Reviewerly/exHarmony huggingface dataset:
Tinjauan Sistematis tentang Penggunaan Media Sosial untuk Promosi Perpustakaan Akademik

This study aims to collect, summarize, analyze, and synthesize information about the use of social media for the promotion of academic libraries in journal articles, undergraduate theses, master theses, and dissertations published in 2012-2021.Researchers conducted a literature search on several online databases subscribed to by the University of Indonesia (Science Direct, Emerald, and ProQuest), open access journal articles indexed at Garuda Ristekbrin, as well as undergraduate theses, theses, and dissertations from the UI Library website (lib.ui.ac.id).The selection process resulted in 14 documents for analysis.The results showed that the most widely used social media for library promotion are Facebook, Instagram, Twitter, and YouTube.The content that users are most interested in is in the form of images and videos.Promotion of libraries on social media can be done in the form of sharing information, promoting services, activities, and collections, providing social media-based services, and quizzes.Challenges faced include lack of competence, high workload of staff, privacy and identity theft issues, slow internet speeds, and frequent power outages.The results of this study can be used by the library to develop its promotion strategy.In addition, researchers who are interested in studying library promotion through social media can look at the results of this study to choose methods and perspectives that have not been used before.
Entanglement transitivity problems

One of the goals of science is to understand the relation between a whole and its parts, as exemplified by the problem of certifying the entanglement of a system from the knowledge of its reduced states. Here, we focus on a different but related question: can a collection of marginal information reveal new marginal information? We answer this affirmatively and show that (non-) entangled marginal states may exhibit (meta)transitivity of entanglement, i.e., implying that a different target marginal must be entangled. By showing that the global $n$-qubit state compatible with certain two-qubit marginals in a tree form is unique, we prove that transitivity exists for a system involving an arbitrarily large number of qubits. We also completely characterize -- in the sense of providing both the necessary and sufficient conditions -- when (meta)transitivity can occur in a tripartite scenario when the two-qudit marginals given are either the Werner states or the isotropic states. Our numerical results suggest that in the tripartite scenario, entanglement transitivity is generic among the marginals derived from pure states.
Lane and Vehicle Detection Using Hough Transform and YOLOv3

Object tracking at dark is critical to minimizing the number of nocturnal traffic crashes. This paper presents a deep convolutional neural network dubbed M-YOLO to enhance the precision of nocturnal object recognition and to be suited for limited contexts (also including microcontrollers in automobiles). To begin, track line images are separated into other * 2S panels based on the features of uneven spatial and temporal dispersion densities. Additionally, the sensor frequency has been limited to four measurement levels, making it even more suited for tiny source localization, like lateral distance measurement. Thirdly, to optimize the connectivity, a fully connected layer throughout the basic Yolo v3 method is reduced by 53 to 49 levels. Lastly, characteristics like cluster center radius and backpropagation are enhanced.
Limitless: A Mobile Application Featuring Next Generation Library Facilities For the Bangladeshi University Students

The University library is one of the parts and parcels of the universities that can assist students and teachers teaching and learning work by providing necessary services related to in-formation sharing, book search, book borrow, research document access, and reading room facilities, among others. A vast amount of the literature works related to library facilities emphasize providing services via offline mode rather than online mode. Most of the existing works on online-based library services focus on a single or limited number of library facilities and resources. The existing research works on university library facilities do not consider multiple library resources, different types of users, and multiple features at the same time. Thus, the existing university library related works mainly suffer from the shortage of library resources along with higher time and cost wastage. To tackle with the existing challenges, this paper presents a mobile application featuring next-generation library facilities for university students in Bangladesh. Our proposed limitless mobile application provides several features for students like book or research document search, borrow, order and access, payment and checkout, course enrollment, reading room allocation, request or donate a book, history, notifications, track order, complaint, among others. By using our proposed application, one member of the university library can access the resources of other university libraries via the membership/join feature. Our review result indicates that the majority of the student users are satisfied with the usefulness and necessity of the proposed mobile application features.
Image Captioning: Methods and Evaluation Metrics

In Computer Vision, image captioning is one of the most fascinating topics. Image captioning simply says generating sentences from a given picture. The process of generating captions from images includes two processes. One of them is image processing and the other one is natural language processing. In this, we use CNN that is a Convolution neural network, and RNN is a recurrent neural network. We use CNN for drawing out properties from the given picture and RNN for creating language. Though, the process is a bit complex and difficult, though we have put in a good amount of time in planning and research for the contentment of every attribute of it. The paper contains a comprehensive study of different models that are used for image captioning. Models that we will be discussing will be the Retrieval-Based Model, Template-Based Model, CNN-RNN based model, and CNN-CNN Model.
Detection Error Contaminated by Outliers to Classify Density Profiles Dependent on the Relative Speed Between a MIMO Sensor and a Human Hand

The detection of human hand intrusion is crucial for improving the productivity of human&#x2013;robot collaboration. Recent trends to safety-related sensors have adopted the concept of radar-based human presence detection. Some of them have already been commercialized. However, it has not yet been elucidated whether radars can sufficiently detect human hand intrusion and satisfy the required safety integrity level. In this study, we present outlier and error profiles obtained by detecting human hand intrusion based on the motion and speeds of the human hand and radar sensor. Our experiments indicate that slow hand movements require further studies from the viewpoint of safety. In addition, we suggest a new noise model demonstrating random noise and temporary outliers based on the recorded noise profiles of actual human participants. The obtained outlier and error profiles can be utilized as an outlier judgement criterion of the sensing in the specific case of the radar.
Alleged corrupt practices on stock theft by public sector officials in the selected rural areas of Giyani, Limpopo Province: Exploring the causes and experiences

The objective of the study was to explore alleged corrupt practices of stock theft by public sector officials in the selected rural areas of Giyani in the Limpopo Province, South Africa, focusing on causes and experiences. The local South African Police Service (SAPS) and Department of Justice and Constitutional Development: Giyani Magistrates’ Court (DOJ &amp; CD: GMC) officials are allegedly touted to be allegedly involved in corrupt and fraudulent activities relating to this crime. From a qualitative standpoint; this study purposively selected 64 participants to form part of Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs) for data collection based on their respective knowledge and exposure to this crime. The collected data was analyzed to reach structured, reliable and conclusions adopting the Tesch technique. Major findings of this study indicate that the local SAPS and DoJ &amp; CD: GMC were implicated in corruption acts, it is established that limited wages, greediness, profit and power, opportunity, as well as inadequate training, poor hiring practices and failure to adhere to a code of ethics are some of the notable causes of police corruption on stock theft cases. The improvement in legislation, punitive methods, remunerations, political partisanship, and the use of anti-corrupt strategies are cited as some recommendations in this study. Moreover, relevant stakeholders should work closely with provincial structures at rural communal levels, while avoiding a silo mentality to enhance collective actions thereof.
TEXTUAL MEANING STRATEGIES IN UX WRITING OF GO-JEK MOBILE APPLICATION

This research intends to examine how textual meaning strategies influence the user of Go-Jek mobile application through UX (User Experience) writing. The data of this research was the UX writing of the Go-Jek mobile application in version 4. 10. 3. All the UX writing in its apps would be disparted into clauses. Then, the theories of UX writing and Systemic Functional Linguistics (SFL), especially the Theme System, are applied in this research. This research has shown that Go-Jek’s UX writing used some textual meaning strategies. The three highest percentages of mood classes are declarative, imperative, and WH-interrogatives. Declarative clauses give a lot of brief information to the user. This information builds the purposeful concept of UX writing. Then, imperative clauses show much conciseness of word choices that eases the user in understanding the guideline of its application step by step. Third, WH- interrogatives clauses indicate conversational or interactivity responses, which create an intimacy between Go-Jek and its user. The interactivity can stimulate and encourage the user to try new services and promotions. Besides, their clear statement or command helps the user in minimizing errors. These strategies are fruitful for both usability and professionalism of the Go-Jek application through UX writing.Keywords; UX writing, User Experience, Systemic Functional Linguistics, Textual meaning
Evaluating the Impact of Immersive Virtual Reality Learning Environments with a Cognitive Load on Students in Various Interaction Modes

The purpose of this study is to discuss how the complex interaction methods in the virtual reality teaching environment affect students' understanding of operational training. A specific medical experiment learning process is designed as a system that integrates three interaction methods. 48 students were tested mainly from the perspective of system usability and system operability, and students' opinions and feedback on the system were also collected by means of unstructured questions and answers. The test results show that additional perceptual channels will increase the cognitive load of learners. The virtual reality system integrating haptics does improve students' learning interest on the one hand, but also increases students' learning and cognitive load on the other hand.
Multi-objective Optimization of Multi-video Synopsis Based on NSGA-III

Multi-video synopsis can display all information of surveillance video and show all sports solution of moving objects in the sight of multi-cameras. However, most of the existing multi-video synopsis can't achieve these functions. This is because these approaches do not comprehensively consider these factors: video target display timing, maximum target display number, target display consistency, maximum moving target display density, and compression ratio. To address the comprehensive optimization problem of multiple elements for multi-video synopsis, a multi-objective optimization algorithm for multi-video synopsis is proposed. The proposed approach differs significantly from the existing methods and has several appealing properties. First, we propose five objective functions, which are consistent in time sequence, coherent in cross-camera pedestrian display, largest in number of moving objects displayed, smallest in density of moving objects, and smallest in compression ratio, then, establish a multi-objective optimization model based on the five objective functions. Second, we build a model for multi-video synopsis. Third, we use the non-dominated sorting genetic algorithm NSGA-III to optimize the multi-object model of the multi-video synopsis. Through such a solution, the poor performance of multi-video synopsis can be avoided by comprehensively considering the main influencing factors of multi-video synopsis. Besides, we present extensive experiments that demonstrate the effectiveness and efficiency of the proposed approach.
Version Release Management for Free vs. Paid Apps: Understanding the Relationship between an Operational Lever and the Marketplace Imperative

This paper seeks to understand how the signal associated with the release of version updates, an operational lever, can drive user engagement with an app, a marketplace imperative. In conceptualizing the frequency of version updates for realizing operational agility, we differentiate between functional and non-functional version updates. A functional version update focuses on the functionality of an app, for example, by introducing a new feature to an app. A non-functional version update, on the other hand, seeks to improve the quality of an app by fixing bugs, improving stability, or addressing performance-related issues. Based on the business monetization model, an app is often referred to as free or paid. We focus on contrasting the relationship between the release of functional/non-functional version updates and the concomitant user engagement for free vs. paid mobile game apps. We view that user expectations for operational agility associated with the release of functional and non-functional version updates would differ for free and paid apps, which, in turn, will lead to different effects on user engagement. This research consists of two studies. Study 1 draws from longitudinal, observational data to examine the differential effects of the signal of continuous improvement created by the release of functional/non-functional version updates for free/paid apps. Using data collected from Apple’s App Store and a leading app analytics platform, spanning over a 7-month period from February 1 to August 30, 2020, we empirically investigated how the frequency of functional/non-functional version updates contributes to user engagement with those free/paid apps. Based on version-level difference-in-differences (DID) and daily app-level panel data analyses, we found that the impact of the release of version updates on user engagement is contingent on the type of version update and the associated monetization model of mobile apps. Study 2 is a controlled experiment that sheds light on user beliefs that are associated with two types of signals that are evoked by functional/non-functional version updates for free/paid apps. Our findings indicate that app version release management is not just an operational lever that is an intrinsic part of release planning but can also influence an app’s marketplace imperative of iteratively managing user engagement.
Simultaneous stoquasticity

Stoquastic Hamiltonians play a role in the computational complexity of the local Hamiltonian problem as well as the study of classical simulability. In particular, stoquastic Hamiltonians can be straightforwardly simulated using Monte Carlo techniques. We address the question of whether two or more Hamiltonians may be made simultaneously stoquastic via a unitary transformation. This question has important implications for the complexity of simulating quantum annealing where quantum advantage is related to the stoquasticity of the Hamiltonians involved in the anneal. We find that for almost all problems no such unitary exists and show that the problem of determining the existence of such a unitary is equivalent to identifying if there is a solution to a system of polynomial (in)equalities in the matrix elements of the initial and transformed Hamiltonians. Solving such a system of equations is NP-hard. We highlight a geometric understanding of this problem in terms of a collection of generalized Bloch vectors.
Gated Recurrent Unit RNN based Non-negative Tucker Decomposition for Satellite Image Compression

Satellite images are often volumetric, requiring a lot of storage and transmission space and time. In this paper, a Gated Recurrent Unit RNN based NTD method has been proposed for satellite image compression. RNN is used to convert spectral sensor into small scale spectral sensor. Entropy encoding is performed for final compression. The proposed method is compared to the standard NTD in the wavelet domain, the computing efficiency is improved by 56.40% while compromising just -0.58 dB of PSNR.
Design and Implementation of Privacy Protection of Charity System Based on Blockchain

With more and more public involvement in the charity field, higher requirements are put forward for user privacy protection in the charity system. As a decentralized, anonymous and immutable distributed ledger, blockchain provides a new idea to solve the privacy protection problems in charity systems. Aiming at the problem of data privacy protection of charity system, user-oriented and data-oriented privacy protection methods are proposed. User-oriented privacy protection by writing smart contracts to limit users&#x0027; access to data and ensure the privacy of data; Data-oriented privacy protection encrypts data by using encryption algorithms. In this paper, an improved AES algorithm is proposed. By dynamically constructing S-box, the algorithm does not have obvious structural characteristics, and various properties are random transformation, which increases the difficulty of cracking; At the same time, the AES algorithm is parallelized to improve the encryption and decryption rates. Experimental results show that the improved AES algorithm can ensure the security of data encryption in charity system and improve the operation efficiency.
Facilitating rearward visibility by controlling eye direction in HMD viewing of panoramic images

The development of HMDs for home use has progressed, and many people can now enjoy VR easily at home. Most VR services for 360-degree image viewing are used in a seated position. However, it is difficult for humans to look rearward in a seated position while rotating the neck and hips [1]. Although it is easy to look rearward when sitting in a swivel chair, it has been reported that the rotation of the seat surface amplifies the user&#x0027;s body movements and increases sensory discrepancy when viewing a 360-degree video with an HMD [2]. In this paper, we propose a new method that enables rearward visibility while sitting in a chair. The direction in which you are looking is called the eye direction. A rearward scenery that is different from the actual eye direction will be presented on the HMD to enable to look rearward without lifting the hips.
Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion

Fusion of high-level symbolic reasoning with lower level signal-based reasoning has attracted significant attention. We propose an architecture that integrates the high-level symbolic domain knowledge using a hierarchical planner with a lower level reinforcement learner that uses hybrid data (structured and unstructured). We introduce a novel neuro-symbolic system, Hybrid Deep RePReL that achieves the best of both worlds-the generalization ability of the planner with the effective learning ability of deep RL. Our results in two domains demonstrate the superiority of our approach in terms of sample efficiency as well as generalization to increased set of objects.
Mathematical morphology on directional data

We define morphological operators and filters for directional images whose pixel values are vectors on the unit sphere. This requires an ordering relation for unit vectors which is obtained by using depth functions. They provide a centre-outward ordering with respect to a specified centre vector. We apply our operators on synthetic directional images and compare them with classical morphological operators for grey-scale images. As application example, we enhance the fault region in a compressed glass foam.
Research on Anti-jamming Technology of Long-distance Transmission of Underground Coal Mine Signal

With the accelerating intelligent process of the underground coal mine, various intelligent products are applied in the underground coal mine, but at present, the problem of interference of various electrical appliances in the underground coal mine remains an important issue; the strong interference environment has affected signal transmission, signal acquisition, and other processes. In response to how to restrain electromagnetic interference in underground coal mines, this paper analyzes and discusses this application scenario for the long-distance transmission process in underground coal mines, and adopts the signal transformation method to suppress the interference in the signal transmission process, which is more adaptable to the complex electromagnetic environment in underground mines.
Testing Tutor

Testing Tutor is a web-based platform that helps instructors support software testing pedagogy by automatically diagnosing the fundamental testing concepts (e.g., boundary value) not covered in students' test suite and subsequently helping students initiate their own learning process about those concepts and systematically improve their test suites. The platform's differentiating features include 1) customizable feedback engine which allows instructors to scaffold the level of feedback (varying from conceptual to detailed), 2) a built-in repository of problems instructors can use, 3) access to digital learning content and 4) modes (learning and development) so instructors can scaffold the level of problems. This demo provides a brief overview of the platform and a walkthrough of two example use cases that illustrate the power of Testing Tutor from the perspectives of an instructor and a student. The two use cases will (1) demonstrate using Testing Tutor at different course levels by walking through the steps for an instructor to configure an assignment and the feedback engine and (2) demonstrate the student's experience submitting an assignment and receiving feedback. Information about Testing Tutor can be found at https://testingtutor.org. This work is supported by NSF IUSE grants 2013296 and 2013342.
Academic Middle Management

Are you the director of undergraduate programs for your department? Or do you want to be one in the future? In many departments, the role of shepherding the undergraduate program is a "middle management" position held by a single person, with pressures and responsibilities unique to the role. This Birds of a Feather session will be an opportunity to build community and learn from one another: what does it mean to effectively lead an undergraduate computing program? what challenges do we face? and how can this role help position us for other professional opportunities?