Reviewerly/exHarmony huggingface dataset:
On Adversarial Vulnerability of PHM algorithms – An initial Study

In almost all PHM applications, driving highest possible performance (prediction accuracy and robustness) of PHM models (fault detection, fault diagnosis and prognostics) has been the top development priority, since PHM models’ performance directly impacts how much business value the PHM models can bring. However, recent research work in other domains, e.g., computer vision (CV), has shown that machine learning (ML) models, especially deep learning models, are vulnerable to adversarial attacks; that is, small deliberately-designed perturbations to the original samples can cause the model to make false predictions with high confidence. In fact, adversarial machine learning (AML) targeting security of ML algorithms against adversaries, has become an emerging ML topic and has attracted tremendous research attention in CV and NLP.&#x0D; &#x0D; Yet, in the PHM community, not much attention has been paid to adversarial vulnerability or security of PHM models. We contend that the economic impact of adversarial attacks to a PHM model might be even bigger than that to hard perceptual problems and thus securing PHM models from adversarial attacks is as important as the PHM models themselves. Also, PHM models, since the data used by the models are primarily time-series sensor measurements, have their own unique characteristics and deserve special attention in securing them. &#x0D; &#x0D; In this paper we attempt to explore the adversarial vulnerability of PHM models by conducting an initial case study. More specifically, we consider several unique characteristics associated with streaming time-series sensor measurements data in developing attack strategies for attacking PHM models. We hope our initial study here can shed some light on and stimulate more research interests in the area of PHM models’ security.
DIFFICULTIES IN SPEAKING ENGLISH OF EFL STUDENTS IN INDONESIA

In Indonesia, English is used as a foreign language. Therefore, students face difficulties when trying to speak English. This research was conducted to find the difficulties that influence students’ speaking and to know what are the causes of those difficulties in English class. The design of this research was descriptive method. Moreover, the researcher used observation and interview as the instruments in this study. The result of the research showed there are some difficulties and causes of those difficulties that make students difficut to speak English. That difficulty comes from students psychological aspect such as anxiety, shyness, fear of mistake, and lack of confidence. Moreover, in student linguistic aspect such as lack of vocabulary, poor pronunciation, and mother tongue interference. Furthermore, the researcher found that the causes of those difficulties are not ready to speak, personality, fear of negative evaluation, feel pressured, less reading English literature, less practicing to speak English, and confusion.
Dormitory Management System Based on Face Recognition

This paper explores the application of face recognition system in dormitory management, and designs an EXE software, which realizes the function of entering and leaving dormitory through face voucher, storing the information of students, and automatically updating relevant data. The face recognition module includes three functions: face image recognition and interception, face alignment, face feature extraction and face verification. The traditional method of HOG is used for recognition and interception, and the method of gray-scale processing and gamma normalization is used for preprocessing to reduce the influence of light. The face alignment uses the 68-point landmarks and similarity transformation to align the face. The face feature extraction uses the pre-trained FaceNet neural network to extract the 128-d feature vector of the face, which is stored in the database or compared with the face in the database to output the Euclidean distance, then compare and find the most possible person according to the distance. The database module includes two functions: storing face information and displaying all information of students MySQL is used to build the database. An automatic dormitory information management system is established through the interconnection interface between MySQL and Python.
Profile Verification Using Blockchain

Blockchain technology opens up opportunities to deliver new business models. Blockchain technology in this era opens doorways to deliver secure and immutable documentation. Across the globe, a huge number of students graduate every year from universities. Their work, both curricular and extracurricular, needs secure storage and verification so that it remains protected and the students can highlight it anywhere without further rounds of verification. The paper presents a way that can ease up the process of doing the verification by using blockchain. A verification protocol is devised using the concept of mentors. A blockchain-based verification system is also set up to demonstrate the working of the verification protocol.
Smart Fall Detection Systems for Elderly Care

Fall is considered to be one of the major health problems for senior adults. According to a report published by World Health Organization, early fall detection is an active problem in the old age group people. The report showed that the falling problem affects 28%–35% of people around 65 years of age and 32%–45% for those over 70 years. So this domain has attracted the attention of researchers to search for an affordable and easy to use solution. This remained an open challenge as no uniformly acceptable solution could be provided so far. The scientists have proposed multiple solutions based on different approaches in providing a successful patient care system (PCS). In this chapter, we have tried to discuss the different state of the art methodologies proposed by the researchers in recent time. This chapter is aimed to provide a brief idea about this research domain starting with very basic concepts. A prototype fall detection system developed by the authors are discussed in the latter part of the chapter that is useful to show one practical implementation of such a system. This prototype, on the testbed, showed an accuracy of 94.45%.
Virtual Machine Performance Prediction Based on Transfer Learning of Bayesian Network

The performance of virtual machines in the cloud is fraught with uncertainty due to the complexity of the environment, which poses a challenge for accurate prediction of virtual machine performance. In addition, a well-performing virtual machine performance prediction model cannot be multiplexed in either the temporal or spatial dimensions. In this paper, we build a virtual machine performance prediction model based on Bayesian network to solve the problem of accurate prediction of virtual machine performance. Furthermore, to achieve multiplexing of the performance prediction model in both temporal and spatial dimensions, we propose a Bayesian network transfer learning approach. Experiments show that in our transfer learning approach, in contrast with reconstruction, the amount of data in the training set was reduced by 90%, and the training time was reduced by 75%, while the macro average precision maintaining 79%.
Detection of Cross-Site Scripting and Phishing Website Vulnerabilities Using Machine Learning

Dynamic web pages are widely used by web applications to provide a better user experience and to attract more web users. The web applications use client-side and server-side scripts to provide dynamic behavior to the web pages. Cross-Site Scripting (XSS) attack uses malicious scripts and links injected into the trusted webpages to steal sensitive data from the victims. In this work, the experimental results obtained using machine learning algorithms (Random Forest Classifier, MLP Classifier, Gen ELM Classifier, Naïve Bayes, Support Vector Machine, and K Neighbours Classifier) for the prediction of XSS attack and phishing websites attacks are implemented. This is done using the features based on normal and malicious URLs and JavaScript. Random Forest Classifier gave better results than MLP Classifier, Gen ELM Classifier, Naïve Bayes, Support Vector Machine, and K Neighbours Classifier based on the features extracted from URL and JavaScript code. All the algorithms gave comparatively better results with discretized attributes, but a noticeable difference in performance was seen only in the case of SVM. A detailed literature survey is presented and proposes a new approach to detect phishing websites by features extraction and machine learning algorithm.
Computational complexity in quantum computing

Our aim is of studying the efficiency of two typical arithmetic calculations {[T. Nakamura and K. Nagata, Int. J. Theor. Phys. {\bf 60}, 70 (2021)]} using the principle of quantum mechanics. We demonstrate some evaluations of three two-variable functions which are elements of a boolean algebra composed of the four-atom set utilizing the Bernstein--Vazirani algorithm. This is faster than a classical apparatus, which would require $2^{12}=4096$ evaluations. Finally, using the three two-variable functions evaluated here, we demonstrate two typical arithmetic calculations in the binary system. Hence, our calculations are faster than a classical apparatus, which would require $2^{12}=4096$ evaluations.
INTERNET FRAUD AND ITS EFFECT ON INFORMATION AND COMMUNICATION TECHNOLOGY IN NIGERIA’S EDUCATION SYSTEM:

Internet fraud has become an increasing form of computer crime. This study investigated the effects of internet fraud on Nigeria’s education system. The study adopted quantitative method and descriptive survey. Journals, articles, books (published and unpublished) and materials from internet complemented the major sources. Findings showed that unemployment and poverty are major causal factors of internet fraud. The study concluded that, despite there markable development in computer technology especially in communication and information technology, internet use by some Nigerian youths has come with fraudulent acts, and this has put Nigeria under scrutiny and brought negative impact on Nigerian education system. The study recommended that, government should enact a comprehensive law on internet fraud and empower graduates by providing employment. It also recommended that curriculum which includes courses on internet fraud, internet management and its prevention should be introduced at both the tertiary and secondary levels. This will assist in taking care of the present social changes amongst the Nigerian society at large.
Planning Paths Through Unknown Space by Imagining What Lies Therein

This paper presents a novel framework for planning paths in maps containing unknown spaces, such as from occlusions. Our approach takes as input a semantically-annotated point cloud, and leverages an image inpainting neural network to generate a reasonable model of unknown space as free or occupied. Our validation campaign shows that it is possible to greatly increase the performance of standard pathfinding algorithms which adopt the general optimistic assumption of treating unknown space as free.
MENINGKATKAN KOSAKATA MELALUI MEDIA GAMBAR

This research aims to (1) find out how processes use of media images in A group of children a vocabulary boost in the Early Childhood Al-Syaukah Pandeglang-Banten. (2) to determine whether the child's vocabulary can be enhanced through Group A media image in the Early Childhood Al-Syaukah Pandeglang-Banten. The method used was the method of Research action (PT) researchers in collaboration with master class with 2 cycle. The subject consists of 12 children consisting of 7 girls and 5 boys in the Early Childhood Al-Syaukah Pandeglang Banten. Engineering data collection done by observation, field notes, interviews and documentation. Instruments used by observation sheet (Check list). Analytical techniques descriptive data are executed qualitative and quantitative. Success criteria of research if the calculation of the percentage reaches 75% of children experience increased vocabulary. Based on the results of research conducted at an early stage in the process of learning through the medium of an image by designing RPPH, prepare the media to be used, setting up a classroom for learning activities and customize the child, then implement the action cycle I of 8 times the action, and the cycle II consisting of 8 times the action (if it hit the target before 8 times the action research can be stopped), the evaluation was done by giving questions about the activities that have children do. The research results obtained in pre child vocabulary research was very low with 28%, then in the cycle I have elevated into 45%, cycle II obtained the results of 78%. Thus, it can be concluded that media images can improving children's vocabulary of Group A in the Early Childhood Al-Syaukah Pandeglang-Banten.
Does high Audit Effort improve Audit Quality? : Evidence from unlisted firms and designated auditors

With the revision of the External Audit Act, a major change is expected in Korea's external audit market. The major goal of the revision to the External Audit Act is to improve the audit quality and accounting transparency.It is expected that the revision of External Audit Act will have the biggest impact on the new system, which is the introduction of a regular designated audit system. This system is introduced on the premise that the quality of audit would be increased by higher independence when the Financial Supervisory Service designated auditors. However, the auditor designation system is also a special system in Korea, and prior research suggests conflicting results about the effect of enhancing audit quality of designated auditors. Caramanis and Lennox (2008) suggested that auditors’ high audit efforts improve audit quality. Therefore, audit quality may be reduced if the auditor does not secure sufficient and adequate audit hours to gathering audit evidence considering audit risks. This study is intended to investigate the auditors’ effort is an important component of audit quality, and that the designated auditor's high quality audit effect, known to provide high quality audit in the Korean audit market, would be due to high audit efforts.The results of this study showed that in all the samples of listed and unlisted firms, audit hours significantly reduces discretionary accruals used as a proxy for the audit quality. In particular, discretionary accruals of the sample performed by the designated auditor is not significantly different from the other samples. However, discretionary accruals of the sample performed by auditors under the auditor designation system was significantly low. But, when the auditors’ effort is controlled, discretionary accruals of all samples is not significantly different. It means that the auditors’ effort is a important factor in determining the quality of the financial reporting. Also, audit quality is not improved by the designated audit itself, but rather by the designated auditors’ high audit quality and audit effort registered in the designated audit system.This study suggests that the audit effort must be taken into account when measuring and substituting the audit quality by suggesting that audit hours are an important determinant of audit quality, and as a major variable for determining the audit quality. This result also suggests that high quality auditors effect is due to high audit effort.
Effect of Mobile Learning App on Undergraduates’ Performance in GNS through A Blended Learning Approach

This study examined the effects of a researcher-developed mobile learning app on the performance of undergraduate students in a compulsory general study course in a Nigerian University. A mixed-method was adopted in the study. A pre-experimental one-group pretest-posttest design was used. The research population involved undergraduates in Nigerian universities. A sample of 21 year-one students, were purposively drawn among University of Ilorin undergraduate students. The group was subjected to pretest, followed by the administration of the treatment, and then post-tested. A simple random sampling method was adopted in selecting the experimental group. It was found that there was a significant difference in the students’ post-test score after they were exposed to the GNS App. t (20) = 4.303, p = < 0.05; and no significant difference was noticed in the male and female students’ performance after being exposed to the treatment. The study concluded that the mobile App when used alongside traditional teaching and learning improved students’ performance in GNS -Use of Library, irrespective of gender
Triangular color codes on trivalent graphs with flag qubits

The color code is a topological quantum error-correcting code supporting a variety of valuable fault-tolerant logical gates. Its two-dimensional version, the triangular color code, may soon be realized with currently available superconducting hardware despite constrained qubit connectivity. To guide this experimental effort, we study the storage threshold of the triangular color code against circuit-level depolarizing noise. First, we adapt the Restriction Decoder to the setting of the triangular color code and to phenomenological noise. Then, we propose a fault-tolerant implementation of the stabilizer measurement circuits, which incorporates flag qubits. We show how information from flag qubits can be used with the Restriction Decoder to maintain the effective distance of the code. We numerically estimate the threshold of the triangular color code to be 0.2%, which is competitive with the thresholds of other topological quantum codes. We also prove that 1-flag stabilizer measurement circuits are sufficient to preserve the full code distance, which may be used to find simpler syndrome extraction circuits of the color code.
LibGuides: System Wide Holds - Training Guide: Placing a Hold Using the Catalogue

The purpose of this guide is to provide staff a reference resource for processing Requests and Holds on NLPL materials.
Timeline summarization in a cross-lingual scenario

Timeline Summarization (TLS) is the main approach that has been used to automatically create timelines of news reports related to some long-running event of interest. These timelines present a good way to keep up-to-date to the topic and follow its development over time, while getting only the salient information related to it. Most of the previous work done on TLS is focused on creating timelines for resources in a monolingual scenario, typically in the English language, and although some of them can be portable to other languages, they are still unable to combine the knowledge that has been extracted from news articles in different languages. The main contribution of this Thesis work is the study and development of TLS strategies tailored to multilingual resources. It aims at combining the textual information from different languages in order to generate a news timeline in a given target language. Among the biggest challenges addressed in this study is the analysis of these multilingual resources, as well as exploring the possibility to use the additional knowledge provided among the languages. The motivation for this is based on the fact that news provided in different languages can demonstrate a different aspect of the same event, as they may portray different cultural, economical or political reflections. The use of this additional knowledge gained from the multilingual resources has been proved to be beneficial, enriching the resources of the various languages and increasing their summarization quality significantly.
The Effectiveness of Educational Environment Based on Smart Learning in Developing English Language Listening Skill among IUG Female Learners

This study aimed to investigate the effectiveness of educational environment based on smart learning in developing English Language listening skill among IUG female learners. To achieve this aim, the researcher adopted the experimental approach. The study was applied on a representative sample of (30) female students of journalism and media second-level at the Islamic University of Gaza, and that is in the second semester of the academic year (2020-2021). In order to collect data, the researcher used one main tool, a pre- and post-listening test, and then he verified the validity and reliability of the test. The findings of the study revealed that There were significant statistically difference at level (0.05) between the average scores of female students in journalism and media at the Islamic University in the pre and post applications to test skill of listening in English language and in favor of the post application. Based upon the previous findings, the study recommended the necessity of implementing smart learning in teaching and learning English listening skill to bring about better outcomes in female students' achievement. Also, the researcher suggested that further research should be conducted concerning the effectiveness of educational environment based on smart learning in teaching different English language skills.
Penerapan Algoritma Linier Congruent Method Pada Aplikasi Pembelajaran Geografi

&lt;p&gt;&lt;strong&gt;&lt;em&gt;Abstract &lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;The Covid-19 pandemic era caused the learning process to be carried out creatively, using media and other learning resources other than textbooks provided by the school, so that learning outcomes can be obtained optimally, especially for geography subjects. This article aims to create a geography learning media model in the form of a quiz that can be used as a learning support media, so that students can learn well, even in situations where they do not interact directly with the teacher. The media development method used is the Multimedia Development Life Cycle and the Linear Congruent Method to manage the randomization process. The components contained in the application are quizzes, word sequences, and puzzles. By using the LCM algorithm in regulating the randomization process, it is hoped that the questions that will be displayed are not easily guessed by students.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Keywords: Linear Congruent Method, Multimedia Development Life Cycle, Geography learning application&lt;/em&gt;&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Abstrak&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Era pandemi Covid-19 menyebabkan proses pembelajaran mesti dilaksanakan secara kreatif, menggunakan media dan sumber-sumber belajar lain selain buku teks yang disediakan oleh pihak sekolah, agar capaian pembelajaran dapat diperoleh secara maksimal, khususnya untuk mata pelajaran geografi. Artikel ini bertujuan untuk membuat sebuah model media pembelajaran geografi dalam bentuk kuis yang dapat digunakan sebagai media pendukung pembelajaran, sehingga siswa dapat belajar dengan baik, walau dalam situasi tidak berinteraksi secara langsung dengan pengajar. Metode pengembangan media yang digunakan adalah &lt;em&gt;Multimedia Development Life Cycle &lt;/em&gt;dan &lt;em&gt;Linier Congruent Method &lt;/em&gt;untuk mengatur proses pengacakan soal. Komponen yang terdapat pada aplikasi berupa kuis, rangkai kata, dan &lt;em&gt;puzzle&lt;/em&gt;&lt;em&gt;. &lt;/em&gt;Dengan menggunakan algoritma LCM dalam mengatur proses pengacakannya, soal-soal yang akan ditampilkan diharapkan tidak mudah ditebak oleh siswa.&lt;/p&gt;&lt;p&gt;Kata kunci&lt;em&gt;: Linier Congruent Method, Multimedia Development Life Cycle,&lt;/em&gt;&lt;em&gt; &lt;/em&gt;Aplikasi pembelajaran Geografi&lt;/p&gt;