Reviewerly/exHarmony huggingface dataset:
Adversarial Secret-Identity Generation Model for Face Anonymization in the Internet of Vehicles

With the rapid development of the Internet of Vehicles, the systematical cameras in vehicles can easily collect mass personal face data, which is very private on the Internet. This article focuses on solving the face protection problem caused by the Internet of Vehicles. Previous studies have proposed various face protection models based on obfuscation, neural networks, or adversarial techniques to prevent the disclosure of identity information. Even with existing face anonymization algorithms, there are several issues, including weak information protection ability, not maintaining the naturalness of a protected face, and not being suitable for various emerging face recognition systems. We propose an adversarial secret-identity generation model to protect personal identities from these problems. Concretely, our model's identity encryption generative adversarial module can generate brand new faces, which ensures naturalness while making other face identification models unable to recognize the identity. In addition, our PFS module extracts the identity set that is least relevant to the inputs and most conducive to model convergence from target data and promotes the generation of excellent faces from the perspective of data. Finally, the protected identities generated by our black-box face deidentification model can resist recognizing various advanced face identification approaches. Extensive experiments prove our model can achieve a 96.5% protection success rate, achieving competitive performance with 98.1% R1-T, 99.2% R5-T, 98.5% R1-U, and 97.1% R5-U against ArcFace and beating out various superior face anonymization algorithms. Meanwhile, we introduce a model compression algorithm to reduce the network scale of this model, demonstrating the scalability of various intelligent vehicles.
Elastic Resource Allocation in Sharding-Based Blockchains

This chapter studies the PBFT-based sharded permissioned blockchain, which executes in either a local datacenter or a rented cloud platform. In such permissioned blockchain, the transaction (TX) assignment strategy could be malicious such that the network shards may possibly receive imbalanced transactions or even bursty-TX injection attacks. An imbalanced transaction assignment brings serious threats to the stability of the sharded blockchain. A stable sharded blockchain can ensure that each shard processes the arrived transactions timely. Since the system stability is closely related to the blockchain throughput, how to maintain a stable sharded blockchain becomes a challenge. To depict the transaction processing in each network shard, we adopt the Lyapunov Optimization framework. Exploiting drift-plus-penalty (DPP) technique, we then propose an adaptive resource-allocation algorithm, which can yield the near-optimal solution for each network shard while the shard queues can also be stably maintained. We also rigorously analyze the theoretical boundaries of both the system objective and the queue length of shards. The numerical results show that the proposed algorithm can achieve a better balance between resource consumption and queue stability than other baselines. We particularly evaluate two representative cases of bursty-TX injection attacks, i.e., the continued attacks against all network shards and the drastic attacks against a single network shard. The evaluation results show that the DPP-based algorithm can well alleviate the imbalanced TX assignment, and simultaneously maintain high throughput while consuming fewer resources than other baselines.
APPLICATION OF TECHNOLOGY FOR THE DEVELOPMENT OF CRITICAL THINKING AS A MEANS OF MODERNIZING THE GEOGRAPHY TEACHING PROCESS

The article highlights the methodical aspects of using technology for the development of students' critical thinking in lessons as a means of modernizing the process of teaching geography in general secondary education institutions. Emphasis is placed on the importance of critical thinking to prevent threats and risks of the information society. The presence of critical thinking is defined as the main condition for countering attempts to manipulate consciousness, disinformation, information attacks and wars, which are not uncommon in the modern information space. The history of the emergence of technology for the development of critical thinking, the development of its conceptual foundations by US scientists is briefly analyzed, as well as the state of research on the problem in Ukraine is outlined. The essence, characteristic features and parameters of critical thinking, its meaning, as well as the features of a person who possesses critical thinking are revealed. It is noted that the development of students' critical thinking is a priority task of the modern education system, which is reflected in the State Standard of Basic Secondary Education in terms of key competencies and comprehensive skills. The main attention is paid to the methodology of applying various methods and techniques for the development of critical thinking in the process of teaching geography. It is emphasized that the method of development of critical thinking involves the formation of students' ability to analyze information, formulate conclusions, express their own position, present arguments, solve problems, and make decisions. The main stages of a geography lesson with the use of technology for the development of critical thinking are outlined: challenge, comprehension, reflection. The didactic possibilities of debates and discussions, problem tasks, interactive methods of discussing debatable issues and situational modeling in the process of developing students' critical thinking in geography lessons are considered. It was concluded that the application of technologies for the development of critical thinking in the process of teaching geography will allow students to better understand the essence of geographical phenomena and processes, learn geographical laws, understand the problems of the modern world and realize the practical significance of geographical knowledge.
Adaptation of Applications to Compare Development Frameworks in Deep Learning for Decentralized Android Applications

Not all frameworks used in machine learning and deep learning integrate with Android, which requires some prerequisites.The primary objective of this paper is to present the results of the analysis and a comparison of deep learning development frameworks, which can be adapted into fully decentralized Android apps from a cloud server.As a work methodology, we develop and/or modify the test applications that these frameworks offer us a priori in such a way that it allows an equitable comparison of the analysed characteristics of interest.These parameters are related to attributes that a user would consider, such as (1) percentage of success; (2) battery consumption; and (3) power consumption of the processor.After analysing numerical results, the proposed framework that best behaves in relation to the analysed characteristics for the development of an Android application is TensorFlow, which obtained the best score against Caffe2 and Snapdragon NPE in the percentage of correct answers, battery consumption, and device CPU power consumption.Data consumption was not considered because we focus on decentralized cloud storage applications in this study.
A Novel Robotic GWO LDI Modeling and Control for Nonlinear Systems

This works aims to develop a new and improved GWO (Grey Wolf Optimizer), the so-called Robotic GWO (RGWO). First, to improve GWO's update formula position with an optimal learning strategy, we adapt the algorithm to real mobile environments, including robots, so that tracking robots can move prey toward targets. Then, the nonlinear active suspension (AS) control system is linearized by a neural network (NN) based linear differential inclusion (LDI) using feedback and feedforward linearization. In theory, it is found that the general SM (Sliding Mode) optimal control cannot provide sudden optimal results for the active linearized suspension system, so a method is proposed to improve the shortcomings of the active linearized suspension system. By constructing an extended SM-optimal manifold function, an improved SM-optimal controller is designed, which incorporates information on the entire structure and the expected performance of the suspension. For comparison purposes, the performance of three kinds of controls: SM optimal refinement control, logic-fuzzy SM control, and PS (passive suspension), shows the proposed controller's advantages . Finally, our improved SM optimal control for nonlinear AS systems, in general, can achieve the actual nominal optimal suspension performance, as confirmed by the simulation results. The results also show that the improved SM optimal control method provides better robustness even when the operating conditions or parameters of the structure vary.
Mathematics as a Part of The Real Life

A flexible instrument with a wide range of possible uses is mathematics. The Queen of all sciences is mathematics. In our daily lives, mathematics is quite important. In the modern world, practically all discoveries and facts are tied to it. An equal progress in mathematics came before every major advancement in science. Nearly every area, including physics, engineering, finance, and many more, uses mathematics. Weather forecasting, teller machines, safe websites, video games, statistical data analysis, polls, and many more applications all use mathematics. From the beginning of human society, "geometry" has played a significant role. Early folks with tools studied the shape of the wheel in an effort to find a way to reduce friction. The "Father of Geometry," the Greek mathematician Euclid of Alexandria, named it after the combination of two words: "geo" for the earth and "metron" for balance. This paper aims to provide an overview of a few mathematical applications.
The Effect of Information Technology on the Effectiveness of Accounting Information Systems at PT Seraphim Karya Agung

This study aims to analyze the influence of information technology on the effectiveness of accounting information systems at PT Seraphim Karya Agung. Phenomena used to test the effectiveness of accounting information systems include: data security, time, accuracy, variety of reports or output, and relevance. The inhibiting factors that exist in the implementation of accounting information systems are human resources, time and completeness of data. The solutions provided to increase the effectiveness of the accounting information system at PT Seraphim Karya Agung are: (1) improving HR soft skills, namely time discipline, by giving warnings and harsh reprimands to undisciplined employees, (2) increasing the ability of accounting information systems to overcome crash down condition of the system which can slow down the process of making financial reports, (3) related to data completeness, the accounting department of auxiliary expenditures that processes financial data that still uses a manual system to immediately transfer its use to accounting information systems by providing education and training
Evaluating Open-Source Facial Recognition Software in Public Security: Effectiveness and Observations on Ethnicity

Context: In the criminal investigation environment, there is often a lack of information about a particular suspect, demanding instruments capable of searching for information based on limited evidence.Facial recognition, utilizing archived photos and/or real-time image capture, acts as one such instrument.Objective: This study aims to analyze the facial recognition resultsof the an open-source and free product, evaluating its effectiveness through acceptable accuracy and sensitivity rates for investigators, with the intention of exploring its potential application in the field of public security.Additionally, an analysis of efficacy by ethnicity was performed, which discussed solutions to avoid racism.Method: A controlled in vitro experiment was conducted, employing a dataset of approximately 20,000 authentic photographs of incarcerated individuals from the prison system of the state of Sergipe, Brazil.Results: The effectiveness results obtained indicate that the open-source and free Face Recognition tool holds potential for identifying individuals in the context of front-view photos of inmates in the prison system and similar Public Security Management applications.Upon completion of the tests and taking into account statistical significance, the software successfully identified incarcerated individuals using their images, achieving an average accuracy rate of over 84.8%, a sensitivity rate of over 89.9%, and an fβ-measure of over 82.5%, in line with the established criteria.It is worth mentioning that replications of this experiment may also validate a better average for the accuracy rate, which reached, for many cases, the final level of 90% and even 100% precision.Conclusion: The effectiveness results demonstrate the potential suitability of the facial recognition tool for identifying individuals, particular-
An Effect of Academic Challenges, Learning with Peers, and Experience with Professors of University Students Participating in Extracurricular Programs on Academic Outcome

본 연구는 대학교육의 질 제고와 성과관리를 위한 비교과 프로그램 참여 대학생의 학업도전, 교우와 학습, 교수와의 경험, 학업성과 간의 관계를 밝히는 데 목적이 있다. 이를 위해 첫째, 비교과 프로그램의 참여 여부에 따라 학업도전, 교우와 학습, 교수와의 경험, 학업성과의 차이가 있는지, 둘째, 비교과 프로그램 참여 대학생의 성별, 학년에 따라 차이가 있는지, 셋째, 비교과 프로그램 참여 대학생의 학업도전, 교우와 학습, 교수와의 경험이 학업성과에 영향을 미치는지 살펴보았다. 연구 결과 비교과 프로그램 참여 여부에 따른 학업도전, 교우와 학습, 교수와의 경험, 학업성과의 평균은 전체에서 유의한 차이를 보였다. 비교과 프로그램 참여 학생의 성별과 학년을 비교한 결과 성별 차이는 크게 나타나지 않았지만, 학년에 따라 차이를 보였다. 학년이 높을수록 교우와 학습, 학업성과가 높은 것으로 나타났으며 종합적으로 비교과 프로그램에 참여한 대학생은 학업도전, 교우와 학습, 교수와의 경험이 학업성과에 유의미한 영향을 미치고 있는 것을 확인하였다. 이에 본 연구에서는 학업성과를 높이기 위한 제안으로 학년에 따른 비교과 프로그램 개발 및 선후배 학생 간의 활발한 교류 등을 제안하며, 적극적인 비교과 프로그램 운영의 필요성을 강조하면서 이에 후속연구를 위한 제언을 하였다.The purpose of this study is to find out a relationship between tacademic challenges, learning with peers, experience with professors, and academic outcome of university students participating in extracurricular programs to improve the quality of university education and managing performance. The following were examined for this purpose: The first was whether there was a difference in academic challenge, learning with peers, experience with professor, and academic outcome according to the participation in the extracurricular programs. The second was whether there was a difference according to gender and year of the university students participating in the extracurricular programs. The third was whether the academic challenges, the learning with peers, and the experience with professors of the students participating in the extracurricular programs had a effect on the academic outcome. As a result of the study, significant differences were found in the averages of academic challenge, learning with peers, experience with professor, and academic outcome according to participation in extracurricular programs. In a comparison by the gender and grade of students participating in the extracurricular program, there was no significant difference according to the gender, while some differences were found according to grade. It is found that as the grades got higher, the level of learning with peers and academic outcome got higher. It is comprehensively found that academic challenge, learning with peers, and experience with professor had a significant effects on academic outcomes in university students who participated in the extracurricular program. Therefore, in this study, the development of extracurricular programs according to grade and enhancement of active exchanges between seniors and juniors are proposed to their enhance academic outcomes, and the need for active extracurricular program operation is emphasized with the suggestions for further studies.
Ability, Motivation and Opportunity (AMO)-enhancing HRM Practices and Corporate Environmental Citizenship: The Mediation Effect of Organizational Ethical Climate

Ability, Motivation and Opportunity (AMO)-enhancing is essential for the effective implementation of corporate environmental citizenship.However, previous studies neglect the link between AMO-enhancing HRM practices and corporate environmental citizenship.This has motivated the paper studies the influence of AMO-enhancing HRM practices on corporate environmental citizenship via the mediating role of organizational ethical climate.This study employed a quantitative approach in the form of survey questionnaires.Survey questionnaires were collected from 200 construction companies and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).The results revealed that ability and opportunity-enhancing HRM practices were found to positively influence corporate environmental citizenship.Motivation-enhancing HRM practices were insignificant in this regard.Similarly, organizational ethical climate did not prove to mediate the relationship between AMO-enhancing HRM practices and corporate environmental citizenship.Therefore, construction companies should invest heavily in ability and opportunity-enhancing HRM practices to pursue corporate environmental citizenship.Instead, construction companies can abandon motivation-enhancing HRM practices and organizational ethical climate if they have limited funds to improve corporate environmental citizenship.Ultimately, policy makers should use these findings to create strategies as guidance for the construction industry to achieve corporate environmental citizenship.
Traditional methods

The focus of this chapter is on solving the one-max and deceptive problems using the exhaustive search (ES) and hill climbing (HC) algorithms. First, the search behavior and pseudocode of ES and HC are given. Next, the implementation is given to help the audience understand not only the ideas of ES and HC but also how they are realized. Then, simulation results are given to show the features of ES and HC and to explain how difficult optimization problems can be. Finally, a discussion is given that is focused on the probability analysis of finding better regions and on the convergence analysis of ES and HC to show their search behavior during the convergence process.
Solution encoding and initialization operator

The very first thing to do to apply a metaheuristic algorithm to an optimization problem is to decide the solution encoding schema. Another issue related to the solution encoding that we need to take into account at the same time is the design of the initialization operator. For the solution encoding issue, the data clustering problem is used as an example to show how and why this optimization problem can be solved by different solution encoding schemata. The reasons to develop different solution encoding schemata are also discussed. Among them are limitations of memory space and computation time, the particular algorithm, and the combination of two or more algorithms. As for initialization, a refinement initialization operator is used to show how it can be used to enhance the performance of a metaheuristic algorithm compared with random initial seeds generated by a typical initialization operator.
Blockchain based Certificate Validation

Certificate management is a tedious task for any university or any other organization. These schemes impose problems in Public Key Infrastructure (PKI). Checking the validity and preserving the security of these documents is of utmost importance. In this work, we have devised a blockchain-based solution for preventing malfunctioning in certificate validation which is an important step for any university. Each certificate is uploaded in its hash format and is stored using blockchain. The hashes are stored in unique transactions in nodes, which are deployed on a private network. Using the SHA-256 hashing algorithm, the certificates are uploaded into the system and can be viewed by anyone with the right credentials. Due to the usage of blockchain technology, the certificates are stored in a decentralized manner, which ensures there is no central point of failure. Any changes in the uploaded document need to be validated by other nodes. This paper also improvises that when certificate uploading is required new nodes are added, instead of modifying the past blocks. This work provides a very user-friendly app where any user with the right credentials can upload documents. In this work, digitized documents are stored using Inter Planetary File System (IPFS) which is distributed method of storage. Our theoretical analysis proves that it is a user-friendly application with the security of blockchain technology in partnership with IPFS. Only the issuer can upload documents and others can only view them. Using our proposed solution, problem of malicious certificates can be tackled with E-certification. The proposed method solves all the issues of storing, validating, and sharing documents. Chaotic Map technique is used in hash generation which is quite simple to implement. The proposed approach Chaotic Key based Certificate validation (CK-Cert) provides a hassle-free solution for certificate managements since it better manages the block size as compared to previously proposed techniques (PBCert and CertChain) as discussed with the help of graphs.
An Optimized Implementation of a Novel Nonlinear Filter for Color Image Restoration

Image processing is becoming more popular because images are being used increasingly in medical diagnosis, biometric monitoring, and character recognition. But these images are frequently contaminated with noise, which can corrupt subsequent image processing stages. Therefore, in this paper, we propose a novel nonlinear filter for removing “salt and pepper” impulsive noise from a complex color image. The new filter is called the Modified Vector Directional Filter (MVDF). The suggested method is based on the traditional Vector Directional Filter (VDF). However, before the candidate pixel is processed by the VDF, the MVDF employs a threshold and the neighboring pixels of the candidate pixel in a 3 × 3 filter window to determine whether it is noise-corrupted or noise-free. Several reference color images corrupted by impulsive noise with intensities ranging from 3% to 20% are used to assess the MVDF’s effectiveness. The results of the experiments show that the MVDF is better than the VDF and the Generalized VDF (GVDF) in terms of the PSNR (Peak Signal-to-Noise Ratio), NCD (Normalized Color Difference), and execution time for the denoised image. In fact, the PSNR is increased by 6.554% and 12.624%, the NCD is decreased by 20.273% and 44.147%, and the execution time is reduced by approximately a factor of 3 for the MVDF relative to the VDF and GVDF, respectively. These results prove the efficiency of the proposed filter. Furthermore, a hardware design is proposed for the MVDF using the High-Level Synthesis (HLS) flow in order to increase its performance. This design, which is implemented on the Xilinx Zynq XCZU9EG Field-Programmable Gate Array (FPGA), allows the restoration of a 256 × 256-pixel image in 2 milliseconds (ms) only.