Reviewerly/exHarmony huggingface dataset:
Preventing Identity Theft using Blockchain Technology

Abstract: This paper's purpose is to describe what Blockchain Technology is and how it can be used to combat identity theft. Despite the fact that blockchain technology came to existence with Bitcoin, blockchain encompasses a comprehensive potential outside of cryptocurrency. Basically, blockchain could be a shared database that permits multiple parties to access information and verify that data in real-time It can transform the approach that we do things in various industries. It is used for a variety of things besides bitcoin, such as tracking ownership, digital assets, physical assets, and voting rights. It can store and run computer code known as smart contracts.
The Effects of Evidence based Decision-Making and Marketing in Software Product Management

Abstract: Past investigations on software product management (SPM) have given a broad image of crafted by a software product manager. In any case, little evidence exists about what standards ought to direct their decisions. A product manager's decision making has a specific degree of subjectivity based on managerial instinct. Be that as it may, supportable software product advancement requires powerful long haul decision making practices. Prerequisites designing, as well as delivery planning and road mapping, are SPM areas with the most significant level of evidence based decision making. In any case, the unmistakable comprehension of evidence based decision making practices is absent. The paper gives an analysis of decision making connected with SPM, uncovers a range of perspectives and approaches and reports assumptions on whether SPM is based on instinct or on the other hand in the event that it is evidence based.
Ethical Hacking Techniques

Abstract: The term ‘Hacker’ was defined to describe experts who utilize their skills to re-develop mainframe systems, increasing their capability and allowing them to multi-task. Nowadays, the term commonly describes skilled programmers who gain unauthorized access into computer systems by exploiting weaknesses or by using bugs, motivated either by malice or mischief. For example, a hacker can produce algorithms to crack passwords, penetrate networks, or even disrupt network services. The number one cause of malicious/unethical hacking entails stealing precious records or monetary advantage. However, now no longer all hacking is dreadful. This brings us to another type of hacking: Ethical hacking
Article and Preposition Use in Interlanguage Development: A Case Study Based on Two Access Positions of UG Perspective

The theory of Universal Grammar (UG) has aroused intense research interest in language acquisition. However, scholars hold different positions on the accessibility of UG in second language acquisition (SLA). The aim of the case study was to identify a L2 learner’s patterns of preposition and article use and determined the accessibility of UG in interlanguage development. Two assumptions of research design were raised based on the indirect access position and full access position of UG. 7 patterns of preposition and article use were eventually identified by error analysis. 6 patterns were categorized as L2 grammatical overgeneralization while 3 patterns were considered as L1 transfer. The final results therefore presented that UG was generally available and directly accessible in the L2 learner’s preposition and article acquisition. The research method provided a potential framework for future study on UG through error analysis. Moreover, this work also implied that UG may show different accessibility in different word classes. Future work should focus on the determination of UG’s accessibility in different lexical categories.
Return and Risk Analysis on Cryptocurrency Assets

This study aims to analyze the return and risk of Cryptocurrency assets in order to find out which crypto assets have small risks and large returns. In this research, the test procedures used were the Kruskal Wallis test and paired sample t-test. The research time span was obtained from January 1, 2019 to December 31, 2021 as well as the time span for data collection for price comparisons before and during the COVID-19 pandemic for 2 months from march 11, 2020. The results of this research are that bitcoin, ethereum, and dogecoin do not have a significant return comparison, for the results of risk research also have the result that there is no significant risk comparison between bitcoin, ethereum, and dogecoin. After that, for the results of the price comparison of bitcoin, ethereum, and dogecoin before the covid-19 pandemic and after the announcement of the covid-19 pandemic, the result is bitcoin and ethereum has a significant comparison between the time before the covid-19 pandemic and after the announcement of covid-19. On the contrary, dogecoin did not face a significant price comparison before the covid-19 pandemic as well as after the announcement of covid-19. Before starting an investment, it is better to look at the ability of Cryptocurrency assets to minimize risks and make sure whether the investment objectives are for the long and short term.
Fake Accounts and Clone Profiles Identification on Social Media Using Machine Learning Algorithms

Fake and Clone profiles are creating dangerous security problems to social network users. Cloning of user profiles is one serious threat, where already existing user’s details are stolen to create duplicate profiles and then it is misused for damaging the identity of original profile owner. They can even launch threats like phishing, stalking, spamming etc. Fake profile is the creation of profile in the name of a person or a company which does not really exist in social media, to carry out malicious activities. In this paper, a detection method has been proposed which can detect Fake and Clone profiles in Twitter. Fake profiles are detected based on number of abuse reports, number of comments per day and number of rejected friend requests, a person who are using fake account. For Profile Cloning detection two Machine Learning algorithms are used. One using Random forest Classification algorithm for classifying the data and Support Vector Machine algorithm. This project has worked with other ML algorithms, those training and testing results are included in this paper.
Distributed Ledger Technology for Fee Payment System by Using Blockchain with Cryptographic Keys and Peer to Peer N/W

The undertaking means to work with quick and secure installment handling of school expenses utilizing block chain innovation. These days understudies were approached to pay school expenses in various techniques, for example, cash, charge card, check and request draft. These sorts of exchanges need a middle to move sum from the trader to recipient. The middle is the bank for this situation. Conventional installment frameworks include focal specialists like the national bank, business banks and government. These strong mediums can handle every one of your activities and have full control of all data through their own frameworks. Much of the time the exchanges might try and come up short. Between making buys, covering bills, enacting cards, etc, 80% of banking communications spin around installments. The typical client interfaces with their bank no less than two times every day for installment related matters, making it the main financial movement that includes different cooperations daily. These issues have driven us take up this task. In this theory, we propose a decentralized school expense exchange techniques utilizing block chain innovation. A block chain is generally a public dispersed record of the record of all exchanges that has been achieved and divided between contributing gatherings and it requires no moderate to move the cash. Every exchange in the public record is confirmable by the member in the framework. Every exchange in block chain contains a list, timestamp and information. Blockchain installment frameworks give more noteworthy security and straightforwardness to the clients and organizations across the world. This is on the grounds that all exchanges should be visible openly and can't be adjusted whenever they are coded into the framework. Blockchain ordinarily is secure once it's in the framework. In this way, there aren't any additional securities that are fundamental for the framework so it's a lot less expensive than the conventional installment framework. In a blockchain installment framework, there aren't any supervisors or workers. There's just a local area of individuals who all together and go by rules on the stage. Hence, costs are decreased and there are lower commission charges.
Kajian Literatur Multi Layer Perceptron Seberapa Baik Performa Algoritma Ini

Multi Layer Perceptron (MLP), one of the deep learning algorithms, has been widely used in classification problem research because it has advantages over other conventional classification methods. This study takes 15 articles that have been published in research journals regarding the application of the multi-layer perceptron algorithm to prediction and classification problems. From the results of the analysis carried out, the results show that the lowest performance value of this algorithm is 62.89%, the highest performance value of this algorithm is 100% and the average performance value of this algorithm is 91.98%. From these values, it can be concluded that the multi layer perceptron algorithm is very good and feasible to be used in solving prediction and classification problems
Privacy Preserving Parallel Distributed Data Stream Anonymization

Sustainable stream processing algorithms have gained popularity in recent years. Flow control is a way of searching and modifying real-time data streams. Missing values are ubiquitous in real-world data streams, making data stream privacy challenging to safeguard. On the other hand, most privacy preservation methods need not take absent values into account when developed. They can anonymize data in certain study, however this results in data loss. This research proposes a unique parallel distributed approach for protecting privacy while using incomplete data streams. This method uses a production computational system to continually anonymize data streams, using clustering to construct each tuple. It clusters data in partial and complete forms using variable and array dimensions as similarity metrics. In order to prevent values and outliers’ pollution, a generalization approach that is based on more than matches is used. The experiments used real data to compare current systems with varied settings. This research will cover several anonymization mechanisms and their advantages. There are also drawbacks. Finally, we will explore the future of continuous data anonymization research.
The Use of Listen-Read-Discuss (L-R-D) Strategy to Improve the Students’ Reading Comprehension at MAN 2 Banyuwangi

Reading skill is one of the language skills that must be owned by the students in learning English. In fact, many students still have problems in reading English texts.This research was intended to improve the XI IPA 3 students’ active participation and their reading comprehension achievement by using Listen – Read – Discuss Strategy at senior high school in Banyuwangi. The participants were the students of class XI IPA 3. The class was chosen as the participants because most students had problems with reading comprehension, mainly to understand the content of the text and to answer the reading comprehension questions of the text. Besides, many students still got bad scores (below the score of KKM) in the reading test. Furthermore, the students were still passive in the reading teaching learning process and their motivation in reading English texts is still low. This condition could be caused by the teaching technique used by the English teacher in teaching reading was still conventional. To solve the students’ problem with reading comprehension, this classroom action research design with the cycle model was conducted. Each cycle covered four stages of activities, namely planning the action, implementing the action, observing the action, evaluating and reflecting of the action. In this research, the data were collected by reading comprehension test and observation. The data collected from reading comprehension test were analyzed quantitatively to find the students’reading comprehension achievement, Then, the data collected from observation were analyzed descriptively to find the percentage of the students’ active participation. Based on the results of reading comprehension test and observation in the first cycle, it could be concluded that the use of Listen-Read-Discuss Strategy could improve the students’ reading comprehension achievement and their reading comprehension achievement in the reading teaching learning process. It means that the students’ reading comprehension achievement was better after they were taught reading by using LRD strategy. Therefore, the English teacher is suggested to use this strategy as an alternative technique in the teaching of reading to improve their reading comprehension achievement,&lt;/P
Boogaloo Bias

Boogaloo Bias is an interactive artwork and research project that addresses some of the known problems with the unregulated use of facial recognition technologies, including the practice of ‘brute forcing’ where, in the absence of high-quality images of a suspect, law enforcement agents have been known to substitute images of celebrities the suspect is reported to resemble. To lam- poon this approach, the Boogaloo Bias facial recognition algorithm searches for members of the anti-law enforcement militia, the Boogaloo Bois, using a fa- cial recognition algorithm trained on faces of characters from the 1984 movie Breakin’ 2: Electric Boogaloo. The film is the namesake for the Boogaloo Bois, an anti-law enforcement militia that emerged from 4chan meme culture. They have been present at both right and left-wing protests in the US since Janu- ary 2020. The system is used to search live video feeds, protest footage, and images that are uploaded to the Boogaloo Bias website. All matches made by the system are false positives. No information from the live feeds or website uploads is saved or shared.
Anastatica: a Musical Experience for Algorithm, Live Coder, and Audience

Anastatica is a musical experience for musician, algorithm, and audience that combines performative elements with the characteristics of an installation. It ex- plores, in real time, the relationship between human performers and generative algorithms, allowing them to interact constructively or destructively using the same language and influenced by non-deterministic factors. Each performance is thus laced with randomness. Through this interplay of acousmatic, aleatoric live coding, the piece questions the nature of artificial intelligence’s involvement in modern society and the illusion of choice in the digital age.
Preemptive Futures: Entropic and Negentropic Information in Speculative Design

Preemption is an anticipatory action taken to secure first-options in maximising future gain and/or minimising loss. For instance, in risk management, responses are planned before a crisis takes place; such preemptive decisions are made based on speculations of possible future(s), directed by information feedback and analysis from a variety of sources. A systematic formulation of preemption and its relationship to computation are deeply rooted in the history of WWII; in the big data era, preemption is further augmented by the collaboration of human and machine intelligences, urging a rethink on how information is produced and used. By tracing a timeline of events around the conceptualisation of informa- tion, this paper aims at understanding the design and planning implications of preemptive decisions and how it may help us in rethinking speculative design. This paper first revises the idea of ‘information’ through a historical and theoret- ical study, and how it had been defined differently through the notion of entropy by Norbert Wiener, Claude Shannon, and Erwin Schrodinger from fields of cy- bernetics, information, and quantum theories. It discusses entropy from three perspectives: information compression and reconstruction, information entropy and energy entropy, interpolation and extrapolation. Finally, based on entropic and negentropic use of information, this paper rethinks the roles of specula- tion and preemption in today’s design context, especially their applications in the collaborative intelligence of humans and machines within distributed, open source networks.
Constructive Interpretation and Text Transformation

This paper considers the project of active transformation of texts through the substitution of words, for instance by the ‘N+7’ method of the Oulipans, which replaces each noun in a text by the seventh subsequent noun in a particular (print) dictionary. This method is conservative in that it only allows for intracate- gorial substitutions; the present paper aims to extend existing semantic interpre- tative mechanisms in order to handle intercategorial substitution. A type shifting system is proposed for this purpose, and applied to an example, followed by discussion of implications and extensions of the system.
Developing a Webpage Phishing Attack Detection Tool

Phishing is an identity theft fraud strategy in which users obtain false website links from fraudulent addresses that tend to belong to legitimate and actual companies in order to steal the receiver's personal information. The proposed tool helps users to check the received URLs using the pre-set white-list to determine whether it is legitimate or not. In addition, the tool can test any URL with the database and the results shows that the tool achieved 100% true positive rate and 100% true negative rate. Furthermore, the tool classifies any URL that neither in the database nor is phishing to the URLs in the database as unknown. However, the tool needs to be developed in terms of unknown URLs to be more reliable.
Datox

Datox explores the imperceptible electromagnetic radiation generated by elec- tronics and digital technologies as sonic material. The work is a music album and a live performance that creates an audiovisual environment that explores sonic possibilities through the amplification of imperceptible sounds. This aims to highlight a material layer that comes before data, the electricity that powers electronic devices. The music album and performance immerse the listener in a sonic environment of non-human agency, the electricity and its voltage differences at the circuitry level of computational devices. The work exposes the dependency of computational societies on energy production from non-re- newable sources such as coal that contribute to environmental pollution and the climate crisis.
Controlador Nebuloso Aplicado ao Equilíbrio de um Pêndulo Invertido Simples

The concept of Fuzzy Logic was created by Loftali Askar-Zadeh in 1965 and is considered one of the main artificial intelligence techniques of the last 50 years. In this contribution, an analytical approach was initially developed of an inverted pendulum in a cart that was numerically simulated in Python language. Then, a fuzzy controller was also developed in Python to keep the inverted pendulum in the vertical position according to the mechanical properties of the system and initial conditions. The controller considers the angle and angular velocity of the pendulum in the adjustment process for the response of the horizontal force applied to the cart. In conclusion, observing the results presented, the fuzzy controller was able to react to the system in a satisfactory way, obtaining an equilibrium position in different configurations of pendulum length.
SIIIGNAL: An Electroacoustic Composition/Instrument in Virtual Reality

SIIIGNAL is an electroacoustic composition/instrument in Virtual Reality (VR). The piece explores modes of interaction afforded by the VR environment; in com- bination with hand-tracking, gestural analysis and the physics engine of Unity3D, it provides a framework for musical expression using the VR medium. The player can instantiate sound particles in the space, perform sample triggering through collision detection, arrange sound objects in space, populate the environment with processing modules, spawn pulses that emanate spherically from the cen- tral sound object throughout the space triggering further sonic events, among others. The piece is divided into multiple sections with changing parameters over time and different rules. It starts requiring simple sonic gestures by the player, and as it progresses, emergent behaviours lead to more sonic complexity and possibilities for musical expression.
Service Quality Improvement Strategy in Library Management at Tadulako University

This study wants to examine how the Tadulako University library can improve its services to users through the development of a strategic plan. It aims to: (1) study and analyzes the quality of services using Tangible dimensions measurement methods (physical appearance), Reliability, Responsiveness, Assurance, and Empathy in the management of services at the University Tadulako; and (2) find strategies to improve the quality of services in the Tadulako University library management. The quantitative and qualitative (mix method) approaches are used in this study to obtain comprehensive, valid, reliable, and objective data. The service quality model uses the Servqual by Zeitham et al. In addition, a descriptive analysis approach is used to provide a description of the research subjects based on variable data. The number of samples is 397 people determined using the Slovin formula, with proportional sampling techniques. The data analysis technique used is the Mathew B. Miles and A. Michael Huberman analysis model. The data validity techniques used include (1) extension of participation; (2) perseverance/grace; and (3) triangulation. Testing research data through validity testing uses product-moment correlation, while reliability testing uses the Alpha-Cronbach method. Data collection techniques used are questionnaires, participant observation, in-depth interviews, documentation, and triangulation. The results of this study show that to improve the quality of service it needs to consider five dimensions of Servqual such as facilities and infrastructure that support service performance, reliability, and responsiveness of officers in serving and helping users who need information quickly and accurately. Providing guarantees of ease in the service process and security guarantees in the library building. The strategy for developing the external environment is done by giving library staff the opportunity to participate in education and training on libraries, collaboration with other universities, improving the quality of IT-based services, and making libraries centers of information for users. While the development of the internal environment is done by improving the quality of library service systems, optimizing the addition of facilities and infrastructure such as update collections, and providing the appropriate formation of human resources in the library so that service can be optimized. A research novelty is an information packaging dimension that supports the improvement of online-based library service quality systems
Motor Current Signature Analysis for Speed Estimation

The induction motors are widely applied due to their low price and ruggedness. There are several methods for speed estimation in the literature. The optical tachometer is an expensive and less reliable method for the speed measurement. Hence sensor less method for speed estimation is an important topic of research. In this paper, speed estimation of induction motor using motor current signature analysis is done. The comparative study of different methods shows that the motor current signature analysis (MCSA) is more accurate in speed estimation. This technique is experimentally verified on a 5HP, 3.7kW, 1430rpm 415V, 50Hz, 7.5A, 3Ø squirrel cage induction motor using LabVIEW. The experimental and simulation results show that the overall speed estimation error is within 5 rpm.