Reviewerly/exHarmony huggingface dataset:
The Usage of Electronic Academic Database Resources Among Lecturers and Postgraduate Students in Western Delta University, Oghara, Delta State, Nigeria

This study investigated the usage of electronic academic databases resources by lecturers and postgraduate students in Western Delta University, Oghara, Delta State, Nigeria. Four objectives with conforming research questions guided the study. The study adopted a descriptive research design. The population of the study consisted of 134 lecturers and postgraduate students in WDU. The instrument for data collection was a structured questionnaire with the title “Usage of Electronic Academic Database Resources Questionnaire (UEADRQ)”. Data was analyzed using frequency counts and percentages. The findings showed that there was a high level of awareness of the electronic academic database by the lecturers and postgraduate students. JSTOR, Elsevier, DOAJ, ProQuest, Science direct, and LexisNexis where been put to maximum usage. Meanwhile, NUC Virtual library, HINARI, Research4life, AGORA and EBSCO Host were used least frequently. The purposes of using the electronic academic datasets were for research, writing of seminar/conference paper, assignments/seminar presentations and getting up-to-date information with subject areas. Lack of search skill, slow internet bandwidth and incessant power outrage were some of the problems preventing against the effective usage of electronic academic database resources in WDU. Based on the findings of this study, it was concluded that electronic academic databases are vital information resources that need to be readily available in academic libraries for use by lecturers and students in the pursuit of their academic advancement. This study recommended that orientation, workshop and seminar should be organized by librarians and university authorities on how to acquire the needed search skills in order to be able to make adequate use of these electronic academic database resources in order to advance academic excellence.
Development of Inquiry-Based E-Poster Media on Natural Science Learning Digestive System Material in Elementary Schools

This study aims to determine the validity and practicality of inquiry-based media development on digestive system-based material in grade 5 elementary school students. The type of research used is development research using a 4-D model (define, design, develop, and disseminate). The research instrument used validation sheets, practicality sheets. While the results were analyzed with descriptive techniques. The results of this study indicate that students' learning motivation increases by using inquiry-based e-poster learning media. This can be seen in the results of the validation test of the e-poster media of the inquiry-based digestive system that was developed which is very valid and the results of the practicality test through a response questionnaire are categorized as very practical. Thus the e-poster media inquiry-based that was developed is valid and practical to use as a means of conveying digestive system material to 5th grade students in elementary schools.
Linear Complexity of Sequences on Koblitz Curves of Genus 2

Abstract In this paper, we consider the hyperelliptic analogue of the Frobenius endomorphism generator and show that it produces sequences with large linear complexity on the Jacobian of genus 2 curves.
DP-RAFT: A Differentially Private Recipe for Accelerated Fine-Tuning

A major direction in differentially private machine learning is differentially private fine-tuning: pretraining a model on a source of "public data" and transferring the extracted features to downstream tasks. This is an important setting because many industry deployments fine-tune publicly available feature extractors on proprietary data for downstream tasks. In this paper, we carefully integrate techniques, both new and from prior work, to solve benchmark tasks in computer vision and natural language processing using differentially private fine-tuning. Our key insight is that by accelerating training with the choice of key hyperparameters, we can quickly drive the model parameters to regions in parameter space where the impact of noise is minimized. We obtain new state-of-the art performance on CIFAR10, CIFAR100, FashionMNIST, STL10, and PersonaChat, including $99 \%$ on CIFAR10 for $\varepsilon=1, \delta=1e-5$-DP.
The Use of Conversational Natural Language Processing Chatbots For Simulated Intelligence in Home Cooking While Integrating with Meta Messenger

Abstract: Conversational Man-made consciousness (computer based intelligence), which permits individuals to have human-like collaborations with PCs, has encountered a blast lately. A large number of fields, for example, medical care, money, and retail have applied conversational simulated intelligence in their sites to save endeavors of getting done with simple jobs and give voice collaboration with end-clients. It empowers clients to find speedy solutions to every now and again got clarification on pressing issues and specialist co-ops to save time to handle more perplexing issues. This paper presents the Natural Language Processing Chatbots Cooking Assistance, which is a conversational specialist that gives matching recipes in view of the data given by clients. The expectation of Natural Language Processing Chatbots Cooking Assistance is to assist clients with disposing of unused fixings in the refrigerator by giving related recipes. Natural Language Processing Chatbots Cooking Assistance permits clients to enter a particular dish name or give a district, type, or potentially elements of the food they might want to have, and afterward it returns a recipe list as indicated by arranging and supplements prerequisites given by clients. The chatbot is assembled utilizing Google Dialog Flow stage to perceive the client's expectations and Spoonacular Programming interface to track down recipes that match the pursuit question. This paper talks about Natural Language Processing Chatbots Cooking Assistance's engineering, usefulness, and insufficiencies to be moved along. It gives a definite illustration of the communication between the chatbot and a client, which illustrates how the UI will work on the issue of finding a user interested recipe.
Students' Perceptions in The Utilization of Zoom Video Conferencing on Speaking Ability in Distance Learning

&lt;em&gt;This research examined students’ perception of the use of Zoom Video Conferencing in successful speaking ability during the COVID-19 outbreak. This research aimed to obtain valid evidence about EFL college students’ own decent or wicked perception of the utilization of Zoom Video Conferencing for sharpening their speaking competencies. The researcher used mix methods approach convergent design with a combination between a quantitative approach and a qualitative approach. In assembling the data, the researcher involved university students in some different majors with 102 participants gathered by sharing the close-ended and open-ended questionnaires in the form of Google Forms in the research. The researcher analyzed the data from close-ended questionnaire results and open-ended questionnaire responses. The results showed that the close-ended questionnaire discovered good perceptions and positive attitudes of students in increasing speaking skills towards Zoom Video Conferencing. Therefore, Zoom Video Conferencing can be a medium in teaching activity during distance learning applications especially in improving speaking ability as it can raise students’ positive attitude and speaking ability in EFL classrooms.&lt;/em&gt;
Teorije in modeli v vedenjskih informacijskovarnostnih raziskavah

Behavioral information security is concerned with explaining the role of users in the information security system, drawing on various psychological, organizational, and criminological theories to explain and predict user behavior. Despite numerous systematic literature reviews on the field of information security, there is no comprehensive systematic review of the theories used in behavioral information security research. The purpose of this paper is to investigate which theories are most widely used in research, in which subject areas they are most used, which factors are most frequently included in research according to each set of theories, and which are most frequently statistically significant. Accordingly, we made two studies involving a systematic review of the literature over the past ten years. The findings suggest that the most used theories include the protection motivation theory and the theory of planned behavior. In these two theories, self-efficacy and perceived usefulness of the technology are factors, which are most often statistically significant in predicting self-protective behavior.
Augmented reality and tangible user interfaces as an extension of computational design tools

Abstract The paper envisions the use of Augmented Reality (AR) as an interactive and communication tool utilized in the architectural design research, education, and practice. It summarises the current knowledge and various applications of this immersive technology in both the theoretical and practical field and focuses on a particular type of the AR implementation – tangible user interfaces (TUI) – in a computational design context. The outcome of the research is an adaptation of the originally GRASS-GIS-powered Tangible Landscape tool into Grasshopper 3D environment, which is more accurate and suitable for the architectural design workflow with respect to 3D computation, algorithmic modelling and different scale management. The newly prototyped tool is reactive to the modifications of the physical model and projects the computed additional information on it in real time and thus can communicate with the designer or observer, which results in a more interactive, haptic man-machine interface. The projected and visualised data on the physical model are the outcome of the computing algorithm designed in Grasshopper that allows for a wide range of applications, including the visualisation of shadows and solar potential analysis and thus depicts the physical model in multiple dimensions. Furthermore, the article discusses the potential and further development of this tool as well as the possibilities of layering different AR technologies in the subsequent research.
The game of Hex, n-dimensional chessboard and Fixed Point Theorem

Abstract The main result of this paper is the algorithmic proof of n-dimensional Steinhaus’ chessboard theorem (as formulated in [12]). Our theorem implies Poincar´e Theorem [8] [7] which is equivalent to the Brouwer Fixed-Point Theorem
Diversifikasi Produk Kelompok Pengrajin Tenun Bima Berbasis Nano Teknologi di Kelurahan Rabadompu Timur Kota Bima

The problems faced by the Bima weaving craftsmen group, especially in East Rabadompu Village, Bima City, include a decrease in sales of Bima weaving products during the pandemic, which affected the income and welfare of Bima weaving craftsmen. So that this Community Partnership Program (PKM) aims to empower and increase the production of Bima weaving artisan groups in East Rabadompu Village, Bima City, by utilizing nanoparticle-based technology to make functional Bima weaving diversification products that are anti-bacterial and self-cleaning. The method used was training and mentoring in the manufacture and application of nanoparticles as a coating material and diversification of Bima weaving products. The results and impacts of the activity are Bima weaving diversification products in the form of pashminas, fans, and woven masks that are anti-bacterial and self-cleaning, with higher economic value. As well as increasing the knowledge and skills of activity participants so that they can apply nanotechnology and make woven diversification products. Therefore, it can increase the added value and economic value of woven products, so that it can also improve the welfare of Bima weaving craftsmen and MSME actors.
Intrinsic decoherence dynamics and dense coding in dipolar spin system

Abstract The quantum decoherence is an ineluctable process when a quantum system interacts with its surrounding environment. Milburn’s dynamical master equation, as a modified shape of the Schrödinger equation, is typically used to study the effects decoherence even without intervention of environment. We studied the temporal evolution of non-local correlations in a dipolar-coupled spin system under the influence of intrinsic decoherence. Primarily, the generation in correlations of Einstein–Podolsky–Rosen steering, measurement-induced non-locality (MIN) and entanglement in an uncorrelated initial system state were studied. Also, the effect of the intrinsic decoherence on the quality of the dense coding capacity dynamics for the dipolar-coupled spin system was examined. Our results highlight that the initial system’s role in defining the quantum correlations’ robustness, and we also brought out the impacts of system’s parameters on the non-local correlations and the efficiency of dense coding process
Pelatihan Pembuatan Interactive Media bagi Guru Sekolah Dasar Negeri Sawahan Kecamatan Turen Kabupaten Malang

The online teaching-learning process mainly means the absence of physical interaction between teachers and students. In this context, the existence of the Web. 2.0-based technologies is expected to bridge the distance between teacher-student and student-student communication. Somehow, it will be a big problem if the teachers do not administer online learning well and appropriately. The facts show that online learning still faces some obstacles, such as the quality of the Internet connection and teacher-student and student-student interaction, including the media applied in the teaching-learning process. Thus, the present community service that involved 30 teachers of elementary schools aims at empowering the teachers with the ability to create interactive media. This activity covers briefing, lecture, demonstration, and workshop on interactive media, such as PowerPoint Presentation (PPT) with voice, Kahoot, and Padlet. The results demonstrate that teachers believe that interactive online learning is not as complicated as they thought and applied in the classrooms.
SenseWorth – A Tweets Classifier

Abstract: A lot of people use tweeter to provide their opinions on various topics including sports, politics, finance, etc. Now the information that generally is present on Twitter does not have any means to check whether the data being twitter is correct or not. So in order to check the authenticity of the data,the data must be classified into true and false. Firstly, the dataset would be created using python by devising the code for the same. The code thus designed would be able to extract the tweets with the amount specified by the user. Hence the CSV would be created. After the creation of the CSV, data pre-processing would be applied to the data such that all the unnecessary data such as emojis, words, and information would be removed automatically, and thus we would receive the tweet without any kind of stop-words. This cleaned data would further be tested and trained with the help of machine learning algorithms. These Machine learning algorithms would generally be used to classify the data according to the domain and provide the user with an authenticated answer whether the tweet is true or not along with its accuracy. This helpsthe userto identify the tweet and thus provide an authenticated answer on which informationto believe and to which we should not
Random Access in Persistent Strings and Segment Selection

We consider compact representations of collections of similar strings that support random access queries. The collection of strings is given by a rooted tree where edges are labeled by an edit operation (inserting, deleting, or replacing a character) and a node represents the string obtained by applying the sequence of edit operations on the path from the root to the node. The goal is to compactly represent the entire collection while supporting fast random access to any part of a string in the collection. This problem captures natural scenarios such as representing the past history of an edited document or representing highly-repetitive collections. Given a tree with $n$ nodes, we show how to represent the corresponding collection in $O(n)$ space and $O(\log n/ \log \log n)$ query time. This improves the previous time-space trade-offs for the problem. Additionally, we show a lower bound proving that the query time is optimal for any solution using near-linear space. To achieve our bounds for random access in persistent strings we show how to reduce the problem to the following natural geometric selection problem on line segments. Consider a set of horizontal line segments in the plane. Given parameters $i$ and $j$, a segment selection query returns the $j$th smallest segment (the segment with the $j$th smallest $y$-coordinate) among the segments crossing the vertical line through $x$-coordinate $i$. The segment selection problem is to preprocess a set of horizontal line segments into a compact data structure that supports fast segment selection queries. We present a solution that uses $O(n)$ space and support segment selection queries in $O(\log n/ \log \log n)$ time, where $n$ is the number of segments. Furthermore, we prove that that this query time is also optimal for any solution using near-linear space.
Artificial neural networks predict human eye movement patterns as an emergent property of training for object classification

Eye movements spatially sample information from the environment to support visual behavior. Artificial Neural Networks (ANNs) optimized on eye movements capture >90% of the explainable variance in static eye movement patterns (MIT/Tübingen Saliency Benchmark, https://saliency.tuebingen.ai), and ANN reconstructions from fMRI responses predict eye movements (O’Connell & Chun, 2018). While this suggest that ANN-like representations could support spatial attention in humans, it is unclear how such representations are learned. Here, we test the hypothesis that ANNs optimized for object recognition incidentally learn features predictive of human eye movement behavior as an emergent property without any direct optimization on eye movement data. We completed a large-scale analysis of eye movement predictivity using 1156 layers from 60 ANNs trained on ImageNet to predict fixation patterns from O’Connell & Walther 2011 and CAT2000 (Borji and Itti, 2015). Across ANNs and datasets, emergent eye movement predictivity – computed as Normalized Scanpath Saliency (NSS) – shows an initial peak in early-middle layers (Average NSS = 0.32, SEM = 0.06), with highest predictivity coming from the final convolutional layers (Average NSS = 0.63 SEM = 0.06), suggesting that eye movement predictive representations develop spontaneously along with object recognition. However, the peak eye movement predictivity overall (NSS = 1.52, final layer from resnet18-contrastive-multiview) is below the best model on the Saliency Benchmark (DeepGaze II, NSS = 1.96), indicating that emergent eye movement predictivity captures only a portion of the explainable behavioral variance. Additionally, we find that eye movement predictivity across the model-zoo is not meaningfully correlated to neural predictivity in monkey V4 and IT (r < 0.21), showing that emergent eye movement predictivity captures independent variance from existing neural benchmarks. We propose emergent eye movement predictivity as a novel quantitative benchmark to compare ANNs to human behavior.
Retracted: Physical Exercise Monitoring System Based on Computer Somatosensory Technology

Exercise Monitoring System Based on Computer Somatosensory Technology" [1] due to concerns that the peer review process has been compromised.Following an investigation conducted by the Hindawi Research Integrity team [2], signifcant concerns were identifed with the peer reviewers assigned to this article; the investigation has concluded that the peer review process was compromised.We therefore can no longer trust the peer review process, and
Are You a Soft Target for Cyber Attack? Drivers of Susceptibility to Social Engineering-Based Cyber Attack (SECA): A Case Study of Mobile Messaging Application

A rise in working and studying from home, activities which depend on the Internet, and the exchange of data coupled with a lack of understanding about security for interacting in cyberspace have made cybersecurity one of the most pressing concerns today. One form, in particular, is a social engineering-based cyber attack. Unfortunately, not much research has been conducted on the susceptibility factors that cause this to happen. This study attempts to understand what factors make a person susceptible to cyber attacks that can be seen from three perspectives: habitual perspective, perception perspective, and social and motivation perspective. The objective of the research is to identify specific characteristics and drivers regarding the social engineering-based cyber attack (SECA) susceptibility of a consumer exposed to social media messaging applications. A quantitative survey was employed to test a total of 114 respondents in Indonesia who are categorized as active Internet users. The study found variables within two of the three perspectives that positively contributed to a consumer’s susceptibility to cyberattack. These factors will provide valuable insight into prevention and knowledge of related risks of cyberattacks based on social engineering in the future.
Evolution of gold sources in the process of formation of gold deposits (evidence from Eastern Yakutia)

In contrast to the established ideas about the relationship of gold mineralization with any specific source, a model is proposed for the evolution of different sources during the formation of geological structures in the eastern framing of the Siberian Platform. The model is based on the calculation of regional clarkes of sedimentary, igneous rocks and minerals with the allocation of stratigraphic levels of primary gold enrichment in sedimentary rocks. The poly-stage and multi-stage nature of the evolution of sources is established through the redistribution of gold in the composition of sedimentary rocks and minerals under the influence of various endogenous heat and mass transfer agents, in particular, under the influence of carbonatites. The main condition for the localization of gold mineralization in the region is the presence of levels of primary supraclarke gold concentrations in turbidites R3, C3—P1, T3 of the deltaic facies of submarine slopes. The main gold concentrators in sediments are marcasite and pyrite. Under the influence of various heat and mass transfer agents, gold is redistributed along the heat flow front, forming zones of dispersed mineralization with its high contents in pyrite and arsenopyrite. Then, under the conditions of late superimposed hydrothermal-metasomatic processes, gold-bearing pyrites and arsenopyrites are released from most of the gold, which appears in the composition of ores of the late stage of ore formation in the form of visible gold particles.