Reviewerly/exHarmony huggingface dataset:
Teaching English speaking for FCE: using Facebook as a tool of instructional practice

The current paper intends to describe the practice and analyse the results of using social networking sites as an additional extra-class tool of developing competence in Speaking in the course of preparation for the well known international exam in English: First Certificate in English. The aim of this paper is to prove the hypothesis that a social media as an effective tool to teach English speaking for upper-intermediate learners to pass the FCE exam and to examine the offered practice experimentally. The study has proven the hypothesis and provided the experimental research. Theoretical (analysis and synthesis), empirical (observation, testing, conducting pedagogical experiment) and statistical (one sample t-test) methods were used to achieve the stated aim. The main results show that the significant difference was observed in the experimental group of 24 Kharkiv non-linguistic university students of the same age where the experiment under the title All in the Same Boat' started on Facebook and was carried out in 2018/2019 academic year. Furthermore, comparing the test results according to 5-band scale in four different criteria at the different stages of the course allowed to compare the development rate of the checked English-Speaking skills. The resulting data confirmed the improvement in students' performance in Speaking test on average in 21.8 % during the first term, and in 29.1 % after the experiment started, overall progress being 57.3 % that is a substantial increase. The authors' experience is significant in the world learning context as it proves the effectiveness of using social media to teach English speaking for upper-intermediate learners to pass the First Certificate in English exam.
From Concept to Practice

Good information security governance will ensure that information is adequately protected. An organization needs a holistic policy framework that assists in providing guidance to ensure that implementations are in line with strategic goals. However, there is little guidance in practically implementing the information security framework that includes the direct-control cycle. This paper sets out to breakdown the direct-control cycle to reveal practical components in implementing strategic, tactical and operational policies in organizations through a literature survey. The output of this paper is a conceptual breakdown of the direct-control cycle that could be used in organizations.
SURFACE STRATEGY TAXONOMY ON FOREIGN LANGUAGE WRITING: A STUDY ON VERB TENSE USAGE

This study is aimed at analyzing errors of verb tense usage found in the learners’ writing production. The second semester students of English Department, STAIN Gajah Putih Takengon enrolled in Writing II course were taken as the participants in this investigation. Eight narrative paragraphs were scrutinized closely to detect errors pertaining to verb tense. In this case, a classification of errors proposed by Dulay, Burt, and Krashen (1982 in Ellis and Barkhuizen, 2005) called Surface Strategy Taxonomy is applied. It comprises four sorts of errors: addition, omission, misformation, and misordering. The finding reveals that the learners’ errors encompass three types of four aforementioned above, i.e. addition, omission, and misformation. Among those, misformation is found to be the most prevalent type commited by the learners, as many as 62 errors making up 72.94 % of all. It was subsequently followed by omission and addition which were 13 errors (15.29 %) and 10 errors (11.77 %) successively. Whereas misordering was not identified among the learners’ errors on paragraph composition. Eventually, a pedagogical implication as a result of this research was made. English instructors are expected to accentuate more on likely-to-produce-errors items to the learners prior to composing a paragraph.
An Algorithm for String Searching

Many problems encountered require string searching to solve them.Thus, string searching algorithms are important.They play the vital role in various fields and applications, including text editing, finding part of DNA in bio informatics engineering, text searching, computer security, linguistics, artificial intelligence and web search engines.In this paper, a string searching algorithm is proposed.The proposed algorithm aims to improve the brute-force searching algorithm.It finds all the occurrences of a pattern within a given text.The pattern and the text are to be preprocessed before the actual searching starts.
FPGA-Based Echo-State Networks

TheSkibinsky-Gitlin, Erik S. hardwareAlomar, Miquel L. implementationCanals, Vincent of EchoFrasser, Christiam F. StateIsern, Eugeni NetworksGalán-Prado, Fabio (ESN) canMorán, Alejandro beRoca, Miquel appliedRosselló, Josep L to situations where a quick response is needed in relation to how a certain signal will evolve. This is due to the possibility of connecting the ESN’s neurons in parallel, which accelerates the calculation process considerably. In this article, we present a proposal for the compact implementation of ESN in Field Programmable Gate Arrays (FPGAs). To maximize the number of neurons, the synapses are implemented using adders and multiplexers instead of multipliers. The hardware implementation has been tested for the prediction of the Santa Fe time-series dataset. The proposed approach allows for significant savings in terms of energy, hardware resources, and computing time compared to other recently published solutions.
Mining User’s Data Based on Customer’s Rating for Prediction and Recommendation—A Comparative Analysis

The business of E-commerce is increasingly becoming popular due to pervasive Internet technologies. It is a human tendency to rely on the data or information, which they receive from their friends and neighbours prior to taking any decision, especially before purchasing any item. Presently, people are getting vast information and worldwide data though Web. Due to information overload, customers often face difficulties to locate their item of interest. Recommender system plays a significant role, and it helps to deal with information overload and further provides personalized recommendations to customers or users. In this paper, recommendation of smartphone was given based on feedback given by customer using weighted mean approach. The prediction was calculated for untried items, based on ratings given by new user using collaborative filtering. The results of recommendation and prediction show the approach is interesting.
The Motivation of Russian and Kazakhstani Faculty Members in the Cross-Cultural Context

Background &amp; Objective: The motivation of university faculty members in a cross-cultural context is one of the main issues in the context of internationalization of higher education. This research aims to explore if there are significant differences in motivational drivers between Kazakhstani and Russian university faculty members based on their cultural background. Methods: The research involves 158 university faculty members from Kazakhstan and Russia. The research applies cross-survey methodology. Results: The findings on the main motivational themes show that Kazakhstani university faculty members have a higher orientation to security and stability and integration of lifestyle. Russian university faculty members have higher levels of autonomy, challenge and entrepreneurship. Conclusion: The conducted research presented the main motivational drivers of Kazakhstani and Russian faculty. It is evident that Kazakhstani and Russian university faculty members have significant differences in motivational profiles, despite the shared Soviet past. Research showed that Russian faculty is motivated by creativity and challenges, whereas their Kazakhstani counterparts seem to be more focused on the security and work-life balance. Nevertheless, the occupational peculiarities show similarities in the attitudes to money and power.
The Assessment Strategy for Selecting and Evaluating Geoenvironmental Remediation

A large volume of oil-contaminated sand remains in the Kuwaiti deserts, causing threat to the groundwater and ecological system.The main aims of this research are to evaluate the situation of Kuwaiti oil lakes and identify the impact of contaminated soil on ecology and humans in Kuwait.This consists of two phases; the first phase summarises the results from field demonstrations and discusses the prospective of using different techniques for remediation of the oil-contaminated soil in Kuwait, while the second phase aims to compare and select the appropriate soil remediation techniques based on UN requirements.In this chapter, decision mechanism was carried out in compliance with the House of Quality (HOQ ) analysis system.The total weighted score for each soil remediation method was determined to obtain the final decision.
Computer USB-Mouse Emulation Using EOG

In this work an analog frontend was developed which allows to evaluate the EOG (electrooculogram) signals in a microcontroller and convert them into position changes of a computer mouse. A drift compensation system overcomes the most common problem of EOG measurements, the baseline drift. Different approaches for how to operate the mouse have been tested, whereby the method of controlling the mouse by giving single commands with defined movements gave the most promising results.
A Genetic Algorithm Design Based on Self-Organizing Dynamic Network

In order to improve the population diversity and convergence performance of genetic algorithm, a self-organizing dynamic network model is introduced into the neighborhood structure of genetic algorithm. In order to evaluate the importance of network nodes more completely and effectively, a new definition of exponential network node fitness is given firstly, which considers the ranking of the objective function value of nodes in neighbor nodes and the number of neighbor nodes. Then, three kinds of topology updating rules, i.e. double production, single production and selective deletion, are proposed to make the network topology evolve dynamically with the evolution of genetic algorithms. Test results of these typical optimization functions show that the genetic algorithm designed in this paper is superior to standard genetic algorithms and small-world genetic algorithms in population diversity and convergence performance.
Resource management for moldable parallel tasks supporting slot time in the Cloud

Moldable parallel tasks are widely used in different areas, such as weather forecast, biocomputing, mechanical calculation, and so on.Considering the deadline and the speedup, scheduling moldable parallel tasks becomes a difficulty.Past work majorly focuses on the LA (List Algorithms) or OMA (Optimizing the Middle Algorithms).Different from prior work, our work normalizes execution time and makes all tasks have the same scope in normalized execution time: [0,1], and then according to the normalized execution time, a method is used to search for the reference execution time without considering the deadline of tasks.According to the reference execution time, we get an initial scheduling result based on AFCFS (Adaptive First Comes First Served) policy.Finally, a heuristic approach is used to improve the performance of the initial scheduling result.We call our method HSRET (a Heuristic Scheduling method based on Reference Execution Time).Comparisons to other methods show that HSRET has good performance in AWT (Average Waiting Time), AET (Average Execution Time), and PUT (Percentages of Unfinished Tasks).
PROTOTYPE SISTEM SMART LOCK DOOR DENGAN TIMER DAN FINGERPRINT SEBAGAI ALAT AUTENTIKASI BERBASIS ARDUINO UNO PADA RUANGAN

Security is a matter that must be often ignored by most people and considers it safe, but in fact someone can still lose his valuables. For example in a room where security is often considered good by most people just by locking the door provided, but often people forget to lock the door. Because forgetting to lock the room door causes someone to lose his valuables. The development of technology that has increasingly sophisticated door security systems must keep abreast of the times. Room door security systems that are currently still using conventional methods are considered insecure at this time, even though there is already a CCTV camera that has been used to monitor the room. Therefore the media is used to make a room safer by locking the room with a timer and fingerprint. If the room occupant forgets to lock the door, the automatic door is locked according to the time specified. When in the room the door will not be locked, but if the occupants want to leave the room and forget to lock the room is automatically locked and when you want to open it using only fingerprints. In research conducted by researchers used a qualitative approach, namely by explaining the problem more specifically to the data or facts obtained. For fingerprint data before use, register is done so that fingerprint data is registered on the system and can be used.Keywords : Autentifikasi, Fingerprint, Timer
Multivariate Bernoulli Logit-Normal Model for Failure Prediction

&#x0D; &#x0D; &#x0D; The failures among connected devices that are geographically close may have correlations and even propagate from one to another. However, there is little research to model this prob- lem due to the lacking of insights of the correlations in such devices. Most existing methods build one model for one de- vice independently so that they are not capable of captur- ing the underlying correlations, which can be important in- formation to leverage for failure prediction. To address this problem, we propose a multivariate Bernoulli Logit-Normal model (MBLN) to explicitly model the correlations of devices and predict failure probabilities of multiple devices simulta- neously. The proposed method is applied to a water tank data set where tanks are connected in a local area. The results indicate that our proposed method outperforms baseline ap- proaches in terms of the prediction performance such as ROC.&#x0D; &#x0D; &#x0D;
Reconfigurable entangled photon source (Conference Presentation)

The quantum information community is entering a period in which scientists and engineers are transitioning from ‘understanding’ to ‘control’ by harnessing aspects of quantum mechanics to realize capabilities in computing, sensing, and communication that are not possible in the classical world. Although many of these quantum technologies are still in their very early stages, it is clear that our future world will include many quantum devices. The existence of multiple devices will, in turn, necessitate the transfer of quantum information between devices—if isolated devices are useful, it follows that connected devices will be even more useful. Therefore, it is imperative to develop the resources needed for connecting quantum devices at different locations. One such resource is quantum entanglement, a physical phenomenon in which two or more quantum systems cannot be described independently, even when separated by large distances. Entanglement is an important resource for quantum computing and is critical for overcoming loss constraints that limit the transfer of quantum states across large distances. The latter can be accomplished via ‘quantum repeaters,’ which propose to connect multiple shorter entangled photon links to form a longer entangled photon link. Much of our understanding of entanglement comes from experiments involving entangled photon pairs, which are still the best candidates for the exchange of quantum information across any appreciable distance. Since the 1990s, spontaneous parametric downconversion (SPDC) has been established in the academic and research community as a reliable source of entangled photon pairs. During this time, source brightness and stability has improved considerably over the first demonstrations. Yet, entangled photon sources are still built primarily by graduate students, and there is significant variability among sources. Moreover, SPDC entangled photon sources lack flexibility, typically designed to output a single type of entangled state. In this paper we report on the efforts to develop a ‘user-programmable’ entangled photon source capable of producing any type of two-photon entangled state. The goal is a source capable of emitting photon pairs with user-defined polarization states. That is, the user will be able to adjust the probability amplitudes {𝛼,𝛽,𝛾,𝛿} in the general expression for a two-photon polarization state, |𝜓⟩=𝛼|𝐻𝐻⟩+𝛽|𝐻𝑉⟩+𝛾|𝑉𝐻⟩+𝛿|𝑉𝑉⟩, thereby accessing any point in the two-photon polarization entanglement Hilbert space. This requires a mapping between the experimentally controllable parameters and the probability amplitudes listed above. We will describe this mapping for our particular experimental setup and will share results showing the states that our system is able to access.
Researches regarding pesticides and it's metabolites dynamics founded in vegetable raw materials in 2014 year and assessment of human health risks

The explosive increase in adopting cloud services leads to the need for accommodating millions to even billions of servers in the supporting infrastructure of data center networks. Thus, providing highly scalable and noticeably fault-tolerant interconnecting architectures with great network capacity, limited delay, and reasonable energy consumption has become of paramount importance. In this paper, Crystal, a server-centric and recursively constructed structure, is presented. Crystal is made out of building blocks inspired by vertex configuration pattern of Archimedean solids and is intrinsically fault-tolerant mainly due to the adoption of multihoming mechanism in the building block. Crystal also scales double exponentially owing to its recursively defined architecture. Furthermore, to increase the routing efficiency and manage different kinds of failures in the network, two exclusively designed routing algorithms are proposed. Theoretical analysis and simulation results all witness that Crystal is highly fault-tolerant and can provide good network capacity and low latency to support delay-sensitive and data-intensive applications. Generally, Crystal satisfies a reasonable trade-off between all the major goals of designing a cloud data center network.
From Personalization to Privatization: Meta Matrix Factorization for Private Rating Predictions.

Matrix factorization (MF) techniques have been shown to be effective for rating predictions (RPs) in personalized recommender systems. Existing MF methods use the same item embeddings and the same RP model for all users, while ignoring the possibility that different users may have different views about the same item and may favor different RP models. We introduce a novel MF framework, named meta matrix factorization (MetaMF), that generates private item embeddings and RP models. Given a vector representing a user, we first obtain a collaborative vector by collecting useful information from all users with a collaborative memory (CM) module. Then, we employ a meta recommender (MR) module to generate private item embeddings and a RP model based on the collaborative vector. To address the challenge of generating a large number of high-dimensional item embeddings, we devise a rise-dimensional generation (RG) strategy that first generates a low-dimensional item embedding matrix and a rise-dimensional matrix, and then multiply them to obtain high-dimensional embeddings. Finally, we use the generated model to produce private RPs for a given user. Experiments on two benchmark datasets show that MetaMF outperforms state-of-the-art MF methods. MetaMF generates similar/dissimilar item embeddings and models for different users to flexibly exploit collaborative filtering (CF), demonstrating the benefits of MetaMF.
The Predator in Your Pocket: A Multidisciplinary Assessment of the Stalkerware Application Industry

The authors would like to offer our sincere thanks to Open Society Foundations, John D. and Catherine T. MacArthur Foundation, Ford Foundation, the Sigrid Rausing Trust, the Oak Foundation, the Australian Communications Consumer Action Network (ACCAN), as well as the Office of the Privacy Commissioner of Canada’s Contributions Program, whose generous funding made this report possible.
ANALISIS PASSWORD CRACKCING MNEGGUNAKAN GPU PROCESS

Data security is one thing that will not be lost in line with the development of digital technology. One of the simplest data security methods is providing passwords or keywords to the data that we want to secure from the hands of irresponsible people. Even so this method does not fully guarantee that our data will not be hacked by hackers because they already have many techniques to break through this security. One way is to use brute force techniques. In this paper, researchers are observing how much influence overclocking a computer graphics card when it is used to do password cracking. The results of the analysis will be useful for optimizing computer graphics cards for password cracking. As well as this analysis is expected to be used as a reference to learn more about computer hardware systems and data security.
Fuzzy Logic Approach to Improving the Digital Images Contrast

In this paper, methods of increasing the contrast of digital images based on fuzzy logic as soft computing technique are considered. The existing classical methods of increasing the contrast, such as the minimum-maximum linear contraction stretching, the general and adaptive methods of equalization of the histogram, the methods for increasing the contrast of the fuzzy sets “white pixel” and “gray pixel” are analyzed. For comparing analysis all methods were evaluated using metrics such as contrast per pixel, Lab Variance, and peak signal-to-noise ratio. The analysis of these methods revealed their advantages and disadvantages: (a) equalization methods greatly increase the contrast, but deform the color component, and also add artifacts to images, in turn, (b) methods based on fuzzy logic less increase contrast, but lack disadvantages in the deformation of the color component. In this paper, a combination of “white pixel” and Gamma-Correction methods is proposed, that leads the brightness of the image to the average, and then increases the contrast of the image based on fuzzy logic technique
Learning Bivariate Functional Causal Models

Finding the causal direction in the cause-effect pair problem has been addressed in the literature by comparing two alternative generative models X → Y and Y → X. In this chapter, we first define what is meant by generative modeling and what are the main assumptions usually invoked in the literature in this bivariate setting. Then we present the theoretical identifiability problem that arises when considering causal graph with only two variables. It will lead us to present the general ideas used in the literature to perform a model selection based on the evaluation of a complexity/fit trade-off. Three main families of methods can be identified: methods making restrictive assumptions on the class of admissible causal mechanism, methods computing a smooth trade-off between fit and complexity and methods exploiting independence between cause and mechanism.