Reviewerly/exHarmony huggingface dataset:
The interpretation of zeta test results: a supplement

Abstract Zeta is a mathematical method which has been used to try to solve authorship attribution problems in both the early modern and modern periods. David Hoover, one of its leading practitioners, has recently made two important claims (Hoover, Zeta revisited, Digital Scholarship in the Humanities, print publication forthcoming). Given his status as an expert on Zeta, these claims are likely to be treated by researchers as authoritative. Most Zeta graphs show a good separation between the base and counter segments. Hoover claims that this is an important finding, rather than, as Pervez Rizvi argued, a mechanical consequence of the method (Rizvi, The interpretation of zeta test results. Digital Scholarship in the Humanities, 34(2): 401–18). Drawing a bisector line is a common technique for interpreting a Zeta graph and, in practice, it produces the same attributions as the ones that Hoover’s less mathematical approach produces. Rizvi argued that this is an unsound technique, an argument that Hoover has now rejected. This paper elaborates Rizvi’s arguments and presents the results of new experiments to show that both of Hoover’s claims are incorrect and should not be accepted.
Insulator Hydrophobic Image Edge Detection Algorithm considering Deconvolution and Deblurring Algorithm

In this paper, the Gram matrix is used to calculate the correlation of the filter response sets under different scale kernels learned by each layer of the network in the deconvolution, and the loss between the corresponding feature response correlations in the multilayer network is calculated. Linear summation is used to obtain a stable, multiscale image model representation. This paper extracts the contours of the salient areas of the image and adjusts the parameters of the deconvolution network to learn the salient area patterns of the image. At the same time, for the image to be generated, a shape template is used to limit the range of the area to be generated in order to obtain a shape image with similar patterns. When the spatial relative relationship characteristics of the image constituent objects are obvious, we appropriately add high-level semantic feature activation values for reinforcement. This paper solves the estimation of the unknown blur kernel by using image prior knowledge, filtering and gradient domain algorithms and other different technologies to obtain image jitter or scene movement information and estimate the size, location, and density of the blur kernel. This paper studies a relatively robust deconvolution model, which is insensitive to random noise, has stable effects, and can overcome the water ripple effect caused by the usual convolution process. This paper attempts to study the fuzzy model with variable space. The usual blur is a spatial invariant model; that is, a single kernel is used to describe the motion of all pixels on the image. By selecting different characteristic parameters, this paper conducts experimental research on some existing hydrophobic indicator function methods and calculates the relationship between characteristic parameters and hydrophobicity when different hydrophobic indicator functions are adopted. One characteristic of the hydrophobic image of composite insulators is low contrast. The traditional method of converting color images to grayscale images cannot improve the image contrast. This paper analyzes the hydrophobic image of the composite insulator, and the extracted B channel component image of the hydrophobic image improves the contrast of the image and facilitates the subsequent segmentation of water traces and background. In this paper, the water repellent image's watermark area is counted, and connected-domain wave processing is used to limit the area of water droplets retained, thereby improving the efficiency of filtering water droplets without having a big impact on the image as a whole. The problem of uneven illumination is an unavoidable problem in the field of image processing, and the resulting reflection problem brings difficulties to image processing. This article regards the reflective area of the watermark as a “hole” and uses the idea of “hole filling” to eliminate the reflective point, which weakens the reflection problem to a certain extent.
The Perception of Students in Using ICT in ESP Course at the Faculty of Mathematics and Science of Universitas Negeri Padang

Information Communication and Technology (ICT) is a form of technology used for creating, displaying, storing, manipulating, and exchanging information to support teaching and learning activities.Since 2017, Universitas Negeri Padang using ICT as a teaching and learning media to improve the quality of teaching and learning activity.Unfortunately, studies about evaluation of user acceptance on using ICT in teaching and learning activity, very specifically ESP course, are still under-researched.Related to this issue, this present research has aim to describe the using ICT in ESP course at Faculty of Mathematics and Science of Universitas Negeri Padang, based on the perceptions of students.This is a qualitative research that describe students' perceptions on using ICT in ESP Course.The subject of this research were the students of Faculty of Mathematics and Science that taken the ESP course in 2020/2021 academic year.The data were collected through a closed-ended questionnaire based on the Technology Acceptance Model (TAM).The findings reveal that a large majority of students have positive perceptions on using ICT in ESP courses as well as for their future careers.
The Importance of Integrating Career Planning Education into High School Curriculum

Adolescents are faced with a variety of life and career options that increasingly demand knowledge and skills.In recent years, educators have placed great importance on the principle that high school should equip students not only with academic knowledge but also with career-related competencies.Hence, career planning education, which typically includes the topics of self-exploration, career exploration, and career development, plays a vital role in supporting young people to manage their experiences related to career and preparing them for the future.This study explored the impacts of career planning education on high school students, the provision of career education in high schools in western countries and China, and provided suggestions for the future delivery of career education curriculum in Chinese high schools.Research has found that students who lack career-planning knowledge and skills may be unable to make wise choices in accordance with their interests and strengths about studies or careers.Some western countries have more advanced and mature practices in career education provision, while such curriculum in Chinese high schools has yet to be comprehensively developed.This study suggests that students should be provided with timely career guidance in high schools in China, which would help them to think more critically about their future goals and possibilities, and become planned about college and career.Therefore, for the delivery of career planning education in schools to be both efficient and effective, policymakers, professional career educators, school administrators, and teachers should work together to promote the development of such curriculum in high schools.
THE DESIGN AND DEVELOPMENT OF DATA HIDING USING DEEP LEARNING

Data hiding is one of the most prominent and important topics. The importance of protecting sensitive data has always been recognized from time immemorial. Steganography is the craft of secured or shrouded composing; the term itself goes back to the fifteenth century, when messages were physically covered up. In present day steganography, the objective is to clandestinely impart an advanced message. The steganographic procedure puts a shrouded message in a vehicle medium, called the transporter. The bearer might be openly noticeable. For included security, the shrouded message can likewise be encoded, accordingly expanding the apparent haphazardness and diminishing the probability of substance disclosure regardless of whether the presence of the message identified. Great acquaintances with steganography and steganalysis. Index Terms -Information Hiding, Deep Learning, Natural language processing (NLP), Convolutional Neural Networks (CNN)
Students' Insights from Interactive Visualizations Arranged Multimodally in Knowledge Visualizations

In this study, a visual analytics application is put into practice in Swedish secondary school social science classrooms. The application offers support to analyse vast amounts of data through interactive data visualizations. Previous studies have demonstrated that the visual interactive interface challenges the traditional practice in school, where students usually demonstrate their knowledge by means of written texts. Thus, this study examines what happens if students work with more malleable, adaptable, or fluid modes when attempting to express their conclusions from work with interactive data visualizations. It aims to detect patterns in how knowledge visualizations are produced and arranged multimodally. Inspired by design-based research, the study conducted two classroom interventions followed by video captures. It employed a socio-material semiotic approach, which enables the study of interactions between both social and material actors. Three patterns emerged when students’ insights were translated into knowledge visualizations – exploring, gathering, and inserting. It became obvious how different actors taking part of such a digital multimodal writing activity affect and change every actor/everyone/everything, which in turn transfers, relocalizes, reformulates, and re-presents the communicated message. Knowing how knowledge visualizations are produced might strengthen students’ visual abilities when transforming insights multimodally.
DESIGN AND BUILD INVENTORY MANAGEMENT INFORMATION SYSTEM USING THE SCRUM METHOD

PT Telkom Akses (PTTA) is a subsidiary of PT Telekomunikasi Indonesia, Tbk (Telkom) which share owned entirely by Telkom. PT Telkom Akses is engaged in the business of providing construction services and network infrastructure management. Data collection manually can result in slow data management and will have an impact on the workflow of PT. Telkom Akses 3 Ilir Palembang. There will be a lot of damaged or duplicated data and finding data will be difficult. Therefore, it is necessary to develop a system that can collect data on incoming and outgoing goods, namely a Web-based Inventory System. The development of this inventory system uses the CodeIgniter3 Framework and Scrum methodology. Scrum is one of the methods that uses the Agile principal, which refers to team collaboration, product incremental, and iterative processes to achieve goals. The results of the evaluation of system testing using the black-box testing method show that the developed system can run well and as expected. Hopefully with the present of this system, it can help PT Telkom Akses 3 Ilir Palembang in performing incoming and outgoing goods data collection.&#x0D; &#x0D; Keyword: Inventroy System, Web, Codeigniter 3, Scrum, BlackBox Testing
A Systematic Multichimera Transform for Color Image Representation

Mathematically representing an image with only a small number of coefficients has been attempted a few times. These attempts represent initial steps to achieve this goal and showed promising results by either working on a small image block size or utilizing a codebook built using a complex operation. The use of the codebook complicated the entire transformation process. In this work, we overcome these difficulties by developing a new scheme called systematic multichimera transform (SMCT). This transform employs simple mathematical functions called fractal half functions to independently build a codebook of image contents and size. These functions satisfy the symmetry under fractal form while breaking the orthogonality condition. The transform can deal with different image block sizes such as 8×8, 16×16, and 32×32. The encoding process is conducted by repetitively finding the similarity between image blocks and codebook blocks to achieve data reduction and preserve important information. The coefficients of the matching process are then employed in the decoding process to reconstruct the image. SMCT produced the highest structural similarity index (SSIM) and a competitive Peak Signal to Noise Ratio (PSNR) over the standard discrete wavelet transform (DWT) and discrete cosine transform (DCT) without degrading important image content.
A Deep Reinforcement Learning Scheduler with Back-filling for High Performance Computing

It is becoming widely accepted that model-based job scheduling strategies are becoming inadequate due to an ever increasing complexity of system infrastructure, highly variable workloads and user requirements. Research into reinforcement learning-based approaches for job scheduling is a compelling and rapidly advancing direction. In this work we propose a novel deep reinforcement learning approach to the classic job scheduling problem. Our approach uses a bounded observation space, allows the learning agent to postpone scheduling to later scheduling cycles and we show experiments that give insights into its performance with respect maximizing utilization and minimizing wait times. Our results show competitive outcomes that indicate our approach is a favourable framework for job scheduling in more complex systems.
Role of Stock Market Performance and Exchange Rate Volatility in the Inflow of Foreign Direct Investment: An Evidence from Pakistan

The purpose of this study was to evaluate the role of macroeconomic variables i.e., stock market performance and exchange rate fluctuations on Foreign Direct Investment (FDI) for Pakistan. The required data was collected for the period of 1996 to 2020 from the World Bank and State Bank of Pakistan. In data analysis, the unit-root tests were performed to decide whether a time-series is stationary or not. An ARDL is constructed to achieve the results of this study. The results of this study provided the evidences that stock market performance and trade openness have positively and significantly linked with FDI. Whereas real GDP growth rate and exchange rates have negative effects on FDI. It is recommended that the trade policies should be devised in such a manner that these policies should promote exports. Furthermore, policies that ensure stable stock market performance could be an important factor for bringing FDI to Pakistan. However, FDI seems to be ineffective from the changes in the rate of inflation.
Provably Secure Certificateless Proxy Signature Scheme in the Standard Model

&lt;p&gt;Proxy signature frees the original signer from the heavy signature work. Many certificateless proxy signature (CLPS) schemes have been proposed in the last ten years. The security proofs of most known schemes are given in the random oracle model (ROM). There are only two CLPS schemes with provably security in the standard model (SM). However, in which the size of the system parameter increase linearly with the size of the user’s identity information. That increase the storage burden of the key generation center. In this paper, a new CLPS scheme is constructed and the security proofs are showed in SM. The size of system parameters and the master key are constant in the scheme. Requiring only three pairing operations, the new scheme is more efficient and suitable for mobile computing.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
A Survey of Applications using Blockchain Technology

In recent years, the performance of blockchain technology in various applications has been broadly debated in Research and Business. Recently, a debated number of applications have become successful with the possibility of implementing blockchain technology in various fields. In this paper, we analyze and record a survey of some important applications that use blockchain technology like E-Voting, Blind Signature, Supply chain, Land registration, Smart Parking systems, etc. Most of the recent research works in applying blockchain have been presented, evaluated, and reported thoroughly. This survey paper stands as helpful guidance for future research works.
A mutual one-time password for online application

The mobile and web application have become more popular due to easy access and be convenient to everybody, it is essential to look at their security issues from different aspects. User authentication is one of these issues that plays an important role for most applications. If a system authenticates a user, it means that person can access what are allowed in the system. One-time password is a kind of authentication that helps to increase the security through identification. Common methods in this area use extra devices such as smart card, token, and cell phone. However, these devices enforce users to carry hardware, to pay money, and to maintain. In this article, we propose a mutual one-time password which employs a formula to generate password for user, and every time user must use previous password and formula to compute new password. The communication line during authentication phase is supposed insecure; and a mutual authentication helps to increase the level of security. Security analysis shows how this method is secure; and comparison with some models shows its positive points.
Performance Impact of Minority Class Reweighting on XGBoost-based Anomaly Detection

This paper explores the impact of reweighting the minority class of an imbalanced fraud dataset on the performance of an XGBoost binary classifier.Classifier performance is measured here in terms of true positive rate, false positive rate, precision, accuracy, AUC-ROC and AUC-PR.Our results suggest that reweighting the minority class has significant impact on these four key performance metrics when the classification threshold is held fixed and the model bias is not corrected.However, this impact becomes insignificant when (1) classification threshold is held fixed and the bias is corrected, or (2) when the target number of predicted positives is held fixed.Since fraud detection often prescribes a target number of cases for special treatment, these findings suggest that reweighting a dataset offers performance advantage only under very specific conditions for XGBoost-based classifiers.These conclusions can also generalize to problems where certain resampling techniques are used instead of reweighting since the two approaches tend to converge for sufficiently large datasets.
The Sharing of Similar Knowledge on Monte Carlo Algorithm applies to Cryptocurrency Trading Problem

Monte Carlo Algorithm is one of the various algorithms of Reinforcement Learning. It is used with problems that have finite states because of the memory problem. It must remember all the experiences to learn and make a decision. If the agent faces an unseen state, The Agent cannot use the experience for the decision to take the action. With these problems, we proposed the algorithm named The Sharing of Similar Knowledge on Monte Carlo Algorithm (SSKMC) to help Monte Carlo conducted with infinite states and leverage the old experience to decide the action when the agent faces a new experience (unseen state). In this paper, we tested the proposed algorithm with the Cryptocurrency Trading problem (Bitcoin) and compared the testing result of the proposed algorithm to Deep Reinforcement Learning (DRL). By the testing result of The Proposed algorithm makes net worth growth more than the DRL method by 1.55%.
A Spam Classification Method Based on Naive Bayes

Currently, spam will do everything possible to bypass or destroy the spam classifier. This paper proposes a naive Bayesian spam classification method, and designs Bernoulli naive Bayes algorithm and polynomial naive Bayes algorithm to classify English spam and Chinese spam respectively. Experiments show that the method proposed in this paper has a high precision rate and recall rate, and can classify spam simply, accurately and efficiently.
Security Attitude Prediction Model of Secret-Related Computer Information System Based on Distributed Parallel Computing Programming

In recent years, there has been an upward trend in the number of leaked secrets. Among them, secret-related computers or networks are connected to the Internet in violation of regulations, cross-use of mobile storage media, and poor security management of secret-related intranets, which are the main reasons for leaks. Therefore, it is of great significance to study the physical isolation and protection technology of classified information systems. Physical isolation is an important part of the protection of classified information systems, which cuts off the possibility of unauthorized outflow of information from the network environment. To achieve the physical isolation of the network environment and build a safe and reliable network, it is necessary to continuously improve the level of network construction and strengthen network management capabilities. At present, the realization of physical isolation technology mainly relies on security products such as firewall, intrusion detection, illegal outreach, host monitoring, and auditing. This study analyzes network security systems such as intrusion detection, network scanning, and firewall. Establishing a model based on network security vulnerabilities and making up for network security hidden dangers caused by holes are generally a passive security system. In a network, the leader of network behavior—human behavior—needs to be constrained according to the requirements of the security management system and monitoring. Accordingly, this study proposes a security monitoring system for computer information network involving classified computer. The system can analyze, monitor, manage, and process the network behavior of the terminal computer host in the local area network, to achieve the purpose of reducing security risks in the network system. Based on the evaluation value sequence, the initial prediction value sequence is obtained by sliding adaptive triple exponential smoothing method. The time-varying weighted Markov chain is used for error prediction, the initial prediction value is corrected, and the accuracy of security situation prediction is improved. According to the security protection requirements of secret-related information systems, a complete, safe, reliable, and controllable security protection system for secret-related information systems is constructed, and the existing security risks and loopholes in secret-related information systems are eliminated to the greatest extent possible. This enables the confidentiality, integrity, and availability of confidential data and information in the computer information system to be reliably protected.