Reviewerly/exHarmony huggingface dataset:
Developing a Risk Management Model for Banking Software Development Projects Based on Fuzzy Inference System

Risk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information technology (IT) systems in all fields and the high failure rate of IT projects in software development and production, it is essential to effectively manage these projects is essential. Therefore, this study is aimed to design a risk management model that seeks to manage the risk of software development projects based on the key criteria of project time, cost, quality and scope. This is presented after making an extensive review of the literature and asking questions from experts in the field. In this regard, after identifying the risks and defining them based on the dimensions and indicators of software development projects, 22 features were identified to evaluate banking software projects. The data were collected for three consecutive years in the country's largest software development eco-system. According to Rough modelling, the most important variables affecting the cost, time, quality and scope of projects were identified and the amount of risk that a project may have in each of these dimensions was shown. Since traditional scales cannot provide the accurate estimation of project risk assessment under uncertainty, the indexes were fuzzy. Finally, the fuzzy expert system was designed by MATLAB software that showed the total risk of each project. To create a graphical user interface, the MATLAB software GUIDE was used. The system can predict the risks of each project before each project begins and helps project managers be prepared to deal with these risks and consider ways to prevent the project from failing. The results showed that quality and time risks were more important than cost and scope risks and had a greater impact on total project deviation.
Planning in the Browser

Traditionally, planning tools are designed as applications that users need to install, taking care of the specificities of their operating system, packages, etc. This often places a significant burden on users, especially due to the academic nature of the software. To remedy this situation, here we propose for planning to jump onto the growing trend of light-weight software use: We demonstrate the possibility to run planning tools directly in the browser. We used the emscripten framework to port Fast Downward into WebAssembly (WASM) code, which allows for in-browser execution at near-native speeds. This allows for in-browser PDDL editing and planner execution without the need for server-side resource management. Moreover, it opens up a host of new possibilities, ranging from the interactive presentation of planning-based analysis to new applications exploiting the availability of planning in browsers to perform user-centric analyses.
Community building through social media in a rural context

The proliferation of social media has transformed the interface between technology and interpersonal communication. In the rural context, there is scarce work done to understand the use of social media by farmers with the objective of community building. To address this gap, the current study endeavoured to gain insights into the WhatsApp community in the rural context formed to facilitate farming among the community members in developing country like India. In this study, an attempt has been made to understand how WhatsApp, as a platform for content generation and sharing, is used by a group of farmers located in remote villages of Gujarat, India. From the study, it is evident that the WhatsApp platform helped to share locally relevant, mainly, the farming related information. WhatsApp group has enabled the members to create their content, and therefore has given rise to a new information and communication ecosystem.
Analysis of Site Selection Optimization of Construction Industrialization Base via Improved Particle Swarm Optimization Algorithm

In order to select the site of the construction industrialization base scientifically and rationally, the METROPOLIS sampling and membrane computing methods are adopted to improve the particle swarm optimization algorithm, and the realization of the improved algorithm in the optimization of the site selection of the construction industrialization base is introduced. In this study, the quantity of the construction base is determined in the actual terrain, and the optimization results before and after the improvement of particle swarm optimization algorithm are compared and analyzed. The result shows that the terrain here is suitable for the establishment of 7 construction industrialization bases. In the optimization of site selection, the improved particle swarm optimization algorithm can help to obtain better site selection optimization results, whose fitness is improved from 1.75 to nearly 1.87. It proves that the improved particle swarm optimization algorithm via METROPOLIS sampling and membrane computing is more efficient than the traditional one. This study is of very important reference value for the application of improved particle swarm optimization in construction industrialization.
Learning Cloud Computing & Core Concepts - Cloud Basics Webinar

The Basics of Cloud Computing Cloud computing is a service that instead of housing servers and databases internally you can have them hosted in a data ...
CCTV News Broadcast Information Mining

CCTV News Broadcast is one of the most popular news programs in China, and it is also the most important propaganda platform in China. CCTV News Broadcast is established to "Improve the quality of publicity", so it is "A product of visual culture of national ideology" and "Taking politics as the standard" is primary appeal. [1] At present, there is little research on the text of CCTV News Broadcast. This paper focuses on the CCTV News Broadcast, using the visualization model based statistics and semantic based keyword extraction model (SKE) to extract the text features of CCTV News Broadcast. It can help the public quickly capture the key information of CCTV News Broadcast. Moreover, this paper also forms a set of Chinese corpus with keywords tagging in the field of CCTV News Broadcast. It provides important data support for machine learning method and subsequent research. In addition, aiming at some important problems found in this paper, this paper proposes further research direction for text data processing in CCTV News Broadcast field.
Sistem Pakar Mendeteksi Kerusakan Sepeda Motor Menggunakan Metode Naïve Bayes di Bengkel Motor SMK Islam Tanjung)

Expert systems are systems or programs that behave as experts. Expert systems are knowledge-based systems that can be used to help solve problems that exist in the real world. Naive Bayes is a simple probabilistic classification that calculates a set of probabilities by adding up frequencies and combinations of values from a dataset, so Naive bayes can be used as a method in expert system applications to determine the probability of a damage that may occur on a motorcycle. in this study, an expert system application was created that could detect motorcycle damage and was able to provide solutions such as an expert at Islamic Vocational High School  Tanjung motorcycle repair shop that built  by using the php programming language .
Arabic To Bangla Machine Translation Using Encoder Decoder Approach

Machine Translation is one of the sub-fields of computational linguistics which includes broad analytical models enlarged by using extremely advanced semantic knowledge. We have converted the Arabic sentences to its corresponding Bangla equivalent sentences using a Neural Machine Translation (NMT) system operated with fixed vocabulary by using Sequence to Sequence (Seq2Seq) mechanism which is structured approach for automatically transferring the source sequences to the target sequences. From experiments,we have achieved 69.76% accuracy in this discipline.
HEART OVER THE HEAD: SCIENCE TEACHERS’ INFLUENCE IN DEVELOPING SELF-AWARENESS AMONG THEIR ADOLESCENT STUDENTS

Self-awareness, at any stage, is very important in an individual’s life as it includes the recognition of cognitive- and social-, as well as emotional intelligence within the self.This study was conducted with an aim to assess ‘teaching with the head’ and ‘teaching with heart’ which one is more powerful in developing self-awareness among their students.The descriptive survey method was used for the 405 students and 58 teachers of Kolkata (South Kolkata and North Kolkata), selected through a random sampling technique. Two standardized questionnaires were prepared for assessing the nature of a student’s self-awareness and teacher’s teaching methods while t-tests were conducted to test the hypotheses. Results indicate that the methods of developing self-awareness must be influenced by the characteristics of the teaching with heart and during adolescence - students become very much aware of themselves which, in turn, emphasizes the requirement of proper development of their self-awareness. Therefore, a major contribution of this study may provide a platform to isolate some of the factors which affect the self-awareness of the adolescent students. KEYWORDS: Self-awareness, adolescent student,teaching with head,teaching with heart, science teacher.
Do we Really Need No-reference Video Quality Metrics?

Objective video quality metrics are an essential part of modern video processing pipelines, guiding video encoding decisions and encoding recipes, helping adaptive bitrate streaming algorithms make smart decisions and providing system-level monitoring capabilities. We will offer a breakdown of an end-to-end such pipeline, highlighting which types of video quality metrics are deployed in each system component and then focus on the single aspect that makes social videos so much different - and one can argue more difficult - to process: their wildly varying and typically inferior source quality. We will then discuss how no-reference video quality metrics have been typically used to measure user-generated video content quality with limited success and make a case for how the video industry can unite and solve this problem at its root.
A secure cloud based image processing technique

With the media industry in its full swing, the need for video editing and censoring has increased in drastic proportions. But as every sector has its own advancements, there are also certain areas where it lags. With more number of media items pouring in, the need to segregate the categories has also increased. Presently, this censoring is done manually by viewer’s who view the content. Though there are strict rules as to which videos should fall under which category, discrepancies occur due to difference in perspectives. Moreover, a content running for 3 min would be judged by an algorithm at faster rates than what is being done manually. Therefore, there is a need for a platform where end users need only upload the content while the sorting would be done automatically. The data sets available from ImageNet API would make it easier for training the model for convolutional neural networks.
A Measurement System for Target Distance and Dimension Based on Monocular Camera

Target measurement has always been a hot topic in computer vision. Image measurement system can realize accurate measurement without contact. In this paper, a target distance and dimension measurement system based on monocular camera is designed, firstly, the imaging principle of monocular camera and the measuring theory based on similar triangle are introduced. Then, the similarity measurement algorithm based on Gaussian filtering and canny edge detection and implementation steps were analysed and summarized.
Analysis of Convolutional Neural Network for Lifelong Learning on Indonesian Sentiment Analysis

Sentiment analysis is a process to obtain the tendency of the authors in an article. Sentiment analysis classifies textual data into a class of positive, negative, or neutral sentiments. CNN is one of the deep learning algorithms capable of classifying textual data into positive, negative, or natural classes. In general, the standard learning methods learn from one domain to produce a model. Another learning paradigm is lifelong learning which is believed to be able to accumulate learning from various domains for learning in the new domain. In this paper, we examine lifelong learning of CNN for sentiment analysis on Indonesian textual data. Our simulation shows that the accuracy of CNN increases with the increase in the number of source domains where CNN learns. This shows that lifelong learning using CNN works well for sentiment analysis on Indonesian textual data.
s-PD sets, rank and kernel of Hadamard codes and construction of Hadamard codes using magma

This article presents the recursive construction of s-PD sets, a special subset of the permutation automorphism group of a code, which enables the correction of s errors of binary linear Hadamard codes over the field F4. We discuss the rank and kernel of these Hadamard codes. We develop new MAGMA functions to generate Hadamard codes over the field F4. We also give MAGMA functions to find the minimum distance and generator matrix of a Hadamard code over F4.
Pattern matching in an open world

Pattern matching is a pervasive and useful feature in functional programming. There have been many attempts to bring similar notions to Object-Oriented Programming (OOP) in the past. However, a key challenge in OOP is how pattern matching can coexist with the open nature of OOP data structures, while at the same time guaranteeing other desirable properties for pattern matching. This paper discusses several desirable properties for pattern matching in an OOP context and shows how existing approaches are lacking some of these properties. We argue that the traditional semantics of pattern matching, which is based on the order of patterns and adopted by many approaches, is in conflict with the openness of data structures. Therefore we suggest that a more restricted, top-level pattern matching model, where the order of patterns is irrelevant, is worthwhile considering in an OOP context. To compensate for the absence of ordered patterns we propose a complementary mechanism for case analysis with defaults, which can be used when nested and/or multiple case analysis is needed. To illustrate our points we develop Castor: a meta-programming library inScala that adopts both ideas. Castor generates code that uses type-safe extensible visitors, and largely removes boilerplate code typically associated with visitors. We illustrate the applicability of our approach with a case study modularizing the interpreters in the famous book ”Types and Programming Languages”.
Modified multi-strategy artificial bee colony algorithm for optimising node coverage problem

To enhance exploitation for artificial bee colony (ABC) algorithm, we propose a modified multi-strategy ABC variant in which a superior information learning strategy is employed. In this strategy, the individuals can learn superior information from an exemplar which has better fitness value, and the exemplar is no longer acted by the global best individual or the elite group. In experiments, 22 well-known test functions are used and six well-established ABC variants are involved in the comparison. The results show that our approach performs better on most of test functions. Furthermore, our approach is applied to solve the node coverage optimisation problem in wireless sensor network. To this end, an improved Boolean sensing model is used to model the objective function, and simulation results indicate that our approach can provide promising performance.
Digital Contact Tracing: The Medium is the Message

This essay investigates digital media devices and networks for addressing the spread and control of the novel coronavirus/COVID-19 infection. But unlike many of the other essays in this special issue, it will not focus on the message — the information and misinformation, the accurate reportageand the rumors, or the news and the fake-news— that is conveyed onthese digital platforms. Instead, I will focus on the use of digital mobile devices and networks to monitor and control the social aspectsof the virus and the vectors of infection. Toward this end, we will considerthe different ways that mobile technology can be employed to address and respond to a global pandemic like COVID-19; and we will examine the opportunities and challenges of DCTT in an effort not just to understand how these technologies work but to extract from this analysis a clear formulation of their possible benefits and attendant costs.
ChangeMacroRecorder: Accurate Recording of Fine-Grained Textual Changes of Source Code

Recording source code changes comes to be well recognized as an effective means for understanding the evolution of existing software and making its future changes efficient. Therefore, modern integrated development environments (IDEs) tend to employ tools that record fine-grained textual changes of source code. However, there is still no satisfactory tool that accurately records textual changes. We propose ChangeMacroRecorder that automatically and silently records all textual changes of source code and in real time correlates those textual changes with actions causing them while a programmer is writing and modifying it on the Eclipse's Java editor. The improvement with respect to the accuracy of recorded textual changes enables both programmers and researchers to exactly understand how the source code was evolved. This paper presents detailed information on how ChangeMacroRecorder achieves the accurate recording of textual changes and demonstrates how accurate textual changes were recorded in our experiment consisting of nine programming tasks.
Analysis of Database Programming Technology in Computer Software Engineering

In the process of rapid development of information technology, the scale of the information industry is continuously expanding, which creates very favorable conditions for the construction and development of computer software engineering. In computer software engineering, programmers need to enhance the application value of programming technology, so as to ensure that they can meet the various needs of users. This requires programmers to study and analyze database programming technology based on computer software engineering. At the same time, the research is carried out from the computer software engineering technology form, analyzes various problems existing in the application process of database programming technology, and puts forward the key points of database programming technology application. Only in this way can we ensure that the functional characteristics of the computer database can be fully exerted, and promote the further development of my country's information industry.
A Mode Study on the Integration of Computer Network Technology and College English Curriculum

With the rapid development of network technology, new vitality has been injected into China's education industry. The backward college English teaching mode in the past is difficult to meet the needs of students. In order to promote the sustainable development of college English teaching, it is necessary to organically integrate computer network with college English teaching, abandon the old teaching ideas, make full use of the diversified functions of network teaching, and arouse students' learning enthusiasm, so as to improve students' English listening and speaking practice ability. Based on this, this paper explores and analyzes the integration mode of computer network technology and college English curriculum.
Efficient Processing of Moving Target Detection Based on SW26010

SW26010 is a nationally-produced processor developed by the National Parallel Computer Engineering Research Center. It has high concurrency. The Sunway TaihuLight System built by SW26010 has reached the top of the super calculation ranking many times. The Gaussian mixture model (GMM) is an effective method for extracting moving objects, but the traditional GMM has high hardware requirements and cannot meet real-time requirements. In this paper, we propose a new moving object detection acceleration method combined with SW26010 processor. First, we transplante the video codec library FFMPEG to SW26010 to support video stream extraction. Next, a sliding window mechanism is proposed on the single-core group to reasonably divide the image data blocks. And we create a double buffer between the master and slave cores to hide the communication delay. Further we improve the computing performance in parallel between multi-core groups. Finally, the experimental verification shows that our method can achieve satisfactory performance acceleration in practical applications. This design scheme has good scalability on the multi-processor group of the Sunway TaihuLight System.
ARCHITECTURAL TREATMENT AND PLANNING OF MODERN SCHOOL LIBRARIES

The professional circles in Russia are discussing changes to the concept of modern school. The architectural treatment and planning of modern school spaces for public use should involve a new, innovative set of functions. One of the key spaces in the educational process to experience planning changes is the library. In this article, the architectural and planning principles of modern school library design are determined, and its functional modules are identified. In a modern Russian school, the library is expanding its functions and possibilities for integrating meta-subject formats. The library is becoming integrated information and communication center, a place of easy access to information and knowledge, collaboration between students and teachers, and experimentation and implementation of creativity and ‘meta-subject’ projects. Library premises should be mobile, transformable and flexible to accommodate any future modifications in the longer term and provide a kind of semantic experiment with cultural, social and professional values in design and research activities.
Taking the trial-and-error out of crystal growth

We investigate the optical force on the nonlinear graphene-wrapped nanoparticle by using the Maxwell's stress tensor together with the mean-field methods. We demonstrate the bistable optical force on the present nanoparticle which is due to the strong localized electric field in graphene at the plasmonic resonant wavelength. To further investigate the critical incident electric field for the up and down transistors, we find that the required switching-up threshold field is highly dependent on the permittivity of the nanoparticle, surrounding medium and Fermi energy instead of the relaxation time, with which one could achieve tunable nonlinear optical force on such graphene-wrapped nanoparticle to satisfy some practical purpose. Our results might supply an alternative way to manipulate nanoparticles and give the guideline for achieving the optical switching in nanoscale.