Reviewerly/exHarmony huggingface dataset:
Design and analyze one object recognition system with human in the loop for unmanned platforms with 5G communication

Unmanned platforms (unmanned aerial vehicles, unmanned vehicles, etc.) have been widely used in various fields. They are generally controlled by human-in-the-loop remote control systems. The video returned by them will greatly help people's work and life, but traditional communications bring challenges to high-speed, ultra-low-latency unmanned platform applications. The large-bandwidth, high-reliability, and low-latency communications provided by 5G technology can well meet the application requirements of human-machine cooperation in unmanned platforms. Visual search represented by object recognition is a very common task in daily life. Although current automatic algorithms can complete part of the task, they have weak understanding and poor environmental adaptability; human operators have strong comprehensive perception capabilities and good environmental adaptability. However, the accuracy is low, individual differences are large, and fatigue is easy. Based on 5G technology, achieving human-machine cooperation can significantly improve system performance. This paper models the process of the human-in-loop multi-object recognition task in unmanned systems and designs four different ways of collaboration between human and expert systems. In addition, we propose to switch the four collaboration manners can be switched dynamically. Especially, based on human factors engineering experiments, this paper analyzes the improvement of the overall system performance with the help of the expert system and the impact of different collaboration manners on the efficiency in the target recognition task. They can provide support for the collaboration between human and unmanned platforms in the context of 5G applications.
Analytics of Multiple-Threshold Model for High Average-Utilization Patterns in Smart City Environments

For the accelerated development in ICT technology and computers, data mining and pattern analytics are used to reveal potential patterns for decision-making in smart city environments. Past works of pattern mining in smart cities focused on frequency constraint that cannot show the patterns involved with multi-factors for evaluation. Also, single-threshold value is mostly considered in the pattern-mining framework, which is not realistic in smart city environments since different infrastructures should have different tolerance factors for pattern analytics. In this paper, we then employ the multi-threshold constraint to evaluate the high utilization patterns that can be applied in the smart city environments. The average-utilization model is also adapted in the designed model that provides a fair and alternative criterion for pattern analytics. Based on the provided results in the experiments, the designed framework shows better effectiveness and efficiency in pattern mining task that can be deployed to analyze the utilization of the varied infrastructure in smart city environments.
Plagiarism Detector using Long Term Common Tracking

In this paper, we will build a cheat detector that scans the text file and divides the binary; Labeling the file as it is written depends on how well the text file matches the source text. Fraud is an effective area of research; Function is not important and the difference between alternately inserted answers and actual function is usually small. This paper is designed with three sections: Data Exploration, Feature Engineering and Training. In this paper we have detailed the terms and conditions of transparency found in our research. We hope to help improve the quality of education in this field and to be involved in solving certain problems in the higher education system (with our questionnaire support and trust results).
Well Begun Is Half Done: How First Respondeners Affect Issue Resolution Process in Open Source Software Development?

Addressing issue reports is an integral part of open source software (OSS) projects. Although several studies have attempted to discover the factors that affect issue resolution, few pay attention to first responders, who is the first to post their comments after an issue report is published. We are interested at how first responders affect issue resolution process for OSS projects. Therefore, we extract the data from Github to perform our empirical study. By obtaining their identity types and speech acts, we analyze the impact of first responders with different identity types on the efficiency of issue resolution based on three metrics and find that identified users especially collaborators make first response can improve the efficiency of issue resolution. Furthermore, we make use of the identity type information of the first responders to forecast the issue lifetime and the results show that this information can also improve the accuracy for short-term prediction. It also verifies that first responders have a direct influence on the issue resolution process.
Using Cardano's method for solving cubic equation in the cryptosystem to protect data security against Cyber attack

With the development taking place these days in information technology and protecting data security of data transmitted over the internet, there is an urgent and necessary need in order to protect data from falling into the hands of unauthorized persons. The difficulty of breaking the cipher text representing by using multiple keys instead of one key in the process of encryption and decryption, so it found that the mathematics represent a basic in many sciences because of the wide using for the concepts of the equations and functions, so one of the important using of the mathematics is in the cryptography science because all the cryptosystems in the world dells with the arithmetic operations, in this paper a new cryptosystem presented through using the 3ed order equation (cubic equation) for one variables and using Cardano's method for solving cubic equation, in order to add more security and complexity to the proposed cryptosystem since there is four different symmetric keys and changeable formula of the equation, many cryptanalysis applied on the proposed cryptosystem to ensure the validity and secrecy of the proposed algorithm, all results show the strength of the cryptosystem against the attacks as shown in the result section.
Sistem Informasi Profil Desa Berbasis Web (Studi Kasus: Desa Purwosari)

In this very modern era, people are required to know and understand developments in existing technology. Technology makes it easy to help every human activity both in the academic world, development, and so on, including in the field of government. The government sector includes village administration. At this time, Purwosari Village still uses a manual system to provide information so that in the end the community cannot get the information needed at any time, so a lot of information is unknown. The purpose of this study was to build a website-based village profile information system in Purwosari. This website-based village profile information system was built using the Prototype method and using DFD and ERD in the website design process. This system will have several features, including village profile, population data, and information related to the village. The result of this research is a website-based village profile information system that can help Purwosari village government employees, and also makes it easier for the village community to get information in Purwosari village.
Multi-sensor Network-Based Trajectory Planning for an Internet of UAVs

In this paper, we present a multi-sensor network-based autonomous trajectory planning scheme for collision avoidance for multiple aerial vehicles. When multiple aerial vehicles are involved in a possible collision, all the aerial vehicles start to form a network by exchanging their information and intentions so as to resolve collisions by maintaining a relative static velocity with respect to their neighbors. Three problems that have arisen from the above process are solved in this paper: (1) how to form a multi-sensor network for the aerial vehicles involved in a possible collision; (2) how a newcomer joins an existing network; and (3) how each aerial vehicle leaves a network and continues to fly in its own direction. Simulations show that, compared with other collision avoidance algorithms, the multi-sensor network-based scheme can solve a large-scale collision avoidance problem and save computation time.
Generalized Conics: Properties and applications

In this paper the properties of the generalized conics are used to create a unified framework for generating various types of the distance fields. The main concept behind this work is a metric that measures the distance from a point to a line segment according to the definition of the ellipse. The proposed representation provides a possibility to efficiently compute the proximity, arithmetic mean of the distances and a space tessellation with regard to the given set of polygonal objects, line segments and points. In addition, the weights can be introduced for objects, their parts and combinations. This fact leads to a hierarchical representation that can be efficiently obtained using the pixel-wise operations. The practical value of the proposed ideas is demonstrated on an example of applications like skeletonization, smoothing and optimal location finding.
Fault Early Warning and Location of Dry-Type Air-Core Reactor Based on Temperature Field

Dry-type air-core reactor is an important equipment in the power system, and its fault can bring great hidden danger to whole system. Most of the existing fault diagnosis methods of the reactor can be divided into three categories: current-based methods, current-based additional effects methods, and temperature-field-based methods. Generally, for constructing the temperature field, the sensor needs to meet the position constraint, that is, all sensors remain the same location on each equipment. However, it is difficult to satisfy this constraint in real work scenarios. To solve this problem, we propose a new method which uses a multi-component normal distribution to fit the temperature field, and then compares the measured temperature with the ideal temperature to infer the running status of the dry-type air-core reactor. Because the RFID chip have stable performance and is wireless passive, we use this chips to collect the temperature of the reactor. The verification experiments show that our proposed method is feasible and effective.
Efficient Private Information Retrieval Protocol with Homomorphically Computing Univariate Polynomials

Private information retrieval (PIR) protocol is a powerful cryptographic tool and has received considerable attention in recent years as it can not only help users to retrieve the needed data from database servers but also protect them from being known by the servers. Although many PIR protocols have been proposed, it remains an open problem to design an efficient PIR protocol whose communication overhead is irrelevant to the database size <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"><mi>N</mi></math> . In this paper, to answer this open problem, we present a new communication-efficient PIR protocol based on our proposed single-ciphertext fully homomorphic encryption (FHE) scheme, which supports unlimited computations with single variable over a single ciphertext even without access to the secret key. Specifically, our proposed PIR protocol is characterized by combining our single-ciphertext FHE with Lagrange interpolating polynomial technique to achieve better communication efficiency. Security analyses show that the proposed PIR protocol can efficiently protect the privacy of the user and the data in the database. In addition, both theoretical analyses and experimental evaluations are conducted, and the results indicate that our proposed PIR protocol is also more efficient and practical than previously reported ones. To the best of our knowledge, our proposed protocol is the first PIR protocol achieving <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"><mi>O</mi><mfenced open="(" close=")" separators="|"><mrow><mn>1</mn></mrow></mfenced></math> communication efficiency on the user side, irrelevant to the database size <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"><mi>N</mi></math> .
A Novel Approach for Improving Security in Software Development in Small Software Firms: A Literature Review

Developing secure software is really a challenge now for all types of software industry like small or big industry. Security is an essential part of any type of software development. There is a number of drawbacks to our existing system of software development starting from conceptualization to the last phase of an SDLC Software security does not depend on maintaining security in each step of software development but also it depends on the technology we are using for maintaining the security of the software. In this paper, we did a literature review to identify the basic security challenges during development of a software and also pointing out research gap. Here, around sixty research articles are reviewed related to software issues or software security.
Unsafe image classification using convolutional neural network for brand safety

Contextual advertising is an advertising form in which the advertisements are served by automated systems based on the context of the host websites. In contextual advertising, deciding the matching level between a brand and a website context is crucial. Brand safety is a strategy to keep a brand's reputation safe by avoiding advertisement placements on inappropriate websites. In this paper, we approach brand safety as an image classification issue to classify and filter websites containing inappropriate images. We propose an image multi-class classification method in order to recognize some categories using for brand safety purpose. We also apply pruning techniques in order to reduce model complexity. In addition, we create a dataset including 56,501 images in six categories: adult, gambling chip, gore, gun, knife and safe. Experimental results show that our proposed method achieves better performance compared to some original methods.
Design of output fluctuation smoothing strategy in photovoltaic power station

The output power of photovoltaic (PV) power station has strong fluctuation and randomness. Large-scale photovoltaic grid connection will affect the safe operation of power grid. In this paper, the smoothing strategy of PV output fluctuation is designed based on the adaptive moving average algorithm, which combined with the PV power prediction technology. The energy storage system compensates the difference between the grid-connected reference power and the actual generation power in real time, smoothing the grid-connected power of PV power station. Firstly, the relationship between the length of fixed sliding window and smoothness, as well as volatility in the moving average algorithm is explored to provide theoretical basis for subsequent parameter selection. Then, in order to enhance the adaptive performance of the algorithm, an adaptive moving average algorithm is proposed to dynamically adjust the length of the sliding window according to the actual power volatility. The PV power prediction curve is smoothed based on the algorithm so that the grid-connected reference power curve can be obtained. Finally, three typical weather conditions of sunny day, cloudy day and overcast day are taken as examples to simulate. The results show both feasibility and effectiveness of the strategy designed to smooth output fluctuation of PV power station.
Characteristic of basic tools of mobile learning in informatics

The article actualizes the possibilities of mobile learning based on the use of mobile devices and technologies available to almost all students. Various approaches to the definition of the concept of "mobile learning" are analyzed, including techno-centric and information-centric approaches. The concept of mobility as one of the attributes of learning tools is revealed. The importance of mobile learning in the current difficult situation of distance learning during the pandemic is substantiated. The characteristic features of mobile learning are highlighted, affecting its main functions, learning tools and independence from the time and place of learning. Possible directions for the implementation of mobile learning are characterized, from simple transfer of educational content to compliance with basic educational theories. From the point of view of the functioning and directions of development of mobile learning, its basic principles in teaching informatics are formulated. The types of students' activities are briefly characterized; some advantages of mobile learning are highlighted and its features as visualization, interactivity, efficiency of use in teaching children with disabilities are characterized. Some popular educational apps for mobile devices are considered, their characteristics are given, and their educational potential is revealed. Examples of mobile applications are given, the use of which in informatics lessons will help to activate the educational and cognitive activity of students and stimulate them to engage in informatics, coding and robotics.
Intelligent Development of Safety Production System under 5G+ Industrial Internet

Abstract As an opportunity for countries around the world to revitalize the manufacturing industry and the transformation and upgrading of our country’s manufacturing industry, the production safety system is an opportunity for the development of advanced information technology, manufacturing technology and artificial intelligence. At this stage, intelligent manufacturing has set off a global research boom. This article mainly introduces the research on the intelligent development of the safety production system under 5G+ Industrial Internet. Through the intelligent research on the safety production system, the development of the early warning system model of the safety production system is carried out. This paper uses 5G + Industrial Internet combined with intelligent manufacturing technology to establish an early warning model. Increase the efficiency of the production system by 34%, greatly reducing the possibility of safety accidents. Based on the traditional safe production system, facing the development needs of intelligent manufacturing technology, and taking the training goal of advanced skilled talents as the direction, this paper deeply analyzes the requirements and characteristics of the training model for the intelligent manufacturing system, and constructs the corresponding Intelligent manufacturing safety production system.
Wordform as the main basis for analysis of natural language text

In the article discuss the application aspects of wordforms of natural language text for decision the mistakes correction problem. Discuss the merits and demerits of two known approaches for decision – deterministic and based on probabilities/ Construction principles of natural language corpus described, wich apply in probability approach. Declare conclusion about necessity of complex using these approaches in dependence on properties of texts.
Energy-Efficient Resources Management in Container- Based Clouds

Cloud enables access to a shared pool of virtual resources through Internet and its adoption rate is increasing because of its high availability, scalability and cost effectiveness. However, cloud data centers are one of the fastest-growing energy consumers and half of their energy consumption is wasted mostly because of inefficient allocation of the server’s resources. Therefore, this thesis focuses on software level energy management techniques that are applicable to containerized cloud environments. Containerized clouds are studied as containers are increasingly gaining popularity. And containers are going to be major deployment model in cloud environments.
Security of multimedia content for ownership identification using signaling technique

The information shared over network like audio and video files will be having major challenge due to security credentials. In large scale systems like cloud infrastructure used to improve the better security from past one decade. The contents are like pictures, audio and video clips are shared over the online training sessions in recent days. Therefore the video files are used to protect using digital signature and digital watermarking. The content of the multimedia files are require the better environment for sharing of knowledge using private and public clouds. The digital signature method is used for multimedia components such as 2D and 3D video clips and shared among the users on cloud infrastructure will be predicted with various cloud based security techniques.
VIRTUAL MUSEUM TOUR IN WASAKA BANJARMASIN TO INTRODUCE THE COLLECTION OF LEADERS AND LOCAL HEROES BASED ON MOBILE AUGMENTED REALITY TECHNOLOGY IN THE NEW NORMAL ERA

Wasaka Museum is one of the museums in Banjarmasin City. However, the information obtained by visitors at this time is only from short writings near the object of the image, and museum guards cannot accompany visitors to get around. Furthermore, the interest of museum visitors has also decreased due to the unavailability of adequate information, minimal services, and the impact of the COVID-19 pandemic. The purpose of this research is to develop applications using Mobile Augmented Reality Technology as a means of promotion, trying to attract visitors with AR interaction treats, and the form of virtual museum tours. The methodology used is the Agile Development Method with the type of Extreme Programming (XP). Then the A/B Testing Method is used to select the user interface design. Marker-Based Tracking is a method of detecting markers so that 3D objects can appear. The conclusion is that the selected interface design is design B with a percentage of 76.9%, all the features in the application have functioned very well, and the results of the usability evaluation with a percentage of 83.33% have an Excellent predicate which means that they can be recommended for further use at the Wasaka Museum Banjarmasin in the New Normal Era.
RobLab: A Testbed for Integrated Perception, Planning, and Control

We present the perception, planning, and control of RobLab, a robotic adaptation of the marble maze game “Labyrinth.” We first present a framework which is capable of autonomously solving the maze by following a planned path. This is achieved using RGB threshold filters to detect the maze walls and track the marble, an A* search to generate a path, and a PID controller to guide the marble along the path. A Behavior Tree is then used to extend this framework to include additional behaviors which improve the system's robustness and enable the operator to override if requested. Experimental results and the adequacy of Behavior Trees as a tool for robotic task execution are discussed. This work aims to provide a case study in prototyping high-level robot behaviors which could later be deployed to a more complex system.
Challenges and Opportunities for Security Assurance in DevOps

This chapter contains background information on the concepts that form the basis for the research. The author provides an overview of the integration of security activities in traditional procedural approaches and discusses the potential differences in agile, iterative, contexts. Concepts such as “continuous integration,” “continuous deployment,” and “shift left” are introduced. The challenges and opportunities to achieve security assurance in DevOps environments are discussed, and the objective of the research project is presented.