Reviewerly/exHarmony huggingface dataset:
Free and Open-Source Automated Open Access Preprint Harvesting

Universities are attempting to ensure that all of their research is publicly accessible because of funding mandates. Many universities have established campus open access (OA) repositories but are struggling with how to upload millions of manuscripts under numerous license agreements while also linking metadata to make them discoverable. To do this manually requires around 15 minutes per manuscript from an experienced librarian. The time and cost to do this campus-wide is prohibitive. To radically reduce the time and costs of this process and to harvest all past work, this article reports on the development and testing of a free and open source (FOSS) JavaScript-based application, aperta-accessum, which does the following: 1) harvests names and emails from a department’s faculty webpage; 2) identifies scholars’ Open Researcher and Contributor IDentifiers (ORCID iDs); 3) obtains digital object identifiers (DOIs) of publications for each scholar; 4) checks for existing copies in an institution’s OA repository; 5) identifies the legal opportunities to provide OA versions of all of the articles not already in the OA repository; 6) sends authors emails requesting a simple upload of author manuscripts; and 7) adds link-harvested metadata from DOIs with uploaded preprints into a bepress repository; the code can be modified for additional repositories. The results of this study show that, in the administrative time needed to make a single document OA manually, aperta-accessum can process approximately five entire departments worth of peer-reviewed articles. Following best practices discussed, it is clear that this open-source OA harvester enables institutional library’s stewardship of OA knowledge on a mass scale for radically reduced costs.
Introduction to Protocol Building Blocks In Cryptography

The Whole point of cryptography is to solve problems. It solves problems that involve secrecy, authentication ,integrity and dishonest people .A protocol Is a series of steps ,involving two or more parties designed to accomplish a task. A series of steps means that the protocol has a sequence, from start to finish. Analyzing stream ciphers is often easier than analyzing block ciphers. For example, one important metric used to analyze LFSR-based generators is linear complexity, or linear span. This is defined as the length, n, of the shortest LFSR that can mimic the generator output. Any sequence generated by a finite-state machine over a finite field has a finite linear complexity [1006]. Linear complexity is important because a simple algorithm, called the Berlekamp-Massey algorithm, can generate this LFSR after examining only 2n bits of the keystream [1005]. Once you’ve generated this LFSR, you’ve broken the stream cipher.
Evaluation of the Symmetrical and Asymmetrical Causality Relationship Between Bitcoin Energy Consumption and Stock Values of Technology Companies

Energy production is a phenomenon that has always preserved its importance for the history of humanity, as well as where the energy is spent and its consumption are also important. This study examined the causality relationship between Bitcoin energy consumption and Apple, Dell Technologies, Lenova Group, HP, Quanta Computer, Compal Electronics, Canon, Wistron and Hewlett Packard Enterprise has been taken into account to represent technology companies’ stock market. In the analysis, daily price data for the period 12.02.2017-07.02.2021 were used. Toda-Yamamoto (1995) symmetric causality test and Hatemi-J (2012) asymmetric causality test were used for used to determine the relationship between Bitcoin energy consumption and technology companies’ stock values. According to the results of the Toda-Yamamoto (1995) causality test, it has been found that there is a causality from Bitcoin energy consumption to Apple's stock value; according to the Hatemi-J (2012) asymmetric causality test results, it has been determined that there is a causality from Bitcoin energy consumption positive shocks to Apple, Dell Technologies, Lenova Group, HP, Quanta Computer, Compal Electronics, Canon, Wistron and Hewlett Packard Enterprise stock values negative shocks and from Bitcoin energy expenditure negative shocks to Hewlett Packard Enterprise negative shocks. According to the results of the study in general, it is seen that the change in Bitcoin energy consumption has an effect on the firm returns of the companies that sell the necessary tools for bitcoin energy production. From this, it can be commented that bitcoin mining is also effective on the stock returns of technology companies as well as many financial factors.
Challenges and Roles of Extension Workers on Cyber Extension as Information Media

Agriculture has been developing, which attracts more attention from all aspects of the economy. Besides, the industrialization of agriculture is the process of transforming agricultural production towards a comprehensive industrial direction in all aspects such as implementing livestock industry or agricultural mechanization, modernization of farming process, production in the form of modern farming (intensive farming, increasing crops, fertilizing in cultivation, and animal production). Thanks to the application of science, technology, and technology in the agricultural sector, agriculture activities have improved their productivity. Agricultural products include cattle, fish, poultry, and crops. The methods include economic institutions (economic laws such as supply and demand, value, competition) and legal, political institutions. One of the methods to implement agriculture extension is a cyber extension or using the power of online networks, computer communications, and digital interactive multimedia. The paper aimed to provide an overview of cyber extension in the context of agriculture development.&#x0D; Keywords: Cyber extension, agriculture extension, adoption, agricultural development
The Relevance in the Value of Grading in the Educational Process

The purpose of this article is to review the literature on the issue of grading as a method and technique of expressing students’ performance in terms of school reality. Initially, a growing concern about the role of assessment of student’s performance in the learning and, generally, in the educational process, is highlighted. Subsequently, the role of student’s performance is approached regarding the methodological issue of measurement and its efficiency in educational and social reality in general. Great importance is given to the pedagogical content of the assessment of students’ performance in association with the educational process and operation of the school. Then, the main issue is discussed referring to the means of expressing, describing, and presenting the outcome of student assessment with a specific reference to quantitative means and specifically to grading. In the last part of this paper, empirical research findings are used to point out the disadvantages of this specific technique. In particular, a reference is made to the errors observed in its use, which pose an important issue of validity, reliability, and objectivity and therefore of its dispute, as well as to the impact on the learning process and the student him/herself. The article concludes with the final notes on the subject.
Engineering Predecessor Data Structures for Dynamic Integer Sets

We present highly optimized data structures for the dynamic predecessor problem, where the task is to maintain a set $S$ of $w$-bit numbers under insertions, deletions, and predecessor queries (return the largest element in $S$ no larger than a given key). The problem of finding predecessors can be viewed as a generalized form of the membership problem, or as a simple version of the nearest neighbour problem. It lies at the core of various real-world problems such as internet routing. In this work, we engineer (1) a simple implementation of the idea of universe reduction, similar to van-Emde-Boas trees (2) variants of y-fast tries [Willard, IPL'83], and (3) B-trees with different strategies for organizing the keys contained in the nodes, including an implementation of dynamic fusion nodes [P\v{a}tra\c{s}cu and Thorup, FOCS'14]. We implement our data structures for $w=32,40,64$, which covers most typical scenarios. Our data structures finish workloads faster than previous approaches while being significantly more space-efficient, e.g., they clearly outperform standard implementations of the STL by finishing up to four times as fast using less than a third of the memory. Our tests also provide more general insights on data structure design, such as how small sets should be stored and handled and if and when new CPU instructions such as advanced vector extensions pay off.
Improving Model and Search for Computer Go

The standard for Deep Reinforcement Learning in games, following Alpha Zero, is to use residual networks and to increase the depth of the network to get better results. We propose to improve mobile networks as an alternative to residual networks and experimentally show the playing strength of the networks according to both their width and their depth. We also propose a generalization of the PUCT search algorithm that improves on PUCT.
GFCL: A GRU-based Federated Continual Learning Framework against Data Poisoning Attacks in IoV

Integration of machine learning (ML) in 5G-based Internet of Vehicles (IoV) networks has enabled intelligent transportation and smart traffic management. Nonetheless, the security against adversarial poisoning attacks is also increasingly becoming a challenging task. Specifically, Deep Reinforcement Learning (DRL) is one of the widely used ML designs in IoV applications. The standard ML security techniques are not effective in DRL where the algorithm learns to solve sequential decision-making through continuous interaction with the environment, and the environment is time-varying, dynamic, and mobile. In this paper, we propose a Gated Recurrent Unit (GRU)-based federated continual learning (GFCL) anomaly detection framework against Sybil-based data poisoning attacks in IoV. The objective is to present a lightweight and scalable framework that learns and detects the illegitimate behavior without having a-priori training dataset consisting of attack samples. We use GRU to predict a future data sequence to analyze and detect illegitimate behavior from vehicles in a federated learning-based distributed manner. We investigate the performance of our framework using real-world vehicle mobility traces. The results demonstrate the effectiveness of our proposed solution in terms of different performance metrics.
Course Scheduling Information System Using Genetic Algorithms

University X is a private university which has 8 faculties, namely Economics, Engineering, Social Sciences, Faculty of Social and Political Sciences, Fikes, Law, Islam and Vocational Studies. One of the leading study programs at the University X is the Informatics Engineering Study Program at the Faculty of Engineering which is currently experiencing problems when the process of dividing space and hour schedules is still manual.The problems that arise include the accumulation of lecture hours for a lecturer who takes more than one course. Another problem is the disruption of the lecture process at the beginning of the semester due to the tentative scheduling system. The preparation of lecture schedules at the Faculty of Engineering, University X is still done semi-manually using Microsoft Excel, so it will take several days to make a schedule. Meanwhile, making a schedule must be done quickly and optimally because it is used for lecture activities, the solution that can overcome the above problems is by creating a Course Scheduling Information System Using Genetic Algorithms.&#x0D; The genetic algorithm is one of the most appropriate algorithms used in solving complex optimization problems, which are difficult to do with conventional methods. The nature of genetic algorithms is looking for possibilities from potential solutions to get the optimal for solving problems. The scope of all viable solutions, i.e. the objects between matching solutions, is called the search space. Each point in the search space represents a viable solution.&#x0D; The limitations of the built problem are: This system is operated by the administrative staff of the study program at the Faculty of Engineering, University X. This system is made using the Codeigniter framework, Responsive Bootstrapping (display) and MySQL as the database and the method used by this system is the genetic algorithm method.&#x0D; The final result of this research is that it is helpful and easy to apply as a tool in helping the optimization process of lecture scheduling in order to minimize schedule collisions in lectures at the Faculty of Engineering, University X
Online New Student Registration System for SMA Negeri 1 Ketaggungan Brebes Using the CodeIgniter Framework

New student registration system manually is still used by some schools in Indonesia. But the problem is that prospective students are still many who feel difficulty with the system of the manual registration and of course they need registration system which more quick and efficient. Moreover, the conditions of the pandemic at this time, where there are rules to keep the protocol of the Health. Such as keeping physical distancing and limiting public service. The research method used in this research is the design and manufacture of the system, namely to design web-based system of a new student registration that can be accessed through a web browser. The online registration system of new students is built with PHP programming language and utilizing a MySQL database as a database server, and using the Codeigniter Framework. The result of this research is the web-based online registration system of new students already have the ability to provide convenience for prospective students to obtain all the information about the acceptance of new students and do the online registration process.
Analisa Alat Kendali Suhu dan Kelembaban berbasis Arduino Mega 2560

Temperature and humidity control systems are widely applied in agriculture. To increase crop yields and make it easier for agricultural actors, especially in plant cultivation, it is important to innovate in the development of technology that is growing rapidly. This study aims to analyze the level of validity and reliability of temperature and humidity control devices in a cultivation test room based on Arduino Mega 2560 with the help of SPSS. The results of the analysis and test of temperature and humidity control devices, with a maximum coefficient of variation of 1.86% and a minimum reliability coefficient of 0.62.
Tingkat Kepuasan Pengguna E-Learning Mahasiswa Pascasarjana Universitas Swasta Terbaik di Jakarta

Innovation learning that is relatively cheaper, easily accessible, or an integrated system as an e-learning platform in blended or hybrid. The purpose of this study was to analyze the effect of using e-learning on the satisfaction level of postgraduate students at a private university in Jakarta during the COVID-19 pandemic. Sample data obtained from postgraduate students; the number is 324 postgraduate students through online questionnaires on a google form. To conduct research testing through PLS-SEM analysis with the help of the SmartPls application version 3.0. The results of this study indicate that for H1 the original sample value is 0.158, the p-value is below 0.05, and the t-statistic is 2.791, which is greater than the t-table value of 1.962. For the results of H2, the original sample value is 0.132 and the p-value is above 0.05, and the t-statistic is 1.583 which is smaller than the t-table value of 1.962. For the H3 results, the original sample value is 0.201, the p-value is below 0.05, and the t-statistic is 2.221 which is greater than the t-table value of 1.962. So that, the overall result of this research is that the quality of the system, and the quality of information that affect the level of user satisfaction.
The Effect of Online Games on Learning Motivation and Learning Achievement

Technological developments make online games increasingly known throughout the community as a means for entertainment and even serve as a sport. This study aims to determine the effect of online games on learning motivation and student achievement. The results of the study show that at a certain level online games can be used as motivation to learn, but at the level of addiction to online games, it is very disturbing for students in learning achievement.
Dispatching Java agents to user for data extraction from third party web sites

Data retrieval on the World Wide Web has been a focus of intensive research in the past few years. The majority of existing approaches concentrate on mechanisms for data discovery and schema induction. Few researchers, however, address issues of performance of data extraction systems. Thus, centralized, server-based data extraction solutions often suffer from congestion and low speed of execution. In this work we present a mechanism for enhancing performance of data retrieval through distributing its functionality to the client computer using Mobile Data Retrieval Agents (MDRA).
Research on the application of carrier phase difference technology in geological exploration

As a new type of GPS measurement technology, GPS-RTK technology has the advantages of high measurement efficiency, high measurement accuracy, and less workload. It has a good application prospect in geological exploration engineering measurement activities. Applying this technology to practice can effectively break through the limitations of traditional measurement methods, reduce errors and workload, and enhance the effectiveness of geological exploration activities. This paper mainly gives an overview of GPS-RTK technology, discusses its specific application function and application strategy in geological exploration engineering measurement, and analyzes the main causes of errors and influences on the accuracy as well as the relevant practical points of the location setting of reference stations and mobile stations.
Biometrie Security System Design Using Keystroke Rhythms Algorith

Biometric technologies are becoming a vital part of computerized security systems. It is likely that biometric security technologies will be of greater importance in the light of terrorism, threads to computer systems. Biometric principals can be generalized as the automatic detection of a person’s suitable physical or neuro physical characteristics. Furthermore physical characteristics refer to the physical properties or attributes of a person that are inherited and neuro physical characteristics are those that depend on person’s behavior. This paper presents the idea of Keystroke Identification classified as a neuro physical characteristics for the purposes of a security system. Pattern recognition in neuro physical security systems have often proof to be difficult. To date two methods are deployed for keystroke pattern recognition. These are based on statistical or vector algorithms. This paper extends the domain of vector based biometric algorithms with a view to increase recognition frequency and reliability.
A Novel Personal Medicine Record Scheme Based on Block Chain and Cryptographic

The World Health Organization (WHO) has defined “eHealth” as “the application of information and communication technology” (ICT) in the medical and health field. This includes “medical care, disease management, public health surveillance, and education and research”. E-Health can improve access to medicine and reduce medical costs. Therefore, it has a far-reaching impact on developing countries and vulnerable groups. However, whenever a medical dispute arises, there are no good handling mechanisms, such as a complaint platform that handles patient or doctor complaints to help reduce litigations in medical disputes. For this reason, the authors propose a study of this concept.
Graph Application in Finding the fastest Path From Subang City To Cirebon City

This paper discusses the application of one of the Discrete Mathematics materials, namely Graph Theory, in determining the fastest route from Subang City, more precisely from Subang Pusakanagara, Subang to Cirebon City. The fastest path is the route taken by considering the minimum travel time from one place to another. There are various ways to determine the minimum travel path, but the goal is the same, namely to find a travel path with the minimum travel time. The research process begins with formulating a problem using Graph Theory with the help of the Google Maps application and the experiences of the researchers. This Google Maps application is very useful when traveling long distances but want to use the path with minimal travel time. After formulating the problem, it is continued with the implementation of the Weighted Average Method and ends with the Floyd Warshall Algorithm. The result of this study is to find the fastest path from the starting point, namely Subang Pusakanagara to the end point, namely Cirebon City.
Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors

Adversarial attacks against deep learning-based object detectors have been studied extensively in the past few years. Most of the attacks proposed have targeted the model's integrity (i.e., caused the model to make incorrect predictions), while adversarial attacks targeting the model's availability, a critical aspect in safety-critical domains such as autonomous driving, have not yet been explored by the machine learning research community. In this paper, we propose a novel attack that negatively affects the decision latency of an end-to-end object detection pipeline. We craft a universal adversarial perturbation (UAP) that targets a widely used technique integrated in many object detector pipelines -- non-maximum suppression (NMS). Our experiments demonstrate the proposed UAP's ability to increase the processing time of individual frames by adding "phantom" objects that overload the NMS algorithm while preserving the detection of the original objects which allows the attack to go undetected for a longer period of time.
Compiling a Higher-Order Smart Contract Language to LLVM

Scilla is a higher-order polymorphic typed intermediate level language for implementing smart contracts. In this talk, we describe a Scilla compiler targeting LLVM, with a focus on mapping Scilla types, values, and its functional language constructs to LLVM-IR. The compiled LLVM-IR, when executed with LLVM's JIT framework, achieves a speedup of about 10x over the reference interpreter on a typical Scilla contract. This reduced latency is crucial in the setting of blockchains, where smart contracts are executed as parts of transactions, to achieve peak transactions processed per second. Experiments on the Ackermann function achieved a speedup of more than 45x. This talk abstract is aimed at both programming language researchers looking to implement an LLVM based compiler for their functional language, as well as at LLVM practitioners.
Modular Representations for Weak Disentanglement

The recently introduced weakly disentangled representations proposed to relax some constraints of the previous definitions of disentanglement, in exchange for more flexibility. However, at the moment, weak disentanglement can only be achieved by increasing the amount of supervision as the number of factors of variations of the data increase. In this paper, we introduce modular representations for weak disentanglement, a novel method that allows to keep the amount of supervised information constant with respect the number of generative factors. The experiments shows that models using modular representations can increase their performance with respect to previous work without the need of additional supervision.