Reviewerly/exHarmony huggingface dataset:
Architecture and design considerations for an autonomous mobile robot

Autonomous mobile robots (AMR) are utilitarian autonomous vehicles that navigate by sensing the environment; this is in contrast to the traditional automated guided vehicles (AGV) which follow predefined paths. This work presents the development and architecture of an industrial AMR for mixed indoor and outdoor navigation.
A Spread Spectrum Based Audio Watermarking Method with Embedding Positions Adaption Using Predominant Local Pulse Extraction

In this paper, a spread spectrum based audio watermarking method with embedding positions adaption is proposed. A method of predominant local pulse (PLP) extraction is introduced to adaptively search for suitable embedded positions. Embedding watermark information at specific positions can reduce the amount of data modifications, thereby suppressing signal distortion caused by embedding. In addition, a embedding procedure based on spread spectrum, which provides robustness, is used in the DCT domain. The method discussed herein can embed watermark not only imperceivable but robust under common signal processing attacks and some of de-synchronization attacks.
The principal Erdős–Gallai differences of a degree sequence

The Erdős–Gallai criteria for recognizing degree sequences of simple graphs involve a system of inequalities. Given a fixed degree sequence, we consider the list of differences of the two sides of these inequalities. These differences have appeared in varying contexts, including characterizations of the split and threshold graphs, and we survey their uses here. Then, enlarging upon properties of these graph families, we show that both the last term and the maximum term of the principal Erdős–Gallai differences of a degree sequence are preserved under graph complementation and are monotonic under the majorization order and Rao's order on degree sequences.
The open discovery initiative &amp; promoting transparency in discovery

NISO recently updated the Open Discovery Initiative Recommended Practice (https://www.niso.org/publications/rp-19-2020-odi), which outlines best practices for working with library discovery services. It defines ways for libraries to assess the level of content provider participation; streamlines the process by which libraries, content providers and discovery service providers work together; defines models for “fair” linking; and suggests usage statistics that should be collected for libraries and for content providers. The recommendations in this document, created by members of the Open Discovery Initiative Standing Committee, enable libraries, discovery service providers, and content providers to work together to the full extent of their abilities - providing the most effective and rich experience to end users.
NIST Testing of a Knapsack Symmetric Cryptosystem on Hamlin Codes Using Source Block Injections

This article proposes a constructing option for a knapsack symmetric cryptosystem based on Hamlin codes. The paper considers a knapsack cryptosystem with a shared memory and a knapsack packing density of more than one, which provides resistance to the Lagarias - Odlyzhko attack. The authors suggest using the bases of recurrent sequences of finite order that ensure the packing density of the knapsack is more than one. The design of the proposed cryptosystem operates in the block-linking mode and uses a block cipher based on Hamlin codes to construct it. The paper presents an encryption algorithm based on Hamlin codes using injections (mutations) of the original block. The authors have carried out NIST test of a knapsack symmetric cryptosystem on Hamlin codes using injections (mutations) of the original block. The results of the test revealed that injections for binary signatures significantly increase the frequency characteristics and, consequently, the cryptographic strength of the encryption system.
Automated DJ Pad Audio Mashups Playback Compositions in Computer Music Utilizing Harmony Search Algorithm

To expedite the arduous music compositions, computer music is essential to combine with the application of computing to music to assist music composers to create music rapidly and creatively using the computer algorithms under the computer musicology with the combination of interdisciplinary computer science and music fields. The prime of the utilizing algorithmic into DJ Pad system is that the physical DJ systems are not portability feasible for everyone due to complexity, time consuming and exorbitant cost. Therefore, the proposed research employs the metaheuristic optimization algorithm that is Harmony Search Algorithm (HSA) to simplify the automated tasks in the sample audio mashups that the audio files are associated with the button at the DJ Pad. Although certain rules are applied that certain keys consist of chords as in audio sample format cannot be played together, the output of the numbers from the HSA algorithms can be mapped as the combinations of the single key or multiple keys pressed in order to automate the audio mashups to produce the music as whole. Due to the same repetitive and mundane combinations using manual methods, it is interesting to allow algorithmic composition to take over to for inspirations to have new set of patterns routinely generated to avoid similar repetitive mashups when it is played manually. Thus, it could transpire the musicians to go beyond the limits of the possible mashup combinations that we humans are not aware of. Since there are numerous metaheuristic algorithms existed, the results and the output of the findings can be used as the benchmark to other popular metaheuristic algorithm that is none other than Genetic Algorithm (GA) to compete the pleasant output generated for the audio mashups
A Cryptocompression System Using AAβ Algorithm and Goldbach G1 Codes

Cryptography is the answer to the problem of digital data security and data compression is the answer to the problem of data size. This study discusses crypto-compression on text files using the AAβ cryptographic algorithm and the Goldbach G1 Code compression algorithm. This test was carried out on homogeneous strings, heterogeneous strings and artificial corpus. bits in the file under study range from 1 to 100000 bits. The value of Compression Ratio (CR), Ratio Of Compression (RC), Space Savings (SS) and Bit rate are calculated in the compression test. The number of bits generated in the encryption and decryption process will be counted in cryptographic testing. In this study, the resulting ciphertext has a size 8 times larger than plaintext. And the size of the ciphertext after being compressed can be reduced bymore than 35%.
Adjustment Level Metrics for Requirements in Project Management

The correct and complete definition of the requirements that are part of the scope of a project is crucial for its successful management. They are usually expressed through a set of raw data and originate from different documents. This article presents a proposal of metrics to determine the degree of completeness of the requirements. Such metrics are based on the combination of simple mathematical models with natural language processing techniques to analyze the degree of completeness and estimation of activities, and the degree of estimation of costs and human resources. This paper describes a proposal of metrics are described, presents a statistical evaluation and the applicability to real cases.
Pandemic Symptoms Real-Time Ranking Platform

COVID-19 takes an increasing share of everyday life and imposes the need for an exploratory data analysis executed by both, professionals and the general public. The primary focus of this paper is designing and implementing a system for processing the vast amount of case data available to obtain overall statistics for symptoms and rank them in real-time. Processing the current data and providing a mechanism to process new data generated in real-time from diverse and many sources is one of the current challenges. Our solution to tackle the challenge is to execute the processing in a massively parallel way enabled by CUDA along with principles and constructs for efficient parallel programming, which are eminent due to the volume and velocity of data, thus, checking the validity of a research question is it possible to process Covid-19 big data challenges more efficiently with GPU-based parallel constructs.
Computer-aided Translation Based on Lampung Language as Low Resource Language

The dialect of api is one of the Lampung dialects. Students, from elementary school to high school, learn the Lampung language as an effort to preserve the local language. For immigrant students who learn Lampung dialect of api, they should use the Lampung language dictionary to help understand the Lampung language. Using the dictionary manually and repeatedly is ineffective and tedious. This study aims to build an initial model of computer-based Lampung language sentence translator machine. The main purpose of the Lampung language sentence translator machine is to help students learn to understand Lampung language sentences with the help of computers automatically. The Lampung language sentence translator machine works by utilizing the Lampung language dictionary. This study made two contributions or novelty. First, dictionary-based Lampung sentence translator machine and dictionary-based Lampung sentence translator machine with additional stemming and post-editing techniques. The Lampung sentence translator machine was tested using 50 Lampung sentences. Translation results were measured by the bilingual evaluation understudy (BLEU) algorithm. In the dictionary-based Lampung sentence translator machine, the translation accuracy is 46.50%, while the dictionary-based Lampung sentence translation machine with additional stemming and post-editing techniques obtains an accuracy of 58.06%.
Folded Electronic Textiles: Weaving, Knitting, Pleating and Coating Three-Dimensional Sensor Structures

Abstract This article reports findings from a one-month design research project in which four textile and fashion designers engaged in collaborative exploration of technical and artistic knowledge inherent in folds and folding. They experimented with textile technologies and construction methods to design, fabricate and analyze three-dimensional dynamic materiality in electronic textiles (e-textiles). The focus was on sensor structures achieved by knitting, weaving, pleating and coating techniques. The analysis of measurements of electrical resistance between one and 36 sensing areas per sample demonstrate the added value of folds integrated into textile sensor structures. The authors discuss types of folding and their aesthetic, textural and sensorial advantages. Detailed information on design, fabrication and experimental results is provided in supplemental materials to the article.
Pervasive Healthcare Computing as a Scientific Care Discipline for Patients

One of the most important issues for people healthcare is how to serve significantly developed facilities to an increasing ratio of needy persons using their financial resource and less available healthcare facilities. Pervasive healthcare service has chosen a positive healthcare solution to many prevailing issues, and it is showing an optimistic conceivable future of the modern healthcare services. Pervasive healthcare may be defined as healthcare service to any needy at anytime and probably anywhere by almost ignoring time and some other constraints including proper coverage and very high-quality real-time services. This chapter discusses an integrated healthcare information system that is designed to use healthcare care and intelligent real-time emergency system, and many applications of healthcare systems, including pathological clinical proof methods as well as the future of pervasive healthcare systems, are also presented and discussed including various aspects.
An Optimal Production Plan for Cashew Nuts Community Enterprise Using Metaheuristic Algorithms

The proper production plan plays an important role in the cashew nuts market enterprise in order to reduce cost. This study aims to find the optimal production plan for cashew nuts using ant lion optimization (ALO), symbiotic organisms search (SOS), particle swarm optimization (PSO) and artificial bee colony algorithm (ABC). The novel objective function is introduced in this study. Three input data set, including production cost, holding cost and inventory quantity are investigated. The experiment cases consist of the frequency of production cycle time in January, February and March, respectively. As a results, four algorithms are available to estimate not only the proper production plan of cashew nuts but also an ability in reducing the inventory and the holding costs. In summary, the ALO algorithm provides better predictive skill than others for the cashew nuts production plan with the lowest RMSE value of 0.0913.
Implementation of KDML-Based Channel Estimator on GNU Radio Platform

Deep learning (DL) technology has been applied to a number of thorny problems in the field of communication, among which channel estimation is always attracting interests. However, DL is often used as an independent channel estimator which have ignored the effective role of traditional estimation methods for practical communication system. Recently a KDML-based channel estimator is proposed which combines traditional channel estimation and DL methods and obtains improved performance in simulation experiments. This paper verifies KDML-based channel estimator on a software-defined radio (SDR) platform. To do this, we design a KDML-based channel estimator framework on GNU radio platform and build an orthogonal frequency division multiplexing (OFDM) system containing learning modules. This framework adopts the long short time memory (LSTM) network to fine-tune the results of the least squares (LS) estimator according to KDML. We collect the channel state information (CSI) on GNU radio platform to train the LSTM network offline and reload the LSTM network back to the GNU radio platform to perform the online channel estimation. The simulation results and air-interface tests both validate the performance of the KDML and effectiveness of our proposed framework.
Research Complex for Unmanned Autonomous Vehicles Control Systems

The software architecture of the testbench complex for unmanned vehicles is presented. The complex is intended for development, modeling and experimental research of control systems of wheeled, tracked and multi-rotor vehicles. This article presents the prototype of wheeled unmanned vehicle, created for training and bench tests in field of collaborative robotics control. Such test bench should solve the problems of researching the control algorithms of individual robots and their groups which ensure the formation of a group of robots with a given orientation in space and automatically control their joint movement along the desired trajectory with preserving the spatial configuration. The solution is achieved using the proposed software and hardware architecture, which is a set of independent programs that exchange signals through the Robot Operating System. The result is the control system for group of mobile robots that includes the motion surface, the technical vision system, mathematical methods of motion control and specialized software. This test bench can reduce the costs associated with the development, implementation, and testing of unmanned vehicle control systems.
Formation of readiness of bachelor chemists for professional and pedagogic interaction with students in the context of digitalisation of education

Digitalisation of education contributes to higher requirements for pedagogue’s qualification, since not only digital competency becomes necessary, but also readiness to transform the teaching process and implement new approaches to the interaction with students using digital educational components. In this regard, there are difficulties in organising professional training for students non-pedagogues with the right to carry out professional activities in the field of education, due to the specifics of their training profile. The article presents the results of the study devoted to the problem of students' readiness formation for professional-pedagogic interaction with pupils in the educational process with digital components, on the example of undergraduate students of ‟Chemistry” training direction. The search for ways to solve the indicated problem is seen in the organisation of their psychological, pedagogic, and methodological support in the process of internships. Experimental work included the development and subsequent testing of the developed programme. Its generalised structure, stages of implementation and applied methods are given in the text of the article. Comparative and contrasting analysis of the data obtained in the process of experimental work allowed drawing conclusions about the effectiveness of the experimental work. Statistical analysis allowed establishing the reliability of the obtained data, indicating the positive dynamics of forming future bachelor chemists' readiness for professional-pedagogic interaction with pupils.
Linguodidactic potential of the electronic textbook as an innovative means of teaching a foreign language at the technical university

The paper considers the features of development and practical use of an electronic foreign language textbook at the technical university. This study is dictated by the need to resolve contradictions between the provisions declared by the higher education standards of the latest generation and the real level of students knowledge of a foreign language. The authors analyze and systematize the requirements for printed and electronic foreign language textbooks. Attention is paid to the advantages of electronic publications over printed ones. The key advantage of the electronic textbook is the presence of hypertext, which makes it possible to implement a nonlinear form of information organization. The paper formulates basic principles of an electronic textbook development, describes its structure and components and highlights the issues of filling the content with language material. The authors proposed the options for tasks aimed at stimulating students communicative and cognitive activity. It is shown that podcasts can be used as multimedia resources to intensify the development of students listening skills. It is emphasized that the availability of special programs for creating electronic textbooks allows the teacher to carry out its development without any special training in the field of programming. As a result of the analysis, the authors come to the conclusion about a high linguodidactic potential of the electronic textbook as a teaching tool.
Understanding Developers’ Work - A Visual Approach for Project Managers

One of the Project Manager’s main activities is to lead the people involved in the project. This activity implies in assembling teams, recognizing the work done by developers, distributing knowledge in the project, among others. Understanding the developers’ work can support the Project Manager in leading the team. In this sense, different strategies have been proposed to provide information about the work done by developers. But, there are still gaps to be explored, such as considering the evolution of the software when visualizing how much the developers have worked and providing the visualization from different perspectives, including project information and individual developers’ work at multiple levels of granularity. In this paper, the Developer Tracker approach is presented to support the Project Manager in understanding the developers’ work. This approach has a set of steps, including SCV mining, calculating quantitative measures, and applying a software visualization technique. To evaluate Developer Tracker, a computational support used by 16 Project Managers from the software industry was developed in an experimental study. The results showed that, in general, the approach was useful in improving Project Managers’ understanding.
Subjective and intuitive decision-making by managers

The article describes the characteristics of the mechanisms of managerial judgments and intuition. It is considered how: intuition and judgments are based on extensive experience and knowledge; they can be understood from the point of view of signal recognition and subsequent recall of relevant experiences from memory. It is shown that intuition and judgment are an analysis that is fixated on the ability to react quickly through recognition. Some pathologies that are often found in managerial behavior, caused by emotions and stress, as well as the lack of appropriate habits, are revealed. In conclusion, it is suggested that managers include the «future» in the managerial «style» or habit.
Robot Obstacle Avoidance Based on Improved Artificial Potential Field Method

Robot avoiding obstacles is a prerequisite for the robot to complete the specified tasks. In order to solve the shortcomings of the traditional artificial potential field method, this paper proposes an improvement plan to establish a new repulsive force function to change the direction of repulsive force to avoid the problems of unreachable target points and local minimum points. Finally, simulation experiments results that the improved artificial potential field method has strong robustness in the face of complex and dynamic scenes, and can reach the target point smoothly.
Allocation of English Remote Guiding based on Deep Reinforcement Learning and Multi-Objective Optimization

Distance education and traditional education are two teaching methods coexisting in modern society, which play an important role in the process of education popularization. The most obvious advantage of distance learning is that students can not be constrained by time, place, space and other aspects. Through distance learning, students can freely arrange their own learning time and schedule. According to the characteristics of superparameter optimization process, this paper uses deep neural network to build an agent to optimize superparameter. On the basis of priority experience playback, the priority of the pre state of the updated sample is adjusted, which makes the sampling more efficient.
A Decentralized Pattern Formation and Navigation Approach For Swarms: Multi-UAV Perspective

This paper proposes a decentralized formation control approach for the swarm of Unmanned Aerial Vehicles (UAVs). The system requires no predefined leaders and followers, and only local information is needed to control the individual UAV. In the proposed algorithm, each UAV motion constitutes local information such as pose and velocities shared with several other closest neighbors using the Nearest Neighbour Search (NNS) algorithm. The proposed approach leveraged a 3D mapping technique known as OctoMap for mapping unknown terrain and uses a variant of Rapid Exploration Random Trees (RRT*) algorithm with path length minimization as optimization objective for UAVs swarm path planning and navigation. We found that our proposed approach can be applied in a hazardous environment where an extensive area needs to be covered for search and rescue missions. The proposed algorithm is tested and validated with three different experiments on a dynamic simulator showing promising results.