Reviewerly/exHarmony huggingface dataset:
An Unsupervised feature extraction method based on self coded neural network

The way to tap the inherent law of ECG data and feature extraction is of vital in the absence of prior knowledge of the situation. This paper presents a self coded neural network model, which is reconstructed after compression of ECG data. The compression process eliminates the redundancy of data within the original data firstly from the low dimensional with more concise representations. In order to verify the features extracted from the neural network, we select the simplest and most direct distance based K nearest neighbour classification method. By using a self compiled neural network to extract features from the data set, the classification accuracy of K nearest neighbour classification can be greatly improved. The experimental results show that the unsupervised feature extraction method based on self coded neural network can effectively extract the features of the data in practical applications.
Exploring Device Capabilities

Mobile devices are not just limited to making phone calls; they are some of the most advanced pieces of consumer technology ever invented. Their real power lies in the various capabilities that reside in a smartphone. The iOS and Android platforms allow us to use various device features to make a more captivating application experience for our users. This chapter explores the following device capabilities:
The Use of Fiction and Nonfiction Text in Reading Comprehension (A Comparative Study at the Second YearStudents of SMAN 8 Gowa)

Based on the research findings, the researcher concluded that givingfiction as reading material to students will enhance students readingcomprehension more than nonfiction. The reason why the students preferred fiction than nonfiction as reading material is fiction can stimulate the students to read more due to being an authentic material and worked with students’ imagination. For further reason, fiction also enhances the ability to detect and understand other people's emotions, so that the students could navigate their social relationship in a better way
Studying the Astrometeorological Relationship between Planet’s Azimuth and Wind Speed Events

Astrometeorology is a great science and gift from our ancestors known to humankind. Compared to statistical and numerical methods of forecasting, astrometeorology method has no time restrictions and weather could be forecasted for the next hour to a date far in the future. Wind speed is the weather parameter plays an important role in crop production. A study on the relationship between the wind speed events and the planet’s azimuth was conducted at Tamil Nadu Agricultural University during 2017-18 as a part of the formulation of astrometeorological rules for wind speed events. Hourly wind speed observed between 2011 and 2016 from each one location from 31 districts of Tamil Nadu were correlated with the ephemeris developed for the same period in Alcyone ephemeris calculator. It could be concluded from the correlation study on individual planet azimuth and wind speed events that the azimuth range of 61 – 120 of all the planets and 240 – 300 had a good influence on wind speed. The 61 – 90 degrees azimuth of the Sun, Mercury, Saturn and Neptune had good influence on calm to light air wind speed events (0 – 12 km). The 91 – 120 degrees azimuth of all the planets had influenced moderately to heavy wind (19 – 45 km/hour). The Moon, Mars, Jupiter, and Neptune at 60 - 90 degrees azimuth had influenced the extreme wind speed events. The Moon, Mars and Saturn at 271 – 300 degrees azimuth had influenced the moderate to heavy wind (19 – 45 km/ hour).
A(k, p)-anonymity Framework to Sanitize Transactional Database with Personalized Sensitivity

In recent years, analyzing transactional data has become an important data analytic task since it can discover important information in several domains, for recommendation, prediction, and personalization. Nonetheless, transactional data sometimes contains sensitive and confidential information such as personal identifiers, information aboutsexual orientations, medical diseases, and religious beliefs. Such information can be analyzed using various data mining algorithms, which may cause security threats to individuals. Several algorithms were proposed to hide sensitive information in databases but most of them assume that sensitive information is the same for all users, which is an unrealistic assumption. Hence, this paper presents a (k, p)-anonymity framework to hide personal sensitive information. The developed ANonymity for Transactional database (ANT) algorithm can hide multiple pieces of sensitive information in transactions. Besides, it let users assign sensitivity values to indicate how sensitive each piece of information is. The designed anonymity algorithm ensures that the percentage of anonymized data does not exceed a predefined maximum sensitivity threshold. Results of several experiments indicate that the proposed algorithm outperforms the-state-of-the-art PTA and Gray-TSP algorithms in terms of information loss and runtime.
PEDESTRIANS TEND TO LOOK AT SCENES WITH HIGHER LUMINANCE AND GREATER SALIENCY AT NIGHT

The mechanism of luminous environmental parameters influencing pedestrian visual behavior is unknown.Field experiments using mobile eye tracking glasses device (ETG) were carried out in outdoor night streets in this study.Two luminous parameters of visual scene, luminance and saliency, were examined by coded image processing and statistical analyses as main influencing factors.The results indicate that distribution of fixations has a clear tendency to higher brightness (68.45%) and greater saliency (78.21%) comparing with chance level (50%).It is suggested that pedestrians at night time tend to look at areas with higher luminance and greater saliency regardless of context of the scene.
4-bit crypto S-boxes: Generation with irreducible polynomials over Galois field GF(24) and cryptanalysis.

4-bit crypto S-boxes play a significant role in encryption and decryption of many cipher algorithms from last 4 decades. Generation and cryptanalysis of generated 4-bit crypto S-boxes is one of the major concerns of modern cryptography till now. In this paper 48, 4-bit crypto S-boxes are generated with addition of all possible additive constants to the each element of crypto S-box of corresponding multiplicative inverses of all elemental polynomials (EPs) under the concerned irreducible polynomials (IPs) over Galois field GF(24). Cryptanalysis of 48 generated 4-bit crypto S-boxes is done with all relevant cryptanalysis algorithms of 4-bit crypto S-boxes. The result shows the better security of generated 4-bit crypto S-boxes.
Alphabet-Board Display as part of the classroom learning space

Abstract Alphabet-boards are commonplace in lower grade classrooms in elementary-schools. If designed correctly, alphabet-boards can help internalize letters into memory. The purpose of this study was to examine alphabet-board characteristics that should be considered by teachers for providing a clear, readable, and applicable pedagogical tool. The research is a mixed qualitative and quantitative study. The former provides a definition of alphabet-board readability characteristics and a scale for analyzing this readability. The latter provides a readability evaluation using a survey (n=399) and statistical analyses. This article provides practical recommendations for implementation of clear and effective alphabet-board pedagogy.
IMPROVING STUDENT LEARNING RESULTS THROUGH THE APPLICATION OF THE QUANTUM TEACHING MODEL

Improving Student Mathematics Learning Outcomes through the Application of the Quantum Teaching Model. This study aims to improve the mathematics learning outcomes of students using the TANDUR type Quantum Teaching learning model with the assisted discussion method of Student Worksheets (LKS). This study is a classroom action research conducted in two cycles. The subject of this study were all students of class VIII.9 SMP Negeri 1 Maros totaling 38 students. Data sources came from students and teachers. Data collection techniques used observation, documentation and tests. The analysis technique used in this study was quantitative analysis techniques. The results showed that the application of the TANDUR type Quantum Teaching method can improve student learning outcomes. in learning Mathematics in class VIII.9 1 Public High School Maros. In addition there is an increase in student activity and teacher performance.
Lexical Formation Error in the Descriptive Writing of Indonesian Tertiary EFL Learners

This study was aimed at identifying the kinds and frequency of formal errors on Indonesian English as a Foreign Language (EFL) learners’ descripting writing. Therefore, descriptive analysis research design was implemented to achieve the objective. The data were collected from the descriptive writing of university students in Indonesia (N = 40). Then, the data were computerized and tabulated by using descriptive statistic (frequency and percentage) in SPSS version 21. The result of this study presents that from 223 errors, suffix was the most frequent formal errors (32.29%) in Formal Misselection, followed by calque (22.87%) in Formal Misformations and omission (12.56%) in Distorsion. In conclusion, most of the students have considerable difficulty in forming the correct form of the words. Therefore, to produce an excellent descriptive writing, the students are suggested to learn and practice more on words formations (grammar).
Fast Implementation of Face Detection Using LPB Classifier on GPGPUs

Face detection is one of the classical computational challenges in computer vision. Detecting faces in an image has many applications in the field of security surveillance, marketing, biometric authentication, social media, photography and many more. Scanning window is most common technique used in face detection. In this method, an image is divided into multiple regions and each region is processed to detect presence of human face. To process an image of size 640 × 480 pixels, 178000 image regions must be processed and at-least 24 frames must be processed within a second, the number of regions to be processed grows significantly for images with higher dimensions and frame rates. With the advent of high resolution video capturing devices capable of recording at higher frame rates, real-time face detection is a challenge as it is computationally intensive process. In this paper, we present a framework which uses scanning-window technique, integral image and Local Binary Pattern (LBP) implemented on GPGPU to process images in short duration with high accuracy. In our experiments, we have achieved processing speed up to 287 frames per second on average with image dimensions of 640 × 480 pixels.
The effect of public speaking training on students’ speaking anxiety and skill

Regardless its importance, speaking always becomes a demanding task to teach. It is a complex skill since it requires not only the language ability, but also related to psychological conditions, such as confidence, especially when it comes to public speaking. This paper elaborates what happened in the public speaking training classes conducted by Language Development and Service Centers at University of Muhammadiyah Banjaramasin. This research employs pre-experimental research design to measure the effect of the training on students’ speaking anxiety and skill. It invites 40 students from the writers’ classes to join the research. A Personal Report of Public Speaking Anxiety (PRPSA) questionnaire and speaking test are two main instruments to collect the data. In addition, result observation also becomes additional data collection to enrich the findings. Finally, this research is expected to give a valid statistical data support as well as ideas for teachers who are interested in planning a public speaking training for their students.
Detecting psycho-anomalies on the world-wide web: current tools and challenges

The rise of the use of Social Media and the overall progress of technology has unfortunately opened new ways for criminals such as paedophiles, serial killers and rapists to exploit the powers that the technology offers in order to lure potential victims. It is of great need to be able to detect extreme criminal behaviours on the World-Wide Web and take measures to protect the general public from the effects of such behaviours. The aim of this chapter is to examine the current data analysis tools and technologies that are used to detect extreme online criminal behaviour and the challenges that exist associated with the use of these technologies. Specific emphasis is given to extreme criminal behaviours such as paedophilia and serial killing as these are considered the most dangerous behaviours. A number of conclusions are drawn in relation to the use and challenges of technological means in order to face such criminal behaviours.
Automated Hot_Text and Huge_Pages: An Easy-to-Adopt Solution Towards High Performing Services

Performance optimizations of large scale services can lead to significant wins on service efficiency and performance. CPU resource is one of the most common performance bottlenecks, hence improving CPU performance has been the focus of many performance optimization efforts. In particular, reducing iTLB (instruction TLB) miss rates can greatly improve CPU performance and speed up service running. At Facebook, we have achieved CPU reduction by applying a solution that firstly identifies hot-text of the (software) binary and then places the binary on huge pages (i.e., 2 MB+ memory pages). The solution is wrapped into an automated framework, enabling service owners to effortlessly adopt it. Our framework has been applied to many services at Facebook, and this paper shares our experiences and findings.
Изучение закономерностей отношения и поведения человека в медиапространстве посредством медиапсихологии

The article analyzes the relationship of the individual and mass media, the psychology of the perception of mass communications, the new role of media in society. Scientific studies are presented in the context of media consumption in the dynamic development of the IT industry and Internet services. The influence of mass media on various spheres of human life is emphasized.
Reform of the Library and Information Service in University Libraries under the Network Environment

With the continuous development of Internet technology, the type of information in the literature has also changed. In order to provide better quality problem-solving services for scientific research work in universities, relevant library intelligence personnel are required to set the entire library information. The service is constantly innovating and reforming. This article has carried out a series of analysis on how to carry out the reform of the library information and title service in colleges and universities under the network environment.
PENGARUH SOCIAL LEARNING NETWORK TERHADAP MOTIVASI DAN HASIL BELAJAR SISWA

The purpose of this study to know the influence of the use of social learning network to motivation and student learning outcomes. This research uses quasi experimental research method using posttest only control group design. Hypothetical test of research using t-test and T2 test. Result of hypothesis test The t-test of learning motivation obtained by Thitung -5,187 with Sig value. 0,000 (&lt;0,05), conclusion H0 rejected and H1 accepted. Result of hypothesis test The t-test of learning result obtained by Thitung -2,950 with Sig value. 0,005 (&lt;0,05), conclusion H0 rejected and H1 accepted. Result of hypothesis T2 test obtained value of F 1,307 with value of Sig. 0,000 (&lt;0,05), conclusion H0 rejected and H1 accepted. Abstrak: Tujuan dari penelitian ini mengetahui pengaruh penggunaan social learning network terhadap motivasi dan hasil belajar siswa. Penelitian ini menggunakan metode penelitian eksperimen semu dengan menggunakan desain posttest only control group . Uji Hipotesis penelitian menggunakan uji-t serta uji T 2 . Hasil uji hipotesis Uji-t motivasi belajar diperoleh T hitung -5,187 dengan nilai Sig . 0,000 (&lt;0,05), kesimpulannya H0 ditolak dan H1 diterima. Hasil uji hipotesis Uji-t hasil belajar diperoleh T hitung -2,950 dengan nilai Sig . 0,005 (&lt;0,05), kesimpulannya H0 ditolak dan H1 diterima. Hasil uji hipotesis T 2 diperoleh nilai F 1,307 dengan nilai Sig. 0,000 (&lt;0,05), kesimpulannya H0 ditolak dan H1 diterima.
A Relay Attack on a Tamper Detection System (Brief Announcement)

This short paper analyzes a tamper detection system for IoT environments, presented by Bagci et al. at ACSAC 2015. It shows that the system is vulnerable to relay attacks.
Multilateral Transparency for Securities Markets through DLT

For decades, changing technology and policy choices have worked to fragment securities markets, rendering them so dark that neither ownership nor real-time price of securities are generally visible to all parties multilaterally. The policies behind these developments are found in the US National Market System and the EU Market in Financial Instruments Directive, together with universal adoption of the indirect holding system, and have painted Western securities markets into a corner from which escape to full transparency has seemed either impossible or prohibitively expensive. Although the reader has a right to skepticism given the exaggerated promises surrounding blockchain in recent years, we demonstrate in this paper that distributed ledger technology (DLT) contains the potential to lead fragmented securities markets back to multilateral transparency. Leading markets generally lack transparency in two ways that derive from their basic structure: multiple platforms on which trades in the same security are matched have separate bid/ask queues and are not consolidated in real time (fragmented pricing), and high-speed transfers of securities are enabled by placing ownership of the securities in financial institutions, preventing transparent ownership (depository or street name ownership). The distributed nature of DLT allows multiple copies of the same pricing queue to be held simultaneously by a large number of order-matching platforms, curing the problem of fragmented pricing. This same distributed nature of DLT would allow the issuers of securities to be nodes in a DLT network, returning control over securities ownership to those issuers and thus restoring transparent ownership through direct holding with the issuer. A serious objection to DLT is that its latency is very high – with a Bitcoin blockchain transaction taking up to 10 minutes. To cure this, we first propose a private network without cumbersome proof-of-work cryptography and, second, introduce into our model the quickly evolving technology of “lightning networks”, which are advanced two-layer off-chain networks conducting high-speed transacting with only periodic memorialization in the permanent DLT network. This paper demonstrates against the background of existing securities trading and settlement that a DLT network could bring multilateral transparency and thus represent the next step in evolution for markets in their current configuration.
LibGuides: Primary Library: Recommended Reading

This guide is for our primary students, parents and teachers. Books available in the PS library recommended by the Librarian
Building economic models and measures of search (tutorial)

Economics provides an intuitive and natural way to formally represent the costs and benefits of interacting with applications, interfaces and devices. By using economic models it is possible to reason about interaction, make predictions about how changes to the system will affect behavior, and measure the performance of people’s interactions with the system. In this tutorial, we first provide an overview of relevant economic theories, before showing how they can be applied to formulate different ranking principles to provide the optimal ranking to users. This is followed by a session showing how economics can be used to model how people interact with search systems, and how to use these models to generate hypotheses about user behavior. The third session focuses on how economics has been used to underpin the measurement of information retrieval systems and applications using the C/W/L framework (which reports the expected utility, expected total utility, expected total cost, and so on) – and how different models of user interaction lead to different metrics. We then show how information foraging theory can be used to measure the performance of an information retrieval system — connecting the theory of how people search with how we measure it. The final session of the day will be spent building economic models and measures of search. Here sample problems will be provided to challenge participants, or participants can bring their own.
ReqPriSec: Security and Privacy aware Web-based Versatile Requirement Engineering Tool

Requirement Engineering is the process of eliciting, analysing, negotiating, specifying and managing functional and non functional requirements of a system.The RE phase faces some challenges like managing ambiguous, incomplete and inconsistent requirements; specifying requirements in unstructured format; inefficient elicitation of requirements from stakeholders and managing various artefacts of requirements along with non functional requirements.These challenges may arise in any software development methodologies and may hinder the progress of project and system development.The security and privacy requirements have not given much attention in RE.There is a strong need of versatile and security-privacy aware RE tool to elicit, manage and specify requirement efficiently and in standardized format.This paper proposes a unique, securityprivacy aware "ReqPriSec" tool to manage and store the requirements in objective manner without major efforts of natural language requirement statements.The "ReqPriSec" tool is tested and evaluated based on different parameters on E-voting case study.
Language Technologies and Digital Humanities 2018, 20–21 September 2018, Faculty of Electrical Engineering, Ljubljana

This paper reports on the Language Technologies and Digital Humanities conference, which took place 20-21 September 2018 at the Faculty of Electrical Engineering in Ljubljana
한국인 초등 영어 학습자들의 관사 학습 실태 연구

This study focuses on analyzing the English article system built in elementary school students who are learning English as a second language and also...
Information security management in cloud computing : a case study

Abstract. Organizations are quickly adopting cloud computing in their daily operations. As a result, spending’s on cloud security solutions are increasing in conjunction with security threats redirecting to the cloud. Information security is a constant race against evolving security threats and it also needs to advance in order to accommodate the cloud computing adaptation.The aim of this thesis is to investigate the topics and issues that are related to information security management in cloud computing environments. Related information security management issues include risk management, security technology selection, security investment decision-making, employees’ security policy compliance, security policy development, and security training. By interviewing three different types of actors (normal employees, IT security specialists, and security managers) in a large ICT-oriented company, this study attempts to get different viewpoints related with the introduced issues and provide suggestions on how to improve information security management in cloud computing environments.This study contributes to the community by attempting to give a holistic perspective on information security management in the specific setting of cloud computing. Results of the research illustrate how investment decisions directly affect all other covered topics that in turn have an effect on one another, forming effective information security.