Reviewerly/exHarmony huggingface dataset:
Multi-message multi-receiver signcryption scheme based on blockchain

&lt;abstract&gt;&lt;p&gt;In conventional message communication systems, the practice of multi-message multi-receiver signcryption communication encounters several challenges, including the vulnerability to Key Generation Center (KGC) attacks, privacy breaches and excessive communication data volume. The KGC necessitates a secure channel to transmit partial private keys, thereby rendering the security of these partial private keys reliant on the integrity of the interaction channel. This dependence introduces concerns regarding the confidentiality of the private keys. Our proposal advocates for the substitution of the KGC in traditional certificateless schemes with blockchain and smart contract technology. Parameters are publicly disclosed on the blockchain, leveraging its tamper-proof property to ensure security. Furthermore, this scheme introduces conventional encryption techniques to achieve user identity privacy in the absence of a secure channel, effectively resolving the issue of user identity disclosure inherent in blockchain-based schemes and enhancing communication privacy. Moreover, users utilize smart contract algorithms to generate a portion of the encrypted private key, thereby minimizing the possibility of third-party attacks. In this paper, the scheme exhibits resilience against various attacks, including KGC leakage attacks, internal privilege attacks, replay attacks, distributed denial of service attacks and Man-in-the-Middle (MITM) attacks. Additionally, it possesses desirable security attributes such as key escrow security and non-repudiation. The proposed scheme has been theoretically and experimentally analyzed under the random oracle model, based on the computational Diffie-Hellman problem and the discrete logarithm problem. It has been proven to possess confidentiality and unforgeability. Compared with similar schemes, our scheme has lower computational cost and shorter ciphertext length. It has obvious advantages in communication and time overhead.&lt;/p&gt;&lt;/abstract&gt;
Manifold-based sparse representation for opinion mining

Abstract What the consumer thinks about an organization's products, services, and events is a crucial performance indicator for businesses. The brief opinion pieces were quickly published on websites and social media platforms and have been analyzed by machine learning methods. The classical text feature representation methods suffer from high dimensionality, sparsity, noisy, irrelevant and redundant information. This paper focuses on how to enhance feature representation for opinion mining. Some nonlinear feature selection methods based on manifold assumption have been exploited to resolve these problems. The inherent manifold configuration was commonly ascertained through a nearest neighbor graph, whereby the neighbors in the current techniques may exhibit diverse polarities. To alleviate this burden, it is proposed to exploit both manifold assumption and sparse property as prior knowledge for opinion representation to learn intrinsic structure from data. First, the graph representation of user reviews based on the mentioned prior knowledge is learned. Then, the spectral properties of the learned graph are exploited to present data in a new feature space. The proposed algorithm is applied to four various common input features on two benchmark datasets, the Internet Movie Database (IMDB) and the Amazon review dataset. Our experiments reveal that the proposed algorithm yields considerable enhancements in terms of F-measure, accuracy, and other standard performance measures compared to the combination of state-of-the-art features with various classifiers. The highest classification accuracies of 99.15 and 91.97 are obtained in the proposed method on IMDB and Amazon using a linear SVM classifier, respectively. The impact of the parameters of the proposed algorithm is also investigated in this paper. The incorporation of a sparse manifold-based representation has led to noteworthy advancements beyond the baseline, and this success serves to validate the underlying assumptions.
Enhanced Collaborative Filtering Algorithm for Movies Recommendation using Big Five Personality Traits

Recommender System suffers from data sparsity and cold start problems which arises when there is no sufficient rating history for user who has recently log into the system and no proper recommendations can be made. This paper develops an Enhanced collaborative filtering algorithm for Movie recommender system Using genre and Big five Personality traits (EMUBP) as system’s input. The experimental result shows that the EMUBP system improved recommendation quality and accuracy by 8.33% compared with the existing state-of-the-art using precision, recall and MAE.
The Influence of the ARIAS (Assurance, Relevance, Interest, Assessment, and Satisfaction) Learning Model Assisted by Documentary Film Media on Enhancing Expository Text Writing Skills in Grade X Students at Senior High School in Bandung

The limited proficiency of high school students in Bandung City composing expository texts. This can be attributed partly to the teachers' constrained experience in devising effective pedagogical models. Consequently, the researchers endeavoured to develop the ARIAS learning model, which incorporates documentary film media as an instructional tool and subsequently evaluated its efficacy in teaching expository text composition. The research methodology employed in this study was rooted in the research and development paradigm. The findings conclusively demonstrated the effectiveness of the ARIAS learning model, complemented by the use of documentary film media, for instructing Grade X students in high schools throughout Bandung City. A notable disparity emerged between the expository text composition instruction in the control group and the experimental group, as confirmed by the T-test results, which yielded a two-tailed p-value of 0.003, well below the established significance level (α) of 0.05 (0.003 &lt; 0.05). This success was further underscored by the variance in average scores between the control class's pretest (55.10) and the experimental class's post-test (74.08). The outcome of this research endeavor is formulating the ARIAS learning model, complemented by documentary film media, to instruct expository text composition. The triumph of this model positions it as a viable alternative for teaching expository text writing, as it actively engages students in the learning process, facilitating the student's personal exploration. Keywords: Expository text, ARIAS, Development, Learning model.
Development of Educational Game Learning Media "Joko the Explorer" on Regional Diversity Material Grade IV SDN Karangtengah 1 Blitar City

This research is aimed to generate a learning media product of area diversity, called “Joko The Explorer,” in the 4th grade of elementary school, that is interesting and valid to the learning experts, media experts, and the teachers as users. Research with the first trial of 6 students and the second trial of 28 students. ADDIE model, with 5 steps, is used to develop this learning media. The steps are; (1) Analysis, (2) Design, (3) Development, (4) Implementation, and (5) Evaluation. The data-collecting techniques consist of interviews and questionnaires. The questionnaires of learning experts, media experts, and teachers as the users are analyzed by using the Likert scale, whereas the students’ questionnaires are analyzed by using Guttman’s scale. The findings, taken from learning experts, show 93.75%, categorized as strongly valid. The findings from media experts showed 93.75%, categorized as strongly valid. The findings from teachers and the users showed 92.85%, categorized as strongly valid. In terms of attractiveness, the students’ questionnaire responses showed an average of 98,42%, categorized as strongly attractive. The percentage shows that the learning media of educational games, “Joko The Explorer,” is categorized as strongly valid, attractive, and can be used without revision. This research concludes that the learning media product of area diversity, called “Joko The Explorer” in the 4th grade of elementary school, is interesting for the students and strongly valid upon the findings from learning experts, media experts, and teachers as the users. The suggestion for further development is to develop not only in terms of area diversity, but also in broad and deep terms related to the Social Sciences or other sciences.
Organized Transnational Crime and Combating Crimes in the Field of Information Technologies (Past and Present)

The article deals with the issue of criminal law aspects of organized crime. The author's vision of the foundations of the concept of organizational and tactical elements of the Ministry of Internal Affairs of Ukraine is presented. Recommendations on prevention and counteraction of transnational computer crimes are provided.
Enhancing the teleportation of quantum Fisher information under correlated generalized amplitude damping noise

The generalized amplitude damping (GAD) noise models the dynamical map of a qubit in contact with a non-zero temperature bosonic reservoir. When two qubits successively pass through the same GAD channel, correlation effects should be taken into account. Therefore, the dynamical map is modeled as correlated GAD (CGAD) noise. In this paper, we investigate the teleportation of quantum Fisher information (QFI) under CGAD noise. We first show that the correlation effects in CGAD noise can enhance the teleported QFI. We then present two probabilistic schemes to improve the teleportation of QFI in CGAD noise by weak measurement (WM) and environment-assisted measurement (EAM). We find the correlation effects of CGAD noise serve to improve the teleportation of QFI and increase the probability of success. Contrary to intuition, the thermal average photon number n doesn’t always play a negative role in our probabilistic schemes. Although a larger n will cause the teleported QFI to decay faster, the corresponding probability of success will be higher. Finally, we introduce a quantity called average QFI to demonstrate that the EAM scheme is superior to the WM scheme with respect to QFI improvement under CGAD noise.
Designing and Evaluating a 3D Virtual World Game for English Language Learning: A Learning Experience Design Approach

This study took an iterative multi-phase learning experience design (LXD) approach to design and evaluate a 3D virtual world game focusing on English language learning. Multiple LXD methods were conducted including empathy interview, heuristic evaluation, cognitive walkthrough, and concurrent think-aloud usability testing, in order to identify usability problems and how learners rated the usability of the intervention. A total of 137 usability problems were identified. Learners rated the game with high overall perceived usability. This study provided evidence for the multi-dimensional usability framework proposed by Jahnke and colleagues and its application at a micro level.
Alt-Tech Topic Modeling Incorporating Atopic Model Selection Strategy

The rapid growth of Alt-tech platforms and concerns over their less stringent content moderation policies, make them a good case for opinion mining. This study aims at investigating the topic models that exist in specific Alt-tech channel on Telegram, using data collected in two time points of 2021 and 2023. Three different topic models of LDA, NMF and Contextualized NTM were explored and a model selection procedure was proposed to choose the best performing model among all. To validate the model selection algorithm quantitatively and qualitatively, the approach was tested on publicly available labelled datasets. For all the experiments, data was pre-processed employing an effective NLP pre-processing procedure along with an Alt-tech customised list of stop-words. Using the validated topic model selection algorithm, LDA topics with Ngram range = (4, 4) were extracted from the targeted Alt-tech dataset. The findings from topic models were qualitatively evaluated by a social scientist and are further discussed. The conclusion of the work suggests that the proposed model selection procedure is effective for corresponding corpus length and context. Future work avenues are suggested to improve the outcome of Alt-tech topic modeling.
Weak Supervision Approach for Arabic Named Entity Recognition

Arabic named entity recognition (NER) is a challenging problem, especially in conversational data such as social media posts. To address this problem, we propose an Arabic weak learner NER model called ANER-HMM, which leverages low quality predictions that provide partial recognition of entities. By combining these predictions, we achieve state of the art NER accuracy for cases for out-of-domain predictions. ANER-HMM leverages a hidden markov model to combine multiple predictions from weak learners and gazetteers. We demonstrate that ANER-HMM outperforms the state-of-the-art Arabic NER methods without requiring any labeled data or training deep learning models which often require large computing resources.
Using an Opportunity Matrix to Select Centers for RBF Neural Networks

When designed correctly, radial basis function (RBF) neural networks can approximate mathematical functions to any arbitrary degree of precision. Multilayer perceptron (MLP) neural networks are also universal function approximators, but RBF neural networks can often be trained several orders of magnitude more quickly than an MLP network with an equivalent level of function approximation capability. The primary challenge with designing a high-quality RBF neural network is selecting the best values for the network’s “centers”, which can be thought of as geometric locations within the input space. Traditionally, the locations for the RBF nodes’ centers are chosen either through random sampling of the training data or by using k-means clustering. The current paper proposes a new algorithm for selecting the locations of the centers by relying on a structure known as an “opportunity matrix”. The performance of the proposed algorithm is compared against that of the random sampling and k-means clustering methods using a large set of experiments involving both a real-world dataset from the steel industry and a variety of mathematical and statistical functions. The results indicate that the proposed opportunity matrix algorithm is almost always much better at selecting locations for an RBF network’s centers than either of the two traditional techniques, yielding RBF neural networks with superior function approximation capabilities.
Partial Recovery of Coherence Loss in Coherence-Assisted Transformation

Coherence-assisted transformation under incoherent operations is discussed. For transformation from the pure state to the mixed state, we show that the coherence loss can be partially recovered by adding auxiliary coherent states. First, we discuss the coherence-assisted transformation for qubit states and give the sufficient and necessary condition for the partial recovery of coherence loss, and the maximum of the recovery of coherence loss is also studied in this case. Second, the maximally coherent state can be obtained in the above recovery scheme, so we give the full characterization of obtaining the maximally coherent state in a qubit system. Finally, we show that the coherence-assisted transformation for arbitrary finite-dimensional main coherent states and low-dimensional auxiliary coherent states is always possible, and the coherence loss also can be partially recovered in these cases.
Peran Dinas Kearsipan dan Perpustakaan Kabupaten Gayo Lues Dalam Mengembangkan Perpustakaan Berbasis Inklusi Sosial

This research titled is "The Role of the Gayo Lues District Archive and Library Agency in Developing a Socially Inclusive Library." The research problem is as follows: 1) the implementation of the development of a socially inclusive library, 2) the opportunities and challenges in developing a socially inclusive library, and 3) the efforts made by the Gayo Lues District Archive and Library Agency in facing these challenges. The purpose of this research is to determine the implementation of the development of a socially inclusive library, the opportunities and challenges faced, and the efforts made by the Gayo Lues District Archive and Library Agency. This research uses a qualitative method with a descriptive approach. The data collection techniques used are observation, interview, and documentation. The results of the research show that the implementation of the development of a socially inclusive library in the Gayo Lues District Archive and Library Agency is going well, with librarians actively involved in revitalization training, library management training, and advocacy through Peer Learning Meetings. The opportunities in this inclusive social library include business opportunities, other social opportunities, and reducing poverty. The Gayo Lues District Archive and Library Agency faces challenges in developing a socially inclusive library, such as lack of cooperation, limited space, and limited budget. Efforts to overcome these challenges include cooperation with other parties and optimal utilization of the budget provided by the center. Keywords: Library Development, Social Inclusion, Gayo Lues District Archive and Library Agency.
Analysis of Language Rules in the Description Text of Class V SDN 2 Karang Bayan Students for the 2021/2022 Academic Year

This study aims to describe the use of language rules in the description text of grade V students of SDN 2 Karang Bayan for the 2021/2022 school year. The subjects of this study were class V students consisting of 16 male students and 12 female students. The object of this study are sentences on the student's description text. The data collection technique used is documentation of the results of student description texts written individually. The type of research used is descriptive qualitative, which is research that aims to describe data in the form of description text related to the linguistic rules of description text with words clearly and in detail. Data processing used by researchers is reading all student description texts, marking errors by coding, grouping data according to the type of error, describing errors, and correcting errors. The results of this study show that the use of linguistic rules in student description texts includes 11 aspects, including nouns, adjectives, transitive verbs, adverbs, standard and non-standard words, connotations and denotations, self-created words, the use of capital letters, word writing, punctuation writing, and figurative language. The use of linguistic rules in student description texts is categorized as very low because it reaches a percentage of 44%. This means that there are still many students who are wrong in using language rules when writing. Meanwhile, the use of inappropriate language rules reached a percentage of 56%. Most students do not apply the rules when writing, especially in writing student description texts. The most common mistakes made by students on the use of capital letters and punctuation writing. Indications that cause errors occur because they are still affected by everyday language and students' inaccuracy after the end of sentences using appropriate punctuation marks so that students do not pay attention to good and correct language rules.
Four-Dimensional Mathematics Creates the Super Universe

In the common theory of the Universe, the redshift of the light wavelength from distant stars indicates the speed of the star. In this study, the model of the Universe is the surface volume of the four-dimensional sphere, and the shape of the Universe results in the most of the redshift of light wavelength. Therefore, there is no dark energy accelerating the Universe. The surface of the four-dimensional sphere is a volume, and this volume is a good model for the Universe. The surface volume of the four-dimensional sphere has been explained by a model of four-dimensional cube, within which the forming of surface volume can be easily shown. The model of four-dimensional cube containing six side cubes is ingenious for explaining the structure of the four-dimensional Universe, but it is not enough because the four-dimensional cube has not six side cubes, but eight side cubes. Therefore, in this study a better method has been created to construct the four-dimensional cube. Our three-dimensional Universe is the surface of the four-dimensional sphere Universe. The volume of our three-dimensional Universe is finite, and beneath it is the infinite volume four-dimensional Super Universe. Two important basic formulae have been derived: The surface volume of the four-dimensional sphere is π3R3 in which R is the radius of the sphere, and the fourth-power volume of the four-dimensional sphere is 1/4 π3R4. The volume of the Universe has been calculated π3R3 = 62 × 1030 ly3. Time as the fourth dimension of the space takes effect only near the speed of light, and therefore it has been ignored in this study.
Recovery of Mail Canceled Sending the Perspective of Memory Forensics

E-mail is mainly used by organizations such as businesses and schools for efficient work processing. Because it handles various tasks, most of the information related to the task is stored in e-mail. If important documents of a company are leaked due to mis-transmission of the e-mail, there is a possibility that the leaked documents may be abused. In preparation for such a case, the sender may cancel the transmission of the e-mail using the ‘cancel transmission’ function. However, if the recipient can restore the canceled e-mail, the sender cannot completely block the mis-transmission of the e-mail. In this paper, we analyze the e-mail storage structure stored in the e-mail data file and the storage structure of the unsent e-mail remaining in the file and attempt to restore the email.
A feasibility study of usability and UX evaluation technologies in multi-touch context: A quantitative and qualitative analysis

The use of multi-touch systems has been increasing in the last few years. These systems also need to pass through an evaluation to check their quality level. For this, usability and User Experience (UX) are two important aspects. Seeking to find out which technologies are being used for this purpose, we performed a Systematic Mapping Study (SMS). We discover that no technologies are being used to evaluate usability and UX on multi-touch interfaces that consider the specificities of this context, such as lack of touch precision and mechanical feedback. We proposed the User Experience and usability Multi-touch Evaluation Questionnaire (UXUMEQ) to fill this gap. This technology was evaluated through a feasibility study performed with 47 participants. Efficiency and effectiveness were compared to a combination of the System usability Scale (SUS) and Intuitive Questionnaire (INTUI). According to quantitative results, UXUMEQ presented a statistically significant difference over SUS+INTUI in terms of efficiency, while in effectiveness the comparison remained similar. In other words, UXUMEQ allows the users to find more problems, though it cannot be said that it saves time in this search compared to SUS+INTUI. UXUMEQ was considered easy to use, proposal-fulfilling, and highly assertive by the study participants. The qualitative data was analyzed and generated in a new version of UXUMEQ.