Reviewerly/exHarmony huggingface dataset:
Side-Channel Analysis Against SecOC-Compliant AES-CMAC

This study presents a side-channel analysis (SCA) attack for AES-CMAC, which is used in the controller area network (CAN) protocol for in-vehicle networks. It is difficult to apply conventional SCAs that focus on a single round of Sboxes in the AES-CMAC, as is the case in the AES-CMAC/CTR because the AES input values are unknown to the attacker owing to its structure. The proposed method focuses on the Sboxes of the first three rounds of AES continuously and obtains the secret key by sequentially estimating the intermediate values using a first-order SCA. Our method can be applied to all versions of the Secure Onboard Communication (SecOC) standard for securing CAN protocols. We apply a deep-learning-based SCA to implement the proposed attack, in addition to conventional correlation power analysis. We demonstrate the effectiveness of the attack through an experiment using AES-CMAC software that is implemented on the PASTA automotive security evaluation platform, which is compliant with the SecOC standard that is defined in the AUTomotive Open System ARchitecture. The results show that the proposed attack can successfully reveal the secret key of AES-CMAC with at most 400,000 and 150 measurements using conventional non-profiling SCA and deep-learning-based SCA, respectively.
Beyond Shannon Limits: Quantum Communications Through Quantum Paths

A crucial step towards the 6th generation (6G) of networks would be a shift in communication paradigm beyond the limits of Shannon's theory. In both classical and quantum Shannon's information theory, communication channels are generally assumed to combine through classical trajectories, so that the associated network path traversed by the information carrier is well-defined. Counter-intuitively, quantum mechanics enables a quantum information carrier to propagate through a quantum path, i.e., through a path such that the causal order of the constituting communications channels becomes indefinite. Quantum paths exhibit astonishing features, such as providing non-null capacity even when no information can be sent through any classical path. In this paper, we study the quantum capacity achievable via a quantum path and establish upper and the lower bounds for it. Our findings reveal the substantial advantage achievable with a quantum path over any classical placements of communications channels in terms of ultimate achievable communication rates. Furthermore, we identify the region where a quantum path incontrovertibly outperforms the amount of transmissible information beyond the limits of conventional quantum Shannon's theory, and we quantify this advantage over classical paths through a conservative estimate.
Target recognition and tracking system based on UAV platform

Abstract Machine learning can extract the features of the target from the known image dataset and detect the target quickly by using the trained deep neural network. Due to UAVs’ fast flight speed and long detection distance, real-time and accurate target detection requirements are relatively high. For such scenarios,a ground object recognition and tracking method that integrates the YOLOv5 target detection algorithm and KCF target tracking algorithm are proposed. The combination of the two algorithms can meet the requirements of recognition speed, recognition rate, and tracking accuracy in the current scene. Two algorithms are run simultaneously in the recognition process, the detection frame with the highest confidence is selected as the final detection result, and the detected target is tracked by the KCF target tracking algorithm based on correlation filtering. The experimental results show that this method not only meets the requirements of recognition distance, recognition accuracy, and recognition speed of ground target but also can track a ground target in real-time, with strong robustness and real-time performance.
Motion measurement of the hand during playing tremolo on mandolin using an inertial sensor (Difference between tremolo by the wrist and by the elbow)

Tremolo is a technique to produce the same note continuously in short spans, and is an important technique for musical performance on a mandolin. However, it is not easy for beginners to master this technique, nor is it easy for even expert players to perform a wide range of expressions. There is no unified view on the proper behavior of tremolo playing, and there are no examples of measured tremolo behavior. In this study, we measured the hand movements during tremolo playing on a mandolin. One test subject was included in this study. An inertial sensor was attached to the back of the hand, and the movement was evaluated by the angles which were the time integrated angular velocity on each axis. Tremolo playing is a combination of elbow and wrist motion. We examined how those motions were used for playing strong/weak tones or fast/slow tremolos. The results showed that there was a clear difference in motion between tremolo using the wrist and tremolo using the elbow. The results also suggested that the combination of each joint motion was changed when adjusting the volume and tremolo speed. It indicated that the measurement of hand movements by inertial sensors could be used to evaluate tremolo playing. Our future plan includes a more detailed analysis of the relationship between musical expression and tremolo movement, and an examination of how movement changes with practice.
Russian education in the historical and sociological perspective. (Review of the monograph: Andreev A. L. Russian education in the pushkin era: system, institutional structure, socio-cultural environments. Moscow: Izdatel`stvo ME`I; 2022, 452 p.)

The article discusses the main provisions of the monograph by A. L. Andreev “Russian education in the Pushkin era: system, institutional structure, socio-cultural environments”. The monograph of A. L. Andreev attracts attention by the fact that the development of education in Russia in the first half of the 19th century is shown from the perspective of a historical and sociological approach, that allows to reveal the deep patterns of development of the sociocultural and intellectual environment, to demonstrate the connection between the cultural environment of Russian society in the first half of the 19th century with the development of educational practices and institutions. The author, using extensive historical material, demonstrates the role of education as a key factor in social and cultural dynamics. The review analyses the main topics of the monograph. Particular attention is paid to the influence of education on such qualitative characteristics of society as “spiritual atmosphere”, “creative environment”, “new intellectual environment”. The formation of the institutional basis of education is traced. The reviewer pays special attention to the formation of a new for that time ideology of education, when education was given the character of a state project that required systematic state decisions. Following the author, the reviewer reflects on the unique nature of the emerging university system, on Russia’s contribution to world achievements in the theory and practice of education. The scientific potential of the monograph under review lies in the fact that the author gives a deep sociological analysis of the changes in the Russian society of that era: the development of new social practices, social institutions, the emergence of civil society, the formation of new sociocultural and intellectual environments.
The Algorithm of Multiple Obstacle Avoidance Tasks for Dual-Arm Robots

To achieve multiple obstacle avoidance tasks consisting of zero-space obstacle avoidance and terminal obstacle avoidance with self-avoidance permission, we propose an algorithm for multiple obstacle avoidance tasks for dual-arm robots. First, we design a self-obstacle avoidance gradient optimization function to implement the self-obstacle avoidance task between the two arms of dual-arm robots by using the pseudo-distance as the basis for the collision judgment. Second, the terminal obstacle avoidance task for dual-arm robots is implemented by applying an adaptive terminal obstacle avoidance velocity. Third, a zero-space obstacle avoidance task for dual-arm robots is realized using an adaptive virtual repulsion force. Finally, a dual-arm robot consisting of two 6-DOF Jaco2 manipulators is simulated in a Matlab environment to verify the obstacle avoidance algorithm of dual-arm robots. The simulation results show that the algorithm proposed in this paper can complete the multi-obstacle avoidance tasks of terminal obstacle avoidance and zero-space obstacle avoidance simultaneously with the premise of realizing the self-obstacle avoidance of dual-arm robots, and has a minor terminal trajectory error, which proves that the algorithm is in the feasibility of completing terminal obstacle avoidance and zero-space obstacle avoidance with the premise of realizing dual-arm robots self-obstacle avoidance.
Use of social media in academic library

Social media is the finest method for reaching library patrons since it allows them to easily share and receive information. Social media has a significant influence on libraries as well. Social media is becoming more recognizable to LIS workers as a flexible platform to contact potential library users.
A Ranking Model for Evaluation of Conversation Partners Based on Rapport Levels

Our proposed ranking model ranks conversation partners based on self-reported rapport levels for each participant. The model is important for tasks that recommend interaction partners based on user rapport built in past interactions, such as matchmaking between a student and a teacher in one-to-one online language classes. To rank conversation partners, we can use a regression model that predicts rapport ratings. It is, however, challenging to learn the mapping from the participants’ behavior to their associated rapport ratings because a subjective scale for rapport ratings may vary across different participants. Hence, we propose a ranking model trained via preference learning (PL). The model avoids the subjective scale bias because the model is trained to predict ordinal relations between two conversation partners based on rapport ratings reported by the same participant. The input of the model is multimodal (acoustic and linguistic) features extracted from two participants’ behaviors in an interaction. Since there is no publicly available dataset for validating the ranking model, we created a new dataset composed of online dyadic (person-to-person) interactions between a participant and several different conversation partners. We compare the ranking model trained via preference learning with the regression model by using evaluation metrics for the ranking. The experimental results show that preference learning is a more suitable approach for ranking conversation partners. Furthermore, we investigate the effect of each modality and the different stages of rapport development on the ranking performance.
Professional self-presentation of research and teaching staff on social network sites

. In the modern labour sphere, the image of an employee in the virtual space has a tangible value, becoming a significant social resource in employment and subsequent career advancement. The degree of demand for a personal brand in the online environment is associated with the characteristics of specific professions. For scientific and pedagogical workers, self-presentation in virtual social networks is significant not only for their career growth, development of social capital and personal brand, but also valuable as a factor in scientific communication. A competent professional self-presentation in the virtual space helps to form a favourable social image that enhances the prestige of a university teacher and scientist. During the pandemic and the transition of educational and research activities to the online space caused by it, the demand for professional self-presentation of educators in the virtual environment has increased significantly. The article analyses the practices of professional self-presentation of scientific and pedagogical workers in virtual social networks. A typology of strategies for using universal social networks (VKontakte, etc.) and professional (scientific) social networks (Research Gate, Academia Edu, Mendeley) is presented. Particular research interest is focused on the practices of communication and professional self-presentation through virtual social networks. The advantages and limitations of the use of online communication by teachers are identified, as well as the types of priority results that users achieve or would like to achieve. For the empirical basis of the analysis the authors used the data of a survey conducted by the method of semi-structured interviews by a research team with the participation of the author of the article of 120 scientific and pedagogical employees of six Russian universities included in the implementation of the 5–100 project. Based on the results of the study, a classification of higher education teachers was formed depending on their awareness and the desire to broadcast content in virtual social networks: experts and opinion leaders, conservatives, spammers, passive, absent. A typology of the strategy of professional self-presentation of scientific and pedagogical workers in virtual social networks has been created: voluntary, forced, non-priority professional self-presentation; refusal of self-presentation (external or internal).
Reverse Self-Distillation Overcoming the Self-Distillation Barrier

Deep neural networks generally cannot gather more helpful information with limited data in image classification, resulting in poor performance. Self-distillation, as a novel knowledge distillation technique, integrates the roles of teacher and student into a single network to solve this problem. A better understanding of the efficiency of self-distillation is critical to its advancement. In this paper, we provide a new perspective: the effectiveness of self-distillation comes not only from distillation but also from the supervisory information provided by the shallow networks. At the same time, we find a barrier that limits the effectiveness of self-distillation. Based on this, reverse self-distillation is proposed. In contrast to self-distillation, the internal knowledge flow is in the opposite direction. Experimental results show that reverse self-distillation can break the barrier of self-distillation and further improve the accuracy of networks. On average, 2.8% and 3.2% accuracy boosts are observed on CIFAR100 and TinyImageNet.
Sign Language Translator

The deaf community in India relies heavily on the Sign Language (SL) as a means of communication. But because so few people are fluent in SL, there is a communication gap between the hearing and deaf communities. The Sign Language Translator (SLT) in this paper employs MediaPipe and LSTM to convert Sign Language (SL) to text and back again. The suggested approach first uses MediaPipe to extract hand movements and facial emotions from movies of SL signals. The LSTM model, which is trained using a sizable dataset of SL signs and their related text labels, is then fed these characteristics. The input feature sequence is processed by the LSTM model, which also creates the matching text labels. A dataset of SL signs and the text labels that go with them was gathered in order to train and test the proposed system. The outcomes demonstrate that the suggested approach performs extremely well when converting SL signs to text and vice versa. The system is useful for usage in real-life scenarios since it can recognise and translate many indications in succession. Overall, a bridge between the hearing and deaf communities in India can be created by the proposed Sign Language Translator system, enabling seamless inclusion and communication. By allowing them to interact with the hearing world more effectively, it has the potential to greatly raise the quality of life for the deaf people in India.
Quantum process tomography of unitary maps from time-delayed measurements

Abstract Quantum process tomography conventionally uses a multitude of initial quantum states and then performs state tomography on the process output. Here we propose and study an alternative approach which requires only a single (or few) known initial states together with time-delayed measurements for reconstructing the unitary map and corresponding Hamiltonian of the time dynamics. The overarching mathematical framework and feasibility guarantee of our method is provided by the Takens embedding theorem. We explain in detail how the reconstruction of a single-qubit Hamiltonian works in this setting and provide numerical methods and experiments for general few-qubit and lattice systems with local interactions. In particular, the method allows to find the Hamiltonian of a two qubit system by observing only one of the qubits.
Anonymous Broadcast Authentication With One-to-Many Transmission to Control IoT Devices

We consider a basic system to securely and remotely control many IoT devices. Specifically, we require that: 1) a system manager broadcasts information to IoT devices, e.g., wireless environment, only the designated devices can identify operations sent from the manager; 2) each IoT device can detect (malicious) manipulation of the broadcast information and hence prevents maliciously generated operations from being executed. In this paper, we introduce <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">anonymous broadcast authentication</i> (ABA) as a core cryptographic primitive of the basic remote-control system. Specifically, we formally define the syntax and security notions for ABA so that it achieves the above requirements. We then show provably-secure ABA constructions and their implementations to provide their practical performance. Our promising results show that the ABA constructions can remotely control devices over a typical wireless network within a second.
HPX filter: a hybrid of Hodrick–Prescott filter and multiple regression

Abstract This paper considers an extension of Hodrick–Prescott (HP) filter. It is a hybrid of HP filter and multiple regression. We refer to the filter as “HPX filter”. It is well known that HP filter has a unique global minimizer and the solution can be represented in matrix notation explicitly. Does HPX filter also have a unique global minimizer? Is it accomplished without any additional assumptions? Can the solution be expressed in matrix notation explicitly? In this paper, we answer these questions. In addition, this paper (i) provides an alternative perspective on the filter by representing it as a generalized ridge regression and (ii) gives an extension of it, which is a hybrid of Whittaker–Henderson method of graduation and multiple regression.
Challenges with internal photons in constructive QED

We find the correct spinor amplitude for a simple photon-mediated process and show that, in contrast, the result for the same process using the standard constructive techniques do not agree with Feynman diagrams when the fermions are massive. Along the way, we analyze the x factor used in photon vertices, we work out the spinor shifts for massive particles when the momenta are analytically continued and we consider the large z limit of the amplitudes in this paper and show that the photon-mediated process does not vanish in this limit for any choice of two of its momenta. For comparison with the photon-mediated process, we also describe two processes with external photons that are mediated by massive particles. In both cases, we show that the current techniques are sufficient and that the final results agree with Feynman diagrams. We also demonstrate that by using a massive photon in our calculations and taking the massless limit at the end, we can achieve agreement with Feynman diagrams in all the processes discussed here, including the photon-mediated amplitudes.
False-Bottom Encryption: Deniable Encryption From Secret Sharing

We show how to implement a deniable encryption method from secret sharing. Unlike the related concept of honey encryption, which employs a preprocessing step in symmetric encryption to re-shape the distribution of a plaintext towards making the real plaintext indistinguishable from a ciphertext for a fake message, we can avoid both, computational intractability assumptions and preprocessing of the data. This accomplishes deniability against an attacker that can force decryptions, and it can brute-force break a ciphertext with sufficient computational power. Following the concept of plausible deniability, we herein have different decryption keys to open up distinct plaintexts from within the same ciphertext. For instance, a plaintext revealed from a ciphertext with a key which was shared by a victim under duress, will convince the attacker that it is real, while the actual secret remains unnoticed. False Bottom Encryption constructs a symmetric scheme (in the sense of using the same key to encrypt and decrypt) that shares the properties of both honey encryption and deniable encryption. We specifically formalize and differentiate “deniable” from “plausibly deniable” as a security feature, showing how plausible deniability falls back to (only) deniability, depending on the plaintext distribution. Our scheme is simple, lightweight to implement and efficient in terms of encryption and decryption, and is based on secret sharing. As such, we do not rely on computational intractability. We corroborate the construction by giving numeric examples and providing implementations of the method as a Jupyter notebook supplementary to this work.
A Control Framework for a Secure Internet of Things within Small-, Medium-, and Micro-Sized Enterprises in a Developing Economy

Small and medium enterprises (SMEs) play a critical role in the economic growth of a nation, and their significance is increasingly acknowledged. More than 90% of commercial establishments, almost 70f% of jobs, and 55% of the GDP are held by SMEs in mature economies. Additionally, this sector accounts for 70% of employment possibilities and up to 40% of the GDP in developing countries. Technologically, the Internet of Things (IoT) enables multiple connected devices, i.e., “things”, to add value to businesses, as they can communicate and send messages or signals promptly. In this article, we investigate various challenges SMEs experience in IoT adoption to further their businesses. Amongst others, the challenges elicited include IoT considerations for SMEs, data, financial availability, and challenges related to the SME environment. Having analysed the challenges, a three-tiered solution framework coined the Secure IoT Control Framework (SIoTCF) to address the said challenges is developed and briefly validated through a theoretical analysis of the elements of the framework. It is hoped that the proposed framework will assist with aspects of design, governance, and maintenance in enhancing the security levels of IoT adoption and usage in SMEs, especially start-ups or less experienced SMEs. Future work in this area will involve surveying SME owners and ICT staff to validate the utility of the SIoTCF further. The study adds to the body of knowledge in general by developing a secure IoT control framework. In the field of ICT, this paradigm is expected to be useful for academics, researchers, and students.