Reviewerly/exHarmony huggingface dataset:
Multi-dimensional Metamorphic Testing Method in Vehicle Intelligent Identification System

The image recognition systems, like other Deep Learning-driven systems, face the problem of Oracle Problem.In order to solve the problem of a single metamorphic relation in the image recognition system testing, a multi-dimensional metamorphic testing method is proposed.First, the multi-dimensional metamorphic relations of general image scene and transformation image background region is constructed; Then Then the derived test images are generated by image transformation technology, and the authenticity and naturalness of the derived test images are detected by introducing structural similarity.Finally, the test results are analyzed by Mean Absolute Error.Experiments conducted on Baidu AI service platform, Jingdong AI open platform and Aliyun visual intelligence open platform show that the multi-dimensional metamorphic testing method detects 3724, 2432 and 2747 inconsistencies in the identification results of the three platforms, and each metamorphic relation in the multi-dimensional metamorphic testing method can detect hundreds of inconsistent behaviors in recognition results.The image recognition system is tested more comprehensively in different image scenes, and the defects of the system are exposed more easily.
A Unified Federated Framework for Internet-of-Things Security Challenges

&#x0D; The protection of sensitive information is among the top priorities of organizations that are involved in manufacturing. Because of this, businesses are afraid of sharing their data with other parties so that they may construct predictive and prognostic models. In such a situation, it is difficult to construct complete models to forecast the breakdown of assets since data from a single firm would not provide the needed range of operating regimes and failure types. Recently, the Internet of Things (IoT) has gotten a lot of interest because of the vast variety of applications it has in numerous fields that communicate across multiple levels of the Internet infrastructure. The Internet of Things is composed of three layers: the physical layer, the network layer, and the application layer. This paper discusses security threats and responses for each layer of the IoT. The research examines different current state-of-the-art IoT security frameworks and suggests a unified IoT network security framework name "A Unified Federated Security Framework." The fuzzy cognitive maps used in the proposed framework are used to represent and evaluate trust connections between entities in federated identity management systems. For Internet of Things networks, the unified federated security architecture suggested in this paper offers comprehensive security characteristics. It also allows for the accurate categorization of all assaults and the capture of the different dangers, which allows for the development and implementation of improved defenses.&#x0D;
Effect of Viewpoint Change on Robot Hand Operation by Gesture- and Button-Based Methods

Teaching pendants with multiple buttons are commonly employed to control working robots; however, such devices are not easy to operate. As an alternative, gesture-based manipulation methods using the operator’s upper limb movements have been studied as a way to operate the robots intuitively. Previous studies involving these methods have generally failed to consider the changing viewpoint of the operator relative to the robot, which may adversely affect operability. This study proposes a novel evaluation method and applies it in a series of experiments to compare the influence of viewpoint change on the operability of the gesture- and button-based operation methods. Experimental results indicate that the operability of the gesture-based method is superior to that of the button-based method for all viewpoint angles, due mainly to shorter non-operating times. An investigation of trial-and-error operation indicates that viewpoint change makes positional operation with the button-based method more difficult but has a relatively minor influence on postural operation.
Face Age Predictions by combining Local and Global Facial Features

Aging is a gradual process, and it is difficult to see changes in the face as a whole, but signs of aging can be found in local areas. Therefore, fusing local face features on the basis of global features can improve the accuracy of age prediction. This paper proposes an age prediction method based on the combination of global facial features and local facial features. First, the local regions such as eyes, nose and mouth are cropped from the pre-processed facial image. Then, feature extraction is performed on the facial image and the cropped local area image, and the extracted features are subjected to feature selection, standardization and PCA dimension reduction. The processed features are then used for age prediction using multi-class support vector machines and neural networks. Experimental results show that this method outperforms previous methods.
Analysis of Error Type and Feedback Efficacy on Genre-Based Writing: Narrative Writing*

The current study aims to analyze EFL learners' error types and teachers’ feedback efficacy in English narrative writing. 60 participants divided into two proficiency groups by TOEIC scores were asked to write each of two narrative essays in class and correct each language-form error in their drafts based on two kinds of feedback (explicitly coded and uncoded). Errors in each group’s drafts and revisions were statistically analyzed based on the error types and feedback methods. The findings of the study are as follows: 1) Overall learners’ writing accuracy and fluency analyzed by tokens and error rate after revision show a significant improvement. 2) Detailed error analysis on narrative writing indicates that in the draft, the error types related to verbs (particularly past tense) are more frequent than others, but in the revisions, the correction activity using feedback shows a positive effect on error types relevant to verbs, one of treatable errors. 3) Students with better English proficiency, given more explicit “coded” feedback, can significantly reduce error rates in both drafts and revisions. This suggests teachers to consider troublesome error types as well as feedback methods when giving error feedback to EFL writers.
PENGEMBANGAN MEDIA KOMIK DIGITAL BERBASIS CANVA PADA MUATAN PELAJARAN BAHASA INDONESIA MATERI SUMBER ENERGI

This study aims to develop an innovation in interesting, varied, and innovative learning media using the Canva application as well as to test the feasibility and validity of the developed media, namely Canva-based digital comic media in Indonesian language lesson content on energy source materials. This type of research is a research and development research with the research subjects of class III students at SDN Kawungluwuk Kab. Cianjur. Data collection in this study used the methods of observation, interviews, and documentation. Data were analyzed using quantitative and qualitative descriptive analysis. The procedure and stages of development on Canva-based digital comic media use the ADDIE model which has five stages, namely analysis, design, development, implementation, and evaluation. The quantitative and qualitative development of digital comics based on Canva is appropriate for use in learning. The results of the validation assessment were processed twice because of revisions to produce the best product. The results of the 1st media expert validator got 91% and the 2nd got 92%, the 1st linguist validator got 64% and the 2nd got 100%, the 1st material expert validator got 84% and the 2nd got 88%. The overall results of all validators 1 get 80% results and the 2nd get 93% results have an increase. Meanwhile, the results of the student response questionnaire obtained 94%. Based on the results of the study, it was shown that the Canva-based digital comic media in the Indonesian language subject matter of energy source material was very feasible to be used as a varied and innovative learning media in learning.&#x0D; Keywords: Development; Learning media innovation; Digital Comics; Canva; Energy sources&#x0D;
Toktarova V. I., Fedorova S. N. Adaptive System of Mathematical Training of Students in the Conditions of the Information and Educational Environment of the University. Yoshkar-Ola: Mari State University, 2020. 488 p.: Opinion Paper

The review analyses the monograph “Adaptive System of Mathematical Training of Students in the Conditions of the Information and Educational Environment of the University” by V. I. Toktarova, S. N. Fedorova, addressed to academic and pedagogical workers of higher education institutions, teachers of secondary schools and vocational education institutions, as well as graduate and post-graduate students in relevant scientific fields and training programme specialisations, participants of advanced training courses in the sphere of education, practicing experts in teaching methodology and specialists in the field of pedagogical technologies. The monograph examines the theoretical and practical foundations of designing an adaptive system of mathematical training of students in the conditions of the information and educational environment of higher educational institutions. The work sheds light on the methodological approaches to the development of an adaptive system of mathematical training of university students, considers the information and educational environment (IEE) of the university as a pedagogical system of a new level. Special attention is paid to describing the conceptual foundations for the implementation of an adaptive system of students’ training in the conditions of the IEE, which includes the structural and functional model and the implementation technology.
Interactive Methods of Contextual Learning as a Way to Enhance the Cognitive Activity of Students in the Process of Studying Non-Core Disciplines at the University: Implementation Experience

The research aims to substantiate the effectiveness of using interactive methods of contextual learning, which will contribute to the enhancement of students’ cognitive activity in the process of studying non-core disciplines at the university. The paper sheds light on the theoretical and practical issues of enhancing the cognitive activity of university students in the process of training in a non-core field of activity. The work describes the most relevant interactive methods for enhancing the cognitive activity of university students from the perspective of contextual learning; uses the experience of their practical application in mathematics classes as an example. The research is novel in that it develops and clarifies scientific ideas about modern interactive methods used in the setting of contextual learning when teaching non-core disciplines to university students and substantiates the possibility of their effective application in the educational process to enhance students’ cognitive activity. As a result, modern interactive methods used in contextual learning at the university have been identified and analysed; the most relevant ones for the use in the process of studying non-core disciplines in order to enhance the cognitive activity of students have been determined. The selected interactive teaching methods were tested in contextual classes in mathematics with the students of an agricultural university in various training programmes. The contextual nature of the classes was due to the presence of problem-based socio-contextual situations, which were resolved by using interactive teaching methods.
Leveraging Blockchain Technology in the Value Chain and the Supply Chain

The chapter will discuss and present four Chinese companies leveraging blockchain technology within their value chain and supply chain to strengthen their business and generate sustainable growth. Two of the companies described are service providers: Hyperchain and Huawei. They offer the possibility to their clients to integrate blockchain technology in order to solve business problems and improve processes within their operations. The other two cases will focus on JD e-commerce and Shunfeng express delivery, which are involved in intense supply chain activities. The descriptions will show how blockchain allowed them to develop a better, more secure, and efficient fluidity of information, capital, and goods.
Speaker Authentication Using GMM-UBM

Today, numerous biometric systems have been suggested and created. Most used among them are face, fingerprint, and voice recognition. Each of them has their own advantages and disadvantages. Discussing about the automatic speaker verification (ASV), speech signal is a natural signal which one can easily obtain even from a telephone call. Research in this area is carried out from decades. This speaker verification technology has advanced in recent years and has become a genuine method for biometric systems. Using an adaptable Gaussian Mixture Model (GMM-UBM), a text-independent speaker verification (TISV) technique has been developed and compared with state-of-art I-vector based speaker recognition system in this research. Parameters for universal background model (UBM) are trained using the EM (Expectation maximization) and MAP adaptation method is used for training speaker models. Multiple false acceptance and false rejection rates are calculated by changing the threshold values for comparison. The results are shown in equal error rate (EER) for both the GMM-UBM, and I-vector based ASV systems, and the lowest EER is found to be 5.31% and 4.74%, respectively, after adjusting the threshold settings and number of Gaussian mixtures utilized.
Image noise removal using optimal deep learning-based noisy pixel identification and image enhancement

Image restoration is utilised to discard image noise without demolishing edge information. A new optimisation based deep model is devised for image enhancement with restoration. Here, the noisy pixel map is detected with Deep Residual Network (DRN). DRN training is carried out using the JayaBat algorithm, which was created by combining the Jaya optimisation method and the Bat algorithm (BA). The statistical model is then used to restore the noisy pixels. The neuro fuzzy model and the Image Enhancement Conditional Generative Adversarial Network (IE-CGAN) are taken into account while enhancing images. Here, the IE-CGAN training is performed with designed CAViaRJayaBat. The CAViaRJayaBat is designed newly by combining the CAViaR and JayaBat algorithms. The proposed CAViaRJayaBat-based IE-CGAN offered improved performance with the best Peak signal to noise ratio (PSNR) of 49.049 dB, the highest Second derivative measure of enhancement (SDME), 62.570 dB, and the highest structural similarity index (SSIM), 0.858.
E-MARKETPLACE FOR SMEs IN TOURISM VILLAGES

The Ngargoyoso tourist attraction area is one of the popular tourist attractions in Karanganyar Regency, especially in Central Java. In this tourist area there are many small and medium enterprises (SMEs) that offer various products, especially original products from Ngargoyoso. The use of information technology to support the marketing and promotion of local products, namely the Electronic Marketplace which is made based on a website with marketing and sales features, is expected to increase income and improve the welfare of the local community. The problem faced by Small and Medium Enterprises in the Ngargoyoso Tourism Village area is that the sales model that is carried out is still conventional and the promotions carried out are still very limited, only limited to the surrounding area. Sometimes tourists who visit don't even know the location of the SMEs in the tourist village of Ngargoyoso. And also many tourists who don't know what products from SMEs and their locations are, considering that currently in the tourist village of Ngargoyoso there is no market or physical store to market souvenirs typical of the products of SMEs in the village of Ngargoyoso. This has resulted in several SME products that have not been exposed to the outside. Even though during the COVID-19 pandemic, such as the current number of tourists visiting the Ngargoyoso tourist village, of course this greatly affects the income value of SMEs in the Ngargoyoso tourist village. Thus, the application of the Electronic Marketplace with a Rule Based Expert System can be used as a promotional media and selling and buying with a wider reach.
Energy consumption monitoring using private blockchain network based on Ethereum smart contracts

Monitoring current consumption in a smart grid involves, along with the acquisition of power consumption in different nodes of the network (through current and voltage sensors), the transmission of measured values through a local network to a central server. From a security point of view, communications between nodes and the central server are exposed. Also, the central server may be exposed to catastrophic attacks or faults that lead to data loss. The solution proposed by us in this paper, uses a private blockchain network and smart contracts based on Ethereum for the transmission of data from nodes. The advantages are: data integrity is ensured, synchronization between nodes as well as ensuring data protection by multiplying them on all nodes. The disadvantage would seem to be related to the increase in energy consumption that each blockchain node involves. As will be presented in the paper, this disadvantage will be removed by its own blockchain solution in which the consensus algorithm is adapted to low power consumption. Together with the own archiving method presented in the article, the solution is an efficient one, implementable at the level of nodes. Data will be presented in comparative analyzes with classic server solutions.
Space-Efficient STR-IC-LCS Computation

One of the most fundamental methods for comparing two given strings A and B is the longest common subsequence (LCS), where the task is to find (the length) of the longest common subsequence. In this paper, we address the STR-IC-LCS problem which is one of the constrained LCS problems proposed by Chen and Chao [J. Comb. Optim, 2011]. A string Z is said to be an STR-IC-LCS of three given strings A, B, and P, if Z is one of the longest common subsequences of A and B that contains P as a substring. We present a space efficient solution for the STR-IC-LCS problem. Our algorithm computes the length of an STR-IC-LCS in $$O(n^2)$$ time and $$O((\ell +1)(n-\ell +1))$$ space where $$\ell $$ is the length of a longest common subsequence of A and B of length n. When $$\ell = O(1)$$ or $$n-\ell = O(1)$$ , then our algorithm uses only linear O(n) space.
Sequentially Swapping Tokens: Further on Graph Classes

We study the following variant of the 15 puzzle. Given a graph and two token placements on the vertices, we want to find a walk of the minimum length (if any exists) such that the sequence of token swappings along the walk obtains one of the given token placements from the other one. This problem was introduced as Sequential Token Swapping by Yamanaka et al. [JGAA 2019], who showed that the problem is intractable in general but polynomial-time solvable for trees, complete graphs, and cycles. In this paper, we present a polynomial-time algorithm for block-cactus graphs, which include all previously known cases. We also present general tools for showing the hardness of problem on restricted graph classes such as chordal graphs and chordal bipartite graphs. We also show that the problem is hard on grids and king’s graphs, which are the graphs corresponding to the 15 puzzle and its variant with relaxed moves.
DESIGN AND BUILD OF PULSE BALANCE DEPOSIT INFORMATION SYSTEM BASED ON WEBSITE AT PT ASIA ADIJAYA PERKASA

The credit balance deposit business is said to be still loved until now, the need for all-in-one online makes it inevitable that device users need to top up pulses, digital wallets, PLN or top up games. This makes transaction requests more and more causing many requests in the deposit process, with this problem the author wants to create a credit deposit information system.&#x0D; In this study, the method used by the researcher divides it into two, namely for the first method of data collection there are observations, interviews, literature studies, and documentation. The second is the system development method using the SDLC (Systems Development Life Cycle) method, there is a needs analysis using pieces analysis, where there are system workflows, use case diagrams, activity diagrams, Sequence diagrams and the last is testing using black box techniques and beta testing.&#x0D; The results of the recommendation system consist of three access rights, namely customer service, owner and member. The credit balance deposit information system can assist in the deposit process from transactions, data presentation and reporting. The results of the black box test show that all functions in the credit balance deposit information system can run as expected. The results of beta testing by filling out the questionnaire show the percentage value of the system suitability is 88.79%.
An AlphaZero-Inspired Approach to Solving Search Problems

AlphaZero and its extension MuZero are computer programs that use machine-learning techniques to play at a superhuman level in chess, go, and a few other games. They achieved this level of play solely with reinforcement learning from self-play, without any domain knowledge except the game rules. It is a natural idea to adapt the methods and techniques used in AlphaZero for solving search problems such as the Boolean satisfiability problem (in its search version). Given a search problem, how to represent it for an AlphaZero-inspired solver? What are the “rules of solving” for this search problem? We describe possible representations in terms of easy-instance solvers and self-reductions, and we give examples of such representations for the satisfiability problem. We also describe a version of Monte Carlo tree search adapted for search problems.
PrivacyMask: Real-world privacy protection in face ID systems

&lt;abstract&gt;&lt;p&gt;Recent works have illustrated that many facial privacy protection methods are effective in specific face recognition algorithms. However, the COVID-19 pandemic has promoted the rapid innovation of face recognition algorithms for face occlusion, especially for the face wearing a mask. It is tricky to avoid being tracked by artificial intelligence only through ordinary props because many facial feature extractors can determine the ID only through a tiny local feature. Therefore, the ubiquitous high-precision camera makes privacy protection worrying. In this paper, we establish an attack method directed against liveness detection. A mask printed with a textured pattern is proposed, which can resist the face extractor optimized for face occlusion. We focus on studying the attack efficiency in adversarial patches mapping from two-dimensional to three-dimensional space. Specifically, we investigate a projection network for the mask structure. It can convert the patches to fit perfectly on the mask. Even if it is deformed, rotated and the lighting changes, it will reduce the recognition ability of the face extractor. The experimental results show that the proposed method can integrate multiple types of face recognition algorithms without significantly reducing the training performance. If we combine it with the static protection method, people can prevent face data from being collected.&lt;/p&gt;&lt;/abstract&gt;