Reviewerly/exHarmony huggingface dataset:
SOTPNARM : SIZE OF TRANSACTION-BASED ON POSITIVE AND NEGATIVE ASSOCIATION RULE

Association rules mining has many algorithm and technic to solve problems. Apriori algorithm is used in market data base. Support and Confidence are two values to calculate and must be compared with threshold minsupp and threshold minconf proposed by user. Improved algorithm about association rules tries to optimize the numbers of itemsets , the quality of association rules. One of the improved algorithm is the Size Of Transaction-based Association Rule Mining( SOTARM) . This paper shows how to extract item sets frequents positives and negatives using the size of transaction, named SOTPNARM. The aim of our proposed solution is not only the using of negative item in the transaction data base when the original item is unfrequented but the negation of the rare item can be among of the association rules found. We begin with the introduction that tells what sets are item frequent, itemsets frequents. Then the proposed solution using the size of transaction with example illustration followed the discussion about the results and we terminate with the conclusion and the perspective
Exploiting Cluster Structure in Probabilistic Matrix Factorization

Low-rank matrix factorization is a basic model for collaborative filtering. The low-rank matrix approximation model is equivalent to represent users and items by latent factors, and rating is obtained by calculating the inner product of factors. Most low-rank matrix approximation models assume the latent factors come from a common Gaussian distribution. However, users with similar preferences or items of the same type tend to have similar factors, thus there exists cluster structure underlying user factors and item factors. In this paper, we exploit the cluster structure in the low-rank matrix factorization model to improve prediction accuracy. Experimental results on MovieLens-1m and MovieLens-10m datasets demonstrate the effectiveness of the proposed methods.
The Next Step in Requirements Management: Artificial Intelligence

In this session we look at automation in requirements management, starting with a view of automation in the review process. We look at the benefits to be gained, and the practicality of automation. Choosing a standard to follow is a necessary step before implementation, and we discuss some of the options, from domain specific templates to an industry agnostic standard. We then look at the IBM Watson IoT approach of Requirements Quality Assistant, how it works, how it was trained, and what value it can add to a project. Finally, we look to the future of Artificial Intelligence and Machine Learning support for the Requirements Management discipline, and how this can aid the requirements engineer at any career stage.
Holistické řízení datacenter: Metodika pro uvedení do provozu víceoborového řízení datacenter s použitím simulace budov

The world data center energy consumption has been growing rapidly and currently is estimated at 1,7–2,2% of the world-wide electricity consumption. Achieving sustainability in this sector calls for development new energy efficient strategies and measures. Current research deals with development of holistic operation i.e. operation, where all essential processes such as data processing, cooling and power delivery and supply (including renewable energy sources) are optimized a coordinated. Testing of modern operational strategies, which is necessary for development and commissioning, is not possible during the regular operation due to the risk of limitation of the services or outage of the data center operation. Any outage of the data center is related with financial and reputation losses. Therefore, the testing is extremely limited. Alternatively, building energy simulation may offer “safe” testing environment for advanced control algorithms and accelerate their implementation in practice. This paper describes a novel workflow for testing of modern control algorithm and new application of building energy simulation of data center.
Structural Correspondence Learning for Cross-Domain Sentiment Analysis in Brazilian Portuguese

Over the years, many approaches to the cross-domain task in Sentiment Analysis have been proposed. The vast majority of such approaches concerns corpora in English language. Following a different methodology, this paper proposes three novel product review datasets written in Brazilian Portuguese. These datasets are freely available and they cannot only be used as benchmark datasets by other researchers, but also to perform domain adaptation comparative assessments. In addition, the entire creation process for the proposed datasets is described. Another contribution resides in the first experimental evaluation of the state-of-the-art algorithm Structural Correspondence Learning (SCL) on cross-domain sentiment analysis (domain adaption). Furthermore, two other variants of the original SCL algorithm are evaluated on the proposed datasets and their performance are compared against each other.
The Virtual Camera

In Chapter 1, you left off running the sample scene prepackaged with VRTK. Although the VRTK demo scene is pretty nifty, it might not have been what you imagined the immersive power of VR could fully create.
Media Pembelajaran Interaktif Pengenalan Nama Hewan dalam Bahasa Inggris

The purpose of this study is to providet interactive learning media as a learning process in class as an effort to improve students' understanding of English, especially for the material of recognizing animal names. The method used is Research and Development (R&D) with the ADDIE (Ananlisys, Design, Development, Implementation, and Evaluation) development model. The developed product contains learning material including animal names and animal characteristics in Indonesia and English, practice questions, and quizzes. The results suggest that the learning media are feasible to use based on the assessment by media experts on the aspect of efficiency with a score, of 70, and by the material experts score of 66 with a Likert scale score. Student assessments gives an average score of 72,173 which fulls in the acceptable category in scoring System Usability Scale (SUS). Student learning outcomes in the class show an average pre-test score of 54.34 and an average post-test of 72.13. After Mann Whitney testing of the pre-test and post-test results of students showed an asymp sig value of 0.011, which means <0.05, it can be concluded that there are differences in learning outcomes in English subjects before and after using interactive learning media. Because there are differences in learning outcomes, it can be said that there is an influence of the use of interactive learning media for animal name recognition in English on improving student learning outcomes.
Factors of motivation to study at future psychologists in the conditions of the information society

In the article review the factors of motivation to study at psychology students in the information society,  review the differences between external and internal factors of motivation at students, review the peculiarities of change of motivational factors in modern information society are considered, the use of multimedia learning in technologies, the results of the empirical study of the factors of motivation to study in psychology students who showed a low level of motivation of training and motivation of preference for social success, social benefits, the use of learning new information technologies, teaching style and attitude of the teacher, the subject of interest.
Polyrematic units between morphosyntax and semantics. An experimental study on didactics of Italian in Kindergarten

This paper presents a didactic experiment on teaching vocabulary in a Kindergarten. The object of the research was to teach polyrematic constructions through vocabulary development activities to a heterogeneous group of children. This research draws on studies in applied linguistics, and focuses on the development of communicative competence.
MUSICAL EDUCATION SKILLS: PROBLEMS AND SOLUTIONS

The article discusses the professional skills of a teacher in the field of music education, its formation and improvement, his/her spiritual outlook, processes directly related to the level of culture, problems and solutions in these processes. Continuing music education, namely children's music and art schools, music and art lyceums and colleges, and then continuing education at higher educational institutions, are an important factor for obtaining excellent musicians and singers. Music is an important part of the spiritual culture of mankind. The process of music education contributes to creativity, creating opportunities for young talents to show their work. The participation of students faresees the work with other in the process of creativity. Students' activity is an important prerequisite for the development of creativity, and a creative approach to each of them is an important issue for the further development of musical abilities and students' performance. At all stages of the educational system, specific goals and objectives are manifested in the performance of young singers and musicians. Universal classifications of music pedagogy are studied.
An Automated Online Spam Detector Based on Deep Cascade Forest

With the development of internet communication, spam is quite ubiquitous in our daily life. It not only disturbs users, but also cms. Although there exists many methods of spam detection in both the area of cyber security and natural language processing, their performance is still not capable to satisfy requirements. In this paper, we implemented deep cascade forest for spam detection, a deep model without using backpropagation. With less hyperparameters, the training cost can be easily controlled and declines compared with that in neutral network methods. Furthermore, the proposed deep cascade forest outperforms other machine learning models in the F1 Score of detection. Therefore, considering the lower training cost, it can be considered as a useful online tool for spam detection.
Water Utility Mobile Application For Meter Reading: Android Based

Water utility companies have a billing process which involves reading the meter as well as knowing the consumption of its customers. The major challenge faced by water utilities in Zambia is inaccurate customer billing. Affecting hugely this inaccurate customer billing is the manual meter reading process. For most water utilities in Zambia meter reading is a very complex task. The current method for meter reading uses manual work of reading the meter and updating details of the customers. The readings are maintained in a record book and due to manual processing of data there are possibilities of generating an incorrect bill. This process cause extra work load on person who is capturing meter readings. The manual process is associated with the following challenges; transfer errors, poor handwriting, manipulation of figures, lack of analysis of readings, low productivity, time pressure, increase in non-revenue water and meter readers not visiting the property. The other problem with manual meter reading is that both the customer and the water utility company have challenges in monitoring and analyzing of consumption trends for customers and it is very difficult to monitor meter readers in the field. Although technologically advanced solutions exist, most water utilities in Zambia have no budget for them. The proposed model comprised of the android mobile application for capturing readings in the field and the web application for analysing readings and monitoring of field workers in real time. A usability test was undertaken consisting of 36 respondents which comprised of 75% meter readers and 25% customers. The results obtained from the mobile application framework, showed that the capturing, uploading, monitoring and analysis of readings were very good for the users and customers who participated in the study. Three user experience areas were used to undertake the survey namely, perceived ease-of-use, perceived flexibility and perceived information accuracy. With the android and web application customers are also able to take their own readings and view graphical usage at any time anywhere.&#x0D;
Enhanced Security Credentials for Image Steganography Using QR Code

The process of digital verification is a real needed factor in the current era of the technological world. Especially in the sector of online payment, verifying the authenticity of the user has always been a challenge and considered unsafe. A privileged process and current breakthrough of technology is the fingerprint recognition and the simplification of its usage in current smartphones and its simplicity. The aim of this work is to create a mode of digital verification that emphasis on verifying the user credentials, especially on secure payments. This is achieved by generation of a QR code by the given input fingerprint. The fingerprint link is converted to hexadecimal value and with that value, the QR code is generated. A signature of the user is saved as an image and is embedded with the QR using additive substitution and discrete wavelength transform (DWT) techniques in steganography. When a fingerprint is given as input to the fingerprint-generated and signature-embedded QR, the QR gets decoded and the given fingerprint is compared with the decoded fingerprint, now the similarity measure is compared among them, if the similarity measure is greater than the threshold set, the verification process will be successful else it asks for a digital doodle signature, now this signature is compared with the engrafted signature of the QR and again similarity of both the image is compared using the standard Image Quality Assessment (IQA) matrix.
Flaws in Strong t-Consistency

Secret sharing is a cryptographic primitive used to securely distribute a secret value S among n participants such that only predetermined subsets of these participants (called access sets) can later reconstruct S. Such a scheme is said to be secure in the information theoretic setting if an adversary with unlimited computational power cannot reduce uncertainty regarding S. Harn and Lin proposed a strong (n, t, n) secret sharing scheme which they claim is information theoretic secure. In this paper we show that this is not the case and that the notion of strong t-consistency used by Harn and Lin as well as Liu et al. actually results in an imperfect scheme that is not secure in the information theoretic setting.
Doin’ Thangs: Input, Events, and Action

If this was a book just about developing in Unity, you’d find an exercise here asking you to wire up a button that responds to a user input with some kind of action. That would be cool, and you’d feel good about your understanding of such an elegant process. However, later, when you sit down to create your own VR experience, you would find that there are many more events you have to publish and subscribe to than you realized. Further, defining each one would send you deep into tinkering with code. Plenty of developers can confidently do this with nothing but Red Bull and a neck pillow, but we are more interested in getting our apps up and running quickly so that we can rapidly prototype and share our experiences. This is why VRTK suits our needs nicely.
Adversarial Training Based Feature Selection

Feature selection is one of key problems in machine learning and data mining. It has been widely accepted that adversarial training is an effective strategy to improve the accuracy and robustness of classifiers. In this paper, in order to improve the performance of feature selection, adversarial training is also adopted, and an adversarial training based feature selection framework is proposed. To validate the effectiveness of the proposed feature selection framework, three classical feature selection algorithms, i.e. Relief-F, Fisher Score and minimum Redundancy and maximum Relevance (mRMR) are chosen and two methods are used to generate adversarial examples in experiments. The experimental results on benchmark datasets containing low-dimension and high-dimension datasets demonstrate show that adversarial training is able to improve the performance of classical feature selection methods in most cases.
THE ROLE OF BASIC CARE IN FOLLOW-UP PATIENT WITH CHRONIC PAIN

INTRODUCTION: Chronic pain can be considered a pathology and not just a symptom, which negatively influences people’s quality of life, causing a decrease in autonomy, isolation and impact on social life. In this context, considering the pain related to chronic health problems, it can be stated that Primary Care represents a strategic service due to its high capillarity and potential to identify health needs of the population, supporting the organization of care throughout the healthcare network. health services. OBJECTIVE: To discuss the role of primary care in the management of patients with chronic pain. METHOD: This is a descriptive study of qualitative approach, conducted through literature review. DISCUSSION: Social determinants can be considered to strongly impact the prevalence of chronic diseases as well as their reflexes such as pain. Social inequalities, differences in access to goods and services, low education, and inequalities in access to information generally determine a higher prevalence of chronic diseases and diseases resulting from the evolution of these diseases. In this context, Primary Care plays a fundamental role as it represents a high capillarity strategic service. CONCLUSION: Primary Care has great potential to identify the health needs of the population, supporting the organization of care throughout the health services network, contributing to factors that negatively impact the health of the population causing pain and psychological distress.
Hardware Architecture Design For Vehicle Detection

Nowadays, road safety systems based on vehicles detection are researched and become one of the important issues in Vietnam. In these systems, there are many study using CNNs which require model and many samples to train and long time in processing. In this paper, we propose an efficient method for solving this problem. This algorithm is called Background Subtraction With Gaussian Mixture Model (GMM) and implemented on FPGA - a dedicated hardware architecture. In our algorithm, all vehicle detection functions, including vehicle corner detection, vehicle region expansion, and vehicle region validation, is implemented using parallel architecture. Our testing model using a stationary camera to capture vehicles on the road and the algorithm is applied in order to detect the moving objects.
Wind disturbance elimination on dual axis solar tracker using fuzzy logic control

Abstract The use of solar energy using solar panels began to be encouraged. Solar panels utilize solar radiation and convert it into clean and renewable energy. The problems of the accuracy of the panel facing right towards radiation are a challenge in the development of a driving system. Solar panels have limited motion, which is a maximum of phi, so that wind disturbances are very dangerous for motor drives and solar panels. This paper aims to eliminate wind disturbances in solar panel drive systems. The fuzzy logic control is used to determine the amount of power given to the driving motor to direct the panel towards solar radiation. Inputs and outputs of fuzzy controllers are arranged by dividing into each of the five members. Simulation results show that the position error of solar panels without wind disturbances reaches 0.3325° in zonal and 0.5210° in meridional. By using wind disturbances, this system managed to maintain errors smaller than 0.4285° in zonal and 0.6116° in meridional. After modifying the rule base and membership function, systems show decreasing of error half of recent trial.
Choir class / Vocal ensemble

The purpose of the course is to improve the vocal-technical skills of singing and the formation of conducting-choral training as the basis for the professional formation of the leader of the ensemble / choral collective and the future music teacher.
Advanced Work Packaging in capital projects: a standardized model for EPC Contractors

The international context in which the major EPC Contractors operate is going through a period of profound transformation. The increasing complexity of the plants, the increasing costs of labor, the increasingly binding contractual requirements, have forced companies around the world to adapt to these market laws and raise the level of competitiveness through targeted business strategies. The main EP&C realities, national leader in the Oil & Gas sector, are constantly moving towards new process management techniques. The following work fits into this context by analyzing and deepening the process of breaking down the scope of work into the so-called Work Packages according to the Advanced Work Packaging methodology. AWP envisages a prioritization of the work, initially agreed between the various disciplines, with the ultimate aim of increasing performance in terms of time, cost, quality and alignment of the three macro-phases: Engineering, Procurement and Construction. After a thorough research on the previous bibliography, we analyzed the current process of management and decomposition of the scope of work. The result is an AWP application model, which, through modifications to the current management processes, provides a quantitative calculation tool to assess the amount of construction work related to a plant. The proposal is also extended to the engineering and procurement phase. This completely standardized process has a general validity and has been demonstrated through the application of two main projects. In the final part, the procedure was extended to all the types of systems made by Tecnimont, further demonstrating the extreme versatility of the methodology.
Online course pack: Understanding finance

This 10 online course pack will help you understand accounting and finance issues, including budgeting, costing, pricing and business finance.
Learning the Fingerboard

“Learning the Fingerboard” presents the means for students to understand the logic of the guitar fingerboard and master its grammar so they will be able to understand more easily and quickly the musical language used by composers. Unlike the piano, which has one location for each note, guitarists can play the same scale, chord, or cadence, in multiple locations. The Segovia scales, however—which are widely used for foundational work—don’t cover large areas of the guitar fingerboard. This section begins with the study of open-position major and minor scales and their associated cadences, major and minor moveable scale forms and related chords, and major and minor long scales, which traverse the length of the fingerboard. Harmony is studied through the working out of triads on each of the four sets of three adjacent strings. The section ends with the first modern edition of cadences in commonly used positions for each key by Franz Bathioli.