Reviewerly/exHarmony huggingface dataset:
Provably Secure Reflection Ciphers

This paper provides the first analysis of reflection ciphers such as Prince from a provable security viewpoint. As a first contribution, we initiate the study of key-alternating reflection ciphers in the ideal permutation model. Specifically, we prove the security of the two-round case and give matching attacks. The resulting security bound takes form $$\mathcal {O}(qp^2/2^{2n}+q^2/2^n)$$ , where $$q$$ is the number of construction evaluations and $$p$$ is the number of direct adversarial queries to the underlying permutation. Since the two-round construction already achieves an interesting security lower bound, this result can also be of interest for the construction of reflection ciphers based on a single public permutation. Our second contribution is a generic key-length extension method for reflection ciphers. It provides an attractive alternative to the FX construction, which is used by Prince and other concrete key-alternating reflection ciphers. We show that our construction leads to better security with minimal changes to existing designs. The security proof is in the ideal cipher model and relies on a reduction to the two-round Even-Mansour cipher with a single round key. In order to obtain the desired result, we sharpen the bad-transcript analysis and consequently improve the best-known bounds for the single-key Even-Mansour cipher with two rounds. This improvement is enabled by a new sum-capture theorem that is of independent interest.
Minimize Collision Risk Global Planner Based Voronoi Graph for Mobile Robot

Ensure safe, reliable, fast and stable robot navigation which requires stable and efficient motion planning algorithm support. In order to reduce the collision risk during robot navigation, we propose minimize collision risk global planner for mobile robot, based on voronoi graph to extract Tyson polygon vertices. Using multiple vertices to form a planning search graph, the collision risk of each edge is calculated i.e. the integral of the distance to the obstacle is used as the weighted value of the edge, and the search is performed using A* to obtain the planning path with the lowest collision risk globally at the current moment. In order to make the planned path more consistent with robot kinematics, we designed the collision and smooth cost function to optimize the path using gradient descent, and the searched path is passed to the local planner after path smooth. The test results on the actual robot show that the robot can effectively avoid narrow areas and effectively reduce the collision rate and replanning times in dynamic environments.
Software Fault Detection by Using Rider Optimization Algorithm (ROA)-Based Deep Neural Network (DNN)

Rider Optimization Algorithm (ROA)-based Deep Neural Network (DNN) model is suggested for software fault detection purposes. The entire work is divided into three phases: feature selection, training and testing, and fault detection. The ROA-based k-nearest neighbor (KNN) classifier performs the features selection task. The output of the ROA KNN classifier is fed as the input to the DNN. The DNN layers detected the faulty section. The features selection task is performed by the ROA-based KNN classifier that classifies the optimal features from all dataset features. The DNN model is trained with the features selected by the ROA-based KNN classifier. The performance of the proposed ROA-DNN model is compared with the PSO-based DNN model of software fault detection. The ROA-based DNN model of software fault detection shows up to 99% accuracy for fault detection.
Blockchain and Government Services

Government services require trusted data, data sharing between goverment, and data sharing between governments and enterprises. Based on the advantages of blockchain technology, government data can be shared and exchanged in a trusted manner based on blockchain, implement a data ownership separation mechanism, promote cross-department and cross-efficient, and low-cost administrative supervision system, and build an intelligent mechanism for pre-event evidence storage, data sharing, and linkage collaboration to optimize administrative supervision, city management, and emergency assurance processor and improve governance efficiency. Implemented in market surveillance, administrative law enforcement, and audit scenarios to provide high-quality, efficient, and convenient mobile government services for enterprises and people.
A Demonstration of BDI-Based Robotic Systems with ROS2

The paper demonstrates our BDI-based tool-kit built on top of ROS2. We present its main features by means of a realistic industrially-inspired scenario where a fleet of autonomous and heterogeneous robotic systems are asked to move and sort boxes to target destinations. The aim of the demo is to show the advantages of combining the expressiveness of the BDI architecture with an integrated planning system. We show how agents are able to find suitable solutions to achieve their goals in an evolving environment, and how agents communicate and cooperate to achieve common objectives.
PELATIHAN PENGGUNAAN ZOOM DALAM KEGIATAN BELAJAR MENGAJAR DI SMK AVICENA RAJEG KABUPATEN TANGERANG

The Covid-19 pandemic which has been endemic for several months, especially in Indonesia. As we all know, one of the consequences of this pandemic is that the government prohibits face-to-face learning in class. This prohibition applies to all levels. Therefore, we need the right media so that the teaching and learning process activities continue. The use of online media is the right choice. This is because in its use there is no need for direct contact between teachers and students. The chosen online application is Zoom where this application has many advantages that allow online learning to run interactively and maximally. The participants of this activity were all teachers of Avicenna Rajeg Vocational School, Tangerang Regency, Banten. In its implementation, lecturers are assisted by students with the aim of involving, introducing, and inviting students to interact in studying the material and its application in the real world. In general, the activity went smoothly, and participants were able to accept and understand the material presented by the lecturer.
EthMB+: A Tamper-Proof Data Query Model Based on B+ Tree and Merkle Tree

The rise of cryptocurrencies has brought blockchain technology into wide focus. Because of its immutable, traceable and consistent protocol, it provides a new solution for trusted data storage and decentralized computing. Most existing blockchain systems store blockchain data in key-value databases with simple semantic descriptions. However, the data storage system only provides a single query mode and limited query types. As a result, it is impossible to carry out effective data analysis and mining on the ever-increasing data in the blockchain system. To expand the data query function of the blockchain system, the data in the maintenance system must not be tampered with. This paper proposes a tamper-proof data query model (EthMB+) based on B+ tree and Merkle tree to ensure users get correct query results. EthMB+ reconstructs the organization by extracting part of the blockchain data and then inserting them into the MB+ tree structure. The query method is designed based on the structure of MB+ tree. Experimental results show that EthMB+ has good usability.
Flexible Group Non-interactive Key Exchange in the Standard Model

In this paper, we constructed a non-interactive group key exchange protocol (GNIKE) with flexibility, i.e., the number of participants in the GNIKE is not predefined. Moreover, our GNIKE construction is only based on multilinear map and conventional cryptographic building blocks. The security proof of our GNIKE is in the standard model and relies on an n-exponent multilinear DDH assumption.
Multimodal Representation Learning-Based Product Matching

This paper describes our methodology for the identical product mining task organized by the China Conference on Knowledge Graph and Semantic Computing (CCKS) 2022. This identical product mining task has two main challenges: 1) How to perform text representation to refine product representation. 2) How to more effectively combine text representation and image representation. For the first challenge, we propose the K-Gram Exponential Decay scheme in the text representation module to aggregate the information of surrounding words. For the second challenge, we apply conventional multimodal representation learning to combine text representation and image representation to generate the item representation. We view the identical product mining task as a binary classification task for product pairs, for which we adopt sample pair-based contrastive learning. Extensive experiments have demonstrated the effectiveness of our method. We won first place in the competition by utilizing model ensemble and post-processing.
Research on Video Compression Algorithm Based on Deep Learning

The storage of any type of data on the web requires the use of that particular type of data. The amount of pictures, movies, and other forms of content that are similar to one another that are circulating on the internet has skyrocketed. Even under the weight of many resource constraints, such as bandwidth bottlenecks and noisy channels, users of the Internet demand the data they access to be easily understood. As a direct result of this, data compression is rapidly becoming an increasingly important topic among the larger engineering community. Using deep neural networks for the purpose of data compression has been the subject of some previous research. Several different machine learning approaches are now being implemented into data compression strategies and put to the test in an effort to achieve improved lossy and lossless compression outcomes. The typical video compressive sensing reconstruction algorithm has an excessively lengthy delay throughout the reconstruction process. It is unable to make full use of the spatial and temporal correlation of video, which results in an improvement in the quality of the reconstruction poor. In this research, a video compression method that is based on deep learning (DL) is proposed, and it has the potential to handle these challenges effectively.
Research on non-contact detection method for conductivity of supercapacitor

In order to detect the conductivity of electrode materials for supercapacitors, a new method is used in this paper, which is called Magnetically Mediated Thermoacoustic Detecting Method (MMTDM). Firstly, the principle of Magnetically Mediated Thermoacoustic Detecting Method is studied. Secondly, the simulation model of Magnetically Mediated Thermoacoustic Detecting Method is built, and the ultrasonic signal of the model is obtained. Finally, the self-made supercapacitor electrode material and pure aluminum foil were used as experimental targets for detection and comparison. The results of numerical simulations and physical experiments show that the Magnetically Mediated Thermoacoustic Detecting Method can realize the non-contact detection of the conductivity of energy storage materials. This paper provides a good theoretical and experimental basis for the application of Magnetically Mediated Thermoacoustic Detecting Method in the non-contact detection of energy storage materials.
Application of modern forecasting technologies in future teacher training

The article deals with the problem of finding new effective educational tools in the preparation of a future teacher.We place special emphasis on the formation of prognostic skills.The ability to predict is included in the implementation of all key functions of the teacher.One of the modern forecasting technologies, the foresight method, is an effective tool for developing prognostic skills of a future teacher.The article systematizes various approaches to the definition of foresight and the stages of applying this technology.To unlock the potential of forecasting technology, we analyzed the educational standard and the competencies, formed during the study of the discipline "Modern problems and innovations in education", identifying implicitly included prognostic skills.We also highlighted the key topics of the course, which require the development of the foresight technology.The article presents an algorithm for its use and an example of its application in teaching students.Rapid Foresight was chosen as a methodology, its main stage being a foresight session on the topic "Skills and competencies of a teacher in distance education".The result of the study was the students' reflective assessment of their prognostic skill development based on the foresight technology.
VM Migration and Live-Update for Reliable Embedded Hypervisor

With the development of hardware virtualization technology, more and more embedded hypervisors are being implemented. Traditional embedded hypervisors focus on resource utilization and real-time performance while neglecting the reliability requirements of embedded applications. In this paper, we implement two fault-tolerant mechanisms for an embedded hypervisor, which makes hypervisor more reliable without significant downtime. We apply VM migration to provide a runtime fault-tolerance mechanism to further enhance hypervisor reliability. To guarantee the regular operation of critical tasks during fault recovery, this paper implements a hypervisor live-update mechanism to complete fault recovery while avoiding migration network delays. Test results show that these mechanisms combine reliability and operational efficiency to meet the needs of embedded applications.
An Investigation on the Usability of Socio-cultural Features for the Authoring Support During the Development of Interactive Discourse Environments (IDE)

Though there have been significant developments in authoring tools for interactive narratives as well as a growing number of models explaining narrative meaning production, there is still a lack of understanding around what type of authoring support is required that can facilitate authors to handle the complex environment they develop by maintaining a high content and experience quality. In this paper, we present an investigation that aims to establish relations between individual information needs and navigation behaviour, which can be used as patterns to support authors in the design and development of interaction processes for Interactive Discourse Environments (IDE). A prototype of an argumentative discourse environment has been developed, in which participants can explore information resources in various media representations and complexity levels to gain better insights on climate change. The navigation behaviour has been tracked, and qualitative interviews have been performed to gain deeper insights in the relation between personal information needs, resource preferences and investigation behaviour. The findings of the analysis show that socio-cultural attributes can be identified that correlate to certain navigation patterns. We also show how those patterns can be made available as content and engine consistency checking devices in an IDE authoring environment.
An Evaluation of Cyber Threat Taxonomies in the framework of Cyber Activism

The billions of new media platforms available online allow people to represent themselves and meet like-minded people. Thus, a human-based, lively and dynamic public opinion is formed in cyberspace as well. A free and egalitarian representation should be given to all groups in order to ensure the democracy of cyberspace. The states and users who carry the current power struggles to the cyber space restrict cyber democracy. In this study, which is handled within the framework of new media and cyber activism, the motivation of hacktivism, which is a marginal and aggressive type of cyber activism, is accepted as proving its existence and power in the cyber field. DDOS (Distributed Denial of Service)attacks are one of the most preferred attack types by hackers, who are the representatives of the struggle for power and public administration in cyberspace. The aim of the study is to help determine the criteria to distinguish cyber activism from other cybercrimes. The criteria used in DDOS taxonomies are presented in the literature. In order to distinguish cyber activism from other cybercrimes, cyber attacks affecting the public in Turkey were examined and a table containing the messages of hackers and findings were presented. As the result, it has been proposed to include the determining criteria in DDOS taxonomies by making hacktivism motivations visible.
The Seamless Integrated Geologic Mapping (SIGMa) extension to the Geologic Map Schema (GeMS)

First posted December 12, 2022 For additional information, contact: Director, Geosciences and Environmental Change Science CenterU.S. Geological SurveyBox 25046, MS-980Denver, CO 80225-0046 Geologic maps are the fundamental building blocks of surface and subsurface three-dimensional geologic framework models of the Earth’s crust. However, as the production and availability of geologic map databases continues to increase, inconsistent data models and the lack of synthesized, national geologic map data at scales appropriate for informed decision making negatively affect the functional integration of geologic map data with other national datasets. The Geologic Map Schema (GeMS) is the publication and archive database standard for geologic map data funded by the U.S. Geological Survey National Cooperative Geologic Mapping Program, and standardizes the organization and content of a single map database. However, synthesizing multiple databases into a seamless geologic map database creates a different set of challenges and database needs than GeMS was designed to accommodate. The Seamless Integrated Geologic Mapping (SIGMa) extension is designed to expand the capabilities of GeMS by enabling integration of map-based geoscience data. In particular, the SIGMa extension enables capturing a diverse and ever-changing set of map units, produced by many contributors operating independently, and by incremental and noncontiguous assembly and publication. Feature-level metadata fields allow data sources and digital compilation methods to be attributed separately and a relational structure is designed to support the link between data sources and features attributed with multiple data sources. Instead of paragraph-style map-unit descriptions that can be highly inconsistent, SIGMa parses fundamental map-unit attributes, including material, genetic process, and age, into thematically specific fields. The SIGMa extension uses a hierarchical map-unit organization to facilitate a dynamic and evolving, formation-level stratigraphic framework. The hierarchy is developed around geologic provinces that represent temporally restricted geologic events, processes, and settings. Geologic provinces can include magmatic events, depositional settings associated with tectonic processes or stable continental margins, and processes that are actively shaping the modern landscape. A geologic province hierarchy places map units into a geologic context at subregional to continental scales and provides the flexibility to support incremental assembly of the stratigraphy.
Role Access Control Search Scheme Based on Attribute Encryption

In order to facilitate data sharing, the data owner stores the data on the cloud server, but for data security, the data is generally encrypted based on cryptography when outsourced to the cloud. Use attribute-based encryption (ABE) to encrypt data Encrypt and upload to the ECs to prevent data abuse and theft. When retrieving data through searchable encryption, there will be data leakage, that is, data that cannot be decrypted by the user will also appear. In this paper, a more fine-grained role access control search scheme based on attribute encryption is proposed, using role-based access control (RBAC) Associate users with system roles. Data owners can specify flexible access policies for the encryption stored in the ECS. When data users retrieve data, the ECS filters the data that does not meet user permissions through the internal authentication system to prevent data leakage. Compared with existing systems in the market, this scheme can effectively prevent privacy data According to the disclosure, it has a higher fine-grained division, which makes the ECS unable to obtain the user’s sensitive information when providing services.
Proposal to modify the Russian standard for electronic digital signature in order to eliminate the broadband covert channel

Most digital signature algorithms have the ability to organize hidden channels for transmitting information. Their presence was revealed after the publication of a digital signature scheme based on the El-Gamal cipher. The bandwidth of these channels ranges from a few bits (narrowband channels) to 256-512 bits (broadband channels). The literature describes several ways to eliminate broadband channels with the help of a supervisor. The analysis of existing methods of elimination of hidden channels in digital signature algorithms is given. The shortcomings of the existing schemes are revealed. A method of modification of the Russian standard of electronic digital signature GOST R 34.10-2012 has been developed in order to eliminate the broadband hidden channel. The method provides for the presence of a supervisor who does not participate in the formation of the signature and can check signed messages for the absence of hidden channels.
Android Application Dictionary of English Terms for Mathematics Learning

Mathematical terms in English often confuse students with their meanings. In its application, the impact on students' difficulties in understanding the concepts being studied. Students also have a problem in making useful conclusions while the books in English-language textbooks. These things make most Mathematics education students low-motivation and challenging to understand the concepts and basic mathematics derived from English-language texts. The term dictionary can be an alternative solution that can be used to overcome the problems. In general, the term dictionary discusses terms that are not common in a field. This Android application also provides a specific explanation of the terms that are the main search words. Android applications that have been developed are named RIGA. RIGA has 100 words or phrases in English and explanations and 100 words or terms in Indonesian along with answers. This study uses qualitative and quantitative data types. Qualitative data were obtained using a questionnaire in the form of suggestions and criticisms given by the test subjects. Meanwhile, quantitative data were obtained from questionnaire distribution scores from the test subjects. The results show that the results of validation by media experts and field trials produce valid results. Thus, it can claim that RIGA can use for the teaching and learning process.
Exploring student challenges in an online project-based course

In addition to sound technical skills, industry jobs require soft skills such as teamwork and good organizational abilities. This is even more important in today's landscape, where working from the office is substituted with working from home. This trend, together with the shift towards distributed teams that are separated geographically and across time zones is expected to create challenges addressed through improved management and soft skills. Organizations of higher learning include the development of capstone or team projects as part of their curricula in order to prepare students for collaborative work and improve their organizational abilities. In this paper, we present an exploratory study focused on the challenges encountered by students in two consecutive iterations of a Team Projects course. The second iteration took place fully online due to the ongoing pandemic. We discovered the lack of face to face communication and schedule synchronization as some of the important challenges reported. We show that mitigating strategies by both teaching staff and the students themselves helped keep communication open and engagement high. We provide a replication package that allows repeating or extending our study.