Reviewerly/exHarmony huggingface dataset:
SSCalc: A Calculus for Solidity Smart Contracts

Smart contracts are programs stored on the blockchain, often developed in a high-level programming language, the most popular of which is Solidity. Smart contracts are used to automate financial transactions and thus bugs can lead to large financial losses. With this paper, we address this problem by describing a verification environment for Solidity in Isabelle/HOL. To this end, we first describe a calculus to reason about Solidity smart contracts. The calculus is formalized in Isabelle/HOL and its soundness is mechanically verified. Then, we describe a Verification Condition Generator to automate the use of the calculus. Our approach can be used to verify the functional correctness of Solidity smart contracts. To demonstrate this, we use it to verify a simple token implemented in Solidity. Our results show that the framework has the potential to significantly reduce the verification effort compared to verifying directly from the semantics.
Geophysical indicators of rare-metal ore content of Akmai-Katpar ore zone (Central Kazakhstan)

Purpose. Identification of geophysical criteria to determine ore content indicators within the territory relying upon systematization of both geological and geophysical materials. Methodology. The research involved innovative techniques used in the field of geology, i.e. GIS technology, and such theoretical scientific approaches as analysis and synthesis of petrophysical data, and data of geophysical anomalies in the context of the analyzed ore zone. Findings. Petrophysical characteristics of Akmai-Katpar ore zone rocks have been generalized and systematized. Petrophysical model of the ore zone has been developed; changes in petrophysical rock characteristics have been defined in terms of Silurian, Devonian, Carboniferous, and Permian systems. The obtained parameters of the petrophysical model are integrated with the identified geophysical anomalies. Geophysical indicators of ore content of the rare-metal ore zone have been determined. Cartographic documents have been specified which made it possible to perform layer-by-layer mapping of Akmai-Katpar ore zone. Originality. For the first time, the systematized geological and petrophysical materials have been applied to build the petrophysical model of Akmai-Katpar ore zone and improve geophysical forecasting criteria. Practical value. It consists in the use of geophysical forecasting criteria while identifying prospective areas where rare metals occur.
Virtualization Basics

This book explains the basics of virtualization and will help you create your own container frameworks like Docker, but a slimmed-down version. Before we get into that process, you need to understand how the Linux kernel supports virtualization and how the evolution of the Linux kernel and CPUs has helped advance virtual machines in terms of performance, which in turn led to the creation of containerization technologies.
Bridging the adoption gap for cryptocurrencies: understanding the affordances that impact approach–avoidance behavior for potential users and continuation usage for actual users

Purpose With the rise of cryptocurrency and its influence on the financial industry, this paper aims to explore cryptocurrency affordances that lead to approach–avoidance behavioral intentions for non-users (potential) and the intention to continue use for users (actual), drawing upon affordance theory and chasm theory. Design/methodology/approach The authors collected data from 480 potential and actual users in Germany and used maximum likelihood structural equation modeling (ML-SEM) to analyze it. In particular, the data consisted of 301 cryptocurrency users in Germany\ the authors used ML-SEM to test the post-adoption model. Additionally, logistic regression was utilized to determine the dominant actual usage method (store of value or medium of exchange) for various cryptocurrency coins. Findings According to the study's results, the perceived value benefits have a positive impact on the behavioral intention of potential users to adopt cryptocurrency, and they influence the intention of actual users to continue using it. However, both perceived volatility and financial risk tolerance are the most crucial factors hindering cryptocurrency adoption, whether in the pre-adoption or the post-adoption stage. Originality/value This is the first study to reveal cryptocurrency affordances and examine their effect on behavioral intentions toward cryptocurrency adoption based on the differences between non-users (potential) and users (actual). Furthermore, the authors explore how cryptocurrency holders perceive and invest in different coins (e.g. NFTs), which sheds light on factors such as financial risk tolerance that affect their decision making.
International Activities on the Digital Platform with Artificial Intelligence in Virtual Space

Digital high-tech platforms provide comprehensive solutions for user interaction on a wide range of issues from various areas of activity. The use of digital high-tech platforms is open and controlled by users. They are beginning to have a major impact on global governance in many areas. Global technology platforms can serve regional integration structures and bring together regional and national development institutions. Building a global architecture of technology platforms will make international activity more stable and less crisis-prone. To do this, technology platforms at different levels of global governance must be compatible and interoperable under common rules of interstate agreements. Technological platforms for international action and management will allow the economic, environmental, climate and many other problems to be quickly solved and controlled by the world community
A SURVEY OF FACIAL GENDER CLASSIFICATION

: Gender is the most critical demographic attribute of human beings. Gender classification from facial images is widely used in computer vision for surveillance, a straightforward task for humans, and a challenging task for machines. This paper provides a study of facial gender classification in the field of computer vision. We highlight the challenges faced during the image capturing process due to factors such as illumination, angle, occlusion, and expressions. We also review various feature extraction approaches used by previous researchers to perform the facial gender classification task. This paper also compares the performances of previous methods on various face datasets to perform gender classification. We observed from the previous studies that good performance had been achieved for a dataset of facial images taken in a controlled environment. However, much more work needs to be done to increase the accuracy and robustness of facial gender classification, especially in uncontrolled environments.
(UN) IDENTIFIED LEXEMES: A FIRST GLANCE AT PUNJABI MORPHOLOGICAL ANALYZER

The paper presents a small survey on Punjabi morphological analyzer and generator, which does not give any morphological response to lexemes of Malawi dialect of Punjabi. This analyzer works well with the standard variety only. However, it fails to provide an answer when the input is colloquial. The random choice of approximately, (42 words/lexemes, e.g. ਕਾਤੋਂ/ ‘why’, ਉਂਈ/ ‘thus’, ਭੁੰਨਹੋਣਾ/ ‘Unbearable’, ਥੁੰਨੀ/ ‘eating’, ਅੜੀ/ ‘stubborn’, ਭਨਾਲੀ/ ‘breaking’, ਮੰਨਲਾ/ ‘suppose’, ਖਿਜੀ/ ‘annoying’ etc.) is not trained either for the analyzer nor the generator. They are unidentified and unrecognized. In this regard, the schemes of SGMA (similar guidelines for morphological analyzer) or SMGMA (similar but modified guidelines for morphological analyzer) could adopt for booming the performance of Punjabi morphological analyzer and widening its scope in the future.
Experiment of Fuzzy Logic on Game System

Abstract: Applications of fuzzy logic in game creation have proven useful, especially when it comes to modelling the behavior of non-player characters (NPCs) in video games. NPC behavior in video games has historically been governed by strict rule-based systems or scripted sequences, which frequently led to restricted and predictable interactions. On the other hand, fuzzy logic adds a degree of flexibility and ambiguity to the decision-making processes of NPCs. By improving the naturalness, adaptability, and emotional resonance of NPC behavior, fuzzy logic may greatly enhance player experiences in games. It provides players with progressively more engaging and dynamic gaming experiences as it continues to be incorporated into game production, opening up new possibilities for interactive narrative, gaming, and immersive virtual worlds. Based on Utku Kose's article, "Developing a Fuzzy Logic Based Game System," I have investigated the use of fuzzy logic in gaming contexts for NPC decision-making in this study.
CYBERPRAGMATIC ANALYSIS OF DIGITAL HUMOR IN WHATSAPP STICKERS

With the growth of digital environment, social interaction between people, particularly university students, is also affected. Communication has become multimodal, meaning people not only send textual messages but also visuals such as videos, memes, stickers, or emojis. These multimodal communication forms are facilitated by digital communication platforms such as WhatsApp and Line. The use of stickers, specifically in WhatsApp, could suggest certain implicatures which are covered in humorous way. The present research aims to describe how the text and the image of WhatsApp stickers create humorous intention and to find out the implicit functions of digital humour of WhatsApp stickers in daily interaction. The data for this study were collected from university students’ communications in their WA, in which 20 students were requested to submit 5 samples of stickers used in actual interactions. As a result, 100 stickers were gathered as the data. The collected data were analysed qualitatively using the theories of digital humour and cyberpragmatic approach. Cyberpragmatic is basically the use of pragmatic concepts in analysing digital data. The results show that WhatsApp stickers were used by the students to convey the feeling of sadness, anger, tiredness, concern, and eagerness, which were represented by the text and image of the stickers. For example, when a student complains about the number of assignments, he sent a sticker showing an ads for headache, where the brand name was changed into “Oh tugas” (oh assignment). The interrelatedness between the text and the image in this sticker can convey the pragmatic implicature in humorous way. Thus, the findings of this study implied that stickers could become an effective way to communicate the intended message of the speakers. Stickers can also be an alternative way of communicating in digital environments beside using other forms of multimodal communication forms such as texts, GIF, meme, and emoji.
Perancangan Media Informasi Sentra Wisata Kuliner Wonorejo di Kota Surabaya Berbasis Website Menggunakan Metode Model View Controller

Surabaya possesses considerable potential for economic growth and the tourism industry. The Surabaya City Government is actively harnessing this potential, one of which involves establishing the Culinary Tourism Center to introduce a variety of traditional Surabaya cuisine. Specifically, the Surabaya City Government has initiated the creation of the Wonorejo Culinary Tourism Center (SWK) to showcase the iconic Surabaya dishes. In pursuit of this objective, an information platform, based on a website, has been developed using PHP programming technology and a MySQL database, employing the Model View Controller approach supported by the CodeIgniter framework. This website is intended to furnish information about the diverse Surabaya dishes accessible at the Wonorejo Culinary Tourism Center to the local community and visitors from beyond Surabaya. The research process encompasses various methodologies, including literature review, observation, interviews, and surveys. The research findings, which encompass both internal and external testing, indicate a success rate of 80.67%. These results signify that this information platform is a valuable tool for facilitating the acquisition of information about the legendary and other culinary offerings available at SWK Wonorejo, benefiting visitors from Surabaya and beyond.
An intelligent 5G interference identification scheme based on multi-source data fusion

5G has the advantages of large bandwidth, low delay, and wide connection, providing strong support for sensing acquisition and interactive control equipment access, data transmission, and online interaction in all aspects of the power grid. The open transmission environment of wireless communication leads to the interference of space electromagnetic waves. Timely detection and diagnosis of interference types and effective measures are the key to ensure the reliable operation of power 5G services. In this paper, an improved SNN neural network is designed to diagnose interference types in 5G bearer power applications. By integrating network topology, terminal position information and air port signal quality data collection, the diagnosis accuracy is effectively improved.
Arsenic Gas on Geothermal Area, Part III: Case Study and Correlation with Temperature

Summary Geothermal fluid carries the heavy metal elements to the surface, one of which is arsenic (As). Arsenic can be found naturally in the earth crust, exist on soil and mineral then can be enter on air, water, and surface environment. In the form of gases, Arsenic are associated with temperature of rock, a volatile element, and which only release on high temperature. In this research, we would to study about arsenic characteristic, arsenic mobilization, and the scheme how arsenic gases can be release on surface with several conditions. Based on references, in Chile, at volcanic area, says the arsenic gas content release with the area which have a high temperature and have several conditions on manifestation type. Then from twice validation on different geothermal area on Indonesia, we get same correlation with the references. Based on that, we assume the arsenic gas content on geothermal area is correlated with high temperature of rock, in a general we called it a heat source.
Komparasi Algoritme Random Forest dan XGBoosting dalam Klasifikasi Performa UMKM

The Covid-19 pandemic has greatly impacted the whole world, especially Indonesia. Various policies have been implemented starting from the implementation of lockdowns, restrictions on large-scale economic activities, and bans from leaving the region. The economic sector is a sector that has been affected quite a lot, one of which is Micro, Small, and Medium Enterprises (MSMEs). As a result of the Covid-19 pandemic, many MSMEs have suffered losses, so many investors have started to consider investing in MSMEs. Therefore, MSMEs need to know their business performance through potential analysis and financial reports to deal with the economic crisis during a pandemic. This study compares two algorithms namely Random Forest and XGBoosting in classifying the good or bad performance of MSME financial conditions. The performance of the developed algorithm will be improved using hyperparameter tuning to obtain the best parameter combination for each algorithm. In this study, the Random Forest algorithm has an accuracy value of 0.944 and an f1-score of 0.944, while the XGBoosting algorithm has an accuracy value of 0.944 and an f1-score of 0.950. Based on the model with the best evaluation metric, six important features are obtained: the 2021 profit and loss variable, 2020 cash, 2020 liabilities, 2020 capital, 2021 sales, and 2021 liabilities.
Implementation of Electronic Module Based Multiple Representation on Buffer Solution Materials to Improve Students’ Self-Regulated Learning and Cognitive Learning Outcomes

This research aims to determine the differences between self-regulated learning (SRL) and cognitive learning outcomes (CLO) of students who use multiple representation-based e-modules with students who use other teaching materials without being based on multiple representations on buffer solution materials and to determine the percentage of effective contribution. The subjects of this study were students of class XI MIPA at one of the high schools in Yogyakarta. The sampling technique carried out is cluster random sampling with a quasi-experiment method by posttest-only control group design. The instruments used are questionnaires on self-regulated learning and cognitive learning outcomes. The data analysis technique used in the field test results used Hotelling's Trace test and the results of effective contribution were obtained from the Partial Eta Squared value. The results showed that the significance value of 0.000 &lt; 0.05 so that H0 was rejected, which means that there are differences in SRL and CLO of students between students who use multiple representation-based e-modules and students who use other teaching materials without multiple representations based on buffer solution materials. The percentage of effective contribution of the use of e-modules to SRL by 16.5%, CLO by 11.8%, and SRL and CLO by 20.3%.
Integrative Monitoring System for Arabic Learning Plans in University-Affiliated Islamic Boarding Schools

Universities often face challenges in ensuring the quality of education, especially in the learning segment during the lecture process. Therefore, this study examines the phenomenon of quality and quantity, which is the basis for the quality of Arabic learning planning at Al-Falah As-Sunniyyah Jember University. The main objective of this study is to identify and explore effective strategies for ensuring the quality and quantity of education through an integrative monitoring system for Arabic language learning planning. Using a qualitative approach and literature studies as methods, the writer collected data by searching related literature. The data were analyzed using qualitative methods involving reading, synthesizing, and interpreting information found in the literature. Research findings confirm that the implementation of an integrative monitoring system appropriately has great potential to be used as the best model in planning Arabic language learning to improve the quality of learning significantly.
Analysis of the Effect of Local Magnitude on Peak Ground Acceleration and Seismic Vulnerability Index for Geothermal Field Monitoring Using Microearthquake

Intensive exploitation of geothermal injection and production can trigger microearthquakes which it signals come from dynamic fractures. The purpose of this study is to decide the impact of local magnitude on mitigation in geothermal fields based on soil acceleration and vulnerability of seismic in geothermal fields. This study uses seismic wave recording data and the geology of the research area. It is focable on calculating local magnitude, ground acceleration and seismic susceptibility index to earthquakes based on ground acceleration and seismic susceptibility index in geothermal fields. The maximum amplitude value represent that the medium classification class (3&lt;A0&lt;6) is associated with a moderate degree of deformation. Natural frequency value are found with a moderate classification (4&lt;f0&lt;10) around the area of injection wells and production wells, indicating that the research area has a moderate level of soil hardness structure. The peak ground acceleration in the study area is classified as moderate (0.25&lt;PGA&lt;0.7) which means that the area has a moderate level of risk. Vulnerability of seismic in the study area is included in the low classification (Kg&lt;10). The local magnitude impact on soil acceleration and vulnerability of seismic in this study has a moderate risk and can be categorised as safe. In the future, this research serves as a basis for proper decision-making in geothermal energy operations, monitoring, and infrastructure development
Scheme for Selection of Deceptions as a Countermeasure for Insider Threats

The number of insider threats and the expense of handling them increase every year, rendering it imperative to adopt measures against insider threats. In particular, insiders must adopt a psychological approach. Psychological approaches can be classified into three categories: deceiving insiders, demoralizing insiders, and luring insiders. The deception simultaneously accomplishes these three approaches. The disruption of enterprise systems by deception mechanisms causes a significant decrease in usability for users. The application of deception mechanisms requires careful consideration. Therefore, when designing deception as a countermeasure against insider threats, usability and security must be balanced from the viewpoint of cost-effectiveness. For evaluating cost-effectiveness of security measures, a method that models the relationship between “assets”, “threats”, and “countermeasures” as well as formulates the countermeasure selection problem as a discrete optimization problem has been proposed. However, these methods assume an external intruder, and to the best of our knowledge, no existing research explicitly covers the selection of countermeasures against insiders (malicious insiders). This paper proposes a scheme to quantitatively evaluate the effectiveness of deception against insider threats and determine the optimal deception mechanism. In the existing method, the relationship between “assets”, “threats”, and “countermeasures” is formulated as a discrete optimization problem, but the proposed method explicitly includes insiders as “threats” and deception as “countermeasures”. In addition, when evaluating the effectiveness of insider-threat countermeasures in the model, the usability of users must be considered. Therefore, by adding “operation” to “assets”, “threats”, and “countermeasures”, the proposed method incorporates the impact of selected countermeasures on the “usability” of business into the formulation of existing methods. Specifically, the existing method is sublimated into a security measure selection method that includes insider threat countermeasures (deceptions) by formulating the objective function of the existing method to be maximized with “usability” as a constraint.
Mixed Reality Equipment Training

The increasing availability and capability of Extended Reality (XR) systems has led to swift augmentation of many daily tasks. Research in Mixed Reality (MR), an XR branch allowing simultaneous interaction with virtual and real objects, has shown great potential for enhancing training such as learning how to use technical equipment. In this work, a pilot study was conducted to evaluate how users perceived instruction details given in a traditional written format or MR application. Participants were asked to set up a complex resin-type 3D printer following one of the instruction formats, having no prior experience with any equipment used. Performance was evaluated in regard to efficiency, precision, perceived difficulty, task comprehension, and experience preferences. This work resulted in clear analysis of how details in written and MR instructions are perceived, which can be used to more effectively leverage MR visuals to convey information in training applications.