Reviewerly/exHarmony huggingface dataset:
Enhancing Side Channel Attack-Resistance of the STTL Combining Multi-Vt Transistors with Capacitance and Current Paths Counterbalancing

Differential power analysis (DPA) exploits the difference between the instantaneous power of the circuit arches transitions to stole the state as information aiming to unveil the cryptographic key. Secure triple track logic (STTL) is a circuit-level countermeasure to DPA attacks based on dual-rail precharge logic (DPL). STTL is robust to attacks due to the delay in an insensitive feature that mitigates the logic glitches generated by the different path delays that lead to the logic gate inputs until they stabilize. The main STTL drawback, however, is the asymmetry of the transistor topology. Asymmetry causes unbalanced internal capacitances and different internal paths for the current flow, and DPA exploits it as a source of information leakage. Our work proposes three circuit topologies, combining multi-Vt transistors with a circuit counterbalancing strategy, aiming to improve the STTL DPA attack-resistance. Data encryption standard substitution-box circuit, designed in a TSMC 40 nm CMOS process, is our application case study to evaluate the DPA attack-resistance. Results gathered at the application-level show that our proposals outperform DPA attack-resistance of the prior work.
A Privacy Preserving Data Publishing Middleware for Unstructured, Textual Social Media Data

Privacy is going to be an integral part of data science and analytics in the coming years. The next hype of data experimentation is going to be heavily dependent on privacy preserving techniques mainly as it’s going to be a legal responsibility rather than a mere social responsibility. Privacy preservation becomes more challenging specially in the context of unstructured data. Social networks have become predominantly popular over the past couple of decades and they are creating a huge data lake at a high velocity. Social media profiles contain a wealth of personal and sensitive information, creating enormous opportunities for third parties to analyze them with different algorithms, draw conclusions and use in disinformation campaigns and micro targeting based dark advertising. This study provides a mitigation mechanism for disinformation campaigns that are done based on the insights extracted from personal/sensitive data analysis. Specifically, this research is aimed at building a privacy preserving data publishing middleware for unstructured social media data without compromising the true analytical value of those data. A novel way is proposed to apply traditional structured privacy preserving techniques on unstructured data. Creating a comprehensive twitter corpus annotated with privacy attributes is another objective of this research, especially because the research community is lacking one.
Quasi-Newton Trust Region Policy Optimization

We propose a trust region method for policy optimization that employs Quasi-Newton approximation for the Hessian, called Quasi-Newton Trust Region Policy Optimization QNTRPO. Gradient descent is the de facto algorithm for reinforcement learning tasks with continuous controls. The algorithm has achieved state-of-the-art performance when used in reinforcement learning across a wide range of tasks. However, the algorithm suffers from a number of drawbacks including: lack of stepsize selection criterion, and slow convergence. We investigate the use of a trust region method using dogleg step and a Quasi-Newton approximation for the Hessian for policy optimization. We demonstrate through numerical experiments over a wide range of challenging continuous control tasks that our particular choice is efficient in terms of number of samples and improves performance
INVESTIGATING ENGLISH DEPARTMENT STUDENTS’ FOREIGN LANGUAGE SPEAKING ANXIETY: A CASE STUDY IN UNIVERSITAS AIRLANGGA, INDONESIA

Anxiety during a speaking performance is a common phenomenon experienced by any EFL learners, including students majoring in English. Focusing on the issue, this study investigates the correlation between students’ foreign language speaking anxiety and speaking achievement. Moreover, this study also observes the levels and the sources of the speaking anxiety among the English Department’s fifth-semester students of Universitas Airlangga. This study used the Foreign Language Speaking Anxiety Scale (FLSAS) by Öztürk and Gurbuz (2014). The FLSAS questionnaire was distributed to 114 students in order to explore the correlation between speaking anxiety and speaking achievement, the speaking anxiety levels, and the speaking anxiety sources. The data collected through questionnaire were analyzed with SPSS 25.0. Pearson Product Moment Correlation isused to determine the correlation, while descriptive statistic alanalys is isused to investigate the levels and the sources for speaking anxiety. Horwitz, Horwitzand Cope’s(1986) theory and Horwitz and Young (1991) about the source and the levels of foreign language speaking anxiety are also used in this study. This study found that there is a significant negative correlation between speaking anxiety levels and speaking achievement. This means the higher the speaking anxiety they experience, the lower the achievement score they get. Most of the students have moderate levels of speaking anxiety, which is mainly due to the fear of negative evaluation.This study indicates that although the EFL learners are often exposed to English, they still experience speaking anxiety. These findings suggest that the lecturers should be more aware of students’ anxiety and use strategies that might encourage the students to speak more confidently.
Construction of risk prediction model for acute type A aortic dissection

ObjectiveTo analyze the risk factors associated with acute type A aortic dissection, and to establish an effective predictive scoring model for early clinical intervention.MethodsA retrospective review of 200 patients diagnosed as acute type A aortic dissection in the Department of Emergency, Guangdong Provincial People's Hospital between April 1, 2012 and March 31, 2017 was conducted as a modeling group. There were 160 males and 40 females with age of (53.30 ±13.19) years. According to the criteria of dissection rupture within 72 h after CTA examination, patients were divided into a rupture group (100 cases) and an unruptured group (100 cases). A prediction model of rupture risk was established based on the multivariate Logistic regression analysis of the risk factors of acute A-type aortic dissection in the early stage. After the establishment of the model, a prospective review of 80 patients diagnosed as acute type A aortic dissection in our hospital between April 1, 2017 and May 31, 2018 was conducted as a validation group. There were 57 males and 23 females with age of (54.00 ±13.68) years. In the validation group, there were 53 patients with rupture and 27 patients without rupture. Furthermore, this model was verified in the validation group. The scores were divided into low-risk rupture and high-risk rupture according to the best cut-off value of the receiver operating model curve of the modeling group.ResultsLogistic regression analysis showed that 10 factors were finally established the rupture risk prediction score model. The factors were as following: age >63 years (2 points), women (2 points), ventilator assisted ventilation (3 points), AST >80 U/L (2 points), no distortion of the inner membrane (2 points), diameter of the aortic sinus >41 mm (1 point), maximum diameter of the ascending aorta >48 mm (1 point), ratio of false lumen area to true lumen area >2.12 (2 points), Lac >1.9 mmol/L (3 points), and WBC >14.2×109 /L (1 point). The results of validation showed that the scoring model had a high predictive value (AUC = 0.928, 95% CI: 0.872-0.984, P < 0.001) and goodness of fit (Hosmer-Lemeshow χ2 = 8.331, P = 0.402). Moreover, the scoring model was further divided into low-risk (0-6 points) and high-risk (7-19 points), with sensitivity of 83.0% and specificity of 86.0%.ConclusionsThe predictive model of dissection risk in the acute type A aortic dissection constructed within 72 h after CTA is helpful for the evaluation of the disease and early intervention, and has certain clinical application value.Key words: aortic dissection; rupture; risk factors; risk score; model
Install and Configure Docker on Linux

I still cannot believe I’m writing this chapter – about Linux, for SQL Server DBAs. In Chapter 1 , I mentioned how Microsoft brought SQL Server to Linux in 2017. That came as a big surprise to a lot of SQL Server DBAs who have only known SQL Server as a relational database engine that runs on a Windows operating system. But just like any technological innovation, you can either choose to embrace it or ignore it. Embracing it gives you an opportunity to grow and take your career to a whole new level.
Multilayer extreme learning machine for hand movement prediction based on electroencephalography

Brain computer interface (BCI) technology connects humans with machines via electroencephalography (EEG). The mechanism of BCI is pattern recognition, which proceeds by feature extraction and classification. Various feature extraction and classification methods can differentiate human motor movements, especially those of the hand. Combinations of these methods can greatly improve the accuracy of the results. This article explores the performances of nine feature-extraction types computed by a multilayer extreme learning machine (ML-ELM). The proposed method was tested on different numbers of EEG channels and different ML-ELM structures. Moreover, the performance of ML-ELM was compared with those of ELM, Support Vector Machine and Naive Bayes in classifying real and imaginary hand movements in offline mode. The ML-ELM with discrete wavelet transform (DWT) as feature extraction outperformed the other classification methods with highest accuracy 0.98. So, the authors also found that the structures influenced the accuracy of ML-ELM for different task, feature extraction used and channel used.
Number in Craft

In this chapter, the authors explore how sensor data features as a material in craft work, alongside the sensors themselves. They are also interested in what it might mean to think about sensor data as itself crafted—that is, not just constructed, or socially shaped, but crafted. To examine the craft of data, we conducted ethnography with people who build or use home energy monitoring equipment and upload the results onto Pachube. Pachube is a website that acts as an open data repository for sensor data of all kinds. Pachube and its users are tied to the larger maker movement, and often the systems used to sense are not commercially made products, but hardware hacks of various kinds. In practice, the craft of making sensors actually useful in a home or elsewhere far more resembles the numbers woven into a basket than sensor manufacturers may care to admit.
Digital Transformation of Technological Design in the Preparation of Design Engineers: History and Prospects

Significant advances in the implementation of information technology in the educational process cannot occur on their own. Success in this area is ensured by many years of hard work aimed at a gradual transition from the use of traditional teaching methods to automated ones. This transition on the example of implementing a computeraided design of technological processes is considered. The stages of the formation of this activity are described, starting with systems based on SM EVM (СМ ЭВМ, abbreviation of Система Малых ЭВМ – literally System of Mini Computers. It was the general name for several types of Soviet minicomputers produced in the 1970s and 1980s) operating under the control of a real-time operating system, and ending with electronic complexes for information support of design and technological design based on PDM systems.
Language Used in Social Media and Its Impact Toward Teens Language Acquisition

The development of technology in the modern era today is so fast and easy to use for the general public, including the information spread through gadgets.Such internet-connected technology makes it easy for users to access information around the world through the most common application for teenagers namely social media.This application is easy to obtain and use, as well as expand the network of teenagers to access information that is educative, recreational and social.This paper discusses the use of social media and its impact on language acquisition in adolescents.The method of data collection uses observation and interviews with students of MTs Negeri Batu, Indonesia.The study results show that the use of social media does not fully have a positive impact on the acquisition of language in adolescents.This research is expected to be a consideration for educators and parents to monitor the use of social media applications for children to contribute more positively.
Psychodiagnosis of Existential Experiences of Youth

There are many problems in psychological reality that make it impossible for any empirical study to be due to the lack of adequate psychodiagnostic tools. The purpose of this article is to select psychodiagnostic tools that would provide an adequate picture of the characteristics of the experiences of young people their transition period. The existential philosophy became the theoretical basis for revealing the profound and essential content of the normative crisis of adolescence since it was in the works of philosophers in this direction that an attempt was made to reveal the inner world of man in his specific identity. Adaptation of the existential paradigm to psychological practice was made by humanistic psychology, which put forward the principle of focusing on the individual subject and study the holistic personality of an average person as the central methodological postulate. Authors used ideographic or phenomenological methods during the research. Hence, the requirements for choosing an adequate methodical admission of our study were: 1) the possibility of receiving in-depth information about the inner experience of the investigated since this is the level of self-knowledge at which the subject reveals his existence; 2) the ability of the chosen methodology to reveal the individual characteristics of each respondent's maturity; 3) the need to analyze how exactly adulthood influenced the realization of primary existential integration (as a new feature of adolescence) and the subsequent life of the subject; it is about realizing the principle of unity of the entire life path of the respondent, revealing the integrity and continuity of the events of his inner world. Among the existing methodical techniques that can directly lead to the phenomenon under study, we can distinguish the method of conversation, which became for us the fundamental and specified in the exact method of an in-depth interview. The article further provides a methodological justification for receiving in-depth interviews to explore adolescent existential experiences.&#x0D;
Analysis of Mammography for Identifying Cancer Cells using Convolution Neural Networks

Breast cancer is the largest causes of women's death.it is the most commonly diagnosed cancer worldwide.the main modules in breast cancer prediction are data collection data pre-processing feature selection and classification.it is important to detect breast cancer as early as possible.The chances of survival of the patient is high advanced classification techniques and artificial intelligence methods has largely been used for breast classification.inthe first part we will be reviewing our breast cancer histology image dataset and we will split the python script into three sets those are a training set, a validation set, a testing set.Next we will use keras libraries to define a convolutional neural network.
\mathcal{H}_{\infty} control for fuzzy markovian jump systems based on sampled-data control method

This paper investigates the problems of $ \mathcal{H}_{\infty} $ performance analysis and sampled-data control about fuzzy Markovian jump systems. Firstly, in order to make full use of the information of both intervals $ x(t_{k}) $ to $ x(t) $ and $ x(t) $ to $ x(t_{k+1}) $, we construct the mode-dependent Lyapunov function, which consists of a two-sided closed-loop function. Built on the above Lyapunov function, the stochastically stable conditions with less conservative are given by using linear matrices inequalities (LMIs). Then, a state feedback controller is presented for the studied systems. At last, an example is offered to illustrate the efficiency of our main results.
Combination of SSD and a Rule-Based Approach for Nighttime Vehicle Detection on Roads

We propose a new approach to detect preceding and on-coming vehicles in front of an ego-vehicle from images captured on roads at night. The new approach comprises two main steps: vehicle candidate generation and candidate verification. Vehicle candidates are generated by using rule-based logics combined with SSD. This combination improves a previous approach [2] in terms of vehicle detection performance. This previous approach presents difficulties in detecting vehicles that are near but performs relatively better performance when detecting vehicles that are far. In contrast, compared with the previous approach, SSD shows a better performance in detecting vehicles that are near. However, SSD performs poorly in detecting vehicles that are far. The verification is realized by a classifier designed by VGG. The experimental results for actual road images illustrate the effectiveness of the proposed algorithm.
Characterization Of Contaminated Soils Using Hyperspectral Spectroscopy: A Case Study Of The Abandoned Hammam Zriba Mine In Tunisia

Laboratory and field Hyperspectral spectroscopy have been widely used for the study of contaminated soils, in particular by predicting the content of heavy metal [1] [2]. The characterization of risk minerals using hyperspectral spectroscopy has however not been addressed. The proposed methodology consists in the characterization of risk minerals in order to predict their contents within agricultural soils around the Hammam Zriba mine in the North of Tunisia using field Hyperspectral spectroscopy. The Continuum Removal (CR) method was processed for a judicious absorption feature selection. The identification of risk minerals as well as the quantification of their contents were revealed by the X-Ray diffraction (XRD) method. Correlation results have shown the convergence between XRD and Hyperspectral analyzes. The selected bands will be used in further time for regression processes, which relate soil VNIR/SWIR (Visible and Near Infrared Short Waves InfraRed) (350-2500 nm) reflectance spectra to the concentration of risk minerals.
Impact of using Backend Genetic Algorithm to Optimize Parameters with the use of Support Vector

This work proposes a new approach, based on Genetic Algorithms and Support Vector Machine to trade in the forex market.In this work, a new algorithm capable of generating technical rules to make investments with a given amount of leverage depending on the certainty of the prediction is presented.To forecast those predictions, a combination of a Support Vector Machine (SVM) algorithmto identify and classify the market in three different stages -, and a Dynamic Genetic Algorithmto optimize trading rules in each type of market, is used.The optimization of the trading rules is based on several technical indicators.Forex data for the EUR/USD currency pair, in a timeframe between the years of 2003 and 2016, is used as training and test data.The proposed architecture for the machine learning system, as well as the implementation and study of the proposed system is described in detail.The use of an hybrid system, combining a SVM and a GA with dynamic approaches such as hyper-mutation and adaptability approaches by training three different GA's for each type of market, provide a new approach for FOREX trading, where it is possible to classify trends using price sequences and therefore using the same classification for optimizing investment strategies with the most appropriate GA.Finally, the work shows promising results during the test period between the 2nd of January of 2015 until the 2nd of March of 2016, where the return on investment obtained is 83%.
The structure of social competence of students in pedagogical university as a scientific problem

The article analyzes the social competence of pupils and students, presents author's own view on the structure of social competence of students of the Pedagogical University.It is noted that social competence is an important component of an active and modern personality that feels comfortable in society.The structure of students' social competence consists of several components, which are responsible for the array of knowledge, behavior, values, motivation, communication and reflection.The social skills that future teachers should possess are analyzed.Introduction.The realities of life in the face of dynamic political, economic, and social changes require appropriate reform of higher and secondary education in accordance with international educational standards.First of all, it concerns the implementation of personality-oriented and competencybased approaches to education, which today are effective factors for improving the quality of education.Among the key competences that modern and active members of society should possess, social competence plays an important role, which ensures a process of constructive interaction with other people and society.Its importance for human life is difficult to overestimate, because the process of socialization of personality, its self-development occure only in interaction and communication.This is especially true of future teachers who need to develop their own personality and learn how to socialize students.Social competence is a multi-component pedagogical category that has its own structure.Its functions and content are usually determined by the specifics of the chosen profession, living conditions and so on.The study of the structure of students' social competence will allow to determine the methods of their development in the social sphere.Analysis of recent researches and publications.Common issues of social competence covered a research area of I.Zymnia, J.Raven.I.Zarubinska, T.Kachalova, S.Krasnokutska, S.Ostapenko explored the social competence of student applicants, including students of pedagogical specialties (S.Bekirov, N.Borbich, N.Sivak, etc.).Different interpretations of social competence and approaches to its study, as well as the peculiarity of the profession of the future teacher actualize the need to clarify the structure of social competence of students of pedagogical universities.The purpose of the article is analysis of social competence in terms of its need for personality development, analysis of the content and structure of social competence of pupils and students, coverage of the author's own view of the structure of social competence of students of the Pedagogical University.Results.Today, there are positive processes in Ukraine related to the upgrading of higher and secondary education.This is facilitated by a number of adopted normative documents, including The Concept of the New Ukrainian School,