Reviewerly/exHarmony huggingface dataset:
Detection of Fraudulent Behaviour in Water Consumption using Machine Learning Algorithms

Data mining is a powerful tool widely used by organizations to enhance their businesses and gain a competitive advantage over their competitors. The data mining process helps in extracting and analysing various data patterns, information or trends from large databases. Various data mining techniques are available to conduct the data mining process. Data mining techniques are used in a variety of applications, one of which is t he detection and prevention of different types of frauds. Although there is existing research on data mining and various data mining techniques that can be used to detect and identify different types of frauds, there is little research tha t synthesizes various facets of fraud that uses the data mining techniques. This research explores the use of two classification techniques (SVM and KNN) to detect suspicious fraud water customers. The SVM based approach uses customer load profile attributes to expose abnormal behaviour that is known to be correlated with non-technical loss activities. The data has been collected from the historical data of the company billing system. To deploy the model, a decision tool has been built using the generated model. The system will help the company to predict suspicious water customers to be inspected on site.
Comprehensive Evaluation of Large-Scale Parallel Matrix Factorization Algorithms

Fast parallel stochastic gradient descent (FPSG) and non-locking stochastic multi-machine (NOMAD) are two representative matrix factorization algorithms for real-time accurate recommendation of large-scale recommender systems. To fairly ascertain the performance of FPSG and NOMAD matrix factorization algorithms, a comprehensive evaluation is presented in this paper. Streaming SIMD extensions (SSE) and different learning rate schedules are applied to evaluate the convergence performance of these two algorithms. The experimental results show that SSE can speed up the convergence performance of original NOMAD algorithm in Netflix dataset. In addition, no matter what learning rate schedules are used, FPSG algorithm has relatively good convergence results than NOMAD under the same parameters and experimental environments.
Conditional waiting-time probabilities for the nth photodection for classical and quantum light sources

Waiting-time probabilities for detecting the nth photon, given that counting commenced at the detection of a photon, for stationary classical and quantum sources are studied and compared with unconditional waiting-time probabilities.
WITHDRAWN: An extensive, multi-sensor dataset for event and fall detection in human activities that includes video recordings and detailed annotations

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IMPLEMENTASI PAIKEM PENGARUHNYA TERHADAP KOMPETENSI, KUALITAS, EFISIENSI DAN EFEKTIVITAS PEMBELAJARAN

The research aimed at developing and implementing the PAIKEM method with Student centered learning, Project Based Learningand cooperative learning, effective learning, fun Learningso the learning in the accounting department able to produce high quality human resources so able to compete in the global or international market.&#x0D; The research method was quantitative with data collection by using interview, questionnaire, documentation, triangulation from class room action research. Analysis method done with Manova to know the influence of the Paikem method implementation toward competence, quality, efficiency, and effectiveness of learning.&#x0D; The results showed that student centered learning, cooperative learning, fun learning influence insignificantly toward learning competence, while project based learning, creative learning, effective learning influence significantly toward learning competence. Then student centered learning, cooperative learning, fun learning influence insignificantly toward learning quality, while project based learning, creative learning, effective learning influence significantly to the learning quality. Then student centered learning, creative learning influence insignificantly toward the learning efficiency, while project based learning, cooperative learning, effective learning influence significantly toward learning efficiency. Toward learning efficiency. Then student centered learning, creative learning, effective learning influence insignificantly toward learning effectiveness, while project based learning, cooperative learning, fun learning influence significantly toward learning effectiveness.
Privacy preserving in big data

Due to the rapid growth of computers and the technology that is capable of capturing data, the data is increasing exponentially; they are collected from the everyday interactions with digital products or services, including mobile devices, information sensing, social media and so on. Big data gives us unprecedented insights and opportunities, but the collected big data contains a large amount of personal or sensitive information, which raises big privacy concerns. This chapter provides an extensive literature review on privacy attack models, privacy-preserving technologies and privacy metrics. We systematically analysis how the data privacy can be disclosed, what kind of privacy technology has been developed and how to evaluate the privacy provided by the proposed privacy-preserving method.
Roles and Classes

Object-oriented programming has been one of the prevailing paradigms in computing in the last few decades. It provides easy abstractions of the problem domain and a way to model it that feels natural. However, there are many ways to orient your programming to objects. As is usual in Perl 6, it does not opt for one of them: it includes them all and lets the user pick their preferred one. This style of programming does not preclude the other styles you have seen: you can do functional-style programming with objects or object-oriented style accessing functions via their class interface.
A Fine-Grained Multilingual Analysis Based on the Appraisal Theory: Application to Arabic and English Videos

The objective of this paper is to compare the opinions of two videos in two different languages. To do so, a fine-grained approach inspired from the appraisal theory is used to analyze the content of the videos that concern the same topic. In general, the methods devoted to sentiment analysis concern the study of the polarity of a text or an utterance. The appraisal approach goes further than the basic polarity sentiments and consider more detailed sentiments by covering additional attributes of opinions such as: Attitude, Graduation and Engagement. In order to achieve such a comparison, in AMIS (Chist-Era project), we collected a corpus of 1503 Arabic and 1874 English videos. These videos need to be aligned in order to compare their contents, that is why we propose several methods to make them comparable. Then the best one is selected to align them and to constitute the data-set necessary for the fine-grained sentiment analysis.
IMPLEMENTASI PROGRAM ESPERO MEMBACA SEBAGAI UPAYA OPTIMALISASI GERAKAN LITERASI SEKOLAH DI SMP NEGERI 2 COLOMADU

The study aims to describe the planning, implementation, supporting, factors and inhibiting factorcs in the implementation of the espero, reading program as an effort of the literacy movement in SMP Negeri 2 Colomadu. Data is collected by interviewing, filling out questionnaires and documents. The data is than analyzed using an interactive model, with stgaes of data reduction, data presentation, and data verification. The result showed that the planning of the espero reading program was carried out with meetings and outreach in the form of pamphlets abd leaflets, the impletation of the espero program to read local, regional, national, newspapers, and ended with a prize quiz. The supporting factors of the espero reading program are, (1)scholl community awareness about the importance of literacy culture, (2) newspaper facilitie, waste banks and places, (3) student activity, (4) support form print media parties, (5) socialization, (6) quiz prizes , and factors inhibiting the reading espero program faced by students and teachers in implementing GLS are (1) instuructions and directions of the teachers that are not clear because students learn to talk alone, (2) lack of interest in reading students because there are some students who don’t like to read, (3) student arrive late, (4) the time given is still lacking, (5) lack of motivations, and enthusiasm of students.
OTS: An Optimal Tasks Scheduling Algorithm Based on QoS in Cloud Computing Network

Cloud Computing has emerged as a service model that offers online accessible resources to the clients.These resources contain storage, servers, and other applications and it provides security, flexibility, and scalability.In Max-Min algorithm where the large tasks have their priority to be scheduled first this leads small tasks to stay longer in the queue until all huge tasks finished their execution.This study presents an optimal tasks scheduling algorithm by enhancing Max-Min algorithm.The simulation results have proven that the Proposed Optimal Tasks Scheduling OTS completes tasks execution with less execution time and higher performance compared with Max-Min and TS algorithms.The overall results show that the performance of the proposed algorithm achieved 6% better in terms of time execution compared of both of Max-Min and TS algorithms
Security of marine-information system

This chapter starts from the security demand of marine-information system to emphatically introduce the main problems in the marine-information system, including wireless-communication security, secure sharing of information, big data security and military-civilian coordination, centers on the marine information security system to discuss the technology and method of guaranteeing the security of marine-information system from the aspects of communication network security, computing environment security, data and application security, security monitoring and forewarning and security support. In addition, it lays emphasis on analyzing and introducing the required key theories and technologies of the network space security for marine-information-system design.
Efektivitas Expressive Writing Untuk Menurunkan Kecemasan Pada Mahasiswa Fresh Graduate Yang Sedang Mencari Kerja

The purpose of this study is to determine the effectiveness of expressive writing to reduce anxiety in fresh graduate students who are looking for work. The hypothesis is that there is an effect of providing expressive writing training with a decrease in anxiety in fresh graduate students who are looking for work. The population in this study were fresh graduate students who were looking for work with a sample of 4 people. The sampling technique used was purposive sampling. The method used is an experiment with a measuring instrument in the form of Work Search Anxiety Scale and Expressive Writing Module. Data analysis was performed with the Wilcoxon Signed Ranks Test analysis. Based on the results of data analysis, it was obtained that the Test Statistic value was 1,461 with sig (2-tailed) = 0,144 (p ≤ 0.05) meaning that there was no significant effect between expressive writing training and decreased anxiety in looking for fresh graduate student work. Factors that influence expressive writing are not effective in reducing anxiety, namely lack of social support from the family, lack of achievement of insight on the subject, and not fulfilling writing characteristics
Challenges For Modernization Of Journalism Education In Russian Universities

The article deals with the challenges of journalism education in modern Russia and the necessity for its modernization. It analyzes the causes of education crisis and the ways of tackling the identified problems. The authors argue the significance of practice-oriented learning (PBL) and the advanced study of media production by the future journalists. PBL generates different competences of future specialists in terms of developing professional, social and personal values. Like many news outlets, journalism education programs are evidently unprepared to respond to such profound structural transformation of the environment. The study indicates that there is a crucial demand in expanding technology training and changing media emphasis tracks. Strenuous PBL approaches allow students to skill-up quickly so that they can spend more time applying skills to real life situations. Employability is a central concern of the current study. Educators owe it to their students to give them the skills to acquire a satisfying career and to be lifelong learners so they can grow with and adapt to an economy that no one can predict. Teachers need to think about and actively prepare students for the world of work. The research revealed the need for a variety of skills such as technical knowledge, habits of mind like problem solving, and social competences like teamwork and communication as a part of an integrated whole.
Image Super-Resolution Model Based on Bypass Convolution and Feature Weighting

Image super-resolution(SR) reconstruction aims at reconstructing corresponding high-resolution images from low-resolution images. Methods based on deep CNN have achieved distinguished performance recently. Among these methods, those based on the single-layer features cannot get top reconstruction results since shallow features are ignored, and those based on multi-layer features need to discriminate good and poor features. To address this issue, we propose a new model, BySEDenseSR (Bypass Convolution Squeeze Excitation Dense). Specifically, We use a squeeze excitation block that learns to assign appropriate weights based on the quality of features. This provides an effective way to suppress the effects of poor features. Furthermore, using bypass convolution, BySEDenseSR reduces the forwarding noise, which improves the stability of middle-layer features. Experiments show that compared to LapSRN, BySEDenseSR improves its peak signal-to-noise ratio (PSNR) by 0.16dB, 0.08dB and 0.03dB respectively on Set5, Set14 and BSD100, at a magnification of 4×.
An Education Profile Model Applied in the Context of Recommender Systems

The systems used in education have evolved bringing new teaching approaches and impacting in traditional learning methods. Also, they present new scenarios to students aiming to improve activities and practices in online systems. Along with this evolution the growing availability of contents has promoting an overload of data. Nowadays, many online educational systems have too much information, content and activities available to students making choices difficult. Educational systems supported by recommender systems allow to offer contents toward the needs and profiles of the students. This work presents a student profile model based on students' preferences and their interactions in online educational systems, with the purpose of allowing the recommendation of contents. To demonstrate the feasibility and evaluation of the proposed model two study scenarios were developed with information from an educational institution. In these scenarios recommendations were carried out using collaborative filtering and content based approaches. From the evaluation of these scenarios, the results demonstrate the viability of the model in producing recommendations that aim to aid the students' learning process when interacting with online educational systems.
Research on the Intelligent Unmanned Vehicle Measurement System

With the expansion of cities and the development of modern life, the traditional vehicle-mounted measurement control system has been difficult to meet the measurement demand in some cases. In order to meet the requirements of vehicle-mounted measurement intelligence and solve the problems of complicated and refined measurement tasks, an intelligent unmanned vehicle-mounted measurement system is proposed. This paper is based on artificial intelligence technology, unmanned vehicle as a platform, the control system modular design, realized unmanned vehicle measurement. This paper presents part of the data obtained from the current manned vehicle measurement, briefly introduces the control system, and discusses the advantages of the intelligent unmanned vehicle measurement system. This study provides some suggestions for the development of intelligent unmanned vehicle measurement equipment.
Describing the Body in New Terms: An Examination of 3D Body-Scanning Technology and Language Use

The current study examined the effects of 3D body scanning technology and language use.The researchers conducted a qualitative experiment that compared 2D and 3D body scans.Results indicated that the technology changed how participants talked about their bodies.Objectification theory was used to interpret the findings.
Squeezed Light Detection Using Quantum Imaging

We propose a method to measure the noise in squeezed light field. We analyze appropriate spatial correlations using quantum imaging, and reduce the effect of pump fluctuations that override the quantum statistics of the field.
End User Commentary on Emerging Approaches in the Analysis of Inks on Questioned Documents

Forensic analysis of inks in a police laboratory aims to clarify for judicial or civil purposes: (a) whether a document has been tampered; (b) the correlation between documents; (c) the correlation between a document and a writing instrument and (d) the correlation between a document and a printing device. To this end, the study, analysis and investigation of the documents’ inks are used in order to address the questions formulated by the criminal investigation or by the court, thus contributing to the resolution of crimes associated with the falsification and counterfeiting of documents such as mockery, forgery of documents, fraud or threats. The forensic analysis of documents in this context encompasses not only the analysis of inks but also the characterization, identification and differentiation of various materials such as paper, glues, coatings, laminates, waxes, amongst others, for which it is necessary to use the traditional imaging techniques and advanced analytical methodologies.
LibGuides: Research: Using "Libguides"

Starting research can be difficult. These resources are specifically built and provided to help you become a better researcher and find what you need.
Using Blockchain for Reputation-Based Cooperation in Federated IoT Domains

The convergence of Internet of Things and Multi-Agent Systems also relies on the association of software agents with IoT devices to benefit from their social attitude to cooperate for services. In this context, the selection of reliable partners for cooperation can be a very difficult task if IoT devices migrate across different domains. To this purpose, we introduce the Reputation Capital model and an algorithm to form agents groups in each IoT federated domain, on the basis of the reputation capital of each agent, to realize a competitive framework. A further essential contribution consists of adopting the blockchain technology to certify the reputation capital of each agent in each federated environment. To verify that the individual reputation capital of devices and, consequently, the overall reputation capital of the IoT community can benefit from the adoption of the proposed approach, we performed some experiments. The results of these experiments witnessed that, under certain conditions, almost all the misleading agents were detected. Moreover, the simulations also have shown that, by adopting our reputation model, malicious actors always pay for services significantly more than honest devices.
Prediction Theory for Stationary Random Signals

Prediction (or forecasting) of future values of the stationary random signals based on the known past depends on the functional analytic tools from Hilbert spaces. Essentially, the optimal predictor is an orthogonal projection of the future values of the signal onto the space spanned by the past values. The chapter presents the relevant Wold decomposition theorem, and an application of the Spectral Representation to the solution of the optimal prediction problem.
Surveying the potential of using speech technologies for post-editing purposes in the context of international organizations: What do professional translators think?

The present study has surveyed professional translators working in six international organizations in order to know more about their views and attitudes with regard to new translation workflows involving two different types of technologies, i.e. machine translation and speech recognition. The main aim of this survey was to identify how feasible it is to implement new post-editing workflows in an international organization using speech as an input method to edit inaccurate machine translation outputs. Overall, the results suggest that the surveyed translators do not hold a negative view on the use of ASR as part of their translation workflow, which provides a promising first step towards investigating the integration of speech based post-editing to translation workflows for productivity and ergonomic gains.
Sound, teknik och roller : Ett utforskande av gitarrens uttrycks- och soundmöjligheter i en ensemble

In this project, Mattias Olofsson has composed and performed music for an ensemble of varying instruments, focusing on different musical roles for the guitar. The music was presented in a concert h ...
Direct Sum Testing: The General Case.

A function $f:[n_1]\times\dots\times[n_d]\to\mathbb{F}_2$ is a direct sum if it is of the form $f\left(a_1,\dots,a_d\right) = f_1(a_1)\oplus\dots \oplus f_d (a_d),$ for some $d$ functions $f_i:[n_i]\to\mathbb{F}_2$ for all $i=1,\dots, d$, and where $n_1,\dots,n_d\in\mathbb{N}$. We present a $4$-query test which distinguishes between direct sums and functions that are far from them. The test relies on the BLR linearity test (Blum, Luby, Rubinfeld, 1993) and on an agreement test which slightly generalizes the direct product test (Dinur, Steurer, 2014). In multiplicative $\pm 1$ notation, our result reads as follows. A $d$-dimensional tensor with $\pm 1$ entries is called a tensor product if it is a tensor product of $d$ vectors with $\pm 1$ entries, or equivalently, if it is of rank $1$. The presented tests can be read as tests for distinguishing between tensor products and tensors that are far from being tensor products. We also present a different test, which queries the function at most $(d+2)$ times, but is easier to analyze.
L’analyse de mélange de code utiliser par les étudiants école du post maitrise département de français comme multilingue sur WhatsApp

&lt;p class="Keyword"&gt;This study analyses the use of&#x0D; the code mix by students in the French School of Post-Masters department. The&#x0D; design of this study is a descriptive qualitative design. Source of the data of&#x0D; this study is the Whatsapp text. The researcher collects the data by screen&#x0D; capture of the text in Whatsapp and transcription. In analyzing the data the&#x0D; researcher used three steps based on Norman in Pitriyani (2007: 21), They are,&#x0D; (1) make the data classification based on types of code mix, (2) make the&#x0D; classification based on the cause factors of code mixing, and (3) find the&#x0D; percentage of each type of code mixing by the Bugin’s formula. The result of&#x0D; this study shows that the type of code mix that frequently occurs is the&#x0D; insertion of words, followed by the insertion of an expression. While the cause&#x0D; of the code mixing factor shows this situation as the most dominant factor in&#x0D; the code mixing, followed by the talking factor of speaker and partner.&lt;/p&gt;
Space-Based Global Quantum Internet

We consider a satellite constellation for global entanglement distribution. We simulate the constellation’s dynamics and estimate entanglement bit rates between earthbound receivers connected by quantum repeaters hosting multimode quantum memories.