a random sampling method. Sample selection using convenience sampling is a sampling technique from the person or unit that is the easiest to find or access&lt;/em&gt;&lt;em&gt;.&lt;/em&gt;&lt;em&gt; &lt;/em&gt;&lt;em&gt;The sampling &lt;/em&gt;&lt;em&gt;done by&lt;/em&gt;&lt;em&gt; the interview method and filled out a questionnaire on the google form. PLS SEM test tool&lt;/em&gt;&lt;em&gt; &lt;/em&gt;&lt;em&gt;used&lt;/em&gt;&lt;em&gt; to data analysis&lt;/em&gt;&lt;em&gt;.&lt;/em&gt;&lt;em&gt; SEM&lt;/em&gt;&lt;em&gt; &lt;/em&gt;(&lt;em&gt;Structural Equation Models&lt;/em&gt;&lt;em&gt;)&lt;/em&gt;&lt;em&gt; is a statistical technique that aims to build or test statistical models, which are usually causal&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This research is a field of consumer behaviour science. The research was conducted on the Bogor Agricultural University campus from December 2020 to April 2021. The author chose the location of this research purposively because the object of the research was active Bogor Agricultural University students&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;The &lt;/em&gt;&lt;em&gt;study &lt;/em&gt;&lt;em&gt;results showed that the product, price, word of mouth, lifestyle, technology, and information factors had a significant effect on students buying book decisions. Location and promotion factors have no significant effect on students purchase book decisions.&lt;/em&gt;&lt;/p&gt;
How exploring Python can level up your data visualization

Data visualization, i.e., the graphical representation of data, is a vital skill for every scientist to develop – aiding with the interpretation of data and providing an accessible way to communicate these data with others. In the scientific world, data visualization is used to produce eye-catching figures to share results with peers and the wider community. While these visualizations are achievable using no coding, they can be restricted by the dataset size, plotting style and overall cost of the software. Learning to code solves many of these issues and while the learning curve remains a barrier to use, programming is becoming a must-have skill in many fields. Python is one of the world’s most popular programming languages and is at the forefront of data analysis and visualization, producing clear, engaging and reproducible figures in all manner of styles. As biological datasets increase in size and number, the reproducibility and flexibility of Python result in an invaluable tool for scientific data visualization. This article will introduce the use of Python for data visualization and provide some guidance on how to get started.
Research on Credit Risk Assessment of Commercial Banks Based on KMV Model

Under the background of the new normal economy, the financing mode of local governments has changed, which has led to the emergence of a new pattern in China's financing market.Under this background, banks are facing the development pressure of subject diversification, financial disintermediation and cross-border competition.Commercial banks also actively promote the compliance development of emerging businesses such as financial market through the "comprehensive direction", so as to form a balanced and complementary development situation with traditional credit business.Therefore, this paper taking credit risk and related theories as the starting point, KMV model is selected to study domestic bank risk monitoring.Then, China Merchants Bank is taken as the research object, Shengjing Bank, Harbin Bank, Qingdao Bank and Chongqing Bank are taken as horizontal comparison.The data sampling time span is January to December 2018, as vertical comparison.Five banks were evaluated for credit risk, and it was found that the default distance of China Merchants Bank was relatively small and the default probability was relatively large.However, according to the calculation and analysis of KMV model, the default probability and return volatility of China Merchants Bank rank first among the five commercial banks, but at the same time, it maintains a high net profit margin of 129.3% in 2018, which shows that China Merchants Bank has a strong ability to control credit risk.
Informative Bayesian Neural Network Priors for Weak Signals

Encoding domain knowledge into the prior over the high-dimensional weight space of a neural network is challenging but essential in applications with limited data and weak signals. Two types of domain knowledge are commonly available in scientific applications: 1. feature sparsity (fraction of features deemed relevant); 2. signal-to-noise ratio, quantified, for instance, as the proportion of variance explained. We show how to encode both types of domain knowledge into the widely used Gaussian scale mixture priors with Automatic Relevance Determination. Specifically, we propose a new joint prior over the local (i.e., feature-specific) scale parameters that encodes knowledge about feature sparsity, and a Stein gradient optimization to tune the hyperparameters in such a way that the distribution induced on the model’s proportion of variance explained matches the prior distribution. We show empirically that the new prior improves prediction accuracy compared to existing neural network priors on publicly available datasets and in a genetics application where signals are weak and sparse, often outperforming even computationally intensive cross-validation for hyperparameter tuning.
Image Forgery Analyse and Detection

The popularity of digital photography has risen in recent years, paving the opportunity for new and inventive ways to create photos.Several software programs are now available that may be used to edit images such that they like the original.In the case of any crime, images are used as authenticated proof, and if they do not remain real, it will pose a problem.In recent years, detecting these types of forgeries has become a big difficulty.It's difficult to tell whether a digital image is real or doctored.Finding tampering marks in a digital image is a difficult undertaking.A copy-move image forgery is used to hide an image object or to add more details to the image, resulting in forgery.In both circumstances, image reliability is jeopardized.Although this technology has numerous benefits; it can also be used as a deceptive technique to hide facts and evidences.In this article, we looked at many types of picture forgery and detection strategies; we concentrated mostly on copy move forgery and its detection technique.
Assessing the scaling of a blockchain-based social contact tracking system

During a pandemic, one of the most important tasks is to track social contacts with those who are sick. This article categorizes projects that track these contacts. Projects are classified by architecture and the common components of such systems are highlighted. It is concluded that the hybrid architecture of such a solution based on an exclusive blockchain will have several advantages, and a conceptual model of such a system is described. However, an analysis of existing blockchain projects showed that their main problem is the unresolved issue of scaling such kinds of systems, which is becoming a key issue in the context of creating a global digital infrastructure of society. Further, the scaling of the system&amp;apos;s conceptual model is assessed based on open-source information about the Moscow metro, and the main conclusions about the selected architectural solutions are confirmed.
Fast Software Implementation of Serial Test and Approximate Entropy Test of Binary Sequence

In many cryptographic applications, random numbers and pseudorandom numbers are required. Many cryptographic protocols require using random or pseudorandom numbers at various points, e.g., for auxiliary data in digital signatures or challenges in authentication protocols. In NIST SP800-22, the focus is on the need for randomness for encryption purposes and describes how to apply a set of statistical randomness tests. These tests can be used to evaluate the data generated by cryptographic algorithms. This paper will study the fast software implementation of the serial test and the approximate entropy test and propose two types of fast implementations of these tests. The first method is to follow the basic steps of these tests and replace bit operations with byte operations. Through this method, compared with the implementation of Fast NIST STS, the efficiency of the serial test and approximate entropy test is increased by 2.164 and 2.100 times, respectively. The second method is based on the first method, combining the statistical characteristics of subsequences of different lengths and further combining the two detections with different detection parameters. In this way, compared to the individual implementation of these tests, the efficiency has been significantly improved. Compared with the implementation of Fast NIST STS, the efficiency of this paper is increased by 4.078 times.
Performance Analysis on Hand Gesture Recognition Using Artificial Neural Network

The communication gap between normal people and hearing impaired people needs to be reduced with the help of advanced technology.Two-way intermediate devices with gestures to words and words to gestures are the best solution for both communities.This paper introduces one-way translation system with gestures to words by combining Artificial Neural Network (ANN) methodology with image processing technology.Human gestures are captured via Laptop Webcam and the system's Graphical User Interface (GUI) translates these gestures into words.Performance analysis for this system is also done.The system is created by using MATLAB environment because it is very easy to manipulate and easy to understand.Gesture recognition is also very important for many other applications such as robotic with artificial intelligent (AI), etc.
AKTUALISASI DIRI UNTUK MENGURANGI PERILAKU BULLYING PADA ANAK

The research method used is descriptive qualitative analysis by presenting research updates and analysis of various opinions in scientific articles that are already in journals. Qualitative research is often described as research that publishes social phenomena and behavior as they exist (in natural setting) and is also appropriate. with facts and implemented in depth, in this case the researcher looks for existing information through journals and also existing online media then it is understood and after that then gets data and information to be added and reviewed through small notes then becomes an existing analysis so that a study that is relevant and accurate. The population and sample used in this study were 30 students consisting of class IV to class VI in the Permata Integrated Elementary School, Probolinggo City and also those from various different backgrounds. The data collection instrument is using a questionnaire in the form of google form which is sent to each student with various types of relevant questions as well as field observations in the form of open interviews during a visit to the student's probolinggo. Keywords: Self-actualization, Bullying, Elementary School
Interference-induced directional emission from an unpolarized two-level emitter into a circulating cavity

Chiral coupling between quantum emitters and evanescent fields allows directional emission into nanophotonic devices and is now considered to be a vital ingredient for the realization of quantum networks. However, such coupling requires a well-defined circular dipole moment for the emitter---something difficult to achieve for solid-state emitters at room temperature due to thermal population of available spin states. Here, we demonstrate that a two-level emitter with a randomly polarized dipole moment can be made to emit directionally into a circulating cavity if a separate emitter is chirally coupled to the same cavity, for the case when both emitter-cavity couplings are strong but in the bad-cavity regime. Our analysis of this system first considers a transient scenario, which highlights the physical mechanism giving rise to the directional emission of the two-level emitter into the cavity. An alternative setup involving a weak laser field continuously driving the system is also considered, where the directionality (our proposed figure of merit for this scheme) is shown to be significantly more robust against noise processes. The results presented here take the form of approximate analytical expressions backed by complete numerical simulations of the system.
Innovative and project activities of future education

The article examines the features of the innovative and project activities of future education managers. The authors focus on project technology as one of the forms of innovative methodological technologies for training future education managers, describes the elements of project technology, defines the basic principles of work on a project and the specifics of attracting future education managers to participate in them. The fact is emphasized that future education managers can be active participants in the process of creating a project, develop their own view of information, identify goals, objectives and look for ways to solve them. The purpose of this article is to focus on innovation project activities as one of the forms of innovative methodological learning technologies, to describe the elements of project technology, to highlight the basic principles of work on a project and the peculiarities of attracting future education managers to participate in them.
Movie Recommendation System by Using Collaborative Filtering

Abstract: This is the era of modern technology where we are all surrounded and covered by technology. This eases our daily life and saves our time and one of the most important techniques that played a very important role in our day-to-day life is the recommendation system. The recommendation system is used in various fields like it is used to recommend products, books, videos, movies, news, and many more. In this paper, we use a Recommendation system for movies we built or a movie recommendation system. It is based on a collaborative filtering approach that makes use of the information provided by the users, analyzes them and recommends movies according to the taste of users. The recommended movie list sorted according to the ratings given to this system is developed in python by using pycharm IDE and MYSQL for database connectivity. The presented recommendation system generates recommendations using various types of knowledge and data about users. Our Recommendation system recommends movies to each and every user by their previous searching history. Here we use some searching techniques as well. We also tried to overcome the cold start problem we use Movielens database. Keywords: Collaborative-filtering, Content-based filtering, Clustering, Recommendation system searching technique, Movies
Factors related to negative self-care adherence in individuals with diabetes mellitus

Objective: to detect factors related to negative adherence to self-care in individuals with diabetes mellitus. Methods: observational, cross-sectional, analytical, and exploratory study, conducted with individuals diagnosed with type 2 diabetes mellitus and followed-up by the Family Health Strategy. The sample consisted of 250 participants. The Summary of Diabetes Self-Care Activities Questionnaire was used for self-care assessment. Association tests, prevalence ratio and Poisson regression with robust variance were performed in the analysis. Results: negative attitudes related to self-care increased by 21% for single/divorced/widowed, 20% for retired, 54% for those who did not diet, 28% for those who did not practice physical activity, 24% for hypertensive, 30% for those with dyslipidemia, and 44% for those with retinopathy. Conclusion: socioeconomic factors, behavioral factors, presence of comorbidities and complications related to diabetes mellitus were related to negative adherence to self-care.
A Hybrid Digital Image Watermarking Scheme Incorporating DWT, DFT, DCT and SVD Transformations

Digital watermarking provides copyright protection and proof of ownership by inserting watermark metadata as owner’s identity in digital documents to prevent authenticity and copyright violations. The paper introduces a new hybrid image watermarking scheme by attaching multiple copies of watermarks in carrier image. The new scheme utilizes the advantages of DWT, DFT, DCT and SVD transformations to offer stable resistance in protecting watermark contents from various external attacks. The proposed scheme uses Haar wavelet, Fourier, Onion Peel Decomposition, DCT, zigzag ordering and SVD transforms to decompose the carrier image in to four levels to maintain imperceptibility in the watermarked images. The algorithm attaches replicas of watermark frequency blocks in all frequency components of host image to provide better robustness against external deprivations in watermarked images. The proposed algorithm also provides the increased probability of extracting at least one undamaged replica of watermark even when other frequencies are damaged by external attacks. The improved experimental results of the proposed scheme in terms of visual analysis and quantitative metrics on different images with different experimental set up demarcate that the proposed watermarking scheme provides stable performance in generating better watermarked images. It is experimentally found that the new scheme produces high quality watermarked images with an average of 7.62% lesser Mean Absolute Error (MAE) and increased Peak Signal to Noise Ratio (PSNR), Mean Structural Similarity Index Measure (MSSIM) and Feature Similarity Index Measure (FSIM) of 5.02 %, 4.37 %, and 2.37 % respectively than the next best algorithms when simulated with 20 sets of watermark and cover images. The watermark images extracted by the proposed algorithm from extremely distorted watermarked images are with better visual and objective values than other methods used in the comparative study. Simulation analysis on 20 sets of watermark and cover images with 30 types of potential attacks reveals that the extracted watermark images through the proposed scheme produces an average of 5.62%, 6.37%, 5.75% improved Pearson Correlation Coefficients (PCC), Number of Changing Pixel Rate (NPCR) and the Unified Averaged Changed Intensity (UACI) values respectively than the next best algorithms used in the comparative study.
Indonesian Online News Extraction and Clustering Using Evolving Clustering

43,000 online media outlets in Indonesia publish at least one to two stories every hour. The amount of information exceeds human processing capacity, resulting in several impacts for humans, such as confusion and psychological pressure. This study proposes the Evolving Clustering method that continually adapts existing model knowledge in the real, ever-evolving environment without re-clustering the data. This study also proposes feature extraction with vector space-based stemming features to improve Indonesian language stemming. The application of the system consists of seven stages, (1) Data Acquisition, (2) Data Pipeline, (3) Keyword Feature Extraction, (4) Data Aggregation, (5) Predefined Cluster using Automatic Clustering algorithm, (6) Evolving Clustering, and (7) News Clustering Result. The experimental results show that Automatic Clustering generated 388 clusters as predefined clusters from 3.000 news. One of them is the unknown cluster. Evolving clustering runs for two days to cluster the news by streaming, resulting in a total of 611 clusters. Evolving clustering goes well, both updating models and adding models. The performance of the Evolving Clustering algorithm is quite good, as evidenced by the cluster accuracy value of 88%. However, some clusters are not right. It should be re-evaluated in the keyword feature extraction process to extract the appropriate features for grouping. In the future, this method can be developed further by adding other functions, updating and adding to the model, and evaluating.
Quantum Computing: Applications and Future Importance

Quantum computing is a fantastic technology that has been evolved throughout time and is 100 trillion times quicker than a supercomputer.It is based on quantum theory, which can do calculations using probability theory and linear algebra.These two disciplines of research are involved in all sub-areas of Data Science and other contemporary technology domains, and can answer a wide range of complex problems which even the most powerful supercomputer cannot carry out.Instead of just 0's and 1's where the classical computers encipher the data or convert the information, it works on qubit that is, it can hold up to two bits which is called as Quantum superposition where it has two different states zero or one in which it can be defined and is also possible for it to exist in both, i.e. a superposition of the two states.Light based quantum computer outperforms the classical super computer by exceeding its performance speed.Quantum computing can solve known problems such as encryption and cyber security.Quantum computing has the ability to process quickly to arrive at a solution and offers well and more computing power to the world of Artificial Intelligence systems and efficient Machine learning systems by solving small and large problems much faster.The main aim or objective of this paper is to discuss about the applications and importance of quantum computing in future which is very helpful to the people who are associated with cryptography, Aviation, Data Analytics, Forecasting, Medical research, Pattern matching, self-driving cars and so on.
Translating Traditional Malay Pottery Motifs To Inspire Ceramic Surface Decoration Design

A particular ceramic product offered by the designers and manufacturers is measured based on its appearance and performance from aesthetic value, design and craftsmanship quality. Products in our daily life play an essential role in bringing us happiness, comfort, convenience and satisfaction to the consumers and buyers. In a Malay community in Malaysia, the Malay Traditional Pottery is one of the Malay arts heritage. Its products used to have a high demand among the locals as well as people from abroad. However, today, demand for Malay Traditional Pottery from the locals has declined significantly. Hence, to improve the product appearance, this study highlights one of the essential factors in ceramic design features, namely surface decoration, by using motifs derived from the Malay Traditional Pottery onto the new contemporary design of the local ceramic products. The surface decoration consists of motifs, patterns, colours, techniques and materials. Surface decoration study would give designers and local ceramic entrepreneurs the product appearance improvement. With such improvements, local ceramic products would become a preferred choice for the consumer’s daily use. This study also aimed to entice the designer to be involved in pattern design and ceramic product surfaces.