Reviewerly/exHarmony huggingface dataset:
Sonifying Gait Kinematics Using the Sound of Wading: A Study on Ecological Movement Representations

Interactive sonification of human movement can enhance motor learning by introducing an additional sensory feedback channel during rehabilitation. Successful past work on sonifying human walking has focused primarily on providing users with feedback on the stance (ground contact) phase of the gait cycle, whilst the equally important swing phase has been largely neglected. In this work, we developed and assessed a swing phase sonification algorithm that generates ecological feedback on limb swing in the form of wading sounds at two different depths. We evaluated the perceptual qualities of the algorithm output in a test with 16 respondents, as well as the user experience of 9 healthy participants in a real-life walking pilot test. Despite our simple approach of simulating wading acoustics using gyroscope-modulated liquid sounds, our results suggested that the simulation sounded perceptually natural, unintrusive during walking, and responded well to limb swing in real-time. Future work includes further improvements to the algorithm followed by rigorous user tests with both healthy and impaired individuals. We believe that this research can contribute to the development of meaningful auditory feedback schemes targeting limb swing.
DESAIN SKENARIO PEMUNCULAN TINGKAT KESULITAN SOAL PADA GAME MATEMATIKA MENGGUNAKAN APLIKASI RULE-BASED SYSTEM (RBS)

In playing games a student (player) sometimes forgets the time, even sacrifices learning time to play the game. That thinking is what underlies this research, that learning while playing is expected to be a solution to increase students' interest in learning. To adjust the scenario to the player's ability, a scenario with varying difficulty levels is prepared. The scenario referred to here is the emergence of problems, so there are also problems with three levels of difficulty, namely easy questions, medium problems, and difficult questions. To determine the center of the cluster, if the difficulty level of the problem is between 0.71 - 1.00 then the problem can be said to be an easy matter, and the range of 0.71 - 1.00 can also be called the easy cluster range, while the cluster center is 0.86, if the difficulty level of the problem is between 0.31 - 0.70 then including the medium problem, and the range of 0.31 - 0.70 can also be called the medium cluster range, while the center of the cluster is 0.50, and if the difficulty level of the problem is between 0.00 - 0.30 then the problem can be said to be a difficult problem, and the range of 0.00 - 0.30 can also be called the difficult cluster range, while the cluster center is 0.15. The Rule-Based System will be used to form rules to direct players to scenarios that match the player's own abilities.
Relational Solver for Java Generics Type System

We present a solver for Java generics type system implemented using relational verifier-to-solver approach. The solver finds solutions for a system of subtyping inequations with free variables and thus can be used to determine a concrete type satisfying a set of constraints. The context of this work is symbolic execution for testing and verification of Java programs.
Regularized Maximum Correntropy Criterion Kalman Filter for Uncalibrated Visual Servoing in the Presence of Non-Gaussian Feature Tracking Noise

Some advantages of using cameras as sensor devices on feedback systems are the flexibility of the data it represents, the possibility to extract real-time information, and the fact that it does not require contact to operate. However, in unstructured scenarios, Image-Based Visual Servoing (IBVS) robot tasks are challenging. Camera calibration and robot kinematics can approximate a jacobian that maps the image features space to the robot actuation space, but they can become error-prone or require online changes. Uncalibrated visual servoing (UVS) aims at executing visual servoing tasks without previous camera calibration or through camera model uncertainties. One way to accomplish that is through jacobian identification using environment information in an estimator, such as the Kalman filter. The Kalman filter is optimal with Gaussian noise, but unstructured environments may present target occlusion, reflection, and other characteristics that confuse feature extraction algorithms, generating outliers. This work proposes RMCKF, a correntropy-induced estimator based on the Kalman Filter and the Maximum Correntropy Criterion that can handle non-Gaussian feature extraction noise. Unlike other approaches, we designed RMCKF for particularities in UVS, to deal with independent features, the IBVS control action, and simulated annealing. We designed Monte Carlo experiments to test RMCKF with non-Gaussian Kalman Filter-based techniques. The results showed that the proposed technique could outperform its relatives, especially in impulsive noise scenarios and various starting configurations.
Breast Imaging Physics in Mammography (Part I)

Breast cancer is the most frequently diagnosed neoplasm in women in Italy. There are several risk factors, but thanks to screening and increased awareness, most breast cancers are diagnosed at an early stage when surgical treatment can most often be conservative and the adopted therapy is more effective. Regular screening is essential but advanced technology is needed to achieve quality diagnoses. Mammography is the gold standard for early detection of breast cancer. It is a specialized technique for detecting breast cancer and, thus, distinguishing normal tissue from cancerous breast tissue. Mammography techniques are based on physical principles: through the proper use of X-rays, the structures of different tissues can be observed. This first part of the paper attempts to explain the physical principles used in mammography. In particular, we will see how a mammogram is composed and what physical principles are used to obtain diagnostic images.
Creation of temporary research teams to improve the quality of specialist training

Improving the quality of specialist training is one of the priorities of any higher education institution. According to the authors of the article, this problem can be solved by the cooperation of all parties involved in the educational process, both within the university and in cooperation with companies, which are the future employers of university graduates. The article is devoted to the study of project initiatives using the mechanism of organizing temporary research teams for the implementation of commercial contracts, with the involvement of trainees for their implementation. On the one hand, this study allowed the authors to identify the basic mechanisms of motivation of all the participants in the areas studied. On the other hand, this study allowed them to develop models for the involvement of industrial partners, their specialists, educational units, teachers and students in the implementation of commercial projects and works that improve the level of training of bachelors, masters, specialists and postgraduates.
Hierarchical Area-Based and Path-Based Heuristic Approaches for Multirobot Coverage Path Planning with Performance Analysis in Surveillance Systems

In this study, we present a systematic exploration of hierarchical designs for multirobot coverage path planning (MCPP) with a special focus on surveillance applications. Unlike conventional studies centered on cleaning tasks, our investigation delves into the realm of surveillance problems, specifically incorporating the sensing range (SR) factor equipped on the robots. Conventional path-based MCPP strategies considering SR, primarily rely on naive approaches, generating nodes (viewpoints) to be visited and a global path based on these nodes. Therefore, our study proposes a general MCPP framework for surveillance by dealing with path-based and area-based structures comprehensively. As the traveling salesman problem (TSP) solvers, our approach incorporates not the naive approach but renowned and powerful algorithms such as genetic algorithms (GAs), and ant colony optimization (ACO) to enhance the planning process. We devise six distinct methods within the proposed MCPP framework. Two methods adopt area-based approaches which segments areas via a hierarchical max-flow routing algorithm based on SR and the number of robots. TSP challenges within each area are tackled using a GA or ACO, and the result paths are allocated to individual robots. The remaining four methods are categorized by the path-based approaches with global–local structures such as GA-GA, GA-ACO, ACO-GA, and ACO-ACO. Unlike conventional methods which requires a global path, we further incorporate ACO- or GA-based local planning. This supplementary step at the local level enhances the quality of the path-planning results, particularly when dealing with a large number of nodes, by preventing any degradation in global path-planning outcomes. An extensive comparative analysis is conducted to evaluate the proposed framework based on execution time, total path length, and idle time. The area-based approaches tend to show a better execution time and overall path length performance compared to the path-based approaches. However, the path-based MCPP methods have the advantage of having a smaller idle time than the area-based MCPP methods. Our study finds that the proposed area-based MCPP method excels in path planning, while the proposed path-based MCPP method demonstrates superior coverage balance performance. By selecting an appropriate MCPP structure based on the specific application requirements, leveraging the strengths of both methodologies, efficient MCPP execution becomes attainable. Looking forward, our future work will focus on tailoring these MCPP structures to diverse real-world conditions, aiming to propose the most suitable approach for specific applications.
“We aim to provide quantum‐centric supercomputing”

Abstract In the southwest of the Stuttgart region in the state of Baden‐Wuerttemberg, the Quantum Village Ehningen has grown a lot over the past two years – this will continue in the future, with the development of completely new potential for industry, science, and society. On April 18, 2023, the Quantum AI Experience &amp; Innovation Center “Q.AX” opened its doors during a ceremony at the former IBM site in Ehningen, attended by minister‐president Winfried Kretschmann.
4SQR-Code: A 4-States QR Code Generation Model for Increasing Data Storing Capacity in the DT Framework

The usage of Quick Response (QR) Codes has become widely popular in recent years, primarily for immense electronic transactions and industry uses. The structural flexibility of QR Code architecture opens many more possibilities for researchers in the domain of the Industrial Internet of Things (IIoT). However, the limited storage capacity of the traditional QR Codes still fails to stretch the data capacity limits. The researchers of this domain have already introduced different kinds of techniques, including data hiding, multiplexing, data compression, color QR Codes, and so on. However, the research on increasing the data storage capacity of the QR Codes is very limited and still operational. The main objective of this work is to increase the data storage capacity of QR Codes in the IIoT domain. In the first part, we have introduced a 4-States pattern-based encoding technique to generate the proposed 4-States QR (4SQR) Code where actual data are encoded into a 4SQR Code image which increases the data storage capacity more than the traditional 2-States QR Code. The proposed 4SQR Code consists of four types of patterns, including Black Square Box (BSB), White Square Box (WSB), Triangle, and Circle, whereas the traditional 2-States QR Codes consist of BSB and WSB. In the second part, the 4SQR Code decoding module has been introduced using the adaptive YOLO V5 algorithm where the proposed 4SQR Code image is decoded into the actual data. The proposed model is tested in a Digital Twin (DT) framework using randomly generated 3000 testing samples for the encoding module that converts into 4SQR Code images successfully and similarly for the decoding module that decodes the 4SQR Code images into the actual data. Experimental results show that this proposed technique offers increased data storage capacity two times than traditional 2-States QR Codes.
The European Commission's approach to extra-contractual liability and AI – An evaluation of the AI liability directive and the revised product liability directive

The European Commission published two proposals that aim to adapt (tort) liability rules to the digital age, the circular economy and the impact of the global value chain. The ‘AI Liability Directive’ contains rules on the disclosure of information and the alleviation of the burden of proof in relation to damage caused by AI systems. The ‘revised Product Liability Directive’ substantially modifies the current product liability regime by broadening the scope, integrating new circumstances to assess the product's defectiveness and introducing provisions regarding presumptions of defectiveness and causation. In this article, we evaluate how both proposals provide some answers to major technological developments – in particular AI – in view of the issues they raise as identified in the legal literature. To do so, we also provide a clear understanding of the major provisions in both proposals, supported by visuals. Although we welcome both proposals for several reasons outlined in the article, different unclarities and inconsistencies need to be resolved. These inter alia relate to the unclarity of terms, the position of claimants, the uncertain interaction with other supranational initiatives and the many interpretation issues with regard to the fault-based liability regime. A more fundamental objection relates to the choice of the revised Product Liability Directive to capture all liability issues with AI systems, which comes at the cost of losing the connection to ‘product’ as a grounding concept. Our findings can be used by policymakers in further adapting and refining both proposals to the digital reality.
Controlled quantum teleportation with the ability to change the destination of qubits

Quantum sciences and technologies introduce a new arena whose applications are widely used in the microscopic world. Quantum communication is also an important branch of quantum science by which we intend to transmit quantum information. Quantum teleportation is important because it uses the entanglement principle which is unique in quantum space to transmit quantum information. In fact, in this type of protocol, no information is sent and everything is transmitted using the miracle of entanglement. In this paper, an attempt is made to present a quantum teleportation scheme that, unlike the other designs, can change the destination of qubits. This means that at the beginning of the protocol, the receivers have no idea who has sent the qubits, and the controller decides how these communications will work. At last, noise analysis is presented.
Kinematic target surface sensing based on improved deep optical flow tracking

Reconstruction of moving target surfaces based on active image sensing techniques, such as phase-shifting profilometry, has attracted intensive research in recent years. The measurement error caused by object motion can be addressed successfully by tracking the object movement. However, it either requires high-cost color imaging equipment or is limited by the assumption of 2D translation movement. Therefore, this paper proposes what we believe to be a new method to reconstruct the kinematic object surfaces with any 2D movement sensed by affordable monochrome camera. An improved RAFT optical flow algorithm is proposed to track the object based on the object fringe pattern image directly. The feature points on the object are retrieved immune to the fringe pattern illumination. Then, the RANSAC algorithm and an iteration selection process are employed to select feature points with high quality optical flow. At last, the motion is described mathematically, and the dynamic object is reconstructed successfully. Experiments are presented to verify the effectiveness of the proposed method.
Geochemical Mobility Associated to Gold and Base Metal Occurrences of Mangodara Sector, in Southern Burkina Faso, Banfora Greenstone Belts (West African Craton)

In the Mangodara area within the Banfora greenstone belts (Baoulé-Mossi domain of the West African Craton), our study focused on geochemical assessment of the mobility of major and trace elements. Gold and base metal occurrences are hosted in highly metamorphic felsic (metarhyolite) and intermediate (metadacite and metaandesite) formations. Common mineral assemblages made up of staurolite - kyanite - pyrophyllite are interpreted to represent the metamorphosed equivalent of aluminous hydrothermal alteration. Associated felsic and intermediate volcanic rocks are enriched in Fe2O3, K2O (metaandesite, metarhyolite) and depleted in MgO, Al2O3, CaO, P2O5, Na2O (metarhyolite) and Fe2O3, MgO, CaO (metaandesite). Al2O3 depletion in mineralized kyanite-staurotide bearing metarhyolites suggests corroded minerals. Mineralized metarhyolites show enrichment in Au, Ag, Ba, Bi, Cr, Cu, Eu, La, Mo, Ni, Pb, S, Sc, V and depletion in As Sb Co, Sn, Zn while mineralized metaandesites show enrichment in Au, Ag, As, Mo, S, Sb and depletion in Co, Sn, Zn, Bi, Cr, Cu, Eu, Ni, Pb, Sc. Ba, La, V are immobile in metaandesites. Finally, Ag, As, Sn appear as geochemical vectors for gold exploration in the study area since gold mineralization is characterized by Au + Ba + Cu + Eu + La + Mo + Ni + S association in metarhyolites and Au + S + Sb + As + Ag + Bi in metaandesites.
Students’ Perceptions of Duolingo Mobile Assisted Language Learning (MALL) in Learning English Vocabulary

This study aimed to find out the students’ perceptions of Duolingo Mobile Assisted Language Learning (MALL) in learning English vocabulary. This study involved 32 seventh-grade students from SMPN 1 Pangkajene during the academic year 2022/2023. Descriptive quantitative was used to carry out the study. This study's data was analyzed using quantitative data from a questionnaire. The questionnaire consisted of 30 closed-ended questions. The study found that the Duolingo application positively impacted students' language learning, particularly in acquiring new vocabulary. Students are becoming more enthusiastic to learn and are practicing and using their language skills in everyday circumstances. Furthermore, after using the Duolingo app, students' vocabulary and ability to recall it rapidly improve, as do structure and pronunciation, making it easier for students to improve their English language acquisition. Students found the app easy, helpful, and enjoyable for their English language learning practice. They prefer it over traditional book-based homework due to its convenience, accessibility in various formats, especially mobile, and gamification. The application’s success is attributed to its varied prompts skill-interleaving lessons gamification aspects and diverse lesson content perceived by the students.
Denoising Vanilla Autoencoder for RGB and GS Images with Gaussian Noise

Noise suppression algorithms have been used in various tasks such as computer vision, industrial inspection, and video surveillance, among others. The robust image processing systems need to be fed with images closer to a real scene; however, sometimes, due to external factors, the data that represent the image captured are altered, which is translated into a loss of information. In this way, there are required procedures to recover data information closest to the real scene. This research project proposes a Denoising Vanilla Autoencoding (DVA) architecture by means of unsupervised neural networks for Gaussian denoising in color and grayscale images. The methodology improves other state-of-the-art architectures by means of objective numerical results. Additionally, a validation set and a high-resolution noisy image set are used, which reveal that our proposal outperforms other types of neural networks responsible for suppressing noise in images.
Securing Semantic Communications with Physical-Layer Semantic Encryption and Obfuscation

Deep learning based semantic communication (DLSC) systems have shown great potential of making wireless networks significantly more efficient by only transmitting the semantics of the data. However, the open nature of wireless channel and fragileness of neural models cause DLSC systems extremely vulnerable to various attacks. Traditional wireless physical layer key (PLK), which relies on reciprocal channel and randomness characteristics between two legitimate users, holds the promise of securing DLSC. The main challenge lies in generating secret keys in the static environment with ultra-low/zero rate. Different from prior efforts that use relays or reconfigurable intelligent surfaces (RIS) to manipulate wireless channels, this paper proposes a novel physical layer semantic encryption scheme by exploring the randomness of bilingual evaluation understudy (BLEU) scores in the field of machine translation, and additionally presents a novel semantic obfuscation mechanism to provide further physical layer protections. Specifically, 1) we calculate the BLEU scores and corresponding weights of the DLSC system. Then, we generate semantic keys (SKey) by feeding the weighted sum of the scores into a hash function. 2) Equipped with the SKey, our proposed subcarrier obfuscation is able to further secure semantic communications with a dynamic dummy data insertion mechanism. Experiments show the effectiveness of our method, especially in the static wireless environment.
Impact of Virtual Reality (Vr) and Augmented Reality (Ar) in Education

Virtual Reality (VR) and Augmented Reality (AR) technologies have emerged as powerful tools with the potential to revolutionize the field of education. This study provides an overview of the impact of VR and AR in education, drawing from existing research and analytical applications. The impact of VR in education is evident in its ability to create immersive and engaging learning experiences. Students can be transported to virtual environments that facilitate experiential learning, from exploring historical landmarks to simulating complex scientific experiments. The result is enhanced student engagement, improved retention of knowledge, and the development of practical skills. AR, on the other hand, overlays digital information onto the real world, enriching traditional educational materials. Interactive textbooks and guided field trips using AR provide students with dynamic and context-rich learning experiences. Language learners benefit from instant translations and pronunciation guides, while complex data becomes tangible through AR visualizations. Both VR and AR contribute to the promotion of collaborative learning, enabling students and educators to interact in virtual environments. These technologies offer new opportunities for special needs education, as they can be customized to cater to the unique requirements of individual learners. The adoption of VR and AR in education comes with challenges, including cost considerations, the need for suitable technical infrastructure, content development complexities, and the necessity to address safety concerns. Integrating VR and AR into the existing curriculum and ensuring alignment with educational objectives are also ongoing challenges. The study aim is to analyse the impact of VR and AR in education.