Reviewerly/exHarmony huggingface dataset:
Efficient Human Activity Recognition Using Lookup Table-Based Neural Architecture Search for Mobile Devices

Mobile devices play a crucial role in human activity recognition as they enable real-time sensing of user interaction for learning algorithms like neural networks. To facilitate human activity recognition on mobile devices, it is important to deploy efficient neural network architectures due to the limited computational capacity of these devices. However, conventional neural architecture search methods often generate less effective architectures because they neglect the specific requirements of target devices on which the neural network would operate in real-time. Moreover, these methods are impractical in the mobile device environment due to their high computational cost for architecture search. To address these challenges, we propose an efficient neural architecture search method based on a latency lookup table. The experimental results on public datasets provide evidence that the proposed method outperforms conventional methods in terms of speed. We achieved a search time of under 1.5 hours on each dataset, which is more than seven times faster on average compared to conventional methods. Furthermore, our in-depth analysis shows that the optimal architecture can vary depending on the target mobile devices, such as Galaxy A31 and S10. By tailoring the models to each device, optimized models achieved an additional 4-5% improvement in inference time for each respective device.
Real Time Person Detection and Classification using YOLO

A Convolutional Neural Network (CNN) is a class of deep neural network most commonly used in analyzing visual images. Various systems and applications have been built to detect and classify the objects in a faster way taking CNN as its foundation. In this paper, we introduce a model to identify and classify people wearing ID card.Our model uses an object detection system called YOLO (You Only Look Once) for detecting and classifying objects in real-time videos. In the YOLO algorithm, a single convolutional network predicts the bounding boxes and the class probabilities for these boxes. We aim to use our model for authentication, surveillance and security purposes at organizations, corporations and educational institutions to detect an unauthorized person at the premises or somebody without a valid identification document. Using the object detection and classification, we aim to build a model which would alert the respective authorities on the matter.
Atomic indirect measurement for efficient quantum optical communication using a squeezed binary phase-shift-keying signal

A squeezed-displaced state can be used as an optical signal for efficient binary quantum optical communication. Here, we consider quantum optical communication where an atomic indirect measurement is used to decide the message encoded in a binary phase-shift-keying signal composed of squeezed-displaced states, and show that the incorrect decision probability of an atomic indirect measurement can be less than that of a homodyne measurement. We further show that an atomic indirect measurement can lower the incorrect decision probability even when the quantum channel is exposed to weak phase-diffusion noise.
Security of Electronic Voting Systems Using Blockchain Technology

The use of electronic voting is becoming more and more common. It not only reduced organization costs, but it also makes voters more interested in casting their ballots. Voting may now be done remotely from any location with the use of the Internet without wasting paper on printing ballots. E-voting systems have new security challenges as a result of their ease of vulnerability to threats; even a little change in votes can result in significant manipulation in voting. This system must be safer, more practical, and more precise. One of the greatest solutions for assuring the electronic voting system’s security is to use blockchain, which makes data irreversible and decentralized and enables end-to-end encryption. As a result, a survey on blockchain’s use in e-voting systems has been conducted in this article, which demonstrates how the current electronic voting system has been replaced.
Communication between grandparents and young grandchildren over distance: Establishing contact with constitutive nonhumans

Physical items are often taken for granted in mediated communication between grandparents (GP) and young grandchildren (GC). This article puts “constitutive nonhumans” at the center of inquiry to understand the potential of physical items and communication technologies to communicate over distance. The notion of phaticity operationalizes the role of constitutive nonhumans to establish and maintain contact over distance, which might have pleasurable or unpleasurable outcomes. A relational view on agency supports the entanglement of humans and nonhumans when they cooperate to communicate over distance. The article reports on a two-phase qualitative study that was conducted in two European countries with 10 GP (aged 60–75 years) and 10 GC (aged 6–11 years). The results identify how the entanglement between constitutive nonhumans conflates emotional connection and contact. Furthermore, the results suggest that the condition of familiarity can direct contact to pleasant or unpleasant outcomes that might differ across mediated and co-located communication.
COUNT: Blockchain framework for resource accountability in e-healthcare

The progress of sensor devices, digital communication, and computing techniques enhances the functionalities of e-healthcare, where the medical facilities are manageable based on the Internet. Now a days, e-healthcare not only helps in disease diagnosis, or tele-medicine, but also implies to general medical scope and medical resource management. Thus, Internet-of-Medical Thing (IoMT) becomes an umbrella term to connect e-healthcare, tele-medicine, and medical supply chain management. In the recent past, the outbreak of COVID-19 pandemic has shown the loopholes in the existing medical systems such as the mismanagement of medical resources and the unavailability of the basic requirements for patients. The medical infrastructure urges for the new frameworks to handle accountability and transparent governance in a medical emergency situation. This motivates us to address medical resource accountability in e-healthcare. In the present work, we introduce the first resource accountability framework to balance the demand–supply of medical facilities in an e-healthcare and IoMT ecosystem. Our solution is based on blockchain and we call it bloCkchained framework for resOUrce accouNTability (COUNT). We use a customized Proof of Vote (PoV) for consensus in COUNT. We call this consensus COUNT-PoV, which is another direction of novelty in our solution. The blocks in the proposed COUNT contain the resource requirements and their availability–production–supply status. Multiple stakeholders are involved in the process based on providing pre-attained credentials; thus, COUNT supports consortium blockchain. Existing literature shows a number of studies for blockchain-based frameworks for e-healthcare; however, those works do not address the accountability and transparency issues of medical e-governance and balancing the demand–supply of the medical facilities/resources. Therefore, our proposed COUNT is beneficial for e-healthcare and IoMTs. We use signcryption process to reduce the complexity of the cryptographic processes, which is an add-on to the contribution. We evaluate our proposed framework based on the Hyperledger Caliper benchmark test with latency, throughput, and resource consumption. Additionally, we also analyse the cost of the implementation. The comparative analysis of our consensus with other stake-based consensus protocols on the COUNT framework shows that our consensus, COUNT-PoV is efficient and suitable for the use of e-healthcare and IoMTs. Moreover, being a generic framework, COUNT is helpful for the e-governance of medical facilities, the vaccination process, and COVID passports.
Implementing and Maintaining a SARS-CoV-2 Exposure Notification Application for Mobile Phones: The Finnish Experience

Exposure notification applications (ENAs) or digital proximity tracing apps were used in several countries during the COVID-19 pandemic. In this viewpoint, we share our experience of implementing and running the Finnish ENA (Koronavilkku), one of the national ENAs with the highest proportion of users during the pandemic. With the aim of strengthening public trust and increasing app uptake, there was a strong prioritization of privacy and data security for the end user throughout the ENA development. This, in turn, limited the use of the app as a tool for health care professionals and deeper insight into its potential effectiveness. The ENA was designed to supplement conventional contact tracing, rather than replace it, and to serve as an early warning system and a trigger for action for the user in case of potential exposure. The predefined target of 40% uptake in the population was achieved within 3 months of the ENA launch. We consider easy-to-understand information produced together with communication experts crucial during the changing pandemic situation. This information educated people about the app as one component in mitigating the pandemic. As the pandemic and its mitigation evolved, the ENA also needed adapting and updating. A few months after its launch, Finland joined European interoperability, which allowed the ENA to share information with ENAs of other countries. We added automatic token issuing to the ENA as of mid-2021. If added earlier and more comprehensively, automatization could have more effectively saved resources in health care services and prevented overburdening contact tracing teams, while also notifying potentially exposed individuals quicker and more reliably. In the spring of 2021, the number of active apps started to gradually decline. Quarantine and testing practices for asymptomatic vaccinated individuals following exposure to the virus were eased and home tests became more common, eventually replacing laboratory testing for much of the population. Taken together, this led to decreased token issuance, which weakened the potential public health usefulness of the app. A self-service option for token issuance would likely have prolonged the lifespan of the app. The ENA was discontinued in mid-2022. Regularly conducted surveys would have helped gain timely knowledge on the use and effectiveness of the app for better responding to the changing needs during the pandemic.
A Study on the Satisfaction and Improvement Plan of Online Learning of Domestic Students : Focusing on Chinese Students

This study investigated the satisfaction of international students in Korea and analyzed the level of satisfaction in various dimensions such as education platform, studying environment, the guidance of instructors, and learners. As a result, 51.32% responded ‘mostly satisfied’, with 24.15% as ‘relatively satisfied’, 18.49% as ‘moderate’, 3.4% as ‘relatively unsatisfied’, and 2.64% as ‘very unsatisfied . The average value of satisfaction was 4.18. The average value of willingness to continue online education after the end of COVID-19 was 3.77, with 7.92% responded ‘strongly disagree’, 8.30% for ‘mildly disagree’, 23.40’% for mostly agree’, 20.00% for ‘relatively agree’, and 40.38% for ‘strongly agree’. In conclusion, international students are basically satisfied with the online education, but there are rooms for improvement in quality of online education. Also, the compounded education of online and offline needs to be further studied.
A Study on the Learning Transfer of Adult Learners in Lifelong Education

The purpose of this study is to identify the learning transfer to effectively meet the motivation and purpose of adult learners in lifelong education. Through this, lifelong education institutions will be able to present efficient management plans that can meet the needs of adult learners. Ultimately, this study will be able to provide basic data that can activate the learning transfer of adult learners in the field of lifelong education in the era of knowledge-based lifelong learning. In addition, it will be able to provide meaningful implications for the preparation of measures to improve the learning outcomes of adult learners in lifelong education. In order to achieve the purpose of this study, this study selected and analyzed 74 domestic academic journals and dissertations registered with the Korea Education and Research Information Service (RISS), focusing on the effectiveness of learning transfer. As a result of this study
A Study on the Satisfaction and Improvement Plan of Online Learning of Domestic Students - Focusing on Chinese Students -

This study investigated the satisfaction of international students in Korea and analyzed the level of satisfaction in various dimensions such as education platform, studying environment, the guidance of instructors, and learners. As a result, 51.32% responded ‘mostly satisfied’, with 24.15% as ‘relatively satisfied’, 18.49% as ‘moderate’, 3.4% as ‘relatively unsatisfied’, and 2.64% as ‘very unsatisfied . The average value of satisfaction was 4.18. The average value of willingness to continue online education after the end of COVID-19 was 3.77, with 7.92% responded ‘strongly disagree’, 8.30% for ‘mildly disagree’, 23.40’% for mostly agree’, 20.00% for ‘relatively agree’, and 40.38% for ‘strongly agree’. In conclusion, international students are basically satisfied with the online education, but there are rooms for improvement in quality of online education. Also, the compounded education of online and offline needs to be further studied.
The BCRobo dataset for Robotic Vision and Autonomous Path Planning in Outdoor Beach Environment

Along with the universalization of autonomous driving and image segmentation, various datasets are available freely for anyone to use to train their own neural network which speeds up the growth of deep learning technology.However, most of the datasets target only urban environments and other offroad environments are still lacking in datasets.This paper presents a beach environment dataset, BCRobo with the aim to contribute to closing the gap of robotic visual perception in offroad environment, especially in beach.
Non Functional Requirements Identification and Classification Using Transfer Learning Model

in this research study, we address the critical task of identifying and classifying non-functional requirements (NFRs) in software development. NFRs, described in the software requirements specification (SRS) document, offer a comprehensive system view and are closely aligned with software design and architecture. However, they are often overlooked compared to functional requirements, leading to potential issues such as rework, increased maintenance efforts, and inefficient resource utilization, impacting project cost and budget. To streamline software development, we propose a novel approach based on transfer learning methods to automate NFR identification and classification, aiming to reduce development time and resource consumption, ultimately leading to improved efficiency. We evaluate multiple state-of-the-art transfer learning models, including XLNet, BERT, Distil BERT, Distil Roberta, Electra-base, and Electra-small, for this purpose. Among them, XLNet demonstrates exceptional performance, achieving an impressive value of 0.91489 for Accuracy, Precision, Recall, and F1 Score. This research highlights the importance of considering non-functional requirements (NFRs) in software development and the negative consequences of neglecting them. It also emphasizes the benefits of using the XLNet tool to automate the identification and classification of NFRs. By using XLNet, we aim to make software development easier, optimize resource usage, and improve the overall quality of software systems.
The Role of Business Incubators in Promoting Entrepreneurship of Higher Education Institutions

This study aims to measure the influence of university incubators on promoting the culture of entrepreneurship and to what extent these incubators guide and motivate students, teaching staff, and university employees to achieve entrepreneurial achievements in various disciplines and fields. The questionnaire was used as a tool to collect the required data. The study population consists of students, teaching staff, administrators, and employees from almost all Jordanian universities, which are estimated to be more than tens of thousands. We distributed the questionnaire among 14 universities, and only 310 responses were collected. Based on the results of the questionnaire that were statistically analyzed, presented, and processed we believe that business incubators are like any existing project. Universities must pay attention to all matters that may lead to their success, including attention to all administrative, financial, and marketing matters, in addition to paying attention to all work they carry out, including the mechanism of helping small projects. It is necessary to introduce an entrepreneurship course within the compulsory requirements at the university level and for first or second-year students, because of its importance in spreading the culture of entrepreneurship among students. We hope that our recommendations will change the horizons of the university community and intellectual level and convert graduate students from “job seekers” into “job creators” which strongly contribute to solving unemployment and poverty problems.
A New Quantum Sealed-Bid Auction Protocol with a Set of Local Indistinguishable Orthogonal Product States

Quantum sealed-bid auction (QSA) is a special form of transaction with significant applications in the economic and financial fields. Using a unique set of locally indistinguishable orthogonal product (LIOP) states, we propose a new QSA protocol in this paper. In the protocol, the bid message is encoded as a quantum sequence of LIOP states, and the different particles of LIOP states are transmitted separately. Even though an attacker obtains a portion of the particles, they cannot recover the entire bid message because of the local indistinguishability of LIOP states. Once the auctioneer announces the winner’s bid, all bidders are able to confirm the authenticity of their bid. With the help of a semi-honest third party, collusion between the auctioneer and a malicious bidder can be discovered. Finally, our protocol is capable of meeting all requirements for secure sealed-bid auctions through security and completeness analysis. Additionally, the proposed protocol does not require any entangled resources and complicated operations, so it can be easily implemented in practice.
A New Approach for Anonymizing Transaction Data with Set Values

This article proposes a new method that can guarantee strong privacy while minimizing information loss in transactional data composed of a set of each attribute value in a relational database, which is not generally well-known structured data. The proposed scheme adopts the same top-down partitioning algorithm as the existing k-anonymity model, using local generalization to optimize safety and CPU execution time. At the same time, the information loss rate, which is a disadvantage of the existing local generalization, is further improved by reallocating transactions through an additional bottom-up tree search process after the partitioning process. Our scheme shows a very fast processing time compared to the HgHs algorithm using generalization and deletion techniques. In terms of information loss, our scheme shows much better performance than any schemes proposed so far, such as the existing local generalization or HgHs algorithm. In order to evaluate the efficiency of our algorithm, the experiment compared its performance with the existing local generalization and the HgHs algorithm, in terms of both execution time and information loss rate. As a result of the experiment, for example, when k is 5 in k-anonymity for the dataset BMS-WebView-2, the execution time of our scheme is up to 255 times faster than the HgHs algorithm, and with regard to the information loss rate, our method showed a maximum rate of 62.37 times lower than the local generalization algorithm.
The Conceptualisation of User-App Interactivity in Augmented Reality-Mediated Learning: Implications for Literacy Education

Augmented reality (AR) is transforming users’ multisensory experiences and heightening the level of engagement with multimodal learning. Scholarly attention is urgently needed to conceptualise and examine user–app interactivity in educational contexts. Drawing on the systemic functional–multimodal discourse analysis approach, this article aims to explore key user roles prompted by AR apps and examine educational functions that these user roles fulfil in AR-mediated learning. Based on our analysis of 14 AR apps selected for a 3-day workshop with six Australian primary school teachers, we identified four categories of user roles that facilitated different literacy activity types during AR-mediated learning. To design effective learning experiences, this article argues that teachers need to consider the resonance between students’ AR experiences and their prior engagement with other forms of digital texts when planning for scaffolding strategies.
Enumerating Steiner triple systems

Abstract Steiner triple systems (STSs) have been classified up to order 19. Earlier estimations of the number of isomorphism classes of STSs of order 21, the smallest open case, are discouraging as for classification, so it is natural to focus on the easier problem of merely counting the isomorphism classes. Computational approaches for counting STSs are here considered and lead to an algorithm that is used to obtain the number of isomorphism classes for order 21: 14,796,207,517,873,771.
Development of Digital Competences in Students of a Public State-Owned Chilean University Considering the Safety Area

The present study was carried out in a Chilean public university with the purpose of describing digital competences in safety area and their relationship with contextual variables in first-year students of different programs. In this research study, we processed the competences of the safety area of the COMPDIG-PED test, which is based on the European reference framework for digital skills DIGCOMP. The instrument was applied to 4360 higher education students, attending undergraduate courses in 2021 and 2022. The results indicated a relationship between the context variables analyzed through the COMPDIG-PED test and the digital safety competences. This relationship is linked to higher scores in the female gender, in students with more years of experience in the use of digital technologies, in those who came from private paid or subsidized institutions, and in those who were trained in a humanist scientific education.