Reviewerly/exHarmony huggingface dataset:
Short Text Sentiment Analysis Based on Multiple Attention Mechanisms and TextCNN-BiLSTM

Researchers have been paying more and more attention lately to the use of natural language processing methods to analyze the sentiment of short text. Due to the characteristics of sparsity and irregularity, short text classification often has a large number of implied semantics, which requires a high feature learning ability of the model. The current common models, like Convolutional Neural Network (CNN), can extract the local information of sentences but ignore the contextual semantic information between words. Bidirectional Long Short-Term Memory Network (BiLSTM) can fill in the deficiencies left by CNN's inability to effectively extract the contextual semantic information of text, but the local features of sentences cannot be extracted well. In this paper, a text sentiment analysis classification model based on multiple attention mechanisms and TextCNN-BiLSTM is proposed. The dynamic word vector representation of text is obtained by the BERT model, local information with different granularity is extracted in parallel by TextCNN with different scales, The global dependence is then mined using the multi-head self-attention process, which reduces the impact of context-dependent long-distance words. To obtain the prediction result of sentiment analysis, the BiLSTM model is finally input to fuse the time sequence information, the attention mechanism is combined to focus on the crucial data. The experimental results show that the accuracy and F1 are improved on two data sets compared with previously reported models.
Knowledge Distilled Ensemble Model for sEMG-based Silent Speech Interface

Voice disorders affect millions of people worldwide. Surface electromyography-based Silent Speech Interfaces (sEMG-based SSIs) have been explored as a potential solution for decades. However, previous works were limited by small vocabularies and manually extracted features from raw data. To address these limitations, we propose a lightweight deep learning knowledge-distilled ensemble model for sEMG-based SSI (KDE-SSI). Our model can classify a 26 NATO phonetic alphabets dataset with 3900 data samples, enabling the unambiguous generation of any English word through spelling. Extensive experiments validate the effectiveness of KDE-SSI, achieving a test accuracy of 85.9%. Our findings also shed light on an end-to-end system for portable, practical equipment.
A Comprehensive Study on Blockchain-based Cloud-Native Storage for Data Confidence

This paper explores the concept of blockchain-based cloud-native storage, which combines the decentralized and immutable nature of blockchain with the scalability and agility of cloud-native architecture. We discuss the significant contributions of leveraging blockchain and cloud-native concepts in storage systems for edge computing, specifically focusing on data security, reliability, and scalability. Furthermore, we address the challenges associated with implementing blockchain and cloud-native concepts in edge storage systems, including network connectivity and resource constraints. By examining these challenges, we aim to provide insights into the practical considerations and potential solutions for effectively integrating blockchain and cloud-native technologies in edge storage environments.
Implementation of S-box for lightweight block cipher

In recent years, the growing use of IoT and electronic devices with limited resources has created a need for lightweight cryptography algorithms that can provide secure communication between devices. National Institute of Standards and Technology (NIST’s) lightweight cryptography initiative aims to develop standards for cryptography algorithms, and in such a algorithm’s S-box is one of the most important elements of this approach. In this paper, we analyze the performance of the S-box when implemented in both serial and parallel modes, with a focus on its use in RFID systems. We present detailed comparisons between the two implementations and discuss the implications of our results. Our findings suggest that the parallel implementation of the S-box may offer improved performance in certain scenarios, highlighting the importance of careful consideration when selecting the most appropriate security primitives for specific applications. Overall, our work contributes to the ongoing effort to develop effective lightweight cryptography solutions for a wide range of electronic devices.
Investigation on the Integrated Cloud and BlockChain (ICBC)Technologies to Secure Healthcare Data Management Systems

Blockchain is emerging as one of the most promising and resourceful security technologies for cloud infrastructures. In a distributed database system, blockchain is used to store, read, and validate transactions. It can improve security, trustworthiness, and privacy by using an unchallengeable, shared distributed ledger on cloud nodes. Cloud-based healthcare systems (CHS) are vulnerable to various threats and attacks such as identity theft, medical fraud, insurance fraud, and alteration of critical patient data. Secure retrieval, access, and storage of data on CHS are necessary to protect critical medical data. Accordingly, the integrated cloud and BlockChain (ICBC) architecture emerge as a potential solution for shaping the next era of a healthcare system while providing efficient, secure, and effective patient care. In this context, this paper presents an in-depth exploration of advanced approaches to securing cloud-based healthcare data management systems using blockchain technologies. It provides a taxonomy and highlights the benefits and limitations of the approaches examined.
TwinFormer: Fine-to-Coarse Temporal Modeling for Long-term Action Recognition

The long-term action in untrimmed video generally contains multiple sub-actions, among which various semantic patterns exist ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , the co-occurrence or sequentiality between sub-actions). These semantic patterns are temporally coarse, and correlated with multiple local contexts which encode the local temporal evolution of visual elements ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , hands, objects) in videos. The local contexts and semantic patterns form the inherent fine-to-coarse temporal structure of long-term actions, which is neglected by existing works. Accordingly, in this work we propose TwinFormer, which exploits a novel fine-to-coarse temporal modeling manner to uncover the temporal structure of long-term actions. The proposed TwinFormer consists of a pair of twin encoders with the same structural design, namely Localcontext Encoder and Semantic-pattern Encoder, and a Temporalbridged Attention to bridge the two twin encoders. The Localcontext Encoder aims to model the local contexts in the longterm action. And the Temporal-bridged Attention is designed to correlate the local contexts with semantic patterns. Furthermore, the Semantic-pattern Encoder reveals the temporal evolution of semantic patterns. Experimental results on three benchmarks demonstrate the effectiveness of the proposed model.
DEVELOPMENT OF GENIALLY BASED EDUTAINMENT GAMES AS MEDIA TO IMPROVE STUDENT’S LEARNING MOTIVATION

The low students’ learning motivation influences the suboptimal learning process. The learning activities tend to be monotonous and make the students have a lack of interest in learning. Making creative and innovative media is an effort that can be made to improve students’ learning motivation. The research aims to develop genially based edutainment game learning as media that can encourage and cultivate students' learning enthusiasm. The research used the Research &amp; Development (R&amp;D) method and the Borg &amp; Gall development model. The research instruments used were validation questionnaires, trial sheets, and learning motivation questionnaires. The research results indicate that edutainment games based on Genially are valid and suitable for use as a learning media to help teachers in Civic Education learning activities. This is supported by the validation results from three experts of media, materials, and learning, with an average value of 88% in the highly valid category. The average score of learning motivation before applying media was 3.31 in the "sufficient" category, and there was an increase average score of 4.42 in the "very high" category after carrying out learning activities through edutainment game media based on Genially. It shows that edutainment game media based on Genially can also increase students' learning motivation in Civic Education learning subjects.
Evaluation of Website Based Information System To Monitor Student Learning Progress In Schools Using ISO/IEC 9126 Standards And GTMetrix

This study aims to evaluate website based information systems that have been developed previously using ISO/IEC 9126 Standards and GTMetrix. Testing of website based information systems using ISO/IEC 9126 is carried out by information system expert, users, and testing using GTMetrix, the user referred to in the test these are administrators, teachers, and student parents. Testing of information system experts takes four measures of quality including functionality, reliability, usability, and portability, while testing on users takes three measures including functionality, usability, and portability, and testing using GTMetrix takes a measure of quality efficiency and serves to assess the performance of the website-based information system developed. The results obtained from the evaluation were testing of information system expert getting a score of 91.17%, administrator user getting a score of 95.11%, teacher user getting a score of 91.35%, student parents getting a score of 83.4%, and testing using GTMetrix getting a score of 86.13% or Grade B. Based on the results of the evaluation using ISO/IEC 9126, it was found that the testing using ISO/IEC 9126 for the tested website-based information system has been meet the expectations of users, especially parents and the school.
Photogrammetry for making real-time measurements of the deformation of fire retarded material subjected to an external heat flux

This work exploits photogrammetry techniques to make real-time measurements on a deforming material subjected to an external heat flux. Using a novel bench design and 3D reconstruction associated to image analysis, the volume of the sample can be accurately calculated. It is applied to a fire retarded polymer (ethylene-vinyl acetate copolymer containing 65 wt% of aluminum trihydroxide as fire retardant). The material shrinks and swells upon heating (heat flux of 35 kW/m2). The volume can be followed as a function of time and it provides quantitative data about the deformation of the material.
Intervention of music therapy on emotional disorders of autistic children in the context of intelligent medical internet of things

Abstract Many parents have been troubled by the emotional problems of autistic children. Emotional disorders are one of the main characteristics of autistic children in terms of thinking, interpersonal relationship, language communication and intelligence. The rapid development of intelligent medicine and the Internet of Things has provided more facilities for music therapy in the field of rehabilitation, such as equipment tools, case analysis and training practice. In this paper, four autistic children with emotional disorders were treated and intervened with Orff music therapy and visual music therapy. The average probability of occurrence of emotional disorders in children with autism No.1 and No.2 before intervention was 53.2% and 53% respectively. After receiving Orff music therapy, the average probability of emotional disorders decreased to 44.9% and 38.6% respectively; the average probability of occurrence of emotional disorders in children with autism No.3 and No.4 before intervention was 40.3% and 50.2% respectively. After receiving visual music therapy, the average probability of occurrence of emotional disorders decreased to 33.7% and 44.2% respectively. Using music, pictures, lighting and other therapeutic elements, the visual and auditory motor sense is organically combined. Through the interaction between the therapist and the treatment object, to adjust the children's emotions, to awaken, stimulate, soothe, catharsis and other spiritual effects.
The Effects of Play-Based Literacy on the Reading Readiness of Grade One Students

The study focused on the Effects of Play-Based Literacy on the Reading Readiness of Grade One Students. This utilized a quasi-experimental, one-group design with pre-test and post-test measures. The participants in this study will be Grade One students in one primary school in Cebu, Philippines.The study will make use of the Fountas and Pinnell Benchmark Assessment Program. The Fountas &amp; Pinnell Benchmark Assessment Program uses benchmark books to assess students' reading levels.The study yielded that in terms of the High-Frequency Words Assessment during the pre-test, five (5) students did not meet expectations during the pretest, while the others met the expectation. Moreover, after the play-based intervention, all of the students either met or exceeded the expectation on the assessment of high-frequency words. Likewise, in terms of reading assessment, it can be seen that there was an increase in the level of students reading readiness after the play-based intervention.The results of the study highlighted the significance of play in the growth of young children, particularly with regard to the impact of play on reading development.
Digital Transformation of Accounting in the Industrial Revolution Era 4.0

The Industrial Revolution 4.0, marked by the accelerated adoption of digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), big data, and other technologies, has significantly impacted various business sectors. One sector that has been fundamentally affected is accounting, which has had to adapt to these changes to remain relevant and efficient in an increasingly complex and dynamic business environment. This study aims to understand and analyze how digital transformation in the Industrial Revolution 4.0 era has affected the field of accounting. The research method used is descriptive-qualitative research. This research reveals that digital transformation in accounting, supported by technologies such as IoT, artificial intelligence, big data, and others, brings operational efficiencies through automation, increases the accuracy of financial data, and drives deep data analysis. Collaboration and communication are also enhanced through a cloud-based platform. However, data protection and privacy are important issues in the digital era. In the Industrial Revolution, 4.0, technologies such as big data analytics, AI, IoT, cloud computing, and blockchain are bringing fundamental changes, enabling accounting to be more proactive, using data analysis for better predictions and customer service, and more intelligent and responsive decision making. Digital transformation continues to change the landscape of the accounting and financial industry, making careful use of the potential of the digital age.
Attribute-Based Multi-input FE (and More) for Attribute-Weighted Sums

Recently, Abdalla, Gong and Wee (Crypto 2020) provided the first functional encryption scheme for attribute-weighted sums (AWS), where encryption takes as input N (unbounded) attribute-value pairs $$\{\textbf{x}_i, \textbf{z}_i\}_{i \in [N]}$$ where $$\textbf{x}_i$$ is public and $$\textbf{z}_i$$ is private, the secret key is associated with an arithmetic branching programs f, and decryption returns the weighted sum $${\sum }_{{i \in [N]}} f(\textbf{x}_i)^\top \textbf{z}_i$$ , leaking no additional information about the $$\textbf{z}_i$$ ’s. We extend FE for AWS to the significantly more challenging multi-party setting and provide the first construction for attribute-based multi-input FE (MIFE) supporting AWS. For $$i \in [n]$$ , encryptor i can choose an attribute $$\textbf{y}_i$$ together with AWS input $$\{\textbf{x}_{i,j}, \textbf{z}_{i,j}\}$$ where $$j \in [N_i]$$ and $$N_i$$ is unbounded, the key generator can choose an access control policy $$g_i$$ along with its AWS function $$h_i$$ for each $$i \in [n]$$ , and the decryptor can compute $$\sum _{i \in [n]}\sum _{j \in [N_{i}]}h_{i}(\textbf{x}_{i,j})^{\top }\textbf{z}_{i,j} \text { iff } g_{i}(\textbf{y}_{i}) =0 \text { for all } i \in [n]$$ Previously, the only known attribute based MIFE was for the inner product functionality (Abdalla et al. Asiacrypt 2020), where additionally, $$\textbf{y}_i$$ had to be fixed during setup and must remain the same for all ciphertexts in a given slot. Our attribute based MIFE implies the notion of multi-input attribute based encryption (MIABE) recently studied by Agrawal, Yadav and Yamada (Crypto 2022) and Francati, Friolo, Malavolta and Venturi (Eurocrypt 2023), for a conjunction of predicates represented as arithmetic branching programs (ABP). Along the way, we also provide the first constructions of multi-client FE (MCFE) $$^3$$ and dynamic decentralized FE (DDFE) for the AWS functionality. Previously, the best known MCFE and DDFE schemes were for inner products (Chotard et al. ePrint 2018, Abdalla, Benhamouda and Gay, Asiacrypt 2019, and Chotard et al. Crypto 2020). Our constructions are based on pairings and proven selectively secure under the matrix DDH assumption.( $$^3$$ The literature considers two notions termed as MCFE, one strictly stronger than the other. The stronger notion implies MIFE while the weaker does not. Here, we refer to the stronger notion, making MCFE a strict generalization of MIFE.)
Impact of Foreign Direct Investment on Economic Growth in the Gambia: Evidence from Time Series Analysis

This paper aims to assess the impact of foreign direct investment on The Gambian economy using time series data from 1980-2018. Estimations were made using the Ordinary Least Square (OLS) together with various other econometric and statistical methods to analyze the nexus between FDI flows and economic growth in The Gambia. The results show a positive link between foreign direct investment and economic growth in The Gambia. This finding suggests that an increase in foreign direct investment will positively impact the economic growth of the country. Based on this finding, the paper recommends that policymakers in the Gambia develop business-friendly environment policies and a quality educational system and ensure political stability to attract foreign investors, which in turn could enhance the country's economic growth prospects.
Chapter 3 A deep survey on quantum computing technologies

There has been significant advancements in Quantum Computing research related to infrastructure and algorithmic complexity in recent years. Since the 1980s, the scientific community has been interested in the possibility of using quantum phenomena to tackle computer issues. Quantum computing systems get their power from the no-cloning theorem, quantum superposition, and quantum entanglement. Based on the fact that these events lack a classical equivalent, it is not possible to reach comparable conclusions using the framework of traditional computing. Already demonstrated are the experimental breakthroughs that can be made with quantum computing technology, and a number of investigations are currently being carried out. In this chapter, we analyze the most recent technological breakthroughs in the field of quantum computing and investigate some of the outstanding issues.
THE IMPLEMENTATION OF GOOGLE MAP TO ENHANCE STUDENTS’ SPEAKING SKILL IN LEARNING ENGLISH AT YASIN 9 DARUSSALAM MODERN BOARDING SCHOOL

The presence kinds of applications are paramount ways to enhance students learning of English, particularly students’ enthusiasts. In this case, the researcher used Google Map to improve students' speaking skills in learning English, as well as to describe the students' responses to this application. Google Maps is one of the media that can be used in English learning because it is a collaborative tool, interactive, and innovative way to increase students' visualization of English material. The design method used by the researcher was Classroom Action Research. The information was gathered from the seventh grade and who was learned using Google Maps. There were ten students in total. The study discovered that each cycle made more progress in terms of students’ participation. Students appeared to be excited about putting their existing insights to use. The improvement is significant, particularly in terms of students’ participation and performance. It was possible to see this by comparing the researcher's notes, student interviews, observation sheets, and student tasks from cycle to cycle three. The use of Google Maps as a learning medium contributes to providing an enjoyable learning medium in English teaching and learning. On the other hand, three students were not actively involved, two were redundant to English, and two had difficulty recognizing unfamiliar words. Nevertheless, in each cycle they show improvement; the students are motivated and there was a desire to learn.&#x0D; &#x0D; &#x0D; Keywords: Speaking Ability, Google Map, Application, Contextually.
Digital Metempsychosis? A Critique of the Two-Worlds Model of Immersivity

The paper proposes the notion of “Two-Worlds Model” (TWM) as a theoretical framework in order to analyse some currents in the contemporary debate on technologically mediated experience. According to this model, technologically mediated experience—especially immersive experience—can be described as a form of “digital metempsychosis”—a feeling of being elsewhere. The paper argues that this model is not new in the history of philosophy, and that it is a very common theoretical and cultural strategy, often used to reduce medial differences—differences in the way of being or of experiencing something—as objectual difference. By analysing some specific topics—the most common accounts of immersive experience, the relation between immersivity and presence, and the notion of “cyberspace”—the paper aims at showing the limits of the TWM, in particular when it is used in order to describe technologically mediated experience.
Evaluating Mobile Banking Application Security Posture Using the OWASP’s MASVS Framework

In the context of financial gain, hackers are motivated to exploit vulnerabilities that could result in financial or data loss. Therefore, it is crucial for financial applications to undergo thorough testing to identify and address such vulnerabilities. Regrettably, many financial institutions neglect proper testing procedures and sometimes even fail to establish a suitable security release baseline. This report presents an analysis of 18 mobile applications, each belonging to a different financial institution in Africa. The selection of these applications was carefully executed, considering institutions of varying sizes, to enable a comparative assessment of security practices across different organizational scales. The assessment was conducted by evaluating the sampled applications against the Mobile Application Security Verification Standard v2.0. This is a set of checklists and guidelines by the Open Web Application Security Project (OWASP) used as a baseline for mobile application security. Due to the extensive nature of the project, the testing scope was limited to the application itself, as experienced by the end user. This included examining the application’s interaction with the back-end server and observing its behavior on the user’s mobile device. It is important to note that this report does not provide a comprehensive analysis, as it excludes the assessment of the server-side API and testing of business logic that requires elevated privileges within the application. Furthermore, a survey was conducted to gain insights into why developers may neglect baseline security thereby introducing potential vulnerabilities in mobile applications. The findings of this survey are also included in a short summary at the end of this document.