Reviewerly/exHarmony huggingface dataset:
Risk-aware Multi-robot Collaboration with Arrival Deadlines in Uncertain Environments

In this paper, we study the problem when a team of robots needs to reach a goal area subject to arrival deadlines, including the time-of-arrival (TOA) deadline and the time-difference-of-arrival (TDOA) deadline. The TOA deadline places an upper limit on the time that all robots arrive at the goal area while TDOA places an upper limit on the difference between the arrival time of any pair of robots. We first propose a formal definition of TOA risk and TDOA risk based on the probability that the TOA deadline and TDOA deadline are violated. Then we propose a new algorithm to derive the optimal communication strategy for the team of robots to minimize the TOA risk and the TDOA risk. In particular, the new algorithm first uses the Monte Carlo method to generate training datasets for a given communication strategy. Then two neural networks are trained to approximate the function that describes how the TOA risk and TDOA risk are related to the communication strategy and the TOA/TDOA deadlines. Obtaining the two neural network models allows the subsequent computation of gradient to optimize the communication topology for the minimization of the TOA risk and TDOA risk. Finally, simulation examples are presented to illustrate the effectiveness of the proposed approach in obtaining optimized communication topologies that are close to the ground truth.
Line Follower Robot Training and Introduction of Internet of Things (IoT) for Students in Jombang City

Background: During the Industrial Revolution 4.0, the Internet of Things (IoT) is the main pillar of people and machines connected to each other. It can be an intelligent system when combined with a robot. This is what underlies the importance of robotics and IoT training, especially to be introduced early on. Purpose: This activity aimed to improve students' knowledge and skills in technology. The target of this activity is high school students in Jombang City. Methods: It starts from the planning, implementation, and evaluation stages. Auditory, visual and kinesthetic techniques are used in this activity, which is in the form of interesting learning media such as power points, videos, as well as demonstrations and practices. Data collection techniques such as questionnaires, pre-test, and post-test, and running tests were carried out to measure the level of skills, knowledge, and satisfaction of participants. Results: A total of 85% of participants did not know about IOT and 83% of the participants already know what the robot. But only 17% ever make robots. Conclusion: After this activity the participants' understanding increased by 20%. Their skills also increased as evidenced by the participants programming themselves so that the robot can run well on the track.
Geochemie a radioaktivita paleozoických hornin na listech 15-31 Bruntál a 15-33 Moravský Beroun a jejich souvislost se složením variské hydrotermální mineralizace

This paper deals with the natural radioactivity of Palaeozoic rocks on the map sheets 15- 31 Bruntál and 15-33 Moravský Beroun in the NE part of the Bohemian Massif. Studied rocks belong to the Vrbno Group (greenschists and phyllites) and mainly to the MoravoSilesian Palaeozoic, particulary to the Andělská Hora, Horní Benešov and Moravice Fms. Potassium, uranium and thorium contents were measured in 1 596 rock samples using a laboratory gamma–ray spectrometer, values of mass activity of 226Ra equivalent (am) were calculated. The average am of analysed rock samples is 138 Bq.kg-1. This value is very close to the am value calculated for the average continental crust. Natural radioactivity of flysch sedimentary rocks of the Andělská Hora, Horní Benešov and Moravice Fms. (1 350 analysed samples, avg. am = 150 Bq.kg-1) grows from psefi tes (conglomerates) to psammites (dominating greywackes) up to the group of aleurites and pelites (siltstones, silty shales, clay shales). The highest uranium and thorium contents, along with other metals (Cs, Ga, Rb, Sn, Zr, La, Ce, Pb, Zn, As) were found in flysch rocks of the Horní Benešov Fm. in the area near Valšov: greywacke shows content up to 13 ppm U and 25 ppm Th (am = 364 Bq.kg-1) and siltstone up to 21 ppm U and 43 ppm Th (am = 624 Bq.kg-1). Low-grade metamorphic mobilization of elements is documented by hydrothermal minerals in syntectonic quartz veins which are e.g. fluorite, sulphides, REE-bearing phases, U-bearing phases.
Minimizing Synchronization Error in Compressed Domain Watermarking

TheDutta, Tanima compressed domain video watermarking hasSoni, Aishwarya been less expensive sinceGupta, Hari Prabhat complete decoding and then re-encoding is not required for watermark embedding. Handling synchronization error due to embedding is a challenging task, especially, due to motion compensation. In this paper, we propose an embedding scheme that can minimize desynchronization in the watermark extraction process at the decoder for embedding in compressed videos with better visual quality. Experimental results show the effectiveness of the proposed scheme.
BACKGROUND, PECULIARITIES AND FACTORS OF THE DEVELOPMENT OF TECHNOPARKS IN RUSSIA

The article considers the genesis of science, education and business integration forms, as well as reviews the key premises for the emergence and development of technoparks in Russia. The current state of technoparks in Russia, resulting in revealing various factors, affecting the successful functioning of technoparks in a particular region of Russia has been analyzed. It has been concluded, that high research and educational potential of the territories, in which the technoparks are located, remains key condition to the development of the latter
Visual Representation of Adjacencies A NetLogo application to turn functional matrices into bubble diagrams

This paper is based on the assumption that a key challenge of good design is spatial organization as a result of functional requirements.The authors present a new NetLogo application that assists designers in understanding proposed functional relationships (of spaces) by visualizing them graphically.In more detail, the tool translates adjacency matrices (as representation of functional relationships) into a graph (in architecture known as bubble diagram).The latter can be considered as a pre-step of the actual design, by which the information about functional interrelations becomes more readable and understandable for the designer.
Digital Governance in Rural Schools of Sri Lanka

ICT has been used as a model for education in many parts of the world. At the end of the conflict in 2009, the Government of Sri Lanka embarked on an e-Sri Lanka initiative aimed at introducing ICT across several sectors. The education sector received substantial investment in ICT, but only a section of this sector was targeted. This study explores the barriers of introducing and implementing ICT. The analysis of the case studies together with the variables identified from the literature review provided the basis for developing the conceptual framework for the study. The target population for this study were teachers and principals in the rural schools of Trincomalee representing the rural population in Sri Lanka. A combined sample of 70 teachers and principals were considered for this survey across 20 schools in the district. The results indicate that internet access, resources, personnel, and security are essential for introducing and implementing ICT education in the rural areas.
Plain language: Can it ever be plain enough?

Three versions of a financial form were compared to each other with regard to usability, understanding and respondents’ experiences. The first version did not explicitly use any plain language techniques; the second version of the form explicitly used some plain language techniques and in the third version even more plain language techniques were employed. Mixed methodologies were used to analyse the three versions. The results of the study show that the first version of the form is the least usable, understandable and is associated with the worst experience, while the second version is more usable, understandable and respondents had a better experience with it. Despite this, the second version still has many issues which are solved in the third version. The study concluded that successfully implementing plain language techniques is an iterative process of testing and refining. The study also concluded that the third version of the form had only marginally better results than the second version, suggesting that the success of implementing plain language techniques might be influenced by other factors – that certain themes or fields are difficult by their very nature and that the employment of plain language techniques do not always have the desired effect.
Morphology-Agnostic Visual Robotic Control

Existing approaches for visuomotor robotic control typically require characterizing the robot in advance by calibrating the camera or performing system identification. We propose MAVRIC, an approach that works with minimal prior knowledge of the robot's morphology, and requires only a camera view containing the robot and its environment and an unknown control interface. MAVRIC revolves around a mutual information-based method for self-recognition, which discovers visual “control points” on the robot body within a few seconds of exploratory interaction, and these control points in turn are then used for visual servoing. MAVRIC can control robots with imprecise actuation, no proprioceptive feedback, unknown morphologies including novel tools, unknown camera poses, and even unsteady handheld cameras. We demonstrate our method on visually-guided 3D point reaching, trajectory following, and robot-to-robot imitation.
Using Virtual Reality Technology for Studying Physics

The field of education is relatively conservative, but at the same time fast evolving sphere of human activity all around the world and in Kazakhstan as well. This is due to constant advances in all technology areas and in information technology in particular. New teaching and learning approaches, methods and techniques are introduced into the educational process, applying various technologies like artificial intelligence, computer vision, robotics, etc. And virtual reality is one of those. Virtual laboratories are one of the computer-based learning systems that can help to study various processes (physical, chemical, etc.) simulating and visualizing them on a personal computer without using the actual equipment or reagents. Moreover, with the help of such simulations it is possible to observe the process in detail, from different points or enlarge the image to a convenient size. In this paper an application that helps to study physics in secondary schools is presented. It contains a set of practical problem tasks from a number of physics sections. Each task has visualization scene with virtual reality integrated. In the article the content, architecture and interface of the application are presented along with the short review of other research in the field of application of virtual reality in education.
Adaptive Background Subtraction Using Manual Approach for Static Images

Background subtraction is considered as one of the preprocessing stage in case of applications related to foreground for dynamic images where the background is removed completely. But if static images are considered, then background subtraction cannot be done in the same manner as in dynamic images as there is no frame difference. Taking the advantage of this, it is proposed to remove the background fully or selectively as per the requirement. This is called as adaptive background as the algorithm adapts to the method used for the selection of the background. The first method proposed is manual, where the required background is selected manually and the success of this depends on the accuracy with which the user can select the background region. Going one step ahead, the next method suggested is the improvement over the first where the region to remove. This region is selected automatically by using seed point technique. The advantage of these techniques for static images is that any region considered as background can be removed as per the need of the user.
Experimental Review Of Mobile Learning Technology Research Activity Theory Framework: 2014 – 2019

In that study, we thoroughly reviewed the pilot cell discipline studies posted of 2014–2019. Moreover, the activity theory framework was adopted in imitation of inspect the insights then trends on cellular learning. That is, the dimension about context, tools, control, communication, topics and objectives have been busy according to analyze the studies. It was once determined so close empirical cellular learning research eager college students between real-world contexts, then the activities were carried out primarily based of the existing faculty curriculums. This potential that researchers yet faculty teachers pointed out the charge concerning situating students into significant study via assisting them link as that had learned from the textbooks in imitation of real-world scenarios and daily life environments. In the meantime, the research frequently worried the college students of actively the usage of cellular structures with verbal exchange facilities according to gather potential through interacting together with peers, events, yet unique real-world education pursuits within the environment. On certain hand, many researchers proposed according to promote students' motivation; of the ignoble hand, those anticipated according to observe more on where the learners, particularly novices yet low-achievement students, had done now staring at theirs previous interactions. Even so, that was found as cellular gadgets had been viewed a important road on permitting students after accumulate self-learning materials instead than solely intercession lesson throughout contexts. As the contemporary research execute remain regarded in accordance with incorporate blended instead than purely selfpaced learning, at that place is nonetheless a extensive space because cellular learning development or development.
A Distribution Protocol for Dealerless Secret Distribution

As the value of bitcoin increases, more incidents such as those involving Mt Gox and Bitfinex will occur in standard centralised systems. The addition of group-based threshold cryptography with the ability to be deployed without a dealer and which supports the non-interactive signing of messages provides for the division of private keys into shares that can be distributed to individuals and groups to provide additional security. This scheme creates a distributed key generation system for bitcoin that removes the necessity for any centralised control list minimising any threat of fraud or attack. In the application of threshold-based solutions for DSA to ECDSA, we have created an entirely distributive signature system for bitcoin that mitigates against any single point of failure. When coupled with retrieval schemes involving CLTV and multisig wallets, our solution provides an infinitely extensible and secure means of deploying bitcoin. Using group and ring-based systems, we can implement blind signatures against issued transactions.
Actuators in Informotion Study

At first, the contemporary situation of recent several years in which noncontinuous innovation occurs continuously is shown. Next, an author’s vision of an ideal society in 2050 is shown. Then, the image of the actuator in 2050 is prospected from the history of the progress of the actuator technology and the present state of the latest research. By 2050, cyber-space (virtual world) and physical-space (real world) will be fused and form a society. All actuators and sensors in the world should be connected through the crowd network. The “Informotion” deals with such network with reference to living organisms. The outlook of informotion in the future and some social system applications are shown.
Prediction of Energy Storage Capacitor Values Based on Neural Networks. (Case of a Planar Capacitor)

Energy storage is a very important operation in continuously operating systems, such as telecommunications systems, embedded systems and power systems. Energy storage can be performed by various means such as batteries and super capacitors. In our work, we used neural networks to determine the capacitance values C of the planar capacitors as a function of the relative permittivity εr, the distance d and the dimensioning (Width and Length) of the capacitor plates and as a function of the maximum desired charge Qmax. The results of simulation will be better and more satisfying if the databases are richer and good.
Entity Relationship Extraction Method Based on Dependency Syntax Analysis and Rules

With the advent of the Internet era, the content of network information has largely increased, hence information extraction has became significant. As an important sub-task of information extraction, entity relationship extraction is also paid more and more attention. Most current entity relationship extraction methods not only require manual annotation, but the quality of annotation also cannot be guaranteed, besides the evaluation criteria has not been unified yet. Therefore, this paper proposes an entity relationship extraction method based on the combination of dependency syntax analysis and rules. The method does not need to annotate the input text manually, dependency parsing is used to determine the sentence components and the relationships among them. Meanwhile, a semantic triple representing entity relations is formed and output by combining rules. The experiment results shows that the method proposed in this paper has a good effect and saves labor cost. The average accuracy in corpus reaches 63.04%, the average output time of triples is shortened as well.
Modified Multi-Grey Wolf Pack for Vital Sign-Based Disease Identification

Noninvasive process of vital sign identification and design of low-cost decision-making system for the betterment of rural health care support is a prime facet of research. The identification of bio-signals from different sensors, noise removal, signal processing, and decision making requires the use of sophisticated expert system. In this chapter, the authors propose a modified multi grey wolf pack optimization technique (MMGWO) for better generalization and diversification. The basic model has been modified using net energy gain of the individual wolf in the process of hunting. Here multiple packs of wolves are considered with simultaneous sharing and conflict among them. The performance of the proposed technique is tested on 23 well known classical benchmark functions, CEC 2014 benchmark problem set along with classical real-life applications. The experimental results and related analysis show that the proposed MMGWO is significantly superior to other existing techniques.
A New Architecture of Service Composition-Based Context-Aware Mobile Learning System

During recent years, the use of mobile devices has been increased with the big evolution of wireless communications and technologies. In the field of education, mobile technologies can have a great influence on learning. Mobile learning (m-learning) is a new technology which enables learners to acquire learning materials anywhere and at any time using mobile and internet technologies. However, learner mobility implies a permanent change of context. So, the adoption of context-awareness in mobile learning has become a crucial topic in this area. In this paper, we propose an architecture of m-learning system based on contextualization and service composition using the orchestration approach. This architecture will automatically and dynamically meet the needs of the user and provide him with appropriated learning resources according to the context changes. Thereby, we focus on the main subsystems of this architecture, and then we propose a scenario of electrotechnic lab using our proposed architecture.
Evaluation System for Groove Feelings Evoked by Drum Sounds

In this study, we define stochastic models for tight and loose groove feelings and propose an evaluation system for the groove feelings evoked by drum sounds. There are two main types of groove feelings, tight and loose, and they are known among professional musicians and music enthusiasts. These groove models are defined as a bivariate normal distribution with deviations for snare and bass drums as random variables. As an application of these models, we propose our evaluation system, in which a monaural, polyphonic drum set recordings is input and evaluations regarding tight and loose are output. We conducted an evaluation experiment and showed that this system correctly identifies tight and loose groove feelings.
Research on Trusted Cloud Computing in Cloud Environment from Security Perspective

"Cloud computingprovides" the brand-new calculation mode for data analysis processing in the current IT field. In other words, the cloud-end data calculation system constituted by lots of server groups can replace the single operation system with the center of personal computers. In order to further discuss the network safety under the "cloud computing" environment, the effective network safety strategy was proposed.
REKA: Relation Extraction with Knowledge-Aware Attention

Relation extraction (RE) is an important task and has wide applications. Distant supervision is widely used in RE methods which can automatically construct labeled data to reduce the manual annotation effort. This method usually results in many instances with incorrect labels. In addition, most of existing relation extraction methods merely rely on the textual content of sentences to extract relation. In fact, many knowledge graphs are off-the-shelf and they can provide useful information of entities and relations, which has the potential to alleviate the noisy data problem and improve the performance of relation extraction. In this paper, we propose a knowledge-aware attention model to incorporate the knowledge graph information into relation extraction. In our approach, we first learn the representations of entities and relations from knowledge graph using graph embedding methods. Then we propose a knowledge-aware word attention model to select the informative words in sentences for relation extraction. In addition, we also propose a knowledge-aware sentence attention model to select useful sentences for RE to alleviate the problem of noisy data brought by distant supervision. We conduct experiments on a widely used dataset and the results show that our approach can effectively improve the performance of neural relation extraction.
Dynamics of Narrow-Minded Belief and Its Cut-Free Sequent Calculus

The purpose of this paper is to consider and formalize an important factor of human intelligence, belief affected by passion, which we call narrow-minded belief. Based on Public Announcement Logic, we define our logic, Logic Of Narrow-minded belief (LON), as that which includes such belief. Semantics for LON is provided by the Kripke-style semantics, and using this semantics, we formally analyze the mental state of the hero of Shakespeare’s tragedy Othello as an example of narrow-minded belief and its formalization. A proof system for it is given by a Hilbert-style proof system. In addition to that, we provide a complete labelled sequent calculus for LON based on the Hilbert-style proof system, and it syntactic cut elimination theorem is shown.