Reviewerly/exHarmony huggingface dataset:
Designing ontologies for behaviours based on temporal passive data

The use of ontologies to model human behaviours that affect health is challenging since this process involves data from multiple inter-related domains that unfold and evolve over time. However, while current ontology development methodologies are generic enough to model any domain of interest, they do not provide design guidelines for modelling time-related aspects. This paper proposes a methodology for ontology development that entails the requirements for behaviours modelling based on passive temporal data. Its main focus is on temporal representations of classes and their holistic relations since no other methodology approaches ontology design from its temporal perspective. We exemplify these ideas by modelling the sleep behaviour domain, its relations to other behavioural aspects, and its effects on health.
Automatic Chinese knowledge-based question answering by the MGBA-LSTM-CNN model

The purpose of knowledge-based question answering (KBQA) is to accurately answer the questions raised by users through knowledge triples. Traditional Chinese KBQA methods rely heavily on artificial features, resulting in unsatisfactory QA results. To solve the above problems, this paper divides Chinese KBQA into two parts: entity extraction and attribute mapping. In the entity extraction stage, the improved Bi-LSTM-CNN-CRF model is used to identify the entity of questions and the Levenshtein distance method is used to resolve the entity link error. In the attribute mapping stage, according to the characteristics of questions and candidate attributes, the MGBA-LSTM-CNN model is proposed to encode questions and candidate attributes from the semantic level and word level, respectively, and splice them into new semantic vectors. Finally, the cosine distance is used to measure the similarity of the two vectors to find candidate attributes most similar to questions. The experimental results show that the system achieves good results in the Chinese question and answer data set.
Naturally decision intelligence: Perfect algorithm generated by the hypothetical and synchronizing model for life system

Decision Intelligence is a methodology that integrates complex systems, machine learning, and decision analysis. It is increasingly interested in finding optimal solutions to the uncertainties noted in machine learning in today’s complex AI systems. Furthermore, Decision Intelligence is a new engineering discipline that augments data science with theories from various sciences. Since decisions are made in all kinds of situations, they will become even more critical in a wide range of academic fields in the future. This paper introduces the ideas of proponents of Decision Intelligence, the promotion of digital decisioning toward automation, and trends in Western companies and Japan. Then, using risk management procedures, our examination of methods to ensure safety in the case of automated driving will be described. In addition, I will describe the challenges of each technology that promotes Decision Intelligence. I will also introduce a new synchronous AI that I am currently working on with the inventor of the challenge. This algorithm generation method is based on a metaphysical view of the synchronous nature of life activity.
Parallax image stitching combining improved feature optimization with optimal seam estimation

In the process of image stitching, many problems will inevitably arise, such as misalignment, artifacts and local structure distortion in the overlapping regions. A parallax image stitching algorithm combining improved feature optimization with an innovative iterative seam estimation is proposed. First, the point features and line features of input images are detected. To optimize point features, the histogram statistical approach is proposed to remove false matching points combined with RANSAC algorithm. Second, the mesh warp is optimized by minimizing the sparse quadratic total energy function so as to achieve accurate alignment in the overlapping regions. Finally, we propose an iterative seam estimation method using an improved quality evaluation strategy. Experimental results show that our method has higher matching accuracy and visually better image stitching performance than other methods.
Theoretical Prediction and Experimental Verification of Hitting Targets of Gravity-Powered Trebuchets

Abstract As one of the early weapons used by the ancient Chinese military, the gravity-powered trebuchet is listed as a mandatory program in science and technology games in several provinces. Due to its entertaining and informative features, this program has received continuous attention and discussion from scholars. Currently, most of the studies on this program are empirical, and few studies have been conducted quantitatively based on theoretical models. Therefore, this study established a theoretical model of the trebuchet projection process from the perspective of system energy conservation and gave an accurate analytical expression of hitting target points. In order to verify the reliability of the theoretical model, experimental tests were conducted. The results showed that the experimental results were relatively consistent with the theoretical predictions. These findings could provide a new research idea for facilitating gravity-powered trebuchets to hit targets accurately.
Robust determination of relaxation times spectra of long-time multirelaxation processes

Long-time relaxation processes occur in numerous physical systems. They are often regarded as multirelaxation processes, which are a superposition of exponential decays with a certain distribution of relaxation times. The relaxation times spectra often convey information about the underlying physics. Extracting the spectrum of relaxation times from experimental data is, however, difficult. This is partly due to the mathematical properties of the problem and partly due to experimental limitations. In this paper, we perform the inversion of time-series relaxation data into a relaxation spectrum using the singular value decomposition accompanied by the Akaike information criterion estimator. We show that this approach does not need any a priori information on the spectral shape and that it delivers a solution that consistently approximates the best one achievable for given experimental dataset. On the contrary, we show that the solution obtained imposing an optimal fit of experimental data is often far from reconstructing well the distribution of relaxation times.
Entangled Frequency-Tunable Microwave Photons in a Superconducting Circuit

We propose a frequency-tunable source to emit entangled microwave photons on the platform of a superconducting circuit, in which two superconducting transmission-line resonators are coupled via a capacitor and one resonator is inserted with a superconducting quantum interference device (SQUID) in the center. By pumping the circuit appropriately with an external coherent microwave signal through the SQUID, microwave photons are emitted in pairs out of the circuit. The entanglement between the two modes is demonstrated by numerically calculating the second-order coherence function and the logarithmic negativity of the output microwave signals. Due to the tunability of SQUID’s equivalent inductance, the frequencies of the entangled microwave photons can be tuned by an external flux bias in situ. Our proposal paves a new way for obtaining entangled frequency-tunable two-mode microwave photons.
Implementation of the Principle of Dualism in Intellectual Property Law on the Example of the Copyright Contract

The relevance of the conducted research is due to the presence of a number of factual contradictions between the position of the courts in considering the issues of exclusive rights to works created during the execution under the contract of copyright with the rules of law contained in the civil legislation of the Russian Federation. The proposed issues are examined from the point of view of copyright and civil law, legal acts of foreign countries, judicial practice of the Russian Federation and foreign courts. The analysis of examples from judicial practice is given as a substantiation of legislative consolidation of the principle. This article reveals the author's view of the principle of duality of intellectual property law as an independent principle of a sub-branch of civil law and its implementation in the contract of copyright. Principles of law are defined by the author as its guiding principles that define the rules of law in the system of legal regulation, its content and direction. The purpose of the study is determined by the title and content of the work: the essential characteristics of the principle of duality of intellectual property rights, including the implementation of contractual relations in the performance of the author's order are considered. The totality of general scientific, special legal methods of knowledge is used: thanks to the analysis and synthesis the approaches to the proposed topic are generalized and conclusions are made. The principle of duality of intellectual property is considered as a fundamental idea of law, neglecting the account of which entails a violation of rights and freedoms and has legal consequences. Recommendations on the legislative consolidation of the mandatory written form of the copyright contract and the contract of alienation of exclusive rights in its continuation are given.
Exploring Factors Affecting People’s Willingness to Use a Voice-Based In-Car Assistant in Electric Cars: An Empirical Study

Voice-based digital assistants are growing in popularity and have been acknowledged as a crucial part of in-car interaction. Currently, academic attention is being paid to various voice assistant scenarios. However, sparse literature focuses on the adoption of voice assistants within the in-vehicle context. The objective of this paper is to examine key factors influencing people’s willingness to use voice assistance in electric cars. First, eight general variables were identified based on the literature review, as well as four demographic variables. These factors were then integrated to construct a hypothetical research model. After that, we carried out an empirical study to examine the structural relationships in the model based on the questionnaire survey results (N = 427). The hypothesis testing results indicated that most path relationships among variables were validated. Finally, we discussed the research findings and developed corresponding design strategies to enhance user acceptance towards in-car voice assistants, both from designers’ and car enterprises’ viewpoints. This article offers valuable theoretical and practical implications for the development of such technologies.
Pipelined Decision Trees for Online Traffic Classification on FPGAs

Abstract Decision tree (DT)-based machine learning (ML) algorithms are one of the preferred solutions for real-time internet traffic classification in terms of their easy implementation on hardware. However, the rapid increase in today’s newly developed applications and the resulting diversity in internet traffic greatly increases the size of DTs. Therefore, the tree-based hardware classifiers cannot keep up with this growth in terms of resource usage and classification speed. To alleviate the problem, we propose to group application classes by certain rules and create an individual small DT per each group. In this article, a pipelined organization of multiple DT data structures, called pipelined decision trees, is proposed as a scalable solution to tree-based traffic classification. We also propose two distinct algorithms, namely confusion matrix-based class aggregation and leaf count-based class aggregation algorithms, to set group creation rules that allows traffic classification on pipelined smaller DTs in a hierarchical order. We further designed an hardware engine on field programmable gate arrays, which can search those pipelined trees within a single clock cycle by transforming them into bit vectors and implementing multiple range comparisons in parallel. Our architecture with 12 classes can run in 928.88 giga bit per second and achieve 96.04% accuracy.
Fast Area Optimization Approach for XNOR/OR-based Fixed Polarity Reed-Muller Logic Circuits based on Multi-strategy Wolf Pack Algorithm

Area optimization is one of the most important contents of circuits logic synthesis. The smaller area has stronger testability and lower cost. However, searching for a circuit with the smallest area in a large-scale space of polarity is a combinatorial optimization problem. The existing optimization approaches are inefficient and do not consider the time cost. In this paper, we propose a multi-strategy wolf pack algorithm (MWPA) to solve high-dimension combinatorial optimization problems. MWPA performs global search based on the proposed global exploration strategy, extends the search area based on the Levy flight strategy, and performs local search based on the proposed deep exploitation strategy. In addition, we propose a fast area optimization approach (FAOA) for fixed polarity Reed-Muller (FPRM) logic circuits based on MWPA, which searches the best polarity corresponding to a FPRM circuit. The experimental results confirm that FAOA is highly effective and can be used as a promising EDA tool.
Contrastive Adversarial Training for Multi-Modal Machine Translation

The multi-modal machine translation task is to improve translation quality with the help of additional visual input. It is expected to disambiguate or complement semantics while there are ambiguous words or incomplete expressions in the sentences. Existing methods have tried many ways to fuse visual information into text representations. However, only a minority of sentences need extra visual information as complementary. Without guidance, models tend to learn text-only translation from the major well-aligned translation pairs. In this article, we propose a contrastive adversarial training approach to enhance visual participation in semantic representation learning. By contrasting multi-modal input with the adversarial samples, the model learns to identify the most informed sample that is coupled with a congruent image and several visual objects extracted from it. This approach can prevent the visual information from being ignored and further fuse cross-modal information. We examine our method in three multi-modal language pairs. Experimental results show that our model is capable of improving translation accuracy. Further analysis shows that our model is more sensitive to visual information.
An Analysis of Students’ Difficulties in Writing Recount Text

Teaching English in Junior High School focuses on improving four language skills namely listening, speaking, reading, and writing. The students are expected to be able to master those four language skills. Improving productive skills is the most important in teaching English. One of the productive skills that have to be improved is writing. However, in practical level, a lot of students have difficulties in writing English texts. Therefore, this research aims to analyze students’ difficulties in writing recount text at the 8th students SMP 15 Kota Serang. The method used in this research was qualitative method which used some instruments like documents, questionnaires, and interview. Based on the result of the research, the most difficult aspects of writing recount encountered by the students were in term of grammar, and then followed by the use of verb, capitalization, the use of to be, punctuation, spelling, preposition, and vocabulary. Moreover, based on the result of students’ recount tasks, the biggest errors made by the students were error of misformation, and then followed by error of omission, error of misorder, and error of addition.
A Qualitative Exploration of Students’ Perception on English Day Program at SMAN 1 West Sumatera

This present research is motivated by the English day program applied at SMAN 1 West Sumatera. This research aims to find out how students perceive the English day program at SMAN 1 West Sumatra. This research used a qualitative method. The research informants were students of the tenth grade of SMAN 1 West Sumatra who took part in English day in the 2021/2022 academic year who were selected by purposive sampling technique. In this research, the researchers acts as the key instrument. Data collection techniques was interviews. Data collection tools were obtained from interview guides, recorders, and field notes. To test the validity of the data, the researchers conducted time triangulation. Data analysis was carried out in three stages: data reduction, data presentation, and conclusion drawing and verification. The results of the data analysis show several students’ perception on English day program at SMAN 1 West Sumatera. The perceptions include: (1) enriching students’ vocabulary; (2) improving students’ grammar mastery; (3) enhancing students’ speaking skills; (4) improving students’ pronunciation; and (5) increasing students’ understanding of English. The negative perception, however, is English day program burdens the students with the punishment. These findings recommend English day program remain to conduct at SMAN 1 West Sumatera.
A Bi-Gram Approach for an Exhaustive Arabic Triliteral Roots Lexicon

With the rapid development of science and technology, many new concepts and terms appear, especially in English. Other languages try to express these concepts with words from their vocabulary. In Arabic, there are many ways to find a counterpart for a particularly new concept, such as using an existing word to denote the new concept, derivation, and blending. When these methods fail, the new concepts are phonetically transliterated. Unfortunately, most of the transliterated terms do not conform to the rules of the Arabic language, and many languages, including Arabic, avoid the use of such terms. Some modern linguists call for using the generation strategy to translate new terms into Arabic based on the idea of the meanings of the Arabic letters. Therefore, it is necessary to provide a resource that contains all Arabic roots with a categorization of what is used, what is available for use, and what is rejected according to the phonetic system. This work provides a comprehensive lexicon that contains all possible triliteral roots and determines the status of each root in terms of usage and acceptability. Additionally, it provides a mechanism for giving preference to roots when there is more than one root that indicates the desired meaning.
Effect of Salesperson Avatar Automatically Mimicking Customer’s Nodding on the Enjoyment of Conversation in Virtual Environments

As the VR industry continues to expand, one area gaining attention is its application in the retail sector. In customer service, a crucial aspect of retail, the skills of a salesperson are vital. However, research on VE in this field is still limited. Imitation behavior is known to be an essential customer service skill. Therefore, this study focuses on the effect of nodding imitation by a salesperson’s avatar on customer service in VE. Consequently, an experiment was conducted in which an avatar of a salesperson that automatically mimics nodding was implemented and provided customer service in a virtual store that simulated a furniture store. The results revealed that when the avatar of the salesperson mimicked nodding, the item of enjoyable interaction aspect of rapport was higher, and a significant difference was observed. This results contribute to the development of customer service within VE and have potential implications for creating effective salesperson avatars.
Hardware‐assisted remote attestation design for critical embedded systems

Abstract Remote attestation, as a challenge‐response protocol, enables a trusted entity, called verifier , to ask a potentially infected device, called prover , to provide integrity assurance about its internal state. Remote attestation is becoming increasingly vital for embedded systems that serve in many critical domains, as part of health, military, transportation and industry services, but still lack the most security features available to high‐end systems. In most attestation techniques, the prover provides a cryptographic checksum of its static memory contents, that is, code segments, to the verifier when requested to demonstrate that the device is loaded with the right software. However, those measurements are subject to two limitations. First, they cannot guarantee that the prover has always had legitimate software in the memory prior to attestation. This is because occasional measurements, triggered by the verifier, still leave the device vulnerable to the compromise between two attestation windows as a time‐of‐check‐to‐time‐of‐use (TOCTOU) problem. Second, including dynamic memory regions in the checksum calculation is not helpful in practice, since the verifier typically does not know what those regions should contain or which checksums should be accepted as valid. Hence, many attack scenarios residing in those dynamic regions (e.g. stack) would also go unnoticed. To reveal attack scenarios exploiting the memory regions and time windows left unattested, we propose an attestation scheme that can continuously monitor both static and dynamic memory regions with better spatial and temporal attestation coverage. Our monitoring mechanism is designed to be performed in real time using a novel hardware security module (HSM) connected to the prover's system bus. The proposed HSM monitors not only the integrity of the code on the prover but also its execution by checking the compliance of the bits seen on the bus according to a runtime integrity model (RIM) of the prover's software. Therefore, our attestation scheme is capable of reporting scenarios that violate both the (static) code and (dynamic) runtime integrity since the deployment time.
Improved Design and Application of Security Federation Algorithm

(1) Background: To avoid affecting the accuracy and practicability of the security federation model due to the geographical and environmental factors involved in each local model and set the corresponding weights for each local model, the local model parameters and weights participated in the calculation at the same time. (2) Methods: Apply the improved model to the income evaluation of taxi drivers. Multiple linear regression was used to fit the local model parameters, and the loss function value was calculated. Then, according to the improved security federation algorithm, the model parameters and local model weights were encrypted by using the Paillier homomorphic encryption algorithm, and the encrypted model parameter information was uploaded to the aggregation server for aggregation average. (3) Results: The experimental results show that after 1000 iterations, the accuracy curve converges in the interval [0.93, 0.97]; the mean accuracy value was 94.27%, and the mean loss function value was 1.0886. It was the same understanding that the mean value of the loss function calculated by the traditional model was 1.9910. (4) From the model and data, the accuracy of the improved model has been improved. It can better reflect the income of taxi drivers.
Challenging Question that my Audience Cannot Answer

In this brief article, I present the surprising, symmetry-breaking behavior of a homogeneous log of maple wood. The log is of square cross-section, and is placed to float in a tank of water. The straight symmetric floating state turns out to be unstable, and it immediately lolls over to an unexpected angle. This could explain why, when I was a young kid, my carefully made boats often did not float upright.