Reviewerly/exHarmony huggingface dataset:
Based on IoT and PGP: A new secure framework using cubic bézier technique and El Gamal elliptic curve cryptosystem for information exchange

The importance of text encryption has considerably increased especially after the dramatic evolution of sensitive information over the dispersed IoTs. This study aims at generating a secure encrypted text to make cryptanalysis infeasible. In this paper, the enhancement of the ElGamal elliptic curve cryptosystem is introduced based on PGP behavior nature and cubic Bézier curve equation. The transmission key of the proposed method is encrypted based on Cubic Bézier curve technique in order to achieve better cryptography criteria and to add more secure and complexity to the complexity of elliptic curve cryptosystem. The main aim of the proposed method is to increase the security features in the session key with encrypting and decrypt the secret message. The National Institute of Standards and Technology (NIST) randomness tests and running time for the encryption and decryption process have been compared with different key sizes to evaluate this method.
SIFAT FISIKA MEKANIKA PAPAN SEMEN PURUN TIKUS (Eleocharis dulcis) PADA BERBAGAI PENGERAS (The physical and mechanics properties of mouse purun cement board on various hardeners)

ABSTRACKThe research objective was to determine the properties of physical and mechanics of mousepurun cement board on various hardeners. The cement board was processed with a size of 30 cmx 30 cm x 2 cm, a ratio of 3: 1, a density of 2 g / cm2, purified water content of 15%, hardenerCa(OH)2, CaCl2, MgCl2 with a concentration of 2%. Before making the cement board thehydration temperature test is carried out, then the resulting board is tested for the physicalproperties of the mechanics. And the grave test for 3 months. Data averaged and SD thentabulated and written in graphical form. The results of the study were hydration temperature:31.38-33.50oC, inhibiting factors: 6.94-10.19%, board water content: 13.55% - 15.77%; density:1.07-1.16 g / cm2; MoR: 22.96 - 30.31 kg / cm2, Compressive strength: 0.84 - 3.34%.Conclusion: Mouse purun can be processed into cement board. The good nature of the cementboard is to treat CaCl2 2% hardener.Keywords: Purun, cement board, hardener, hydration and MoR
Analysis of Deep Learning Algorithms for Image Denoising

A deep learning-based image denoising model for removing non-additive non-gaussian noise from images is proposed in this paper. Images are considered unstructured data, and these are easily corrupted in the complex environment. Due to the noise in the digital images, poor image quality-related issues arise in the images. Image noise reduction is an issue in the realm of image processing. Learning-based algorithms for image denoising have gotten a lot of focus because of their superior denoising performance. Deep learning models are neural networks that have multi-layer structures. These structures are very helpful for extracting very complex features from input images and then remove noise. An extensive database of images is used to train and validate the model. The qualitative evaluation based on visual quality is used to assess the denoised images. The quantitative assessment with mean squared error, peak signal to noise ratio, and structural similarity index measure is used to evaluate the denoising outcomes.
Spiral-Sooty Tern Optimization Algorithm for Dynamic Modelling of A Twin Rotor System

This paper presents a hybrid Spiral - Sooty Tern Algorithm (SSTA) which is an improved version of the original STOA. A spiral model is incorporated into the Sooty-Tern Optimization Algorithm (STOA) structure. A random switching is utilized to change from random-based to deterministic-based searching operations and vice versa. This is to balance between the exploration and exploitation of all searching agents throughout a feasible search area. For solving a real-world problem, the proposed SSTA algorithm in comparison to STOA is applied to optimize parameters of a linear Autoregressive-Exogenous (ARX) dynamic model for a twin rotor system. The dynamic modelling of the system is challenging in the presence of cross coupling effect between the main and tail rotors. 3000 pairs of captured input-output data from the system are used for the identification and optimization purpose. Result of the test has shown that the SSTA has achieved a better accuracy performance compared to the competing algorithm. For dynamic modelling of the nonlinear system, both SSTA and STOA have acquired a sufficiently good model for the twin rotor system.
ARTETERAPIA COMO ESTRATÉGIA PARA PROMOÇÃO DE QUALIDADE DE VIDA DO POLICIAL EM ESTRESSE LABORAL

Objective: to list aspects of art therapy as an ally in the process of prevention, health promotion and improvement of the policeman’s quality of life in reducing the level of work stress. Methodology: This is a literature review, carried out from January 2022 to July 2022, from the Virtual Health Library (VHL) in the databases, LILACS and in the SCIELO electronic library Revistas Eletrônicas, Theses, dissertations and other bases, having as descriptors “art therapy, police, stress and quality of life. Results: the articles and literature demonstrated the therapeutic potential that art therapy has and it is perceived as an important strategy contributing in a relevant and profound way to the human being in the world, being a welcoming and healing resource for people with stress and in the most different. contexts, linked to the commitment that the subject reconstituted himself as the author of his own history.
Quality Engineering in AI Services

This short paper discusses some of the challenges in testing AI systems, proposes some good practices and advocates a shift to a customer-driven approach, driven by problems customers need to solve rather than problems engineers can solve.
Executive Summary

Digitalisation opens up new possibilities for education. While education has always been rich in data such as grades or administrative information on students’ absenteeism, the use of data to help students learn better and teachers to teach better, and to inform decision-making in educational administrations is recent. Education stakeholders have had a difficult relationship with technology, alternating between strong enthusiasm and scepticism. Might digital technology, and, notably, smart, technologies based on artificial intelligence (AI), learning analytics, robotics, and others, transform education in the same way they are transforming the rest of society? If so, how might this look? This book explores this question.
Modular Design and Implementation for Rapid Deployment of Autonomous Systems

This paper describes the autonomous systems, which Technical University of Denmark used to participate in Challenge 2 of the Mohamed Bin Zayed International Robotics Challenge. We participated with two autonomous vehicles in the Challenge: an aerial and a ground vehicle. The mission of both of the vehicles was to locate blocks and use them to build a wall in a marked location. Our ground solution consisted of a SKID steered vehicle, with a Universal Robots arm attached to it, and our aerial solution was a DJI M100 quadrotor in X configuration, equipped with a rangefinder and camera. Both platforms each have their own custom build end-effector, designed for lifting flat magnetic objects. The software was designed with a modular approach based on the mobotware framework, such that mission scripts could rapidly be assembled at the deployment site. A state of the art neural network, for detecting blocks, was trained for our ground vehicle. The effectiveness of the modular approach was tested in the challenge, and our lessons learned is included in the paper.
SafeML Extensions for Human-Machine Cooperation

Robots that can coexist with humans are needed in manufacturing and service fields, but there are issues in ensuring safety. SafeML, which is a model-based approach to develop safe robots, has been proposed in the past. This time, we extend the specification to such human-machine cooperation and introduce a model example.
TED TALKS AS A MEDIA RESOURCE TO STIMULATE THE DEVELOPMENT OF PROFESSIONAL FLEXIBILITY OF SENIOR EXECUTIVES OF COMPANIES IN THE SYSTEM OF ADDITIONAL EDUCATION

In the context of the modernization of the economy in the BANI world, there is a strong urge for high-quality training of senior executives of companies with a high level of professional exibility. The purpose of this study is to theoretically substantiate the stimulation of the development of professional exibility when using TED Talks as an e-learning media resource. Using the methods of document analysis, theoretical analysis, comparison, contextual and morphological analysis and synthesis, the following results were obtained: the de nition of the e-learning tool TED Talks, identi ed its capabilities and substantiated the adequacy of the formation of professional exibility of senior executives of companies with its help. The TED Talks package of electronic tools was developed and tested, which includes materials for stimulating the development of strategic management abilities of senior executives of companies, human resources of the enterprise, market analysis, the use of technical innovation, action in unforeseen circumstances, and self-improvement. The materials of this article can be useful to teachers involved in the implementation of programs for continuing professional development in English.
Fine-Tuning OCR Error Detection and Correction in a Polish Corpus of Scientific Abstracts

The paper explores the idea of detecting and correcting post-OCR errors in a corpus of Polish scientific abstracts by first evaluating several available spellchecking approaches and then reusing one of the rule-based solutions to eliminate frequent errors most likely resulting from technical problems of the OCR process. The fine-tuning consisted in removing word breaks, rejecting corrections which change the case of the output, removing unnecessary spaces between word segments and restoring Polish letters replaced with spaces whenever the correction resulted in a valid Polish word. The obtained system proved competitive with language model-based solutions.
Object Search Method using Bayesian Estimation and Natural Language Processing for Mobile Manipulator

We propose a method that makes a mobile robot search for a target object using Bayesian estimation and natural language processing. When searching for an object, the robot must estimate where a person puts it. Otherwise, it takes too much time due to fruitless search. A previous research has proposed to implement human thinking processes on search to robots for efficient search. However, it is necessary to register the relation between each target object and the furniture where the object is put. Our method uses natural language processing to implement human thinking processes on search. The robot creates a map of the environment and divides the map to create an areas. Each area is evaluated by Bayesian inference and natural language processing. This allows robots to find objects efficiently. We have verified that this method works in a simulated environment built with Gazebo.
Multi-agent reinforcement learning based on estimation of others’ intentions leveraging self-policies

The complexity of Multi-Agent Reinforcement Learning (MARL) problems increases exponentially with the number of agents. Poor scalability to the number results in limited applications of MARL to large-scale multi-agent systems.
Machine Learning or Lexicon Based Sentiment Analysis Techniques on Social Media Posts

Social media provides an accessible and effective platform for individuals to offer thoughts and opinions across a wide range of interest areas. It also provides a great opportunity for researchers and businesses to understand and analyse a large volume of online data for decision-making purposes. Opinions on social media platforms, such as Twitter, can be very important for many industries due to the wide variety of topics and large volume of data available. However, extracting and analysing this data can prove to be very challenging due to its diversity and complexity. Recent methods of sentiment analysis of social media content rely on Natural Language Processing techniques on a fundamental sentiment lexicon, as well as machine learning oriented techniques. In this work, we evaluate representatives of different sentiment analysis methods, make recommendations and discuss advantages and disadvantages. Specifically we look into: 1) variation of VADER, a lexicon based method; 2) a machine learning neural network based method; and 3) a Sentiment Classifier using Word Sense Disambiguation, Maximum Entropy and Naive Bayes Classifiers. The results indicate that there is a significant correlation among all three sentiment analysis methods, which demonstrates their ability to accurately determine the sentiment of social media posts. Additionally, the modified version of VADER, a lexicon based method, is considered to be the most accurate and most appropriate method to use for the semantic analysis of social media posts, based on its strong correlation and low computational time. Obtained findings and recommendations can be valuable for researchers working on sentiment analysis techniques for large data sets.
Extending Smartphone-Based Hand Gesture Recognition for Augmented Reality Applications with Two-Finger-Pinch and Thumb-Orientation Gestures

Augmented Reality (AR) on smartphones, while limited compared to their headset-styled counterparts (e.g., Microsoft HoloLens and Magic Leap), may be improved by supporting Hand Gesture Recognition (HGR) without requiring the expensive hardware found on the said headsets. This study improves the overall smartphone support of an existing HGR framework, named Augmented-reality Mobile Device Gestures (AMDG), and adds two new gestures: two-finger-pinch and thumb-orientation gestures, which are alternatives to existing gestures that may help improve overall user experience. A user study is also conducted to evaluate the usability of these two gestures in a realistic scenario. This study finds that the two-finger-pinch gesture is possibly more usable than the air-tap gesture (popularized by HoloLens) for the purpose of moving AR objects in a scene, and that the thumb-orientation gesture is a potentially viable simplification of whole-hand orientation (with some caveats relating to ease of execution and detection).
Quantum Annealing Error Mitigation Using Mirror Symmetries on Different Generations of Quantum Annealers

We present an effective method of error mitigation on adiabatic quantum annealing machines. This method involves a mirror symmetric property of the adiabatic quantum device underlying graph. The methodology is tested on different generations of D-Wave annealing devices. An initial Hamiltonian is formed with two mirror- symmetric graphs k = k′, coupled with either ferromagnetic (M > 0) or antiferromagnetic (M < 0) graph edges, and then implemented on the underlying D-Wave Chimera graph. Examining the returned solution states at the end of annealing process, allows one to discard returned states that are not the ground state of the problem Hamiltonian. The approach is applicable to any quantum adiabatic device. We used the method to compare the performances of different generations of adiabatic devices.
Design of a performance evaluation platform for ultra-light crypto-system to develop a secure IoT node in edge computing

Internet of things (IoT) is an ever-growing technology involving various battery-operated remote devices. Such devices require security to avoid sensitive data loss, which is being communicated by the nodes. In such a scenario, lightweight ciphers (LWC) are used to provide security in a low-end IoT environment, which is essential to validate against a resource-constrained ecosystem. Many low resource-oriented LWCs like PRESENT, SIMON, and SPECK are proposed after AES, CLEFIA, Piccolo, and TWINE to maintain less area for security and more for application development. A novel framework is introduced in this paper for evaluating the performance of novel ciphers compared to previous ciphers. We evaluated the ANU, VAYU, and NUX compared to PRESENT, SIMON and SPECK using popular tiny devices concerning several important hardware metrics. This paper provides the importance of other LWC evaluations after the cryptanalysis phase and the use of framework setup for the hardware experts.
Proposal of Robot Hand using Closed Link Mechanism

In this research, we propose a robot hand using a closed link mechanism. The proposed robot hand (HSCR-HA) is used for communication with the deaf. The HSCR-HA has the closed link mechanism, which enables bending and stretching of fingers by wires and springs. Response characteristics of joint angles of fingers were experimentally evaluated. From the experimental results, The each settling time of each joint angles of index finger was 247 ms for the first joint (DIP joint), 238 ms for the second joint (PIP joint), and 175 ms for the third joint (MP joint). In addition, the effect of the hand direction is negligible for use as communication with the deaf.
THE TEAM TASK AS A MEANS OF DEVELOPING FOR SOCIO-CULTURAL COMPETENCES IN PRE-SCHOOL CHILDREN

In this article, the subject of the problem is that the social environment continuously is changing. That is why it`s inevitable for changes to occur in educational environments also, because education prepares the adolescent for his social existence as in the global society. A key task of modern education is to develop competences of the 21st century. Among them is socio-cultural competences which is important for child`s existence in the world of adults. The most important thing in modern education is to build in the child the ability to develop throughout life. More and more educators are looking for innovative methods and forms of work to help with the problems, mentioned above. The article proposes the team task as an innovative form of work for developing sociocultural competences in children. The publication`s hope is that it will reach to more teachers at the preschool stage because it is a fundamental stage for every child as a future student and later – an active citizen of the world.
CLI

In this chapter we briefly summarize the command line tools that you can use for building, administration, and some maintenance tasks running outside Android Studio.
Cryptanalysis and Repair of a Gabidulin Code Based Cryptosystem from ACISP 2018

This paper presents a key recovery attack on a rank metric based cryptosystem proposed by Lau and Tan at ACISP 2018, which uses Gabidulin codes as the underlying decodable code. This attack is shown to cost polynomial time and therefore completely breaks the cryptosystem. Specifically, we convert the problem of recovering the private key into solving a multivariate linear system over the base field. We then present a simple repair for this scheme, which is shown to require exponential complexity for the proposed attack. Additionally, we apply this attack to cryptanalyze another Gabidulin code based cryptosystem proposed by Loidreau at PQCrypto 2017, and improve Loidreau’s result in a talk at CBCrypto 2021.
A Conformer Based Automated Speech Recognition for Armenian Language

The article is aimed to represent Armenian automated speech recognition model and its applications in different fields of economy. Because of the lack of Armenian speech corpora, in this article we fine-tuned the voice recognition and text symbol generating parts using a Conformer pre-trained model and a compact Armenian language model. The article focuses the attention of readers on the problem of recognizing human speech and transforming it to a text, especially for non-mainstream languages. The paper is prepared with scientific abstraction and a combined analysis of many recent implementations of the discussed approach. The sources' credibility, relevance and authenticity have been confirmed by their extensive research. As to conclude, though it is pretty challenging to develop ASR model for non-mainstream languages, it was proven that the employment of Conformerbased transformers in conjunction with language models is effective for Armenian speech recognition. It was also proven that the technique employed in this article is applicable for other languages too, with some adjustments.
Klasifikasi Cerita Pendek Berbahasa Bali Berdasarkan Umur Pembaca dengan Metode Naive Bayes

Short stories are short stories that tell an event that has happened in a short and clear way. Parents should be able to choose short stories that are suitable for their children because if the stories that parents bring to children are not in accordance with their age, it can affect the development of children. In this study, we will build a system that can classify text. The method used in this research is Nave Bayes with feature selection, namely Genetic Algorithm. This research was conducted to help parents so that their children do not read short stories that are not appropriate for their age so that they do not interfere with their child's development. The data used are children's short stories, youth short stories and adult short stories in Balinese. The best model performance is generated in the training and validation process using new data. The results of testing the Naïve Bayes method without feature selection are 66% accuracy, 66% precision, 67% recall and 66% F1-score. While the Naïve Bayes method uses feature selection, namely 72% accuracy, 72% precision, 78% recall and 73% F1-score.
Development of Violin-playing Robot

This study reports design and fabrication of the left hand of a violin-playing robot. Our previous left hand uses a link mechanism and a rack mechanism, which are driven by RC servomotors mounted on the left hand. Since this increases the mass of the hand, it was necessary to reduce the weight of the hand to allow the left arm to move fast. Each joint of the new left finger is driven by a wire, which allows us to install the actuator outside of the hand. The mass of the fabricated left finger is small by 30 % compared with our previous hand’s finger. We conducted a step response experiment and confirmed that the finger reached to the reference angle within 0.8 ms.
Performance Analysis of Data Storage and Management Models for Microservice-Based Edge Systems

The rapid proliferation of distributed cloud applications has increased demand on computing infrastructures. Thus, it is important to reduce unnecessary data flow to cloud services to decrease costs and system latency for end-users. Accordingly, edge computing can provide significant benefits in optimizing data traffic. In terms of performance, heavyweight applications are undesired in edge systems. Instead, microservices are preferred for providing lightweight and suitable solutions for edge computing systems with limited resources. Importantly, the data storage and management mechanism used by a microservice-based edge system is a vital consideration for optimizing data traffic between the cloud and the end-user system. Ensuring data reliability and edge system performance depends on the adopted model. This study examined three different data storage and management models for microservice-based edge systems. The models included microservices with their own databases or where a database was distributed among microservices. All models were tested for synchronous and asynchronous operation of microservices in distributed edge devices. The study aim was to find a suitable data storage and management model, especially for microservice-based edge systems with limited resources.