Reviewerly/exHarmony huggingface dataset:
First results of computerized adaptive testing for an online physics test

Tests are an essential tool to assess students’ ability. In online education these tests are mostly of static nature with the same items for each student. In contrast computerized adaptive testing concepts take into account the information about the test user automatically collected in an online test. The aim is a comparably precise test result with fewer test items (questions). An implementation of such a computerized adaptive test (CAT) is presented here. The adaptation process is based on the precise knowledge of the item parameters, e.g. difficulty, in the item pool. An estimation of the knowledge level of the test user has to be performed in real time after each answer. With this information the next item can be selected accordingly. This leads to a highly individualized test for each test user. For all items the parameters were determined with methods of the item response theory (IRT) in the framework of the probabilistic test theory. For that real test results of former first year students in engineering science had been analyzed. The prototype of such a CAT has been developed. It focusses on a physics test for prospective students in the STEM fields. In fall 2021 the pilot phase was conducted with first year students in engineering science. The CAT shows that the same precision can be achieved with a mean of 9.3 items compared to 12 in the static test. The acceptance among the students is high. The correlation between the static test and the CAT is satisfactory.
Do Not Give a Dog Bread Every Time He Wags His Tail: Stealing Passwords through Content Queries (CONQUER) Attacks

Android accessibility service was designed to assist individuals with disabilities in using Android devices.However, it has been exploited by attackers to steal user passwords due to design shortcomings.Google has implemented various countermeasures to make it difficult for these types of attacks to be successful on modern Android devices.In this paper, we present a new type of side channel attack called content queries (CONQUER) that can bypass these defenses.We discovered that Android does not prevent the content of passwords from being queried by the accessibility service, allowing malware with this service enabled to enumerate the combinations of content to brute force the password.While this attack seems simple to execute, there are several challenges that must be addressed in order to successfully launch it against real-world apps.These include the use of lazy query to differentiate targeted password strings, active query to determine the right timing for the attack, and timingand state-based side channels to infer case-sensitive passwords.Our evaluation results demonstrate that the CONQUER attack is effective at stealing passwords, with an average one-time success rate of 64.91%.This attack also poses a threat to all Android versions from 4.1 to 12, and can be used against tens of thousands of apps.In addition, we analyzed the root cause of the CONQUER attack and discussed several countermeasures to mitigate the potential security risks it poses.
StealthyIMU: Stealing Permission-protected Private Information From Smartphone Voice Assistant Using Zero-Permission Sensors

Voice User Interfaces (VUIs) are becoming an indispensable module that enables hands-free interaction between human users and smartphones.Unfortunately, recent research revealed a side channel that allows zero-permission motion sensors to eavesdrop on the VUI voices from the co-located smartphone loudspeaker.Nonetheless, these threats are limited to leaking a small set of digits and hot words.In this paper, we propose StealthyIMU, a new threat that uses motion sensors to steal permission-protected private information from the VUIs.We develop a set of efficient models to detect and extract private information, taking advantage of the deterministic structures in the VUI responses.Our experiments show that StealthyIMU can steal private information from 23 types of frequently-used voice commands to acquire contacts, search history, calendar, home address, and even GPS trace with high accuracy.We further propose effective mechanisms to defend against StealthyIMU without noticeably impacting the user experience.
Gun Detection in CCTV Images using HAAR-Like Features

Automated video-based surveillance is an important area of research to assist the security personnel to detect the incident of any abnormal events in the surroundings. The objective of this paper is to develop a framework for automatic gun detection using closed-circuit television (CCTV) images. The methodology presented in this paper involves the development of a framework for automatic gun detection using closed-circuit television (CCTV) images, with the aim of enhancing the surveillance of crime and improving human security. The proposed approach consists of a dataset of CCTV images containing instances of guns, as well as non-gun images for comparison. These images would be used to train the proposed algorithm to recognize and identify guns in future CCTV images. The proposed framework is designed for an indoor environment and uses Haar-like features for gun detection. The proposed system involves the installation of CCTV cameras in a suitable corner of an indoor environment for surveillance. The CCTV cameras capture the scene and the frames of the scene are compared with a predefined dataset for automatic gun detection. The proposed approach draws a bounding box and raises an alarm if it detects a gun in a frame extracted from a captured scene. This provides a visual indication of the presence of a gun, making it easier for relevant authorities to quickly identify and respond to the threat. The proposed system shows promising results in real-time applications and about 90% accuracy has been achieved.
Covid-19 pandemic influences relationships on innovation, environmental practices and social actions in enterprise: the theoretical framework

Purpose: This study aims to analyze the relationships between the Covid-19 Pandemic, innovation, environmental practices, social actions, and the influence on people's quality of life, in the context of Brazilian organizations, through the proposition of a Theoretical Framework. Methodology /Approach: The methodology was qualitative and exploratory research, through a theoretical and systematic review of the Scopus database. For data analysis, content analysis was used, with categories listed a priori. Originality/Value: In the research, 4 theoretical propositions were listed, which were analyzed through a systematic review in the Scopus database, as it is one of the largest databases of scientific articles reviewed by peers worldwide. Findings: In the course of the research, with the filter used by Article title, it was identified that the largest number of publications (269 documents) went to Proposition 1, in second place with 16 publications we present Proposition 3, occupying the third place emerges Proposition 4 with 10 publications, and as the last classified we have Proposition 2 with only 1 published article. Theoretical and methodological contributions: The impact of the research is linked to the validation of a theoretical framework, which presents factors that the Covid-19 pandemic is influencing the development of Brazilian organizations, as well as the information collected will provide the academic community and professionals in related areas, a better understanding of the performance of organizations, showing subsidies for managers, from organizations of different segments and sizes, to improve decision-making in the face of the pandemic in the environmental, social and improvement of people's quality of life.
A Phenomenological Study of Academic Probation Experience: Focusing on the Case of University A

The purpose of this study was to investigate causes of academic probation, major affectivity and university life experiences of college students before and after receiving academic probation at A university. 11 interviewees(five males and six female) participated in this study. This qualitative study applied the phenomenological analysis method of Colaizzi. University life experiences of college students who received academic probations were expressed by 107 significant statement and clustered into 22 formulated meanings, 5 themes, 3 themeclusters. As a result of qualitatively analyzing experiences of academic probation, 3 themeclusters of 'self-understanding/ confirmation of possibility/ supportive environment' and 1 final category of 'adaptation effort' were found. These results of the study are expected to be utilized as baseline data for preparing measures to support the ‘college adaptation’ of students on academic probation,
Protecting Attacks on Unmanned Aerial Vehicles using Homomorphic Encryption

With the exponential growth in the usage of unmanned aerial vehicles (UAV), often known as drones, for military, civilian, and recreational purposes. Security of internal communication modules and communication to the ground control station is considered the foremost challenge. Hacking into the system and attacking the internal communication devices with malicious code can disaster the vehicle's system. The need for having a secure communication channel between the internal modules of the vehicle and transmission of data to the ground control station is of utmost crucial. Existing mechanisms based on conventional encryption methods are highly suspectable to attacks as their keys can be broken by employing high computing power. Another challenge with these approaches is undesired high-level data communication latency affecting real-time communication. This study implements a homographic encryption-based technique for secure communication. In addition, we also propose a key regeneration algorithm based on pallier homomorphic encryption. Simulations were conducted using OMNET++ and Aerial Vehicle Network Simulator (AVENS). In this study 54 encryption attacks were collected from different sources. Compared to Digital Encryption Standard (DES) and Advanced Digital Encryption (AES), the proposed approach defended all the communication attacks between the UAV and the ground control station.
Testing effectiveness of social mobility and communication orientation model using problem-based learning for the visual impairment students

This study aims to test the effectiveness of the social mobility and communication orientation model based on internet mobile application technology (IT-SMCOM) for problem-based learning in Universitas Negeri Surabaya (Unesa) campus environment. This research method measures the effectiveness of internet mobile application technology for problem-based learning in Unesa campus environment. The results of expert validation test data and performance tests were analyzed using a descriptive form of percentage assessment of the observer team. The test results of media product experts and practitioners scored 100% excellently, and Special Education experts scored 87%. Then the effectiveness test through main field testing five visually impaired students affected by the Covid 19 pandemic scored 93% excellent (1 person), a score of 75% good (2 people), and a score of 62% adequate (2 people). Operational field testing, ten people from the Indonesian visual impairment association group and the Surabaya and Sidoarjo inclusive high school groups scored 100% excellent (one person), score 94% very good (three people), score 81% good (one person) and score 81%-84% very good (three people), score 65%- 70% adequate (two people), The conclusion of the results of data analysis of expert validation tests, practitioners suggest that the product is feasible to be tested in the field. The product effectiveness test shows that the product trial results depend on the development of the behavior and characteristics of each individual with visual impairment. Keywords: visual impairment, social, mobility, orientation, communication
TRAINING ON THE USE OF EDUPOINT: MINI DRIVE LEARNING RESOURCES FOR DISASTER EMERGENCY SCHOOLS IN PADALUYU VILLAGE, CUGENANG SUB-DISTRICT, CIANJUR REGENCY

The results of initial observations, especially in Padaluyu Village, Cugenang District, obtained data that there were 27 RTs spread across Padaluyu Village. The condition of 8 RTs experienced very severe damage (all houses collapsed) 19 RTs experienced severe and moderate damage. There are elementary schools in Cugenang District that need assistance related to the implementation of learning, especially the availability of learning resources, namely SDN Padamamur, SDN Padaluyu, and SDN Kembang Manis 2. The purpose of implementing this PKM is to overcome problems experienced by partners related to obstacles in the learning process that occur due to the earthquake. With the damage to some school rooms, learning must be diverted elsewhere. Therefore the development of Edupoint is considered appropriate to overcome this problem. EduPoint is a learning tool designed as a medium for providing access to mobile learning that can be accessed via various devices such as laptops, computers, smartphones and tablets in a local network so that it does not require quota or unstable signals due to earthquake conditions. This tool is designed so that students can study anywhere without having to take place in the classroom. The design concept of this tool is intended to accommodate the learning process so that it can continue under any conditions so that it can be easily moved wherever learning conditions take place (portable). After completing the development of the tool, training is needed for teachers to use it. The training activity on using EduPoint: Mini Drive Learning Resources for Disaster Emergency Schools ran smoothly. The response from the partners and training participants was very good thanks to the good cooperation between the University of Ibn Khaldun Bogor and the partners involved. The results of the training show that teachers are able to properly use the learning resources accessed through EduPoint.
Topology Identification for Complex Dynamical Networks Based on XGBoost Using Multiple Feature Sequences

Efficient method of topology identification is the basis for studying and controlling complex dynamical networks. In this paper, a novel data-driven identification method called MFE-XGBoost based on multiple feature extractors and extreme gradient boosting (XGBoost) is proposed. We use multiple feature extractors to extract latent features of different dimensions from time series of node states, then construct classification and regression tree (CART) in XGBoost using feature sequences. We binarize the information gain matrix calculated by CARTs, then obtain the adjacency matrix of the network to realize topology identification. The results show that, compared with other methods, MFE-XGBoost has higher accuracy and better anti-interference performance, because it considers the characteristics of more dimensions and designs a reasonable threshold selection method for binarization. MFE-XGBoost requires shorter time series to achieve a good identification effect because of the good fitting ability of XGBoost.
Relationship between education and economic growth

The purpose of this research is to examine the relationship between educational attainment and economic growth in Albania. This research analyses how educational opportunities contribute to Albania’s economic growth via the use of empirical data. Additionally, it examines the relationship between education and economic development in Albania. Using general economic theory as a starting point, this study analyses some of the potential implications for Albanian economic and educational policy. By stimulating technological innovation and boosting capital and labor productivity, education expenditure increases the economy’s revenue. Using statistical analysis, empirical research attempts to ascertain the true causal effect of educational and training quality on individual salaries, firm profitability, and the economy as a whole. The results suggest that education may be a critical factor in Albania’s long-term economic growth, making it a critical component of the country’s economic strategy. According to the study’s results, the government and private sector should collaborate to improve education quality via public-private partnerships. The impact of education on economic development and its relationship is portrayed in this study since it should be a primary goal of policymakers.
Developing Critical Thinking Skills to Promote Creativity

The National Teaching & Learning ForumVolume 32, Issue 3 p. 3-5 Creativity Café Developing Critical Thinking Skills to Promote Creativity Russell Carpenter, Russell CarpenterSearch for more papers by this authorKevin Dvorak, Kevin DvorakSearch for more papers by this authorKelly A. Concannon, Kelly A. ConcannonSearch for more papers by this author Russell Carpenter, Russell CarpenterSearch for more papers by this authorKevin Dvorak, Kevin DvorakSearch for more papers by this authorKelly A. Concannon, Kelly A. ConcannonSearch for more papers by this author First published: 14 March 2023 https://doi.org/10.1002/ntlf.30361Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. Volume32, Issue3March 2023Pages 3-5 RelatedInformation
Social Media Sentiment Analysis Using BERT During COVID-19

This paper discusses the use of BERT, an advanced natural language processing (NLP) technique, for social media analytics in regard to the COVID-19 pandemic. BERT enables the extraction of meaningful insights from large amounts of data, such as tweets and articles, relating to the pandemic. In particular, we discuss the various applications of BERT in social media analytics and its potential to provide useful insights into the spread of the virus, public sentiment, and the effectiveness of public health initiatives. Additionally, we discuss the challenges of applying BERT to social media analytics and the need for further research and development in this area.
Novel Approach for Multimodal Sentiment Analysis in online Social Media Platform

Social media contain a large amount of raw data that has been uploaded by users in the form of text, videos, photos and audio. Sentiment analysis is used to analyse raw text to drive objective quantitative results using natural language processing, machine learning, and other data analytics techniques. Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. At present text-based sentiment analysis depends on the development of word embedding and Machine Learning models that take in conclusion via enormous text collection. Text based Sentiment Analysis is presently generally utilized as consumer loyalty appraisal and brand insight investigation. This paper presents multimodal analysis of social media data characterize issues and the feeling in advancements in ongoing audits and investigation of multimodal assessment which generally includes video websites, human-human connections, pictures, human-machine and spoken surveys. Recurrent Neural networks (RNNs) along with the Long-Short Term Memory (LSTM) are the methodologies that are used to increase the performance.
Crowd Counting Using Scale Enhanced Network with Dual Attention Booster

Crowd counting has been a fundamental yet challenging problem in pattern recognition. Most recent deep models for crowd counting rely on Convolutional Neural Networks (CNNs). Although CNN visual features comprise the spatial and channel features, existing deep models on crowd counting have limited descriptive ability as they only focus on the spatial or channel information. In this paper, we propose Scale Enhanced Network with Dual Attention Booster named as SEN-DAB, a novel method to jointly learn the representations of spatial and channel information for crowd counting. Moreover, to further leverage the multi-scale information, a pyramid residual scale enhanced block is presented to process the multi-scale features. As a result, the learned spatial, channel and multi-scale features can be robust to appearance changes of the crowd. Our model is tested on three benchmarks and the experimental results confirm that the promising performance of SEN-DAB when compared with various networks.
THE EFFECTS OF MOBILE INTERACTIVE APPS FOR TEACHING CHEMISTRY IN CZECH AND KAZAKH SCHOOLS

Interactive apps allow educators to teach without being restricted by time and place, enabling learning in or outside the classroom in places where learning occurs naturally (Huang, Lin,&amp; Cheng, 2010). They also give the teacher the ability to connect with learners on a more personal level with the help of mobile digital devices that the learners use on a regular basis (Ward et al.,2013). In addition, these apps make learning fun through friendly competitions, challenges, making it an excellent means of encouraging students’ engagement in learning (Ding, Er &amp;Orey, 2018). This contribution investigated whether the use of mobile interactive apps influenced students’ opinions and boosted their engagement in the chemistry. It covers about 15 popular, mostly free apps that can be used to learn chemistry. The first verification was carried out from December 2018 to January 2019 with specialized school-board information technologies in Karaganda (Kazakhstan). The results showed that more than 70 % of the students (8-9th grade) enjoy working with interactive apps,which positively affects their opinions towards the subject. In the next part, we will therefore focus on verification of the use of interactive apps in the Czech Republic.
THE EFFECTIVENESS OF USING ANDROID-BASED LEARNING MEDIA ON THE COGNITIVE ASPECTS OF STUDENTS WITH SPECIAL NEEDS

This article aims to investigate the effect of using instructional content based on Android on the cognitive capabilities of students who were deaf. Using a quantitative and pre-experimental methodology, the authors selected a one-group pre-post-test design will be used for the study approach. The sample of the research consisted of 8 kids, who were the subjects under investigation. For data collecting, this study made use of pre- and post-test questions; for data analysis, the normality test, the homogeneity test, and the paired sample T-test were used. The research indicated that there was a statistically significant improvement between the pre-test and post-test averages, with the pre-test average standing at 31.25 and the post-test average standing at 46.25 respectively. That is to say, people's performance on the post-test, on average, was higher than their performance on the pre-test. The authors assume that the gaps between the pre- and post-test scores are about average. The sum/difference computation yields the number 15. Consequently, with a Sig. (2-tailed) of 0.005 - 0.05, Ha is accepted, whereas H0 is denied. This indicates that the use of Android-based educational content has a significant positive effect on the cognitive components of students, even so, the outcomes were not satisfactory. Keywords: Android-Based Learning, Special Needs, Cognition DOI： https://doi.org/10.35741/issn.0258-2724.58.1.54