Reviewerly/exHarmony huggingface dataset:
LibGuides: Library Policies : Meeting Room use

Writing library policies and procedures is an important task, but is often at the bottom of a busy library board's to-do list. This guide is designed to provide some sample policies, along with resources to make the process a little faster and easier. Thi
Comparison of Effects of Radiofrequency Ablation of Liver Cancer Guided by CT Images Based on Deep Learning Algorithm

Objective. To investigate the paper radiofrequency ablation (RFA) CT-guided feasibility of hepatocellular carcinoma (primary liver cancer) treatment, safety, and clinical efficacy of the use of deep learning algorithms. Method. A total of 47 cases of primary liver cancer patients were included: 21 cases of CT-guided liver lesions in line with RFA (C-CT group) and, in the same period, 26 cases of spiral CT-guided liver lesions in line with RFA (S-CT group). Two groups of patients were recorded immediately after the total operation time and ablation time, the acceptable radiation dose was observed in the incidence of postoperative complications of 7d, and the postoperative hospital stay was recorded to evaluate the efficacy of the treatment of lesions in 1, 3, and 6 months after RFA. Results. All 47 patients were successful; two technical success rates were 100%. There was a significant difference ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>P</mi> </math> &lt; 0.05) in the total operation time groups, ablation time, and acceptable radiation dose. And there was no significant difference ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mi>P</mi> </math> &lt; 0.05) in postoperative complications of 7d groups, postoperative hospital stay, and local disease control. There was a significant difference ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mi>P</mi> </math> &lt; 0.05) in the S-CT group, seven ablation residual or recurrent lesions during the follow-up ratio of 26.9%, and C-CT groups compared with only 14.3%. Conclusion. CT-guided RFA treatment of primary liver cancer patients is safe, effective, and superior to the conventional spiral CT-guided ablation lesion site-specific terms.
LibGuides: Biases in Research and Beyond: Literacy Reference Guide: Category Scope Notes

Resources gathered by the Faculty Research Council on identifying and combating bias in academia and academic research.
AMVAE: Asymmetric Multimodal Variational Autoencoder for Multi-view Representation

Real-world data are typically described using multiple modalities or multiple types of descriptors that are considered as multiple views. The data from different modalities locate in different subspaces, therefore the representations associated with similar semantics would be different. To solve this problem, many approaches have been proposed for fusion representation using data from multiple views. Although effectiveness achieved, most existing models lack precision for gradient diffusion. We proposed Asymmetric Multimodal Variational Autoencoder (AMVAE) to reduce the effect. The proposed model has two key components: multiple autoencoders and multimodal variational autoencoder. Multiple autoencoders are responsible for encoding view-specific data, while the multimodal variational autoencoder guides the generation of fusion representation. The proposed model effectively solves the problem of low precision. The experimental results show that our method is state of the art on several benchmark datasets for both clustering and classification tasks.
Feedback strategies on verbal and nonverbal cues toimprove communication skills

In this thesis, we present findings on designingand validating real-time and post feedback on nonverbal skills inface to face communication skills with a humanoid agent. Thetechnical challenges included a real-time machine learningframework that can automatically process the audio-video data viaa webcam, allowing the users to converse in natural language andreceive live and post feedback on smile intensity, volumemodulation, pauses, synchronicity, body language, eye-contact,sentiment and turn-taking. Our initial exploration includeddesigning a wizard-of-oz experiment validating the form factors(i.e., flashing icons using the traffic light analogy) forreal-time feedback using 46 college students. Using the data, wetrained a hidden Markov model to generate feedback. The feedbackon verbal cue was generated by performing sentiment and wordcategory analysis. For post feedback, we summarized the nonverbalfeedback using the support vector machine. The technicalcontributions were validated in three unique contexts: 1) helpingindividuals with autism; 2) helping elderly with their socialskills; 3) helping physicians improve their interactions skillswith patients. Applications to speed-dating and autism: In arandomized control study with 47 college students, we found thatthe feedback helped improve eye contact and gesture. In apreliminary study with nine teenagers with autism, we identifiedseveral design guidelines which include, briefing the users,making positive acknowledgments, and personalizing dialogue.Applications to aging: In a pilot study with 25 older adults,participants found the feedback useful and were able to reflect onthe feedback. In a subsequent longitudinal study with 18 olderadults, participants improved their eye contact and smiling.Applications to patient-physician communication: In the context ofpatient-physician communication, we conducted a study with eightclinicians where they found the feedback intuitive and easy tofollow. Additionally, we identified two communication behaviors ofphysicians that help improve patients’ prognosis understanding - 1)lecturing style of a conversational structure by maximizingentropy, and 2) the positive language patterns (i.e., sentimenttrajectory) using k-means clustering. We used a data set thatincludes conversations between physicians (N=38) and late-stagecancer patients (N=382). With statistical analysis, we show thatphysicians who were lecturing their patients and did not varytheir positive sentiment had patients with prognosismisunderstanding. During global pandemics (e.g., COVID-19), whensocial distancing is recommended, most communication is takingplace online. This indicates the need for online communicationtraining programs that can overcome social and globalboundaries.
Investigation the impact of Classroom Interaction on EFL Students’ Proficiency

This paper aims at tracing the implications of the term ( classroom interaction) and the types of interaction that can be used in EFL learning and its importance in increasing students' proficiency ; the study used the descriptive analytical approach to achieve the target goals. Finally it is concluded that classroom interaction can be achieved through following many techniques and methods, and by practicing language through interaction students will be able to use language communicatively.
An Analysis of Deixis in Game of Thrones:The Dance of Dragons Movie Script

English is an international language. Beside to unite people in the whole world as its official role, it also has uniqueness in terms of oral communication dealing with the context. In this study, the deictic expressions are unmasked in speakers’ English utterances based on deixis framework. Descriptive qualitative approach was applied to succeed this study. The source of data was the utterances of characters in the movie script of Game of Thrones: The Dance of Dragon. Data collection process was conducted by doing documentary technique. The findings reveal that five types of deixis were found which were frequently expressed by characters in that movie. Five types of deixis were regularly uttered 221 times and the dominant one was person deixis namely 139 times. The reason why person deixis is dominant because most of characters involved in the conversation in movie Game of Thrones: The Dance of Dragons were surrounded by a variety of characteristics which steered them to use person deixis to refer to the object they aimed at.
Pengaruh Model Pembelajaran PBL dengan Media Bingo Pada Materi Laju Reaksi Terhadap Hasil Belajar dan Aktivitas Siswa

This study aims to determine whether there are significant differences in learning outcomes and student activities among students who are taught with the Problem Based Learning model and Bingo media with students who are taught with Problem Based Learning without Bingo media. The population in this study were all students of class XI MIA MAS Univa Medan consisting of 2 classes. The sample was determined by purposive sampling, class XI MIA 1 as an experimental class and class XI MIA 2 as a control class. This type of research is quasi-experimental. The research data were obtained by providing pretest and posttest of 20 multiple choice and validated student activity questionnaires. The data analysis technique is using t-test and hypothesis testing to find out the increase in student learning outcomes and activities. The results obtained with the gain value for the learning outcomes of the experimental class are (88%) and the control class (71%). Hypothesis testing results for learning outcomes obtained tcount (9.81)> ttable (1.671) and the results of hypothesis testing for student activities obtained tcount (4.45)> ttable (1.671) then it is concluded that there is an influence of learning outcomes and student activities that are learned with Problem Based Learning (PBL) learning model on the reaction rate material using Bingo media.
Color image encryption using linear feedback shift registers by three dimensional permutation and substitution operations

This study proposes a scale-invariant digital color image encryption method that includes three main steps the pre-substitution, the 3D scale-invariant modular chaotic map, and the post-substitution. 1) The pre-substitution: At the first stage, pixels of plain sub-images are XOR with different key patterns. By starting from one of the plain sub-images, the pixels of the selected plain sub-image is XOR with the initial key, and the result is used as the cipher sub-image and as the next key pattern for performing XOR operations on the next plain sub-image. In other words, the XOR result of each step is used as the next step key pattern, 2) the 3D permutation: At the second stage,  first the red, green, and blue components of a $M times N$ color image is divided to m sub-images with size $n times n$. Then m sub-images are partitioned into $k = leftlceil {frac{m}{n}} rightrceil $ windows $W_1$ to $W_k$ with size $n times n$ sub-images. The last two i؟¼$W_k-1$ and i؟¼$W_k$ windows may be overlap in several sub-images. Finally, the three-dimensional modular chaotic maps are performed on the $W_1$i؟¼ to $W_k$i؟¼ windows with MIPF keys and selected by LFSR, 3) the post-substitution: At the final stage, the $M times N$ color image is initially divided into a set of color sub-images. Then, the 24-bit pixels of each sub-images are circularly shifted with several bits specified in the secret key. Modular arithmetic is used in the 3D scale-invariant chaotic maps to increase keyspace and enhance security parameters. With repeat at least one round of main steps, the proposed encryption scheme reaches optimum parameter values and it is highly sensitive to minor differences in both secret key and plain image. The proposed encryption method for images improves the standard parameters of evaluation such as entropy, adjacent pixel correlations, histogram, and expanded keyspace.
Optimizations of Isogeny-based Key Exchange

Supersingular Isogeny Diffie-Hellman (SIDH) is a key exchange scheme that is believed tobe quantum-resistant. It is based on the difficulty of finding a certain isogeny between givenelliptic curves. Over the last nine years, optimizations have been proposed that significantlyincreased the performance of its implementations. Today, SIDH is a promising candidate inthe US National Institute for Standards and Technology’s (NIST’s) post-quantum cryptographystandardization process.This work is a self-contained introduction to the active research on SIDH from a high-level,algorithmic lens. After an introduction to elliptic curves and SIDH itself, we describe themathematical and algorithmic building blocks of the fastest known implementations.Regarding elliptic curves, we describe which algorithms, data structures and trade-offs regard-ing elliptic curve arithmetic and isogeny computations exist and quantify their runtime cost infield operations. These findings are then tailored to the situation of SIDH. As a result, we giveefficient algorithms for the performance-critical parts of the protocol.
PERFECTIONOF CLASSIFICATION ACCURACY IN TEXT CATEGORIZATION

Problems and strategies for text classification have already been known for a long time. Theyre widely utilised by companies like Google and Yahoo for email spam screening, sentiment analysis of Twitter data, and automatic news categories in Google alerts. Were still working on getting the findings to be as accurate as possible. When dealing with large amounts of text data, however, the models performance and accuracy become a difficulty. The type of words utilised in the corpus and the type of features produced for classification have a big impact on the performance of a text classification model.
Technology Innovation To Modern Designs Gasing or Top Spinning in Community Culture

This paper will discuss the technology that brings innovation to modern design in the culture of society. The design of modern technology has helped reintroduce old games that are gasing or top spinning to the new generation. The invention of modern technology in the redesign of the lace design has helped to bring the interest of today’s generation closer to the lace game. Modern technology in the design of the original design has also gained popularity among people of all ages. In this regard, how the extent to which modern technology plays a role in influencing the production of a variety of design in gasing or top spinning the needs and requirements of modern society. In addition, why the extent to which the game of gasing or top spinning can help create team spirit in the game of gasing or top spinning. In addition to examining how modern technologies that use new technologies have been implementing the reforms in the field are gaining popularity among the community culture. Re-documenting this study could add further sources of reference to other researchers in the future.
Transformational influence of fake messages on the behavioral activity of an individual: psycholinguistic aspect

The article highlights the issue of the psychological impact of fakes on the individual, which is intensively increased through various mass media and especially social networks. The general research aim comprises the study of features of the psychological influence of fakes on an individual and classification of this influence. It was proven that fakes intensify the person's stress, weaken adaptive reserves, reduce efficiency, and lead to stress disorders. Numerous fake messages cause intense emotional transformation of the individual through the emotional receptivity of the message. It was found that under the influence of fakes, a person's direct participation in the information cycle through the mass media contributes to the consolidation of his behavior into certain groups. Fake information encourages fake modeling of one's own future and determines its influence on one's status in society. It was shown that human perception of emotional audiovisual narratives causes the tunnel vision. Pragmatic assumptions stimulate the individual to perceive fake information as the absolute truth, and in situations of uncertainty - to show a pronounced activity with a growing preference for information. Fakes can worsen physical and mental health, cause changes in mental processes, motivation, priorities and affect interaction in the society. That is why, the knowledge of features of the psychological impact of fakes on an individual will help understand the need to analyze information content, search, critically select and test messages to maintain one’s mental health.
New artificial neural network design for chua chaotic system prediction using FPGA hardware co-simulation

This study aims to design a new architecture of the Artificial Neural Networks (ANNs) using the Xilinx System Generator (XSG) and its hardware co-simulation equivalent model using Field Programmable Gate Array (FPGA) to predict the behavior of Chua's chaotic system and use it in hiding information. The work proposed consists of two main sections. In the first section, Matlab R2016a was used to build a 3×4×3 Feed Forward Neural Network (FFNN). The training results demonstrate that FFNN training in the Bayesian regulation algorithm is sufficiently accurate to directly implement. The second section demonstrates the hardware implementation of the network with the Xilinx System Generator (XSG) on the Xilinx Artix7 xc7a100t-1csg324 chip. Finally, the message was first encrypted using a dynamic Chua system and then decrypted using ANN's chaotic dynamics. ANN models were developed to implement hardware in the Field Programmable Gates Array (FPGA) system using the IEEE 754 Single precision floating-point format. The ANN design method illustrated can be extended to other chaotic systems in general.
Governance-Based Library Management, More Effective and Efficient

This study was conducted to determine how implementation of management in the activities of the package service program. Management in question is how to implement management functions such as planning, organizing, staffing, directing, budgeting, and monitoring. This research is a descriptive research with a qualitative approach. Data collection techniques in this study were through interviews, observation, and literature review. The results or data obtained are analyzed using three stages, namely data reduction, then the data is presented in the form of narrative text and draws conclusions according to the problem formulation that has been described. The results of the study indicate that in running the program, the package service has implemented management functions. Activities related to planning are carefully arranged, the stages of activities, a series of times are aligned. Implementation in activities by grouping activities, division of labor and providing direct directions is also implemented so that it goes according to plan even though limited transportation facilities hinder the delivery of package services to the locations of the fostered libraries. Meanwhile, for coaching activities now no longer use the budget. Supervision is carried out by going directly to the target library, but the time to supervise the assisted library in the Jakarta area is still not on schedule.
CAUGHT IN A CROSSFIRE: CAMPAIGN SPEECHES OF PRESIDENT RODRIGO ROA DUTERTE (PRRD)

Through the use of critical discourse analysis, this study aimed to analyze PRRD’s campaign speeches with the purpose of establishing its discursive patterns. The study employed the descriptive-qualitative design which utilized Critical Discourse Analysis, anchored with Systemic Functional Linguistics (SFL) by Halliday. Results show the highest frequency of the following lexico-grammatical features: modals will, would, should, and shall; pronoun I (me); and verb tense present simple. Results also reveal that verbal process constitutes the highest in terms of transitivity, while it is positive median politeness for modality. Also, the analysis reveals that the informative, regulatory, and instrumental are the dominant functions of language used by PRRD. Based on the findings, PRRD stressed his campaign speeches with willingness, determination, certainty, and fortitude, with greater involvement of himself; PRRD had gone extra-mile to attack the personalities of the other parties for self-projection and self-promotion, along with the expression of enthusiasm, optimism, and determination to elicit support from the populace; and PRRD focused on neutralizing the asymmetrical power relations that existed between him and the electorate, but with the emphasis of control, and needs of his countrymen. KEYWORDS—Critical Discourse Analysis, Campaign Speeches, Language Functions, Discourse Features, Transitivity, Modality
The Pursuit of Knowledge: Discovering and Localizing Novel Categories Using Dual Memory

We tackle object category discovery, which is the problem of discovering and localizing novel objects in a large unlabeled dataset. While existing methods show results on datasets with less cluttered scenes and fewer object instances per image, we present our results on the challenging COCO dataset. Moreover, we argue that, rather than discovering new categories from scratch, discovery algorithms can benefit from identifying what is already known and focusing their attention on the unknown. We propose a method that exploits prior knowledge about certain object types to discover new categories by leveraging two memory modules, namely Working and Semantic memory. We show the performance of our detector on the COCO minival dataset to demonstrate its in-the-wild capabilities.
Digital Divide and Online Instruction Delivery Readiness Among Nigerian Universities in an Era of COVID-19

This study on the digital divide and online instructional delivery readiness among universities in Nigeria employed the descriptive survey research design. Six universities were selected in South-South, Nigeria. These include two federal, two-state, and two privately-owned universities. The selected universities are the University of Calabar, University of Benin, (federally owned), River State University of Science and Technology; Cross River University of Technology (state universities) and Arthur Jarvis University, Akpabuyo and Benson Idahosa University Benin City (private universities) all in South-South Zone, Nigeria. Three faculties were selected from each university. These include Education, Science and Social Sciences. Different departments were randomly selected within each of the selected faculties. The population of the study was 10,274 undergraduate students during the 2020 academic session. A random sampling procedure was employed to choose undergraduates from all levels in the selected departments using a sampling percentage of 20% to give a sample size of 2,596. The instrument for data collection was a questionnaire. The questionnaire collected data on demography, availability of ICT infrastructure, staff and students ICT skills, factors deepening the divide, and online instruction readiness of universities. Data collected were analyzed using the Statistical Package for Social Science version 23 (SPSS) to get frequency and percentages. The results from the analyses reveal that a greater percentage of the students are highly proficient in ICT skills, private universities had more ICTs than public universities, and it was also though private universities were ready, the sampled public universities were not technically ready for online instructional delivery.
Multi-Class Motor Imagery Classification

The Motor Imagery (MI) classification task is a high dimensionmultivariate and complicated subject. In this respect, the originalsignals are analyzed and minimal unique features of the classes are