Reviewerly/exHarmony huggingface dataset:
Comparison of hemoglobin level measurement results using sodium lauryl sulphate with oshiro and mansoor procedure

The method of measuring Hb levels recommended by ICSH uses the HiCN method. However, it has a high risk due to the toxicity of the reagent. Therefore, the determination of Hb has been developed using the SLS method. According to Oshiro and Mansoor, who both stated that there was no significant difference between SLS and HiCN, this method has two distinct procedures. This study aims to determine the comparison between the measurement results of hemoglobin levels using sodium lauryl sulfate with the Oshiro procedure and Mansoor. The research design used is analytical research. The data obtained from the results of measuring Hb levels with the Oshiro and Manshoor procedures was given to students of the Diploma IV Study Program of Medical Laboratory Technology, Rajawali Health Institute batch 2018, which collected 49 people. The sampling technique used was saturated sampling to reduce the error rate in the study. The results of the normality test of the data in this study showed n of the two procedures was 49 mean±SD for the Oshiro procedure 13.09±0.56 and p = 0.200. Meanwhile, the Mansoor procedure had a meanSD of 13.09±0.57 and a p-value of 0.059. Because the probability of both being p &gt; 0.05, the data is declared normally distributed. The results of the average difference test from the data of this study show the mean±SD of the pairwise difference between the Oshiro and Mansoor procedures is 0.002±0.059 and the p value = 0.811. If P &gt; 0.05, then it is stated that there is no significant difference between the two groups. The conclusion of this study is that the result of measuring Hb levels using the SLS procedure is reliable. Oshiro and Mansoor conform to HiCN and there is no significant difference in the mean results.
Introduction to The Political Economy and Feasibility of Bitcoin and Cryptocurrencies

Some, especially of the older generation, agree with Roubini and others that "Crypto is the mother of all scams" and blockchain is "no better than a spreadsheet/database". Yet, if there is demand for a good, such as fine wines, or bitcoins, and its supply can be kept limited, then that good will have a positive price. As with Plato's ideal forms, bitcoins and cryptocurrencies may in some ways be more real and ideal than more earthly forms of money.
DIRECTIVE AND EXPRESSIVE SPEECH ACTS USED BY TRAVIS PARKER IN THE CHOICE MOVIE

This paper aimed to explore the categories of speech acts used by Travis Parker as the main character of The Choice movie. Data were collected using a qualitative method and analyzed using a descriptive analysis technique. Results showed that the main character used directive and expressive speech acts. The directive ones included the acts of ordering, commanding, warning, suggestion, requesting, forbidding, and inviting. Specifically, the act of ordering something appeared once, commanding four times, giving a suggestion once, requesting twice, forbidding twice, and inviting someone once. Furthermore, the expressive function included the acts of apologizing, thanking, greeting, and compliment. Specifically, the act of apologizing for someone appeared six times, giving thanks once, greetings three times, and giving a compliment three times. Exploring the roles and context of speech acts in The Choice movie from a sociolinguistic perspective will contribute to English learning-teaching.
Autoregressive Perturbations for Data Poisoning

The prevalence of data scraping from social media as a means to obtain datasets has led to growing concerns regarding unauthorized use of data. Data poisoning attacks have been proposed as a bulwark against scraping, as they make data "unlearnable" by adding small, imperceptible perturbations. Unfortunately, existing methods require knowledge of both the target architecture and the complete dataset so that a surrogate network can be trained, the parameters of which are used to generate the attack. In this work, we introduce autoregressive (AR) poisoning, a method that can generate poisoned data without access to the broader dataset. The proposed AR perturbations are generic, can be applied across different datasets, and can poison different architectures. Compared to existing unlearnable methods, our AR poisons are more resistant against common defenses such as adversarial training and strong data augmentations. Our analysis further provides insight into what makes an effective data poison.
A proposal to reduce false alarms in anomaly detection systems with counterfactuals generated through multi-objective constrained optimization

Abstract Anomaly detection systems are a field of study responsible for implementing techniques capable of detecting abnormal changes in time series. These abnormal changes have a particular usage in industrial applications such as water monitoring and manufacturing. One of the challenges in these systems is to reduce the number of false-positives: it is not desired to trigger false alarms to the users frequently. In order to solve this challenge, we propose a strategy using a counterfactual generation algorithm to be applied as a post-processing method on a previously trained, standard anomaly detection anomaly. This counterfactual generation algorithm is modeled as a multi-objective optimization constrained problem. These counterfactuals are then evaluated by a classifier trained to find members of false-positives. Results show that this proposal can successfully reduce the number of false-positives.
Detection of VPNs using Machine Learning

Abstract: The nature of the tools used by criminal actors to hide their identities has made it is very challenging to detect unauthorized users. Network security is any move an association makes to forestall vindictive use or coincidental harm to the organization's private information, its clients, or their gadgets. The objective of organization security is to keep the organization running and valid for every authentic client. Since there are such countless ways that an organization’s security can be compromised, network security includes a wide scope of rehearses. Most of normal assaults against networks are intended to acquire admittance to data, by keeping an eye on the correspondences and information of clients, rather than to harm the actual organization. However, assailants can do more than taking the information. They might have the option to harm clients' gadgets or control frameworks to acquire actual admittance to offices. This leaves the association's property and individuals in danger of damage. Network security extensively comprises of approaches, cycles and practices embraced to forestall, recognize and screen unapproved access, abuse, change, or disavowal of organization available assets. This work presents computational model that can detect the use of virtual private networks to gain unauthorized access.
ОСВІТНІ ТЕХНОЛОГІЇ В НАВЧАЛЬНОМУ ПРОЦЕСІ ТРЕТЬОГО ТИСЯЧОЛІТТЯ

The basic principles of development of technologies of education and education of building civilizations of the third millennium are presented in the work
The Study of the Opinions of Medical University Students about the Format of Lectures in the “Postcovid” Period

The chapter is devoted to the study of the opinions of students of N.N. Burdenko VSMU regarding the further format of lectures in the «post-COVID» period. The presented topic is very relevant, since at present the pandemic of a new coronavirus infection that arose in 2020 has begun to decline – there is a daily widespread decrease in detected cases of the disease. For students of higher educational institutions this means the gradual removal of various kinds of restrictions – a smooth transition from the forced distance period to the classic full-time format. The purpose of this work was to determine the attitude of medical students in general to the lecture material, both as part of an integrated learning process, and to determine the attitude directly to its full-time – traditional and remote presentation. The objects of the study were 300 students of the medical faculty of the N.N. Burdenko Voronezh State Medical University, divided into three groups of 100 people, depending on the course – 2, 4, 6. The study was based on an original questionnaire specially developed by the authors, which became the basis of an anonymous survey. It can be said that the main direction of the study was to determine the opinion of students regarding the possible transition of lecture material in the next semester to full-time – the traditional format. At the same time, the study of positive and negative aspects, both remote and full-time lecturing, was of great importance in the work. The results obtained are also particularly interesting because all students of the first group (2nd year) have never had the experience of attending lectures in full-time format – after all, their admission to the university took place after the start of the pandemic. The data obtained in the work are of interest to teachers of various departments of a medical university, and the opinions of students can be taken into account and used in the future when planning the format of lecturing.
"Teaching Independent Parts Separately" (TIPSy-GAN) : Improving Accuracy and Stability in Unsupervised Adversarial 2D to 3D Pose Estimation

We present TIPSy-GAN, a new approach to improve the accuracy and stability in unsupervised adversarial 2D to 3D human pose estimation. In our work we demonstrate that the human kinematic skeleton should not be assumed as a single spatially codependent structure; in fact, we posit when a full 2D pose is provided during training, there is an inherent bias learned where the 3D coordinate of a keypoint is spatially codependent on the 2D coordinates of all other keypoints. To investigate our hypothesis we follow previous adversarial approaches but train two generators on spatially independent parts of the kinematic skeleton, the torso and the legs. We find that improving the self-consistency cycle is key to lowering the evaluation error and therefore introduce new consistency constraints during training. A TIPSy model is produced via knowledge distillation from these generators which can predict the 3D ordinates for the entire 2D pose with improved results. Furthermore, we address an unanswered question in prior work of how long to train in a truly unsupervised scenario. We show that for two independent generators training adversarially has improved stability than that of a solo generator which collapses. TIPSy decreases the average error by 17\% when compared to that of a baseline solo generator on the Human3.6M dataset. TIPSy improves upon other unsupervised approaches while also performing strongly against supervised and weakly-supervised approaches during evaluation on both the Human3.6M and MPI-INF-3DHP datasets.
Pemanfaatan Pojok Literasi Sekolah dalam Gerakan Literasi Sekolah Dasar Negeri 3 Bandungrejo

The point in this community service activity (PKM) is to improve the quality of literacy through the Literacy Movement. This activity was carried out at SDN 3 Bandungrejo during September to December 2021. The targets of service include teachers, students, and parents/guardians. The method used is the use of the literacy corner in assisting the Literacy Movement. The service program is structured based on the problems found during the observation process. The absence of libraries as literacy facilities encourages the development of the School Literacy Corner program to improve the quality of literacy, especially the numeracy literacy of students. In addition, it was found that two students in fourth grade and one student in third grade were not fluent in reading. In maintaining the sustainability of the program, this service involves several parties, namely teachers, parents, and the literacy driving community. The existence of collaboration between parties makes this activity successful and sustainable in improving student literacy
Improved Whale Optimization Algorithm and Low-Energy Consumption Design of Circuit Breaker

In the transmission and distribution system, the high-energy consumption of the low-voltage circuit breaker easily leads to the decrease of the distribution efficiency of the system. Therefore, on the basis of calculating the internal power consumption of circuit breakers, combining with several factors affecting the energy consumption of circuit breakers, the low-energy consumption mathematical model of circuit breakers is built, and an improved whale optimization algorithm (LA-WOA) is proposed for optimization. The Lévy flight mechanism and the adaptive weight factor are introduced into the traditional whale algorithm to enhance the global and local search ability of the algorithm and also improve the convergence speed and accuracy of the algorithm. The test function simulation experiment proves that the improved algorithm has better performance than other algorithms. Furthermore, the improved LA-WOA algorithm is used to iteratively solve the low-energy consumption mathematical model of the circuit breaker. The experimental results show that the improved algorithm obtains a lower-energy consumption value, which can effectively improve the design efficiency and accuracy of the circuit breaker.
photoQR: A novel ID card with an encoded view

&lt;p&gt;photoQR: A novel ID card with an encoded view&lt;/p&gt; &lt;p&gt;&lt;br&gt;&lt;/p&gt; &lt;p&gt;Livio Tenze, Enrique Canessa&lt;/p&gt; &lt;p&gt;&lt;br&gt;&lt;/p&gt; &lt;p&gt;There is an increasing interest in developing techniques to identify and assess data to allow an easy and continuous access to resources, services or places that require thorough ID control. Usually, in order to give access to these resources, different kinds of documents are mandatory. In order to avoid forgeries without the need of extra credentials, a new system –named photoQR, is here proposed. This system is based on a ID card having two objects: one person’s picture (pre-processed via blur and/or swirl techniques) and one QR code containing embedded data related to the picture. The idea is that the picture and the QR code can assess each other by a proper hash value in the QR. The QR without the picture cannot be assessed and vice versa. An open source prototype of the photoQR system has been implemented in Python and can be used both in offline and real-time environments, which effectively combines security concepts and image processing algorithms to obtain data assessment.&lt;/p&gt;
Comparative Analysis of Cryptographic Hash Algorithms

Abstract: Cloud is the on-demand availability for data storage management in large-scale companies and even for government sites where the data should be highly confidential. Here, data security plays an equivalent role to data storage. Cloud security is a collection of security measures that are designed to protect cloud-based infrastructure, data, and applications. The level of cloud security differs based on the type of cloud services. Cloud security protects the cloud environment from several attacks like distributed denial of attack, and malware, and prevents unauthorized user access. A crucial component of cloud security in large-scale organizations and for the government is focused on protecting the business contents like customer details, secret design documents, financial records, etc. Keywords: MD5, SHA12, padding bits, buffers, salt hashes, keyed hashes, adaptive hashes.
Implementasi Algoritma Base64 Sebagai Tingkat Keamanan Data Pada Website Sistem Informasi Pencatat Barang

The slowness of a job can be affected by many things, mostly due to the large number of files for a single activity. The introduction of a computerized goods recording system is intended to assist users in carrying out their work and facilitate users in finding information on incoming and outgoing goods data. The application made has additional features from previous research, namely exporting incoming and outgoing goods data in the form of 3D graphics and there is a live chat that functions for interaction between application users. For data security, the transaction id stored in the database uses base64 encryption, aiming to secure data from irresponsible parties. In the encryption process, it has been tested using 300 data and has a file size of 1MiB (Mebibyte) by making the data safe and cannot be cracked by other parties. In testing the attack on encrypted data in this application, 20 methods of attack were proven to be unhackable, unless using the encode that was made in this application. The data security process used is to encrypt the transaction id of incoming goods and outgoing goods stored in the database and the description results are found on the website page
MEDIA ART AS A DIRECTION FOR THE DEVELOPMENT OF ARTISTIC DESIGN OF THE ARCHITECTURAL ENVIRONMENT

The article examines media artworks, which are created using artificial intelligence technologies and computers in unusual digital forms, as an intermediary between the viewer and spatial art and allow rethinking the theoretical achievements of artistic design. The purpose of the article is to systematize information about the patterns of development of media art, the definition of forms of media art, its principles and methods in the study of media art as one of the directions of development of artistic design of the architectural environment. Materials and methods. Literary and information sources, comparative analysis, structural and logical modeling, systematization of research results, methods of experimental design. The article analyzes modern forms of media art: installations, cinema, video, animation, internet art, web art, software as art; virtual reality, musical environment. Five principles of media art have been established - these are the principles of interactivity, intellectual play, random access, coding of visual information and collaboration. Digital ways of creating a visual image of a work are considered. Their harmonious combination helps to develop a dynamic emotional architectural environment in accordance with the request of the audience. A comparative analysis of the principles and methods of media art and artistic design of the architectural environment revealed their significant relationship, and the same processes and phenomena are interpreted from different positions, as a result of which they acquire a new meaning and significant differences. This allows us to consider media art as one of the most promising ways for the development of artistic design.
Semantic Autoencoder and Its Potential Usage for Adversarial Attack

Autoencoder can give rise to an appropriate latent representation of the input data, however, the representation which is solely based on the intrinsic property of the input data, is usually inferior to express some semantic information. A typical case is the potential incapability of forming a clear boundary upon clustering of these representations. By encoding the latent representation that not only depends on the content of the input data, but also the semantic of the input data, such as label information, we propose an enhanced autoencoder architecture named semantic autoencoder. Experiments of representation distribution via t-SNE shows a clear distinction between these two types of encoders and confirm the supremacy of the semantic one, whilst the decoded samples of these two types of autoencoders exhibit faint dissimilarity either objectively or subjectively. Based on this observation, we consider adversarial attacks to learning algorithms that rely on the latent representation obtained via autoencoders. It turns out that latent contents of adversarial samples constructed from semantic encoder with deliberate wrong label information exhibit different distribution compared with that of the original input data, while both of these samples manifest very marginal difference. This new way of attack set up by our work is worthy of attention due to the necessity to secure the widespread deep learning applications.
Fake Reviews Detection Using Multidimensional Representations with Fine-Grained Aspects Plan

Abstract: As the trend to shop online is growing day by day and lot of people are interested in purchasing the products of their need from the online stores. This way of shopping does not take a lot of time of a customer. In this case reviews on online websites play a important role in sales of the product because people try to get all the pros and cons of any product before they buy it. Most of the people needs genuine information about the product while online shopping. Before spending their money on particular product can analyse the various comments in the website. In this scenario, they did not recognize whether it may be fake or genuine. Customer place the order for particular product only by considering the reviews of that product. Here, it might be possible that reviews are fake. Now here query is which are fake reviews? Fake reviews may be good or bad compliment on the products. To detect such type of reviews we have developed the system. In this research, the dataset of different fake reviews provided by Flipkart are considered where reviews sentiments are included and using the LOGISTIC REGRESSION CLASSIFIER the reviews are classified into two categories i.e. fake and genuine. So user can save his/her time only by reading genuine reviews and gives accuracy about the product. Keywords: Fake reviews, review sentiment, logistic regression classifier, detection, feature extraction, web scrapping.
A Review of Incremental Reuse Method in Software Reuse Process

Abstract: In the late 1960s, the concept of software reuse was proposed. The legacy of software engineering process shows that the scope and field of software reuse was not particularly new. However, it is considered that software reuse is in its primary stages and has yet to reach its full capacity. The utilization of software components from entire stages of the software engineering process in new applications is called as software reuse. Given the economically costly and difficulty of building qualitative software, repurposing prior software investments is enticing. We propose that software reuse should be considered as part of a fully systematic approach that considers a wide range of technological, economical, managerial, organisational, and legal considerations, and we wrap up with a synopsis of the important research issues in all these verticals. This paper summarises our progress in software reuse research. Keywords: Software Reuse, Incremental Reuse Method (IRM), Reuse Process, Artifact, Software Component