Reviewerly/exHarmony huggingface dataset:
Spring Security Architecture and Design

In Chapter 3 , you developed an initial application secured with Spring Security. You got an overview of how this application worked and looked at some of the Spring Security components put into action in common Spring Security–secured applications. This chapter extends those explanations and delve deeply into the framework.
A Practical Multiparty Private Set Intersection Protocol Based on Bloom Filters for Unbalanced Scenarios

Multiparty Private Set Intersection (MPSI) is dedicated to finding the intersection of datasets of multiple participants without disclosing any other information. Although many MPSI protocols have been presented, there are still some important practical scenarios that require in-depth consideration such as an unbalanced scenario, where the server’s dataset is much larger than the clients’ datasets, and in cases where the number of participants is large. This paper proposes a practical MPSI protocol for unbalanced scenarios. The protocol uses the Bloom filter, an efficient data structure, and the ElGamal encryption algorithm to reduce the computation of clients and the server; adopts randomization technology to solve the encryption problem of the 0s in the Bloom filter; and introduces the idea of the Shamir threshold secret-sharing scheme to adapt to multiple environments. A formal security proof and three detailed experiments are given. The results of the experiments showed that the new protocol is very suitable for unbalanced scenarios with a large number of participants, and it has a significant improvement in efficiency compared with the typical related protocol (TIFS 2022).
Congestive Heart Failure Category Classification Using Neural Networks in Short-Term Series

Congestive heart failure carries immense importance in the realm of public health. This significance arises from its substantial influence on the number of lives lost, economic burdens, the potential for prevention, and the opportunity to enhance the well-being of both individuals and the broader community through decision-making in healthcare. Several researchers have proposed neural networks for classification of different congestive heart failure categories. However, there is little information about the confidence of the prediction on short-term series. Therefore, evaluating classification models is required for effective decision-making in healthcare. This paper explores the use of three classical variants of neural networks to classify three groups of patients with congestive heart failure. The study considered the iterative method Multilayer Perceptron neural network (MLP), two non-iterative models (Extreme Learning Machine (ELM) and Random Vector Functional Link Network (RVFL)), and the CNN approach. The results showed that the deep feature learning system obtained better classification rates than MLP, ELM, and RVFL. Several scenarios designed by coupling some deep feature maps with the RVFL and MLP models showed very high simulation accuracy. The overall accuracy rate of CNN–MLP and CNN–RVFL varies between 98% and 99%.
Market-Inspired Framework for Securing Internet of Things Computing Environment

IoT security, also known as Internet of Things security, is an innovation component that focuses on protecting connected devices and systems on the Internet of Things (IoT). There are several fields which relate to the IoT framework such as computers, mechanical and computerized machines, objects, creatures, and people. Each thing has a unique identifier and the ability to transfer data across an organization. The Internet of Things organizations help to obtain a practical advantage by taking care of the hardships of consolidating wearables, sensors, associations, cloud, and applications without choosing security. Development is stressed over partner contraptions with each other to work with the correspondence between them. The devices that are related will really need to share the information that can be used as a commitment by any contraption that is dependent upon various contraptions for input. It is known as the Trap of Things, like the Internet. This development requires certifications to sort out among contraptions. Different industry-unequivocal data and IoT development expertise cover firmware improvement, transportability, conveyed registering, and data assessment, for making the market space an impressive range for end clients. The end clients receive soft assembled decisions concerning solid data assessment in IoT organizations. Nowadays, many IoT applications, computations, and organizations are utilizing services over the Internet. These are the most important applications that need security from the cyber web. If cyberattacks are going on in IoT devices, security is a must for the end users.
Using Artificial Intelligence Methods to Create a Chatbot for University Questions and Answers

A chatbot is a computer program that uses general rules and Artificial Intelligence techniques to simulate human conversation. This paper highlights the different scenarios of human-computer interaction and the journey it has gone through from evolution to evolvement to innovation to the development of the technical era. Here, the main focus is on the ways humans interact with the computer and how it has changed day-to-day life and reduced human efforts in performing everyday activities. There is an impact of HCI (Human–Computer Interaction) on people and has consequences in the form of both advantages and disadvantages of this interaction. The various innovations and machines have given birth to human–computer interaction as well as technology interaction. The main objective is to style the interface amongst men as well with Personal Computers (PCs) as usual as the interface amid beings. The user can interact in this system using text or voice. As per way as interaction is concerned direct, indirect, and strategic interaction of humans with computers and the latest gadgets is possible. Dynamic intelligence makes it like real-time communication with an individual. It can handle the user request and offer relevant information that can be used as a friend one would seek for knowledge. The proposed system is developed using the Rasa of an open-source platform. Further, the article focuses on the features and role of chatbots in an educational context. High precision in sentence analysis is attained with the aid of the proposed method up to a 91% hit ratio. The hit rate for the similarity computation is high. The system can handle a broader variety of requests as a consequence of its ability to recognize many ways to phrase the same inquiry and map them to related results.
Bitcoin: The nexus between regulation and recognition

Abstract The article analyses the current issues contributing to the volatility of Bitcoin as the reliability of this new technology diminishes, leading to increased unpredictability of its value. Legal efforts and literature regarding Bitcoin have primarily focused on protecting society from the illegal use of this digital technology, with little emphasis on integrating it as an asset. However, this article proposes that countries adopt Bitcoin-related legislation, incorporating recognition and regulation clauses to transform Bitcoin into a stable, less volatile and functional digital asset. In the context of legal history, primary legal domains, such as contracts, family, trade and others, have been integrated through recognition and regulation processes. Therefore, we argue that adopting Bitcoin-specific legislation that recognizes this new technology while comprehensively regulating the associated risks would enhance the coin's stability and reduce volatility, ultimately increasing trust among digital investors and users.
Podcast resources in academic libraries: Audio lending technology and studio recording spaces in American research libraries

This paper aims to discover the prevalence of audio lending technology in American research libraries and to determine any prevailing trends in the specific kinds of equipment used by these institutions. The researcher looked at the website of every member of the Association of Research Libraries and recorded information about audio lending technology in five categories: podcasting kits, USB microphones, other microphones, digital voice recorders, and audio interfaces. Information about a podcast recording studio, both in the library and on the greater institution’s campus was also recorded. The results indicate a majority of American research libraries offer a recording space and lendable audio technologies. Digital voice recorders, USB microphones, and non-USB microphones are the most common types of equipment offered.
Un repertorio di siti e risorse online per l’apprendimento/insegnamento del russo

Starting from the assumption of the added value of using information technology in language teaching, this work presents a vast inventory of sites and online resources for learning/teaching Russian. The resources have been divided into different sections according to the skills (phonetic, phonological, lexical, morphosyntactic, textual) that are intended to be practised and developed. In addition, a section is specifically dedicated to various tools, useful for inserting the graphic accent, for nominal and verbal inflection and for checking the declension of anthroponyms, toponyms and numerals, aspects that usually present difficulties for learners. The aim of the description and analysis of the resources is to put the user, teacher or learner, in a position in which they consciously and safely choose supports that are functional to the teaching objectives. Selected sites, resources and tools are aimed at learners of different levels of language proficiency, from absolute beginners to advanced learners.
Developing Constrained Interval Operators for Fuzzy Logic with Interval Values

A well-known problem in the interval analysis literature is the overestimation and loss of information. In this article, we define new interval operators, called constrained interval operators, that preserve information and mitigate overestimation. These operators are investigated in terms of correction, algebraic properties, and orders. It is shown that a large part of the properties studied is preserved by this operator, while others remain preserved with the condition of continuity, as is the case of the exchange principle. In addition, a comparative study is carried out between this operator g¨ and the best interval representation: g^. Although g¨⊆g^ and g¨ do not preserve the Moore correction, we do not have a loss of relevant information since everything that is lost is irrelevant, mitigating the overestimation.
A theory of factors affecting continuous experimentation (FACE)

Abstract Context Continuous experimentation (CE) is used by many companies with internet-facing products to improve their business models and software solutions based on user data. Some companies deliberately adopt a systematic experiment-driven approach to software development while some companies use CE in a more ad-hoc fashion. Objective The goal of this study is to identify factors for success in CE that explain the variations in the utility and efficacy of CE between different companies. Method We conducted a multi-case study of 12 companies involved with CE and performed 27 interviews with practitioners at these companies. Based on that empirical data, we then built a theory of factors at play in CE. Results We introduce a theory of Factors Affecting Continuous Experimentation (FACE). The theory includes three factors, namely 1) processes and infrastructure for CE, 2) the user problem complexity of the product offering, and 3) incentive structures for CE. The theory explains how these factors affect the effectiveness of CE and its ability to achieve problem-solution and product-market fit. Conclusions Our theory may inspire practitioners to assess an organisation’s potential for adopting CE and to identify factors that pose challenges in gaining value from CE practices. Our results also provide a basis for defining practitioner guidelines and a starting point for further research on how contextual factors affect CE and how these may be mitigated.
Single-Image Simultaneous Destriping and Denoising: Double Low-Rank Property

When a remote sensing camera work in push-broom mode, the obtained image usually contains significant stripe noise and random noise due to differences in detector response and environmental factors. Traditional approaches typically treat them as two independent problems and process the image sequentially, which not only increases the risk of information loss and structural damage, but also faces the situation of noise mutual influence. To overcome the drawbacks of traditional methods, this paper leverages the double low-rank characteristics in the underlying prior of degraded images and presents a novel approach for addressing both destriping and denoising tasks simultaneously. We utilize the commonality that both can be treated as inverse problems and place them in the same optimization framework, while designing an alternating direction method of multipliers (ADMM) strategy for solving them, achieving the synchronous removal of both stripe noise and random noise. Compared with traditional approaches, synchronous denoising technology can more accurately evaluate the distribution characteristics of noise, better utilize the original information of the image, and achieve better destriping and denoising results. To assess the efficacy of the proposed algorithm, extensive simulations and experiments were conducted in this paper. The results show that compared with state-of-the-art algorithms, the proposed method can more effectively suppress random noise, achieve better synchronous denoising results, and it exhibits a stronger robustness.
Permissibility vs. Feasibility: AI in service from a CX perspective

Purpose This paper aims to provide researchers and practitioners with a consumer-focused alternative for considering the integration of artificial intelligence (AI) into services. Design/methodology/approach The paper reviews and critiques the most popular frameworks for addressing AI in service. It offers an alternative approach, one grounded in social psychology and leveraging influential concepts from management and human–computer interaction. Findings The frameworks that dominate discourse on this topic (e.g. Huang and Rust, 2018) are fixated on assessing technology-determined feasibility rather than consumer-granted permissibility (CGP). Proposed is an alternative framework consisting of three barriers to CGP (experiential, motivational and definitional) and three responses (communicate, motivate and recreate). Research limitations/implications The implication of this research is that consistent with most modern marketing thought, researchers and practitioners should approach service design from the perspective of customer experience, and that the exercise of classifying service occupation tasks in terms of questionably conceived AI intelligences should be avoided. Originality/value Indicative of originality, this paper offers an approach to considering AI in services that is nearly the polar opposite of that widely advocated by e.g., Huang et al., (2019); Huang and Rust (2018, 2021a, 2021b, 2022b). Indicative of value is that their highly cited paradigm is optimized for predicting the rate at which AI will take over service tasks/occupations, a niche topic compared to the mainstream challenge of integrating AI into service offerings.
The Position of Foreign Investment in the Indonesian Economic System Based on Pancasila and the 1945 Constitution of the Republic of Indonesia

Objective: This research aims to find arguments (theories) to ensure that foreign direct investment does not conflict with but is in accordance with the values of Pancasila and the provisions of the 1945 Constitution of the Republic of Indonesia. Conceptual foundation: Each country in the world cannot isolate itself but must establish relationships and work together to achieve the good of those countries. Robert Jackson and Georg Sorensen said that each other's countries are independent and have sovereignty. But they are not estranged from each other. They are adjacent to and influence each other and side by side and opposite each other. Therefore, complete separation of one country from another is not an option. A country that is isolated and disconnected from other countries will usually suffer. Method: This research is normative juridical using conceptual, statutory, and historical approaches. The legal materials used are primary legal materials and secondary legal materials, which are collected systematically according to the issues of concern in this research and the collection technique uses literature study, then the problems are analyzed qualitatively. Result and conclusion: Foreign direct investment has a position as part and complement of the Indonesian economic system because its existence is in accordance with the values contained in Pancasila and the 1945 Constitution of the Republic of Indonesia. Contribution: The results of this research convince and invite the Indonesian people that the presence of foreign direct investment in the Indonesian economic system no longer needs to be debated, but accept foreign direct investment as a complement and encourage growth and realize the welfare of the Indonesian people in accordance with the Preamble to the Constitution of the Republic of Indonesia.
Optimizing Hardware Resource Utilization for Accelerating the NTRU-KEM Algorithm

This paper focuses on enhancing the performance of the Nth-degree truncated-polynomial ring units key encapsulation mechanism (NTRU-KEM) algorithm, which ensures post-quantum resistance in the field of key establishment cryptography. The NTRU-KEM, while robust, suffers from increased storage and computational demands compared to classical cryptography, leading to significant memory and performance overheads. In environments with limited resources, the negative impacts of these overheads are more noticeable, leading researchers to investigate ways to speed up processes while also ensuring they are efficient in terms of area utilization. To address this, our research carefully examines the detailed functions of the NTRU-KEM algorithm, adopting a software/hardware co-design approach. This approach allows for customized computation, adapting to the varying requirements of operational timings and iterations. The key contribution is the development of a novel hardware acceleration technique focused on optimizing bus utilization. This technique enables parallel processing of multiple sub-functions, enhancing the overall efficiency of the system. Furthermore, we introduce a unique integrated register array that significantly reduces the spatial footprint of the design by merging multiple registers within the accelerator. In experiments conducted, the results of our work were found to be remarkable, with a time-area efficiency achieved that surpasses previous work by an average of 25.37 times. This achievement underscores the effectiveness of our optimization in accelerating the NTRU-KEM algorithm.
Practical NTRU Signcryption in the Standard Model

Based on the NTRU trapdoor used in NIST's Falcon, a signcryption scheme following the sign-then-encrypt paradigm is constructed. The existing partitioning technique based on Waters hash over the lattice can not complete the security reduction in the standard model for the signature part due to the "partiality" of the pre-image generated with the NTRU trapdoor. To address this, a variant of Waters hash over small integers is proposed and, the probability of the successful reduction is analyzed. The resulting signcryption achieves existential unforgeability under the adaptive chosen-message attacks. By utilizing the uniqueness of the secret and the noise in an NTRU instance, the tag used in encryption is eliminated. Furthermore, a method to construct tamper-sensitive lattice public key encryption is proposed. This approach implants the ciphertext-sensitive information into the lattice public key encryption and binds it to the encrypted information. The malleability to the public key ciphertext triggers the change of the message-signature pair so that the IND-CCA2 security of the entire ciphertext can be guaranteed by the signature for the message. Thanks to the rational design and the efficiency of the NTRU trapdoor, the computational overhead of the proposed scheme is reduced significantly compared to the existing lattice-based signcryption scheme, reaching orders of magnitude improvement in efficiency. The experiment shows that the proposed scheme is efficient.
Automated Route Planning from LiDAR Point Clouds for Agricultural Applications

This paper develops an algorithm to compute optimal routes for an autonomous compost turner. In commercial composting, the material to be composted is piled up in large heaps called windrows and turned regularly by compost turners. The environment at the composting site is constantly changing, as the locations of the windrows change with each turning procedure. Therefore, we propose a novel method that automatically computes routes on a composting plant from LiDAR data. The LiDAR is mounted on the compost turner together with a dual-antenna GNSS receiver, an IMU, and rotary encoders. An extended Kalman filter is used to obtain the vehicle’s pose. Through direct georeferencing, a global point cloud is obtained. The routing algorithm crops, segments, and filters the point cloud until the points along the ridge of each windrow remain. These points are used to compute the optimal routes along each windrow. Furthermore, a user can select the windrows which need to be turned and the algorithm then computes the most efficient path for the compost turner, which also includes the passages between the windrows. The method was tested within a simulation environment using a 3D model of the composting site. The results show that the algorithm detects the windrows and computes the routes with sufficient accuracy for autonomous compost turning.