Reviewerly/exHarmony huggingface dataset:
Role of Blockchain and Cryptocurrency to Redefine the Future Economy

The virtual currencies have practiced a steady process and carry on to experience it. In fact, these cryptocurrencies found a significant place in the society and are already integrated because more people make use of them as one of the payment methods for products and services. These cryptocurrencies are using not only payment purposes but also invest in them to increase the capital. Blockchain is a peer-to-peer distributed ledger of time-stamped transactions. The entire ethos was decentralized and away from all central banks. Hence, it is a pressure group against the centralization and the control of fiat money. The central banks are controlling the traditional physical currency but the cryptocurrency and block chain technology, the user maintains a copy of their ledger and all copies of other ledgers which are synchronized through a consensus algorithm. In the recent past, due to high publicity regarding the blockchain technology both private and public sector organizations have opened their eyes and looked at the technology. The researcher also made an attempt to analyze the market cap of the Bitcoin and ten other leading cryptocurrencies since October 2013. The prime objectives of the study are: a) to study the role and future developments of blockchain and cryptocurrencies. B) To compare the market cap of Bitcoin with other top ten prominent cryptocurrencies. In fact, as of April 2021 more than 4000 cryptocurrencies are in existence but many of these cryptocurrencies have very little market cap and no trading volume. Some are more popular and offer communities of investors and backers. Bitcoin is the pioneer among the cryptocurrencies and introduced in the year 2009. Correlation analysis is employed to compare the relationship between Bitcoin market cap and other ten cryptocurrencies. In fact, as of April 2021 more than 4000 cryptocurrencies are in existence but many of these cryptocurrencies have very little market cap and no trading volume. Some are more popular and offer communities of investors and backers. After well examining and based on the previous study the researcher has chosen ten important cryptocurrencies other than Bitcoin. It is practiced that the analysts and researchers rank the digital coins in terms of their market cap. Here the researcher has selected these coins not only in terms of market cap but there are some other reasons such as the stability and other special features of the virtual currency. Within a decade the blockchain technology reached almost all parts of the globe. At present people from an average income group are trying to save or invest their money in cryptocurrencies. Transparency, security, privacy, cross border payments, low cost, minimizing errors and no central agency to control are the main future of the blockchain. Once the price of Bitcoin is decreased or increased it will directly influence the other cryptocurrencies in the near future blockchain technology will be more efficient and redefine the future financial system of the world.
Minimal subset generation on Lazy Associative Classification based on cogency and Harmonic Mean

Lazy learning associative classification method gains higher accuracy than counterpart eager method. The majority of the existing lazy associative classification algorithms generate an exponential number of subsets that increase the computation time. Moreover, lazy learning associative classification with traditional support and confidence measure leads to missed out some rare and prime subsets. The proposed method overcome this problem by focusing on the important feature of the given test instance. As a outcome the proposed system is able to generate a minimal number of high-quality rare itemset as a subset. The proposed rare lazy associative classifier produces high quality subsets and increases classifier accuracy, according to the empirical results. Experiment results show that the proposed algorithm attains better accuracy and reduce the computation time than traditional lazy learning associative classification.
EVALUASI PROGRAM PENDIDIKAN NON FORMAL PADA RUMOH BACA HASAN-SAVVAS DI KOTA LHOKSEUMAWE

This study aims to evaluate non-formal education programs at Rumoh Baca Hasan-Savvas in Kota Lhokseumawe because in general, the community reading park is difficult to find in Aceh. This study was conducted to find out how the evaluation of non-formal education program on Rumoh Baca Hasan-Savvas in the evaluation of Context, Input, Process, and Product?. The type of this research is qualitative evaluation research, with phenomenological approach of field study. The sample in this study was the head of the Rumoh Baca Hasan-Savvas institute, the person in charge of the program and the students who were taken at random. Data were collected by observation, interview and documentation. The data collected is analyzed by organizing the data, spelling it into units, synthesizing, arranging into patterns, choosing what is important and learning, and making conclusions. The results of this study indicate that in the evaluation of the context: the goal in eradicating illiteracy and marginalization and the context of the program has been implemented fairly well. In the input evaluation: the age level, the area of residence and the background of the learners vary according to the initial provision of the program, the staff education background on Rumoh Baca Hasan-Savvas 90% is S2, in general the teaching staff has experience in the field so as to provide good service to the participants though still short of teachers, donors who help the implementation of the program in Rumoh Baca Hasan-Savvas come from domestic and abroad but still still need other funding for the future. In Process Evaluation: student recruitment process, program management strategy, learning strategy has been done well enough, schedule of program implementation either literacy activity or creative class have been given to every learner but sometimes still hampered on availability of books for literacy activities as well as materials standard for the creation class, the person in charge of the program is appropriate because it is appointed directly by the head of the institution based on the mature consideration. In Product Evaluation: improved achievements and behavioral changes are increasingly for the better.
WEDDING EVENT ORGANIZER WEB-BASED

Wedding Event Organizer Web-Based is a web-based system that will be used by potential users especially for those who are going to use wedding event services. This web- based system will help wedding organizer in handling their business and easier the customer to search information regarding wedding organizer. By using this web-application, user is expected to fulfil the minimum needs that required for them to keep in track with current technology.
IMPLEMENTATION OF CONTENTANALYZER FOR INFORMATION LEAKAGE DETECTION AND PREVENTION ON ANDROID SMART DEVICES

Android has been the most commonly used operating system in smartphone due to its ease ofuse in transferring and receiving of information on various forms. Today, professionals indiverse spheres of life currently prefer to use their personal Smartphones and tablets as the casemay be for carrying out corporate work related tasks like email, documents, calendar, corporateapps among others, which has greatly helped in achieving a balance between personal andcorporate life. Literature shows that several phenomena had been developed to preventmalicious applications from stealing personal sensitive information from smart phones but thereis still the need for efficient solutions.This study used a conceptual approach for theimplementation of a ContentAnalyzer for information leakage detection and prevention onandroid-based devices. This implementation will improve through the codes in the file activitiesand vulnerabilities that could be problem on android-based devices.
Geology, Geochemistry and Some Genetic Discussion of The IIC Anomaly, Bafq Ditrict, Central Iran

Zaqia IIC anomaly is located in the east of Bafq city in Yazd province. Alteration associated with mineralization has appeared within volcanic, intrusive and sedimentary rocks. The set of alterations of this anomaly consist potassium, sericitic and silicate alterations, with less sodic-calcic alterations. Iron minerals are observed in the form of veins and masses with various compositions in this deposit. Iron ore in Zaqia IIC anomaly is related to magma and hydrothermal fluids. A collection of accumulated zones is composed of high-temperature minerals at depth to subvolcanic assemblages on the surface. REE patterns in iron ores in IIC anomalies indicate LREE enrichment and Eu negative anomaly. The negative Eu anomaly shows the reducing conditions of the mineralizing fluid. Isotopic studies have been conducted to examine the source of the fluid. The mineralizing fluid source in this anomaly is sedimentary-metamorphism. Field observations, mineralogy, alterations along with ore geochemical data show that a magmatic fluid is turned to an iron-rich brine fluid; moreover, an IIC anomaly is formed.
Blockchain: Una revolución de vieja data

espanolLa revolucion de la tecnologia blockchainfue producto del desarrollo de tecnicas matematicas que se fueron complementando con otras tecnologias que ha llevado a organizaciones publicas y privadas a reconducir y adaptar sus infraestructuras y modelo de negocios. El derecho argentino ha evolucionado lentamente, pero de a poco intenta ponerse al dia. EnglishThe blockchain technology revolution was the product of the development of mathematical techniques that were complemented with other technologies that has led public and private organizations to redirect and adapt their infrastructures and business model. Argentine law has evolved slowly, but little by little it tries to catch up.
R/V SONNE Cruise SO255 "VITIAZ": An integrated major element, trace element and Sr-Nd-Pb-Hf isotope data set of volcanic rocks from the Colville and Kermadec Ridges, the Quaternary Kermadec volcanic front and the Havre Trough backarc basin, Version 1.0

Cruise SO255 of the German Research Vessel SONNE surveyed the Kermadec Arc System from ca 35°S to 28°S in 2017. Volcanic rocks were obtained by dredge from the Neogene Colville and Kermadec ridges that represent the split remnants of the preceding Vitiaz Arc, the Havre Trough backarc and Quaternary volcanic centers of the Kermadec Arc. The overarching goal of SO255 VITIAZ is to elucidate the physical and chemical conditions that control the development of subduction zones, including evolution of mature arc systems, and the transition from arc splitting to back-arc basin generation. The correlated dataset reports major element data for 317 samples, trace element data for 285 samples, radiogenic Sr-Nd-Pb isotope ratios for 155 samples and radiogenic Hf isotope ratios for 88 samples. These include eight topic related samples of cruises TAN0206, TAN1611 of the New Zealand research vessel TANGAROA and one sample of cruise B30 of the Russian research vessel VOLCANOLOG.
Fooling an unbounded adversary with a short key, repeatedly: The honey encryption perspective

This article is motivated by the classical results from Shannon that put the simple and elegant one-time pad away from practice: key length has to be as large as message length and the same key could not be used more than once. In particular, we consider encryption algorithm to be defined relative to specific message distributions in order to trade for unconditional security. Such a notion named honey encryption (HE) was originally proposed for achieving best possible security for password based encryption where secrete key may have very small amount of entropy. Exploring message distributions as in HE indeed helps circumvent the classical restrictions on secret keys.We give a new and very simple honey encryption scheme satisfying the unconditional semantic security (for the targeted message distribution) in the standard model (all previous constructions are in the random oracle model, even for message recovery security only). Our new construction can be paired with an extremely simple yet tighter analysis, while all previous analyses (even for message recovery security only) were fairly complicated and require stronger assumptions. We also show a concrete instantiation further enables the secret key to be used for encrypting multiple messages.
Selection of Key Features of Correction Strategies for Community Corrections Personnel and Method of Case Marking

The traditional community correction model adopts the method of artificially formulating correction strategies, which has problems such as strong subjectivity and inconsistent judicial level. Because of the wide distribution of community corrections personnel, the uneven standards for correction strategy formulation by local judicial personnel and the problem that it is almost impossible to form effective correction strategies in poor and remote areas, and the amount of data for correction personnel information is large, the way to manually formulate correction strategies The efficiency is low. This paper proposes a clustering algorithm for correcting personnel status information based on feature subspace, localizes the high-dimensional data search problem in related dimensions, solves the problem of automatic labeling of correction strategy tags, and provides some references for judicial personnel to formulate correction strategies.
Perturbation Type Categorization for Multiple ℓp Bounded Adversarial Robustness

Despite the recent advances in adversarial training based defenses, deep neural networks are still vulnerable to adversarial attacks outside the perturbation type they are trained to be robust against. Recent works have proposed defenses to improve the robustness of a single model against the union of multiple perturbation types. However, when evaluating the model against each individual attack, these methods still suffer significant trade-offs compared to the ones specifically trained to be robust against that perturbation type. In this work, we introduce the problem of categorizing adversarial examples based on their lp perturbation types. Based on our analysis, we propose PROTECTOR, a two-stage pipeline to improve the robustness against multiple perturbation types. Instead of training a single predictor, PROTECTOR first categorizes the perturbation type of the input, and then utilizes a predictor specifically trained against the predicted perturbation type to make the final prediction. We first theoretically show that adversarial examples created by different perturbation types constitute different distributions, which makes it possible to distinguish them. Further, we show that at test time the adversary faces a natural trade-off between fooling the perturbation type classifier and the succeeding predictor optimized with perturbation specific adversarial training. This makes it challenging for an adversary to plant strong attacks against the whole pipeline. In addition, we demonstrate the realization of this trade-off in deep networks by adding random noise to the model input at test time, enabling enhanced robustness against strong adaptive attacks. Extensive experiments on MNIST and CIFAR-10 show that PROTECTOR outperforms prior adversarial training based defenses by over 5%, when tested against the union of l1,l2,l∞ attacks.
Pengembangan Buku Pengayaan Dinamika Hidrosfer pada Materi Perairan Darat sebagai Pengetahuan Kebencanaan di Sekolah Menengah Atas Negeri 1 Kartasura Kabupaten Sukoharjo

The purpose of this study were (1) Knowing the development of enrichment books asteaching materials for students of Kartasura 1 Senior High School in Sukoharjo District,(2) Knowing the effectiveness of the hydrosphere development enrichment book inKartasura 1 Senior High School, Sukoharjo District. The development model in thisstudy used the modification of Thiagaraja 4D model into 3D model (Define, Design,Development). The study design used a pretest-posttest control group design with 67respondents. The study was conducted at Kartasura 1 Senior High School, SukoharjoDistrict by using purposive random sampling. two classes, namely, control class andexperimental class. Analysis of the data paired sample t-test to test the hypothesis. Theresult indicated that the development of media enrichment books is worthy / good sothat it can be used for teachers and students in the learning process. There was anincrease of students learning of control class and experiment class. The difference in theresults of understanding the material dynamics of terrestrial hydrosphere as theknowledge base of flood mitigation in the control class increased with the average valueof pretest 40 and the average posttest 53 while the difference in the results of studentunderstanding in the experimental class at pretest and posttest by 43 and the averageposttest by 66. The results of the T-test showed a significant value (2-tailed) = 0002which mean less than 0.05 so that H0 was rejected and H1 was accepted, and then theproduct developed was effective to be used in the learning process.
An Improved GRU Network for Human Motion Prediction

Human motion prediction is a research field with broad application prospects. With the development of deep learning, researchers have used advanced deep-learning algorithms in this field. This paper aims to combine GRU with 1D-CNN without increasing network parameters. In this paper, we use GRU to learn the continuity of human movement, and then use one-dimensional convolution networks to reduce the dimensions and to generate predicted actions. At last, we utilize the motion weight matrix which uses simple operations to get the weight from its own motion data, so as to improve the model's robustness. The test results on Human3.6M database show that our method gets a good result in short-term prediction and performs better than other GRU-based methods in long-term prediction. Other network using our ideas can also improve the prediction effect.
Fitri Tomyam Seafood Menu Order Android Mobile Application

Fitri Tomyam Seafood Menu Order Android Mobile Application is an android based mobile application that was developed to aid the business process in the aspect of delivery orders for Fitri Tomyam Seafood restaurant. The existing manual process of taking delivery orders where delivery orders are taken via WhatsApp platform is not an efficient method in managing delivery orders and provides poor customer service. Therefore, to build this project, an object oriented software development method was used in this project. Whereas, this application was developed using Android Studio and Firebase database. Overall, Fitri Tomyam Seafood Menu Order Android Mobile Application enables this restaurant to provide better customer service in delivery orders.
A Secure Device Access Based on Blockchain for IoT in Smart City

With the development of new generation information technology, the feasibility of smart city has been significantly improved, and a large number of smart city technologies have been proposed. In this context, a more feasible device access technology is of great significance to ensure the normal operation of smart city network services. Therefore, this paper proposes a secure blockchain device access scheme based on elliptic curve digital signature algorithm and zero knowledge proof algorithm.
Studi Komparasi Metode Machine Learning untuk Klasifikasi Citra Huruf Vokal Hiragana

Japanese is one of the most difficult languages to understand and read. Japanese writing that does not use the alphabet is the reason for the difficulty of the Japanese language to read. There are three types of Japanese, namely kanji, katakana, and hiragana. Hiragana letters are the most commonly used type of writing. In addition, hiragana has a cursive nature, so each person's writing will be different. Machine learning methods can be used to read Japanese letters by recognizing the image of the letters. The Japanese letters that are used in this study are hiragana vowels. This study focuses on conducting a comparative study of machine learning methods for the image classification of Japanese letters. The machine learning methods that were successfully compared are Naïve Bayes, Support Vector Machine, Decision Tree, Random Forest, and K-Nearest Neighbor. The results of the comparative study show that the K-Nearest Neighbor method is the best method for image classification of hiragana vowels. K-Nearest Neighbor gets an accuracy of 89.4% with a low error rate.
Lower Bound for m3(2,37) and Related Code

In a finite projective plane PG(2, q), an (k, n)-arc is a set of k points of a projective plane such that some n, but non + 1 of them, are collinear. Here, the integer n is the degree of the arc and k ≥ n. The maximum size of an (k,n)-arc inPG(2,q) is denoted by mn(2,q). In this paper the classification of the (k,3)-arcs in PG(2,37) is presented. It has been obtainedusing a computer-based exhaustive search that exploits Secant distributions inequivalent (k,3)-arcs and produces exactly onerepresentative of each equivalence class. We established that 50 ≤ m3(2,37). The constructed (50,3)-arcs give the respectivelower bounds on m3(2,37). As a consequence there exist new three-dimensional linear codes over GF(37).
Extreme Programming for Execution of Large and Geographical Distributed Software Projects

There have been a number of software development processes. Based on their advantages and disadvantages, they are accepted and utilized. But none of the development process can be claimed to be suitable to all the projects as the development context/scenarios differ. Therefore, there is a need to model the software development process based on the on-going situations. In this paper, we define and develop a software development process that uses Micro Service Architecture and DevOp culture for Extreme Programming (XP). The proposed software development process can be used for large, complex and geographically distributed software system. A literature review was conducted to understand the currently used software development process and architectures in extreme programming. Nevertheless, in practice, the usage of extreme programming in large scale companies/systems is not known. This study aims to evaluate the impact of the usage of XP process on the development of large-scale distributed systems, while taking online shopping services as a case study. A case study is conducted in an organization that develops software that are large-size and complex by modifying the extreme programming. Questionnaires were prepared and qualitative analysis was carried out. The case study aided in learning about the effectiveness of combining XP with DevOp. Further, outcomes of Crystal-Clear Methodology that depends on people rather than processes and Extreme Programming were compared. As a result of this process, XP can handle large, complex and geographical distributed software systems. Developed software becomes much faster, cost effective, loosely coupled, deployable across the globe. It is observed that practices of Extreme Programming when adapted in the project gives rise to output like people factor and also helps creating ideas and solutions for complex design issues. This is the approach for conceptualization and implementation of overall systems.