Reviewerly/exHarmony huggingface dataset:
Pose-Invariant Face Recognition in Surveillance Scenarios Using Extreme Learning Machine Based Domain Adaptation

Face Recognition (FR) under adversarial conditions has been a big challenge for researchers in the computer vision community. FR performance deteriorates in surveillance condition due to poor illumination, blur, noise, and pose variation in test samples (probe), when compared to training samples (gallery). Even recent deep learning methods fail to perform well in such conditions. This paper proposes a novel framework called PIFR-EDA (Pose-Invariant Face Recognition using Extreme learning machine based Domain Adaptation) that performs pose-invariant face recognition (PIFR) in cross-domain settings. It consists of two stages where the first stage performs face frontalization using a single unmodified 3D facial model and the second stage performs the task of robust domain adaptation by simultaneously learning a category transformation matrix and an \(\ell _{1,1}\)-regularized sparse extreme learning machine classifier. The proposed method outperforms state-of-the-art shallow and deep methods (in terms of rank-1 recognition rates) when experimented on three real-world face datasets captured using surveillance cameras.
Guides: ebooks: Getting Started

RRC Libraries has an extensive collection of ebooks allowing students from all campuses (including regional ones) to access them via the internet. This guide will give you an introduction to everything you need to know.
Hardware Trojan on SIMON Architecture for Key Retrieval

The need of an hour is the research on design and impacts of Hardware Trojan Horse in a crypto module to serve the purpose of secret key recovery. SIMON is a light weight block cipher that indulges to optimally work with hardware environment. Few papers have come up with the fault attack on SIMON cipher. In this paper, two bit toggle fault attack on 29 $$^{th}$$ round of the SIMON by intruding Hardware Trojan Horse is realized. The structural design of Hardware Trojan includes activation of two payloads with a single trigger. In consequence, the round key of SIMON cipher is retrieved by executing Differential Fault Analysis, using the fault free and completely faulty ciphertext. The power consumption of the SIMON design for both with and without Hardware Trojan is estimated using Simulation Activity Information File (.saif) on ZYNQ 7000 SoC family FPGA board and observed that there is minimal overhead of 1.32%. Provided, almost negligible difference of one LUT in area utilization is discerned. This infers that the insertion of designed HTH in the SIMON module have created an imperceptible impact and bypasses the testing process.
Level Set Image Segmentation Based on Non-independent and Identically Distributed

Aiming at the problems of traditional image segmentation methods such as single image type and falling into false boundary, a level set image segmentation algorithm based on non-independent and identically distributed (non-IID) is proposed. The traditional image segmentation method basically assumes that all samples are independent and have the same distribution. However, this assumption does not hold. In this paper, the image is segmented into several pixel blocks by super-pixel segmentation method. The feature vectors are extracted from the pixel blocks by non-IID method. We combine the obtained feature vectors with the CV model to change the energy function of the level set method and apply the new energy function to image segmentation. The experimental results show that the proposed algorithm can segment all kinds of images and has a good segmentation effect for weak edge images.
The Program for Cooperative Cataloging’s Transformative Role as a Leader of Change

The transformation of library metadata encoded in MARC to linked data will enable libraries to participate in the Semantic Web. This transformation, however, will be an iterative development dependent upon community-based decisions. The PCC, as a community-based organization, is ideally positioned to lead this transformation. As PCC guides this transition, three broad areas must be resolved: the conversion of legacy data to linked data, the use of identifiers to support controlled headings, and the transformation of current workflows to linked-data counterparts. By embracing the Web as a community, PCC can confirm its relevance in a complex web of global data.
Untapped potential for software engineering in an emerging society: The case of Papua New Guinea.

Technological advancement is a main driver for societal change. The Papua New Guinean (PNG) society is currently undergoing technological, economic, and social transformations, with first signs indicating the development of a local software engineering community. To characterise challenges and opportunities associated with a country's progress toward becoming a member of the global software engineering community, we set out to explore the situation in PNG. To this end, we organised a local software engineering workshop and invited students, educators and industry experts to participate. Besides collecting data by distributing a questionnaire (n=52) and by recording talks (n=3) during the workshop, we conducted an in-depth focus group session with local actors (n=5). Based on a thematic analysis of the resulting qualitative data, we present five themes that capture challenges and opportunities for PNG software engineers. We further discuss local implications for emerging societies such as PNG and global implications for software engineering in general.
Psychological well-being: analysis and interpretation applying Compositional Data Analysis methods

One of the applications of Psychology that makes use of Statisticas is that which refers to the analysis of psychological well-being tests. However, this analysis was not systematic until Carol Riff proposed in 1989 a test to describe, analyze and interpret the psychological well-being of people. The model is based on six descriptive fields or dimensions of psychological well-being: self-acceptance, positive relations, autonomy, environmental mastery, purpose in life and personal growth. To measure these theoretical dimensions, an instrument known as Scale of Physiological Well Being (SPWB) was developed, with 120 items forming the original scale. Nowadays, there exist several different versions of the instruent in different languages and with different numbers of items. To interpret the results of the different dimensions, the scores of each of them must be added up and compared with the maximum and minimum possible score, since there are no existing ready-reckoners. Application of the previous methodology generates certain problems when interpreting the results individually, since there is no normative or reference group with which to compare the results obtained. Applying methods of Compositional Data Analysis such as the centered log-ratio transformation (CLR), relative position ratios (RPR) of each individual can be obtained in relation to each of the indicators used. Positive values of the position ratio indicate that the subject is above the (geometric) mean of the normative group and negative values of the position ratio indicate that the subject is below the mean of the normative group. The average of the relative position ratios allows to obtain a global indicator or profile of subjective wellbeing for each individual, nor only in relation to himself but also in the context of the group in which he has been analyzed.
Engineering Technology Program of Study

This is a sample program of study for students in the engineering technology program. Before registering for engineering technology classes, please consult your advisor.
Toolkit for the Creation of a Drama Dataset

This paper presents a novel prototype service that concerns the creation of a drama dataset. The approach relies on an ontological representation of the dramatic qualities, the characterizing elements of a drama that abstract from the linguistic or media expression. A toolkit for the friendly encoding of the dramatic qualities overcomes the difficulties of the formal representation.
Dark Web Threat Intelligence and Market Analysis

It is described that the dark network is usually the dark side of the World Wide Web. At the same time, there are many threatening crime information in the dark network. It is a hidden part of the Internet and has gradually become a place for illegal activities, including the drug market, child pornography, gun sales, Financial fraud, assassination of employment, etc. Most criminals use specialized tools to access dark networks, such as TOR, which enable them to access networks anonymously. As a result, it has brought serious difficulties to research and law enforcement personnel. To achieve active cyber threat intelligence in cybersecurity research, this paper proposes a hidden network threat intelligence analysis framework, which is primarily used to identify the sellers of the dark network market and identify the sellers who have the greatest impact on these markets.
SSE String Manipulation

With SSE version 4.2, four compare-string instructions were introduced: two instructions for strings with implicit lengths and two instructions for strings with explicit lengths. Two of these four instructions use masks.
Delving into the Cognizance of Information and Communication Technology (ICT) among Undergraduate Students

We cannot deny the significant influence of Information and Communication Technology (ICT) in one’s lives. The impact is highly acknowledged, and the education field is at no exception. The advancement of ICT has indirectly affected students and their learning process. However, there lies a question as to how much undergraduate students utilise ICT in their daily lives. Are they prone to using it for recreational as compared to the educational purpose? Thus, this study aims to fathom undergraduate students’ perspectives in regard to their ICT usage, perceived ICT competencies, perceptions of ICT, and attitudes towards ICT. In addition, the difference based on gender factor was also investigated besides the correlation between the variables. This quantitative study employed a questionnaire as the research instrument and open-ended questions to unearth the respondents’ views concerning the issue. 283 undergraduate students were involved in this study. The findings showed mixed results pertaining to the elements investigated. In detail, the respondents asserted that ICT is synonymous with their undergraduate lives as it equips them with the necessary skills for their prospective careers. However, few elements need to be rectified and solidified to meet the expectation of ICT. This is crucial as it may inform the higher authority the current state of ICT cognizance and usage among the higher learning institutions students.
Improved vowel labeling for prenasal merger using customized forced alignment

Forced alignment is a popular technique for gaining phone-level audio transcriptions, but the pronunciation dictionaries used by it are typically based on standard varieties of US English, leading to errorful outputs for non-standard varieties. We employ a customized pronunciation dictionary with the Montreal Forced Aligner to increase labeling accuracy of the prenasal merger (a.k.a. pin-pen merger) in Southern US English. We allow the aligner to choose between IH (/ɪ/) and EH (/ɛ/) in words where the merger is expected, rather than enforcing a standard, unmerged pronunciation. We examine the tokens reclassified from EH to IH when using the new dictionary, and we use formant values to study the acoustic separation (measured by Pillai scores and Euclidean distances between centroids) between vowel formant clusters. When applied to the Digital Archive of Southern Speech (DASS), we find that the modification increases the separation between the prenasal allophones of IH and EH, and also that the proportion of prenasal EH tokens reclassified to IH is correlated with the original degree of separation between prenasal IH and EH for each DASS speaker. K-means clustering is also used to show the modification yields more accurate phonetic transcriptions, measured by increased precision and recall.
The compensation of deformation measurement in large field of view based on digital speckle pattern interferometry

Digital speckle pattern interferometry (DSPI) is a high-precision measurement method for measuring the surface deformation of an object. Compared with other measurement techniques, it has the advantages of full-field measurement, real-time, non-contact, high precision and high sensitivity, which has made the technology widely concerned by the measurement community since its birth. However, the application calculation of most of the existing digital speckle interference is based on the paraxial and approximate vertical calculations, ignoring the large fluctuation range of the angle between the laser illumination direction and the CCD observation direction. It makes the measurement error of large field of view larger when the size of the object is large . Therefore, when measuring a large field of view, it is necessary to correct the existing measurement formula. This paper proposes a new method for applying digital speckle interference to large field of view measurement. Based on the basic principle of digital speckle interferometry, the corresponding compensation coefficient is obtained through mathematical relationship to compensate the measurement result of large field of view.
Self-Discovery Writing Using Image Literacy and Simile

본 연구는 대학 글쓰기 교육에서 긍정적 자기발견의 글쓰기를 위해 이미지 리터 러시와 오레오맵(OREO Map) 형식 및 직유를 활용하였다. 먼저 학습자는 ‘나를 표현할 수 있는 이미지’를 탐색하였다. 탐색 방법은 자기 분석과 지인 인터뷰를 이미지로 연결하는 것이다. 다음으로 덜어내기 기법을 사용하여 대표 이미지를 선정하였다. 덜어내기 기법은 자신을 가장 압도하고 있는 대표 자질을 선별하는 데 도움을 주는 기법으로 자기이해에 조력한다. 이어 오레오맵 형식을 바탕으로 직유를 활용해 대표 이미지를 문자화하였다. 긍정적 자기발견은 자기수용을 동반하므로 설득적 메시지 구성을 돕는 오레오맵을 사용하였다. 또한 긍정적 자기발견은 자기탐색의 생산적 확장이므로 역동성과 방향성을 특질로 갖는 직유를 활용하였다. 마지막으로 구성한 내용을 연결하여 글쓰기를 진행하였다. 그 결과 학습자는 단계가 진행될수록 긍정적 자기를 면밀화하였고, 자기집중의 언어를 탈중심성으로 확장하면서 의식 수준 향상을 보여주었다. 본 연구는 제로텍스트 시대의 학습자 특성을 고려하여 이미지 리터러시를 활용하였고, 오레오맵과 직유의 자질을 자기발견 글쓰기로 연결하여 발달적 글쓰기 방안의 다양성을 확보하였다.This study utilizes image literacy, the OREO Map format, and similes to promote positive self-discovery in college writing education. First, learners explore images that can express themselves, which links selfanalysis and acquaintance interviews to pictures. Second, students select representative images through an extraction technique that aids selfunderstanding because it helps the learner identify the qualities that best represent them. Third, based on the OREO Map format, they use similes to develop a representative description. The OREO Map is used to organize persuasive messages since positive self-discovery is accompanied by self-discipline and students use similes with dynamic qualities because positive self-discovery is an extension of self-exploration. Finally, learners connect all of these elements so that they can proceed with writing. As a result, the students developed positive self-imagery as they worked through the steps. Their writing evolved from selfcentered to non-centralized language, and demonstrated a growth of consciousness. If we take the learner characteristics of the Zero-Text era into account, this study utilizes image literacy, and connects the OREO Map method and the capacity of the simile with self-discovery writing to secure diversity in the developmental writing system.
On construction of the comparison function of program motion in probable statement

On construction of the comparison function of program motion in probable statementIn the class of ordinary differential equations the following modification of the inverse problem of differential systems was previously considered: to construct both a set of systems of differential equations and a set of comparison functions for the given program motion.In this article, the modification of the inverse problem is considered in Stochastic case.In this problem it is assumed that random perturbations are from the class of processes with independent increments.By the given program of motion, two sets are constructed: the set of first-order Itô stochastic differential equations and the set of comparison functions.It is proved that there is a stability in probability of the given program motion with respect to the constructed comparison functions.To solve the problem Lyapunov functions method is used.Using Lyapunov's second method makes it is possible to weaken the conditions imposed on the components of the constructed comparison functions, in contrast to the application of the Lyapunov characteristic numbers method for solving the inverse problem in the class of ordinary differential equations.The following cases are considered: 1) comparison functions obviously not depending on time; 2) the set of comparison vector functions depends on y and t; 3) the set of comparison vector functions has the form Q(λ, t, where λ(y, t) describes an analytically given program motion; 4) the set of comparison vector functions has the form C(t)λ.
The Research of Chinese Ethnical Face Recognition Based on Deep Learning

Face recognition emerged in the seventies. With the introduction of deep learning methods, especially the convolution neural networks (CNNs), more and more traditional machine learning techniques have been recently superseded by them. In a multi-ethnic country like China, the study for Chinese ethnical face recognition (CEFR) has practical demands and applications. In this paper, we provide a brief of popular face recognition procedure based on deep learning method firstly. Then, as lacking of the corresponding dataset, we construct a collection of Chinese ethnical face images (CCEFI) including Han, Uygur, Tibetan and Mongolian. Based on multi-task cascaded convolution networks (MTCNN) [14] and residual networks (ResNets) [11, 12], our proposed model can achieve promising results for face detection and classification. Specifically, the average precision reaches 75% on CCEFI self-draft. Experimental results indicate that our model is able to detect the face in some constrained environments and distinguish its ethnical category. Meanwhile, the dataset established by us would be a useful dataset for relevant work.
Using Your Library with React

React is a widespread and popular library for user interface development in JavaScript. At the same time, D3.js is the most successful library for creating visualizations for the browser. Their prevalence means that in many projects, we need to make them work together. In this chapter, we will explore the use of D3.js charts within React applications.
Interactive Methods for Organizing Pre-Service Teaching Practice

The paper deals with the problem of organizing effective pre-service teaching practice for bachelor’s students. Improving the quality of students’ practical training is vital and could be based on the use of interactive teaching methods. The paper presents the typology and principles for organizing professional pedagogical internships aimed at students’ personal development and preparation for professional world. This problem is considered in the framework of activity-based approach where key elements are individual creativity, self-development and self-actualization acquired through active learning. The paper also reveals the goals and objectives for all types of professional pedagogical training, and provides examples of their implementation. It is shown that pedagogical training during pre-service teaching forms first professional students’ experience and reveals a specific nature of educational work.
The Life and Death of a Tectonic Plate: Imaging the Juan de Fuca Plate with Amphibious Seismic Data

Author(s): Hawley, William Bythewood | Advisor(s): Allen, Richard M | Abstract: Understanding of Earth’s evolution has been hindered, in part, by the technical challenges associated with placing seismic instruments on the seafloor. As technology improves, more arrays of ocean bottom seismometers are being deployed around the ocean basins. Perhaps the most ambitious such array, the Cascadia Initiative, covered the entirety of a small oceanic plate, the Juan de Fuca plate, with ocean bottom seismometers in a four-year experiment. That array is the primary motivation for this study.The two models presented in this work, CASC16-P and CASC19-S, are teleseismic tomographic studies. They are each the first of their kind to use offshore and onshore data to simultaneously image the P- and S-wave seismic velocity structure of the mantle beneath the Juan de Fuca and North American plates. These models have provided insight into the tectonics of oceanic plates: how they are created, how they might interact with the mantle over the course of their life, how they might be influenced by an overriding continental plate, how they behave in the mantle after subduction, and how subduction could cease.This work focuses on the on- and offshore regions of the Pacific Northwest of the United States—in particular, on the interaction between the Juan de Fuca plate, the North American plate, and the upper mantle. But it also demonstrates the value in oceanic arrays. The offshore instruments used in this study have allowed the identification of new features offshore, and better resolution of features near the coastlines. Ocean bottom seismology represents a rapidly growing new frontier that has the potential to investigate earth evolution in detail that was not previously possible. The work we present here has both helped illuminate the tectonics of the Pacific Northwest, and helped generate detailed hypotheses about the nature of global tectonics that will be tested elsewhere.
LibGuides: Zotero for MLA, APA and Chicago Citations: Synchronize your library

Zotero (pronounced zoh-TAIR-oh) is a program that collects, manages, and cites research sources. It's easy to use, lives in your web browser where you do your work, and best of all it's free.
Cosaliency Detection in Images Using Structured Matrix Decomposition and Objectness Prior

Cosaliency detection methods typically fail to perform in the situation where the foreground has multiple components. This paper proposes a novel framework, Cosaliency via Structured Matrix Decomposition (CSMD), for efficient detection of cosalient objects. This paper addresses the issue of saliency detection for images with multiple components in the foreground, by proposing a superpixel level, objectness prior. In this paper, we further propose a novel fusion technique to combine objectness prior to the cosaliency object detection framework. The proposed model is evaluated on challenging benchmark cosaliency dataset that has multiple components in the foreground. It outperforms prominent state-of-the-art methods in terms of efficiency.
Countess: "To Boldly Go" - Fall 2019 Library Mini-Conference: "To Boldly Go" -- 2019 Library Mini-Conference

In this LibGuide you'll find presentation topics for the Library's fall 2019 mini-conference. Our theme this year is in observance of the 50th anniversary of the Apollo Moon Mission. Observing the 50th anniversary of the Apollo Moon Mission (with a little Sci-Fi thrown in).