Reviewerly/exHarmony huggingface dataset:
The Comparative Analysis of Motivation and Student’s Learning Outcomes by Using The Learning Media of Web E-Learning and Schoology in VHS

This study aims to: (1) find out the comparison of student learning outcomes between the use of learning media of web e-learning and schoology in Web Programming and Mobile Device subjects (WPMD), and (2) find out the increase in student completeness by using the learning media of web e-learning and schoology on WPMD subjects. The research method used is quantitative with quasi-experimental research involving two groups, namely the control and experimental groups. While the research design used was pre-test post-test control group design. The subjects of this study were students of class XII RPL at SMK Negeri 1 Sukorejo. Data collection techniques carried out by providing research instruments and test instruments. While the data analysis technique uses normality test, homogeneity test, and independent samples t-test. The results of this study indicate that: (1) Significant results of 0.000 are smaller than 0.05, which means that learning outcomes in WPMD subjects have significant differences between the control and experimental groups. (2) The results of the study note that the control group experienced an increase in completeness of 11.43% while the experimental group amounted to 94.12%. Increased completeness in the experimental group was higher when compared to the control group.
Estimating Water Demand and Plant Evapotranspiration Using the Cropwat App

Water management is very important for plants and good water management can increase the productivity of rice, corn and soybeans, hereinafter referred to as PAJALE. This paper aims to estimate the water requirements of PAJALE plants using the cropwatt model. The results of the analysis show that each plant has different water requirements in each growth phase which was analyzed using cropwatt application throughout the year with medium textured soil types. Rice, corn and soybeans are the main food commodities in Indonesia. Corn and soybeans are generally planted after rice in irrigated and rainfed rice fields, making them susceptible to drought. Therefore, information using cropwatt applications, especially rainfall, temperature, Air humidity and solar radiation are very important in determining the time of planting and the right water requirements for plants. The purpose of the study was to determine the planting time and water requirements of rice, corn and soybeans, based on the results of cropwatt 8.0 analysis, and to compile a time map of Indonesian food crops so that the risk of production failure due to drought can be avoided.
Telling the Technical Services Story: Communicating Value

"Telling the Technical Services Story: Communicating Value." Cataloging & Classification Quarterly, 60(3-4), pp. 332–333
Designing Trustworthy User Interfaces for the Voluntary Carbon Market: A Randomized Online Experiment

The voluntary carbon market is an important building block in the fight against climate change. However, it is not trivial for consumers to verify whether carbon offset projects deliver what they promise. While technical solutions for measuring their impact are emerging, there is a lack of understanding of how to translate carbon offset data into trustworthy interface designs. With interaction between users and offset projects mainly happening online, it is critical to meet this design challenge. To this end, we designed and evaluated interfaces with varying trust cues for carbon offset projects in a randomized online experiment (n=244). Our results show that content design, particularly financial and forest-related quantitative data presented at the right detail level, increases the perceived trustworthiness, while images have no significant effect. We contribute the first specific guidance for interface designers for carbon offsets and discuss implications for interaction design.
Analysis of issues in the initial operation for the successful implementation of the autonomous police system - Based on the survey of the local police committees -

With the introduction of the autonomous police system by the Moon Jae-in government, local governments are expected to provide local-specific public security services that reflect the needs of residents and comprehensive public security services through linking local administration and public security administration. The purpose of this study was to analyze the issues of the initial operation of the autonomous police system and to suggest improvement plans for the local police committee, which is a key organization for the successful implementation of the autonomous police system. To this end, a survey was conducted from July 1st to July 15th, 2021 on the organization and operation of the local police committee, personnel rights, budgetary rights, scope and linkage of the affairs targeting 18 local police committees.&#x0D; Based on the survey results, policy recommendations for the successful implementation of the autonomous police system were presented. First, it may be considered to allocate the recommended number of committee members to each recommendation institution in order to secure diversity of the local police committees. Second, the National Police Agency should cooperatively share personnel and budget information with the local police committees. Third, the independent personnel rights management system within the local police committee should be prospectively reviewed. Fourth, it is necessary to come up with various financial support measures that allow local governments to independently operate them. Fifth, it is necessary to continuously discuss improvement plans for local police affairs by reflecting the opinions and experiences of national police officers who perform local police affairs in the field. Sixth, for the personnel and budgetary authority of the local police committee to be effectively exercised, the facilities･manpower･budget of the national police must be completely transferred to the local governments.
Collusion-Resistant Worker Set Selection for Transparent and Verifiable Voting

Collusion occurs when multiple malicious participants of a distributed protocol work together to sabotage or spy on honest participants. decentralized protocols often rely on a subset of participants called workers for critical operations. Collusion between workers can be particularly harmful to the security of the protocol. We propose two protocols that select a subset of workers from the set of participants such that the probability of the workers colluding together is minimized. Our first solution is a decentralized protocol that randomly selects workers in a verifiable manner without any trusted entities. The second solution is an algorithm that uses a social graph of participants and community detection to select workers that are socially distant in order to reduce the probability of collusion. We present our solutions in the context of a decentralized voting protocol proposed by Schiedermeier et al. (A transparent referendum protocol with immutable proceedings and verifiable outcome for trustless networks, Springer, Cham, 2019) that guarantees transparency and verifiability. Enabling collusion-resistance in order to ensure democratic voting is clearly of paramount importance thus the voting protocol provides a suitable use case for our solutions.
HTTPS Event-Flow Correlation: Improving Situational Awareness in Encrypted Web Traffic

Achieving situational awareness is a challenging process in current HTTPS-dominant web traffic. In this paper, we propose a new approach to encrypted web traffic monitoring. First, we design a method for correlating host-based and network monitoring data based on their common features and a correlation time-window. Then we analyze the correlation results in detail to identify configurations of web servers and monitoring infrastructure that negatively affect the correlation. We describe these properties and possible data preprocessing techniques to minimize their impact on correlation performance. Furthermore, to test the correlation method’s behavior in different web server setups and for recent encryption protocols, we modify it by adapting the correlation features to TLS 1.3 and QUIC. Finally, we evaluate the correlation method on a dataset collected from a campus network. The results show that while the correlation requires monitoring of custom event and flow features, it remains feasible even when using encryption protocols designed for the near future.
A Systematic Review on Cybersecurity &amp; Data Protection

This paper identifies the understanding of Cybersecurity. This paper analyses the awareness, presence and challenges of Cybersecurity and Data protection. This paper also identifies what people think about Cybersecurity as well as measures we can use to strengthen Cybersecurity.
Defending wi-fi network discovery from time correlation tracking

To prevent tracking a Wi-Fi device based on its MAC address, several operating systems have adopted MAC address randomization to conceal its factory-assigned address. This feature benefits users when their devices scan for networks, but a flaw arises when timing between transmissions stays consistent despite MAC address randomization in use. We present a defense mechanism, implemented with the Netlink library, against a time correlation attack for probe request packets on Wi-Fi devices. We show how adding random jitter to probe request transmissions renders a timing correlation attack infeasible to track devices during network discovery.
Pengembangan Media Pembelajaran Multimedia Interaktif Berbasis Video Tutorial Editing Materi Media Audiovisual

ADDIE model which consists of 5 stages, namely analysis (pre-test), design (making plans for implementing services and media scripts), development (making media, after the media is completed, then the researcher validates with three experts: material experts, media experts and linguists), implementation (small group test and field test), evaluation (post-test). Based on the results of the comments and suggestions given by the three experts, the results of the media are valid and worth testing. The results of the field test questionnaire, obtained a percentage of questionnaire scores of 87.4%. This percentage is in the range of 80% -100% which is included in the category of very practical whereas, the results of student guidance tests obtained results from all three aspects in the pre-test 42.6% and 66.4% post-test with an N-gain of 0.7 including in category (g) ≥0.70, which is high, it shows that interactive multimedia learning media based on video tutorials editing audiovisual media material is effective in IT media courses and guidance and innovation innovation at Sriwijaya University.
Research of Computer Network Security and Protection Strategy

With the broad notoriety of computer organize applications, its security is additionally gotten a tall degree of attention. Variables influencing the security of organize is complex, for to do a great job of network security could be an orderly work, has the tall challenge. For security and unwavering quality issues of computer arrange framework, this paper combined with practical work involvement, from the danger of arranging security, security innovation, network some Proposals and measures for the system plan rule, in arrange to create the masses of clients in computer systems to improve security mindfulness and master certain organize security innovation.
Uniform generation of infinite traces

Abstract We introduce an algorithm for the uniform generation of infinite traces, i.e. , infinite words up to commutation of some letters. The algorithm outputs on-the-fly approximations of a theoretical infinite trace, the latter being distributed according to the exact uniform probability measure. The average size of the approximation grows linearly with the time of execution of the algorithm, provided that some–costly–precomputations have been done.
Data utility and data governance in cryptocurrencies

This chapter discusses three policy goals related to information generated by the cryptocurrency network: personal autonomy, development of the digital economy, and the prevention of crime. It explains how current data protection law and privacy rights can be assessed against these goals in the context of cryptocurrency. Analysis shows how unstable coins on the public chain, stable coins on the private chain, and state-backed currency on the private chain can benefit but also create risks to the three policy goals. It also assesses whether current data protection law and privacy law are able to address and mitigate any risks. There is a political dimension in cryptocurrency at the domestic level in terms of how citizens can participate in a more democratised space. At the international level, the data location requirement has also posted political challenges due to national security laws. While regulators focus on the economics of cryptocurrency, it is international politics that will set the standards, deciding how policy goals, such as these three, are to be fulfilled, what information amounts to public good to be shared by whom and with whom, and how data protection and privacy law will set the new international or regional standards.
19. Breastgan: Artificial Intelligence-enabled Breast Augmentation Simulation

Purpose: Managing patient expectations is important to ensuring patient satisfaction in aesthetic medicine. To this end, computer technology developed to photograph, digitize, and manipulate three-dimensional (3D) objects has been applied to the female breast. However, the systems remain complex, physically cumbersome, and extremely expensive. The authors of the current study wish to introduce the plastic surgery community to BreastGAN (Breast Generative Adversarial Network), a portable, artificial intelligence-equipped tool trained on real clinical images to simulate breast augmentation outcomes. Methods: Charts of all patients who underwent bilateral breast augmentation performed by the senior author were retrieved and analyzed. Frontal before and after images were collected from each patient’s chart, cropped in a standardized fashion, and used to train a neural network designed to manipulate before images to simulate a surgical result. AI-generated frontal after images were then compared to the real surgical results. Results: Standardizing the evaluation of surgical results is a timeless challenge which persists in the context of AI-synthesized after images. In this study, AI-generated images were comparable to real surgical results. Conclusion: This study features a portable, cost-effective neural network trained on real clinical images and designed to simulate surgical results following bilateral breast augmentation. Tools trained on a larger dataset of standardized surgical image pairs will be the subject of future studies.
Context-Driven Method in Realization of Optimized Human-Robot Interaction

Perceptual uncertainty and environmental volatility are among the most enduring challenges in robotic research today. Contemporary robotic systems are usually designed to work in specific and controlled domains where a total number of variables is defined. Traditional solutions therefore often result in over-constrained interaction spaces or rigid system architectures where any unexpected change can result in system failure. The focus of this work is set on achieving a constant adaptation of the system to changes through interaction. A computational mechanism based on the entropy reduction method is integrated along with the three-component control model. This model is seen as a context-to-data interpreter used to provide context-aware reasoning to the technical system. The mechanism is using a decrease in interaction uncertainties when proofs are provided to the system. In this way, the robot can choose the right interaction strategy that resolves reasoning ambiguities most efficiently
UF-VTON: Toward User-Friendly Virtual Try-On Network

Image-based virtual try-on aims to transfer a clothes onto a person while preserving both person's and cloth's attributes. However, the existing methods to realize this task require a target clothes, which cannot be obtained in most cases. To address this issue, we propose a novel user-friendly virtual try-on network (UF-VTON), which only requires a person image and an image of another person wearing a target clothes to generate a result of the person wearing the target clothes. Specifically, we adopt a knowledge distillation scheme to construct a new triple dataset for supervised learning, propose a new three-step pipeline (coarse synthesis, clothing alignment, and refinement synthesis) for try-on task, and utilize an end-to-end training strategy to further refine the results. In particular, we design a new synthesis network that includes both CNN blocks and swin-transformer blocks to capture global and local information and generate highly-realistic try-on images. Qualitative and quantitative experiments show that our method achieves the state-of-the-art virtual try-on performance.
Alienability Splits in Swedish from a Diachronic Perspective

The paper discusses possessive expressions with body-part nouns in Swedish (1300–1550) with particular focus on the so-called alienability splits, i.e., separate patterns of marking possession for alienable and inalienable entities. The key problem to be addressed is to what extent such splits can be found in Swedish and the aim of the study is to establish when they arise and what motivates their formation. The inalienable possessive constructions with body-part referents in Modern Swedish include the so-called implicit possession, where only the definite article is used and the inalienable prepositional construction of the type ‘the head on him’. The analyzed material consists of Old Swedish prosaic texts written between 1300 and 1550. The corpus includes eight texts and amounts to ca. 250,000 words. The material is studied both quantitatively and qualitatively; collostructional analysis is used for the statistical overview of the data. The results of the collostructional analysis confirm that the implicit possessive construction first appears in Period II (1350–1450) and becomes grammaticalized in the late 1400s. The inalienable prepositional construction is not found in the material studied and thus must be of later origin. The results suggest further that the inalienable possessive constructions do not arise as a result of the speaker’s wish to disambiguate the notion of inalienability but are a by-product of other diachronic processes, such as the grammaticalization of the definite article in the indirect anaphoric context.
Probabilistic Linear Solvers: Algorithmic Scaffold

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Delineation of geochemical anomalies for mineral exploration using combining U-statistic method and fractal technique: U-N and U-A models

In this study, by using the algorithm of the U-statistic and fractal methods and combining them with each other, a new combined method as U values fractal model (U-N and U-A) is introduced. Then, the proposed method is employed to determine the boundaries of background and anomalous populations. Results show that in U-N and U-A fractal models, the first fracture boundary is much clearer and more accurate than previous fractal models (C-N and C-A) in the same condition. In U-N model, due to the nature of the U method algorithm, there is a discontinuity as exact threshold between background and anomaly that in U-A model, this does not exist due to the homogenization of U values. In this method, the exact threshold between background and anomaly is determined by U-statistic method and by its combination with the fractal method, in each population, sub-populations are identified more accurately and simply than concentration fractal model.
Regulating personal data usage in COVID-19 control conditions

Concern has been widely expressed about the potential for COVID-19 control technologies and resultant data sharing negatively impacting on civil rights, invading personal privacy, undermining citizen dignity through expansive data matching and ultimately providing opportunities for data use well beyond the brief of virus mitigation. This chapter offers suggestions regarding effective and inclusive regulatory responses when faced with extended surveillance, tracking/tracing, public/private provider data sharing and any breakdown in personal data firewalls, or otherwise conventional aggregated data deviations and distortion. In doing so, the chapter explores personal data usage in the context of COVID-19 as a regulatory enterprise. It addresses four fundamental features influencing the ultimate regulatory decision and direction: why, when, where and what, and presents a regulatory strategy to address the challenges of data usage in COVID-19 control conditions. It is proposed that this model is based on three facets. Firstly, the creation of an independent agency that researches potential personal data challenges transitioning out of the control situations. Secondly, Enforced Self-regulation Units tasked with the responsible operation and eventual decommissioning of surveillance technologies, and their data repositories, on a technology-specific focus. Thirdly, Civil Society Empowerment Initiatives that act as a counterbalance to the negative impact strenuous data protection regulation may have on current and future pandemic control strategies.
SQL Injection Attacks on Indian Websites

Today, the Indian economy is the fastest growing large economy, and it is mainly based on various web applications used in the different private and public sectors of the country. Web applications are the essential component of end-to-end digital communication. During the current COVID-19 pandemic, every human being depends on web applications to complete numerous day-to-day transactions, such as financial, banking, and official. Nowadays, the security of database-driven web applications is the biggest concern because of widespread ignorance about it. This chapter aims to point out the structured query language injection (SQLI) flaws present in several secure Indian websites and to make their system administrator aware of the consequences of such a dangerous vulnerability. We intimate these Indian organizations regarding such a dangerous vulnerability. Moreover, we suggest preventive guidelines that will help these organizations avoid such crucial web vulnerability through this work.
Comparison of Data Classification Results for Leap Motion Recovery Gestures

Static and dynamic gestures are frequently used in activities supporting learning, recovery healthcare, engineering, and 3D games to increase the interactivity between man and machine. The gestures are detected via hardware devices and data is processed using different software methods. This paper presents the manner of detection and interpretation of two gestures, a hand rotation gesture and a palm closing and opening gesture, using the Leap Motion device. These two dynamic gestures are very often used in hand recovery exercises. For comparing the two gestures we use data classification methods, Support Vector Machine (SVM) and Multilayer Perceptron (MLP). The data for the gesture classification were 80% training data and 20% testing data. The metrics for comparison are precision, recall, F1-score, and the total number of testing cases (support). The SVM classifier gives an accuracy of 99.4% and the MLP classifier a 96.2%. We built two confusion matrices for better visualizing the results.