Reviewerly/exHarmony huggingface dataset:
Colla-Config: A stakeholders preferences-based approach for product lines collaborative configuration

During collaborative configuration of software product lines (SPL), multiple stakeholders contribute together in building a single product specification. Conflicting situations can arise during the configuration process due to contradictions between some/all stakeholders’ configuration choices. Detecting and resolving such situation rise two major challenges: choosing which choices to omit, and taking stakeholders’ preferences into account. Several SPL collaborative configuration approaches are available. However, they either do not present detailed information on the strategies for conflict resolution, or they rely on a systematic process that resolves conflicts by prioritizing configuration decisions made at earlier stage, constraining therefore some of stakeholders’ choices. The lack of flexibility may hinder conflict resolution as choices taken at earlier stages overlay those at later phases. To mitigate these limitations, we propose a new collaborative configuration approach (Colla-Config) that provides a preference-based conflict resolution method within a free-order configuration process; each stakeholder expresses his/her preferences through a set of substitution rules, and freely makes his/her configuration decisions towards the desired product, without being constrained by the configuration decisions made by the other ones. To assess the feasibility and the usability of the proposed approach, we conducted a usability test designed following the ISO/IEC 25062:2006 Common Industry Format for usability tests. Results of the experiments provide preliminary evidence of the approach feasibility and the tool ability to properly support the SPL collaborative configuration.
New Trend of Doing Things with Technology Pertaining to Nursing “Technology modern trends that drive Healthcare”

Nursing is dynamic by its own way and this dynamism give rise to various trends. Sound empirical knowledge is the base of nursing as in any other profession. This knowledge is the base for all the innovations which in turn evolve as trends in nursing. The trends in nursing education are the cornerstone for the dynamic nature of nursing profession. The article outlines various trends in nursing education with reference to India. Thus, the software can be seen as part of an abstract rationality, whereas how it is deployed by nurses is based on a practical rationality that places practice and experience first and sees the technology and protocols as tools.
Digital competency factor analysis among the digital native generation

The purpose of this study is to develop and analyze the feasibility of a digital competency measurement tool suitable for the digital native generation. The study was conducted among 394 four-year college students of E University located in Gyeonggi-do. As for the research method, the factors composing digital competency were synthesized through a literature review on the constituent factors of digital competency. The sub-measurement items were developed focusing on the constituent factors of digital competency derived through literature review. As for the data collection method, an online survey webpage was opened, and an e-mail was sent to the participating students so that they could participate in the survey. The collected data were analyzed using the PASW Statistics 18.0 program. First, a frequency analysis was conducted to examine the demographic and sociological factors of the subjects. Furthermore, to find out the digital competency level of university students, the digital native generation, the average value was calculated with descriptive statistics. In addition, factor analysis was performed to analyze the convergent validity of detailed indicators of each area of the digital competency measurement tool. As a result of measuring the digital competency of the students participating in the test, the level of digital competency perceived by the students was found to be generally high, and in particular, the overall average of the sub-factors in the application area showed a high average value for all three sub-factors. Also, as a result of analyzing the validity of the digital competency components, the overall explanatory variance of the 54 component models developed in this study was high.
Simulation of Web Page Big Data Capture Method Based on WNN Optimized by Locust Algorithm

In order to improve web page big data capturing ratio, the wavelet neural network (WNN) optimized by improved locust algorithm is established for capturing web page big data. First, the web page big data method is established, and the corresponding mathematical model is studied. Secondly, the neural network is established, and Legendre wavelet basis function is used as excitation function of hidden layer of WNN, and the theory models of input layer, output layer and hidden layer are constructed, and then the improved locust optimization algorithm is designed based on Levy flight local search strategy, linear decreasing parameter random jump strategy, decreasing coefficient update strategy and weight coefficient update strategy. Finally, a case study is carried out for validating the proposed web big data capturing method, results illustrate that the proposed method based on WNN optimized by improved locust algorithm can effectively improve web page big data capturing efficiency and accuracy, which has wide application view.
A Cooperative Flow Simulator for Distributed Computing Based on Full-Dimensional Definable Network

To improve the efficiency of cluster computing, the research of cooperative flow scheduling algorithms provides another idea for further optimization. Cluster computing frameworks such as Spark and Map-Reduce carry running cluster computing tasks and have distinct stage division and dependency characteristics. With limited network resources, the overall completion time of the job can be reduced by minimizing the wait time of the computing phase due to the bottleneck of transmission capacity. The introduction of an artificial intelligence algorithm can provide a solution to this NP-hard problem. The simulator designed in this paper can realize the overall process of cooperative traffic generation, scheduling policy configuration, and scheduling effect feedback closed-loop through packet sender, packet receiver, scheduler, and programmable switch components according to the dependency between cluster computing stages.
High Capacity Information Hiding Method Based on Interpolation and Ones’ complement

Data hiding is an important technology for privacy protection. The proposed information hiding method is based on neighborhood mean interpolation (NMI) and $1'\mathrm{s}$ complement. Different from other previous schemes, the proposed method can embed at least one bit of secret data in each pixel. Also, in some cases, secret data is converted to its one’s complement. This makes the hiding ability better than other schemes. Experimental results comparing the proposed interpolation method with other methods show that the proposed method achieves more than 20% improvement in hiding ability and 8% improvement in PSNR.
Traditional Chinese scene text recognition

Signboards, street signs, billboards, slogans and advertisements which can be seen everywhere in the urban area contain a lot of text and convey many information. If these street texts, which provide text information about the location, can be automatically located and identified in the image, it will be useful for application including scene understanding, smart cities, construction of smart transportation, robotics, automatic steering, assisting visual impairments or travelers. Therefore, this paper uses artificial intelligence technology to recognize the text in the scene. The recognition results can be used in various places to make daily life more convenient and technological.
Design of a Low-power Compass FIR Filter for Electrocardiogram Signals Noise Removal

In recent years, electrocardiogram measuring instruments have been developing towards miniaturization, which has also promoted the development of miniaturization of circuits and low power consumption. FIR filters are suitable for filtering out noise and revealing the obvious characteristic waveforms in an electrocardiogram, but they have high power consumption. Therefore, under the premise of maintaining stable performance and the advantages of low power consumption, this paper proposed a new architecture named the compass form FIR filter. When the high order number M = 256, the power consumption of the linear phase form was 28.2112 mW, while the power consumption of the compass form FIR was 24.0749 mW. The power consumption of the compass FIR was lower than that of the linear phase form FIR, with a difference of 4.1363 mW. Therefore, the compass form FIR filter designed in this paper had the advantages of low power consumption and high filtering performance under set conditions and high order specifications.
A New Way to Squash Bugs: Functional programming is hard to learn but yields fewer nasty surprises

YOU'D EXPECT THE LONGEST ANDMOST COSTLY PHASE in the life cycle of a software productto be the intital development of the system, when all those great features are first imagined and then created. In fact, the hardest part comes later, during the maintenance phase. that's when programmers pay the price for the shortcuts they took during development. So why did they take shortcuts? Maybe they didn't realize that they were cutting any corners. Only when their code was deployed and exercised by a lot of users did its hidden flaws come to light. And maybe the developers were rushed.pressures would almost guarantee antee that their software will contain more bugs than it would otherwise.
Crowd crush detection in large mass gatherings via federated learning across multicamera environment

Crowd crush in mass gatherings during large events are more frequent nowadays. It may get threatening quickly and even cause the death of many. Single camera surveillance is not efficient in large events spreading over wide areas. In multicamera surveillance environment, the centralized decision may not be favourable due to solitude and safety concerns. Moreover, existing neural networks need a large amount of training data for accurate detection. This paper proposes a low-cost system that uses a federated learning setup with light-weight model to reduce overheads during training and protect crowd privacy. We introduce a new loss function, denoted by contrastive focal loss, to reduce false positives and organize overcrowded regions in minimal time. We collect crowd crush and stampede videos to create a new annotated dataset, named as CrowdStampede. We achieve good results under different data distribution settings.
Creating an Asset Development Plan

An Asset Development Plan (ADP), also known as an Integrated Development Plan (IDP), Integrated Program Plan (IPP), or Product Development Plan (PDP), is the project team’s guide for how to maximize the value of an asset. This chapter describes the utility of an ADP in drug development and the best-practice contents of a complete ADP. For development project managers who are creating an ADP for the first time in a company, this chapter will enable them to create a skeleton document for their team to start with. For development project managers in an organization that already has ADPs, this chapter will describe the context for each of the key components.11.1 Introduction
Construction of WeChat public platform for Japanese learning based on Internet+

In order to meet the diversified needs of Japanese learning, this study, combined with the concept of Internet +, conducts research on the construction of WeChat public platform for Japanese learning. Firstly, the relevant research concepts and the basic architecture of the platform are determined, and then the database and relevant important technologies applied in the platform are discussed in detail. Finally, on this basis, the expected functional modules of the WeChat public platform for Japanese learning are described, so as to provide reference for future teaching and learning based on the WeChat public platform.
Application research of gesture recognition based on lightweight neural network

With the promotion of smart city and other technologies, the application of embedded vision detection equipment is becoming more and more popular, among which gesture recognition is an important application of embedded vision detection equipment. At present, gesture recognition technology on embedded visual detection equipment is mostly implemented by calling API in domestic and foreign researches and products. But this method needs the support of stable communication network and has certain delay problem. To solve the above problems, this paper proposes a lightweight neural network model that can be deployed on embedded devices, which can realize local gesture recognition on embedded terminals without network remote transmission. The network builds a training framework on PyTorch and uses a homemade dataset for training, then lightens the network and finally deploys on raspberry PI for gesture recognition. Experimental results show that this network can run at a higher rate in raspberry PI 4B (4GB), and the model size is greatly reduced. The final recognition effect is good, and it has high practical value.
Design of multimedia vocal music learning system based on Visual C++

With the continuous development of digital multimedia technology, digital multimedia technology has realized the integration with medical treatment, education, traditional scientific research and other fields, and become the trend of future development. The application of digital multimedia technology to reform vocal music performance teaching is an important means of innovative vocal music teaching, but also an inevitable choice to promote the development of vocal music teaching. Digital multimedia technology will be one of the irreplaceable important carriers in vocal music performance teaching. In the application of digital media, many new teaching modes have appeared in the design of vocal music learning system in colleges and universities. Digital multimedia technology has effectively broken the limitations of traditional vocal music teaching and provided new possibilities for the informatization and modernization of vocal music performance teaching and learning. This paper mainly describes the design of multimedia vocal music learning system based on Visual C++, according to the current problems in multimedia vocal music teaching, and put forward their own solutions, the purpose is to speed up the design process of multimedia vocal music learning system, improve the progress of students learning.
Metadata design and integration algorithm of science and technology resources among colleges

Under the influence of the epidemic, the offline cooperation between college laboratories has decreased, more and more cooperation is going online. Therefore, the research on the integration and sharing of heterogeneously described university resources has become a hot topic. Based on some scientific metadata standard research, this paper proposes metadata standards including university talents, instruments, laboratories by analyzing the metadata standards of existing scientific data. Then, a heterogeneous scientific data integration mapping algorithm is designed.
Malicious SQL data injection detection

SQL injection attack could obtain sensitive information in the database, tamper or delete illegally obtained information, etc., which causes immeasurable losses to the system. Aiming at SQL injection attack, this paper proposes a new SQL injection detection scheme that combines traditional detection methods with abstract syntax tree structure judgment based on semantic analysis. The solution includes modules such as data preprocessing, SQL statement pre-assembly, and semantic analysis. By assembling the user input content and the actual SQL template statement to form a complete SQL statement, the statement is subjected to structural judgment and semantic analysis to determine the request and precisely identify malicious injection attack.
Particle swarm optimization algorithm based on biological symbiosis mechanism and adaptive inertial weight

On the basis of the standard particle swarm optimization and the bionic theory, the standard particle swarm optimization algorithm is improved based on the biological symbiosis mechanism, and the weight selection strategy and search space of the standard particle swarm are improved. The weighted particle swarm optimization algorithm (Particle swarm optimization based on biological symbiosis mechanism and self-adaptive inertia weight, PSO-BSMSIW) has been verified by the test function, and the algorithm has significantly improved the convergence speed and accuracy.
GHG Impact Analysis on the Performance of Solar PV Output using SVM Kernel Debugging

Day ahead forecasting of solar PV plant will enable the market operator to participate in the spot market. Increase in greenhouse gas concentration such as COx, NOx and SOx in the air is also affecting the performance of solar PV (SPV) performance not directly but indirectly. The decrease in solar concentration due to the interaction of GHG has a direct relationship on the performance of SPV output. In order to investigate this effect, here the author has made an attempt to show the impact of GHG concentration on solar PV performance using MATLAB program. Disturbance in solar irradiance has been given as an input as a function of GHG concentration. All the results were validated using experimental analysis.
Towards Data Minimization and Access Control for Immunization Data Sharing

The global interest in taking preventative measures has intensified in response to the coronavirus epidemic. The vaccination certificate is one approach used to control the spread of disease while enabling people to carry out their regular lives and interact with each other as they normally would. Most services require their users to provide proof of immunization; however, the information they require seems to be either overly personal or unrelated to the service's intended use. Immunization Information System (IIS), the data owner, is indeed accountable for safeguarding client data and privacy in accordance with ethical considerations. In order to ensure that requests for data access are acknowledged by data subjects and that only the fields required to fulfill the usage purpose are given, some mechanisms must be presented. In this study, consent management blockchain with add-on modules that enable loose-coupling integration with existing vaccination applications is presented in an attempt to provide such functionality without adding extra burden to IIS. To limit the quantity and sensitivity of the data retrieved, a data filtering scheme is proposed. Additionally, a source authentication technique is introduced to guarantee that data is delivered to the authorized requesters. To make sure all transaction requests are processed regardless of limitations in the execution capability of the blockchain, job queues are presented to reduce transactions' conflicts. This allows multiple transactions to be executed in parallel and resolves scalability and performance concerns which are the major issues found when integrating blockchain with large-scaled production systems.
On Performance Measures During Behavior Detection Algorithms Implementation - Case Study

During the last few decades, the development of information and communication technology, Internet of Things (IoT), Big Data and AI has brought several unique tools with extraordinary added value. One can easily see that all these technologies and tools are now available via standard services at home, in cars, in a public life and during the social interconnection with the environment. Machine learning is a technology that computers can learn on their own to create and predict models. Furthermore, deep learning is a field of machine learning using deep neural network theory, using the principle of neural network corresponding to the human brain. Expansion of cities and population growth necessitate utilizing automated video surveillance and computer vision-based analyses for pedestrian and vehicle safety together with the growth of number of cars and traffic infrastructure [1]. All these aspects of modern technology give us several questions. How can we be so sure that all these “smart” algorithms work reliably? In this work, we introduce a case study for predicting an object behaviour with respect to its safety. Predicting trajectory of an object, either being detected or occluded, provides to predict all probable risky situations by exploiting the last seen parameters of the object movement even when it disappears. All the scenes, including potential collision situation, rely on object detection and tracking. One question remains! How can we measure the performance?
Apply Manta Ray Foraging Optimization to Solve the Continuous-Time Markov Chain Problems

Continuous-time Markov chains problems (CTMCP) are continuous-time, discrete-state stochastic problems that can be modeled by the continuous-time Markov chains. Solving the CTMCP by existing algorithms becomes highly time-consuming when the problem size is increased. Ordinal optimization (OO) theory provides a reliable framework to solve CTMCP. However, the stochastic inequality constraints limit the efficiency and competitiveness of OO theory. In this work, a method combining ordinal optimization (OO) and manta ray foraging optimization (MRFO) is developed for solving the CTMCP in a reasonable time. MRFO is a swarm intelligence metaheuristic technique that arises from the modeling of the hunting mechanism of manta rays in nature. The proposed method is applied for finding the optimal number of agents to minimize the total cost of agents under service level constraints in a multi-skill call center. Experimental results of the proposed approach are compared to three heuristic methods. Simulation results show that the proposed method can obtain an illustrious decision vector with a higher computing performance and solution quality than the three heuristic approaches.
Architectural Patterns

Software engineering is as much about teamwork as it is about technology. This introductory textbook covers both. For courses featuring a team project, it offers tips and templates for aligning classroom concepts with the needs of the students' projects. Students will learn how software is developed in industry by adopting agile methods, discovering requirements, designing modular systems, selecting effective tests, and using metrics to track progress. The book also covers the 'why' behind the 'how-to', to prepare students for advances in industry practices. The chapters explore ways of eliciting what users really want, how clean architecture divides and conquers the inherent complexity of software systems, how test coverage is essential for detecting the inevitable defects in code, and much more. Ravi Sethi provides real-life case studies and examples to demonstrate practical applications of the concepts. Online resources include sample project materials for students, and lecture slides for instructors.