Reviewerly/exHarmony huggingface dataset:
semiPQA: A Study on Product Question Answering over Semi-structured Data

Product question answering (PQA) aims to automatically address customer questions to improve their online shopping experience.Current research mainly focuses on finding answers from either unstructured text, like product descriptions and user reviews, or structured knowledge bases with pre-defined schemas.Apart from the above two sources, a lot of product information is represented in a semistructured way, e.g., key-value pairs, lists, tables, json and xml files, etc.These semistructured data can be a valuable answer source since they are better organized than free text, while being easier to construct than structured knowledge bases.However, little attention has been paid to them.To fill in this blank, here we study how to effectively incorporate semi-structured answer sources for PQA and focus on presenting answers in a natural, fluent sentence.To this end, we present semiPQA: a dataset to benchmark PQA over semi-structured data.It contains 11,243 written questions about json-formatted data covering 320 unique attribute types.Each data point is paired with manually-annotated text that describes its contents, so that we can train a neural answer presenter to present the data in a natural way.We provide baseline results and a deep analysis on the successes and challenges of leveraging semi-structured data for PQA.In general, state-of-the-art neural models can perform remarkably well when dealing with seen attribute types.For unseen attribute types, however, a noticeable drop is observed for both answer presentation and attribute ranking.
Interactive WSI Review and Annotation Tracker, and Digital Visualization Tool for Pathologist Diagnosis of Whole Slide Images

A digital whole slide image user-tracker tool was built to study pathologists' view patterns during diagnosis, enabling actions, timestamps, zoom levels, viewports information, and task-based annotations, in any selected time interval, to be reconstructed for visualization.
Knowledge Graphs in Practice

In this chapter, we discuss some of the most prominent knowledge graphs that have emerged in the past years. We begin by discussing open knowledge graphs, most of which have been published on the Web per the guidelines and protocols described in Chapter 9. We later discuss enterprise knowledge graphs that have been created by companies from diverse industries for a wide range ofapplications.
Semantic-MDBScan: An Approach to Assign a Semantic Interpretation to Behavior Changes Detected in Data Stream Scenarios

A great variety of real-world problems can be satisfactorily solved by automatic agents that use adaptive learning techniques conceived to deal with data stream scenarios. The success of such agents depends on their ability to detect changes and on using such information to conveniently adapt their decision-making modules. Several detecting change methods have been proposed, with emphasis on the M-DBScan algorithm, which is the basis of this proposal. However, none of these methods is able to capture the meaning of the identified changes. Thus, the main contribution of this work is to propose an extended version of M-DBScan, called Semantic-MDBScan, with such ability. The proposed approach was validated through artificial datasets representing distinct scenarios. The experiments show that Semantic-MDBScan in fact achieves the intended goal.
Application

In this chapter we use Git in developing two open source circuit design projects. We will see how Git is a functional tool for managing projects. In this chapter we will try to study how to develop a project using systematic approaches discussed in Chapter 5 and how Git’s tools can be useful in each step.
Understanding three-tier model and selecting best CMS: a new generation web development

Content management system (CMS) has become a very popular web-based publishing tool these days. A number of CMSs like WordPress, ExpressionEngine, Drupal, SilverStripe, Alfresco, Joomla, Magento, Mango, etc. are in use for website development. Availability of different CMSs creates a dilemma to select the appropriate system since every CMS has its own advantages and disadvantages. In the absence of any criteria for comparison of three most commonly used CMS viz WordPress, Joomla and Drupal, a survey of more than 200 software developers was conducted. This paper provides an insight for selection and viability of a specific CMS on the basis of ten parameters from the perspective of a software developer and organisational needs. CMS platforms provide a framework to model data and define functionality as well for implementing custom applications using reusable components. In this paper, we propose a three tier model of CMS. Each layer encapsulates components with distinct functionality and a set of users.
Perancangan Game Edukasi Pengetahuan Dasar Untuk Anak Usia Dini Berbasis Android di PAUD Tunas Bahari Padang

Educational games are games that have educational content that is educational. Basic knowledge educational game for early childhood based on android is made for PAUD Tunas Bahari Padang children. Where in the current state of Covid19, PAUD Tunas Bahari Padang children are eliminated from the learning process at school, therefore of course they really need this educational game to learn while playing. This basic knowledge educational game for early childhood based on android is designed using the SDLC model. The SDLC model is a model that has a characteristic that the work of each phase must be done first before moving on to the next phase. Where the phases are analysis, design, code generation, application testing, maintenance and repair. The design of basic knowledge educational games for early childhood based on android in PAUD Tunas Bahari Padang was made using android studio software and designed using photoshop, and the testing used black box testing.
Implementing Electronic Voting System in Pakistan: Readiness, Challenges and Way Forward

The purpose of this paper is to explore the possibility of implementing an Electronic Voting System EVS in Pakistan, as well as highlight some potential areas where improvement may be needed. The research is broken down into three sections: readiness, opportunities, and challenges. In the Readiness section, the researcher looks at factors such as public trust, resources, and technical infrastructure that would be necessary for an EVM to be successfully implemented in Pakistan. The Opportunities section discusses the favorable conditions in Pakistan for the implementation of the EVM, while the Challenges section outlines some of the obstacles that may need to be overcome before a system like this can be put in place. Based on our findings, the researcher provides a number of recommendations for moving forward with this initiative. Hopefully, this research provides a useful starting point for further discussion on this important topic in Pakistan
DISTANCE EDUCATION IN HIGHER EDUCATIONAL INSTITUTIONS: TODAY’S CHALLENGE OR REALITY

The article studies of the problem of distance education in higher education institutions and its impact on the quality of the learning process.The essence of the concept of "distance education" and its categories are specified.The authors consider Moodle, Zoom and Google Meet to be the most popular distance learning tools due to their relative ease in use and cost-effectiveness.Surveys and analysis of the theoretical literature allowed to identify the main advantages and disadvantages of the introduction of distance education.Prospects for further research in this area are the need to improve the legal framework and scientific and methodological framework, ensuring an appropriate level of computer skills, competences in working with interactive technologies both teachers and applicants.Key words: distance education, higher
An Analysis of the Pre-writing Strategies Employed by Chinese college students in the timed examination

This thesis is trying to analyze the pre-writing strategies used by Chinese college students in a timed examination. The purposes of this study is to identify the possible strategies the Chinese college students claimed they used in the pre-writing stage of the timed examination, find if differences exist between the pre-writing strategies employed by skilled writers and unskilled writers, and find which strategy best facilitate writing in a timed condition.
Smart Bird Cage Based on STM32 for Turtledove Bird Using Solar Panel

Background: One type of bird that is widely bred and maintained is the turtledove. At turtledove breeding, bird cage maintenance is still done manually for cage lighting, feeding and drinking. Manual maintenance of the cage will make it difficult for farmers who have a fairly busy schedule or often leave the house.&#x0D; Aim: For that reason, the authors decided to make a Smart Bird Cage.&#x0D; Method: In this study, the authors used STM32F4 Discovery and ESP8266 as control centers via smartphones. The sensors that will be used are the temperature sensor and the Light Dependent Sensor (LDR). The outputs are 5 volt dc motor, 5V dc pump motor, buzzer and exhaust fan using on/off control with internet of things (IoT). While the control system for heating the cage uses the PWM control method on the AC module control for the brightness level of incandescent lamps.&#x0D; Findings: The results of this study are the temperature in the bird cage is controlled with a heating lamp that turns on when the temperature is below 30 oC and with the IoT system used by farmers, they do not have to worry about managing bird cage consumption when outside the city.
A Survey of Property Crime Incident Links and Their Discovery Techniques

Big data analytics based on deep learning provide a ray of hope for technical means to deal with the big underlying data such as transcript text and online records of criminal incidents of financial misappropriation. As a result, discovering the composition of criminal incidents and the connections between criminal incidents from semi-structured or even unstructured data and constructing the discovery into an automatic computerized system becomes an essential topic of scientific research. Detection can use the results to obtain the basis for case stringing, improve the efficiency of analysis, and reduce the work intensity of advanced police resources. This paper reviews the current research on crime incident linkage and its discovery, mainly including. (1) Review the current state of research on inter-crime incident linkage discovery and the extraction of entity relations, which is the subject of this paper. (2) To summarize and classify inter-crime incident linkage discovery methods and entity relation extraction from the current state of affairs. (3) We point out that the common challenges that need to be solved are the self-correction problem of the "incident linkage" sample machine screening problem and "entity relation" labeling. (4) We suggest a research approach to discover incident links and property crimes.
Sandia's Uncertainty Calculator: A Case Study in the Graded Approach

Software is used everywhere in a calibration lab, from controlling measurement equipment to performing statistical calculations to storing calibration records in a database. Yet the importance and details of software validation and quality assurance are not often discussed. A graded approach to software quality assurance (SQA) is typically used, where software with a higher risk of adverse consequences upon failure requires a higher level of rigor. The Sandia National Laboratories Uncertainty Calculator (Suncal) is open-source, free software for performing various statistical calculations related to metrology, including Guide to the Expression of Uncertainty in Measurement (GUM) and Monte Carlo uncertainty propagation, decision risk analysis, uncertainty in curve fitting, and analysis of variance. The SQA activities for the Suncal evolved over time. In its infancy, Suncal was simply a few code functions shared among a handful of coworkers, and SQA activities were almost nonexistent. As Suncal grew into a more formal library of algorithms with a full-featured user interface, and especially after it was released to the public, the SQA rigor level increased to match the tool’s increased risk and visibility. Suncal, and the SQA activities to ensure it operates correctly are discussed below.
HER2-MCNN: a HER2 classification method based on multi convolution neural network

Breast cancer is the most common malignant tumor in women and the second leading cause of cancer death. In breast cancer, about 20&#x0025; to 30&#x0025; of patients would have the positive phenomenon of human epidermal growth factor receptor 2 (HER2), also known as HER2 positive breast cancer. So far, different models have been proposed by using computer network to help HER2 classification. However, the existing single network model has a single receptive field scale, which can not extract multiple abstract features of the image well. Therefore, we designed a compound network, in which we use different network to extract the image features. Then the image information extracted from different networks was fused by linear weighted fusion algorithm, after that the weight in linear weighted fusion was optimized by experimental comparison. Finally, the SVM classifier was used to output the HER2 image categories. The experimental results showed that the proposed network has high accuracy for HER2 classification.
Insurance Transactions through Blockchain Applications: Current Status and Implications for the Domestic Insurance Industry

This paper discusses the necessity for introducing blockchain technology into insurance sales channels. We focus on two factors that have hindered the sustainable development of the domestic insurance industry. The first problem is that insurance companies’ profitability is on the decline and the second issue relates to information asymmetry problems besetting insurance sales channels. The channels are heavily concentrated on general agencies (GA) but the GA channel has been characterized by problems such as incomplete sales and high termination rates. Due to the advantages of blockchain technology such as the transparency of information and reduction in transaction and security costs, insurance sales channels such as GA can help reduce insurance companies’ business costs and alleviate information asymmetry by adopting blockchain technology. Thus, in this paper, we discuss ways to utilize applications using blockchain platforms in insurance sales channels. This paper also introduces the web-based blockchain application of International Business Machines (IBM) and suggests that various stakeholders of insurance can interact through blockchain applications.&#x0D;
Fish Schooling Algorithm and Hash Based Indexing for Text Document Retrieval

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
New Species Orchid Recognition System Using Convolutional Neural Network

Orchid is famous for its variety and its beauty. Every year, about a hundred of new species names are published. The study is to determine whether the orchid species can be recognized using a convolutional neural network algorithm and to test the accuracy of the classification model. Transfer learning was also implemented in this project to skip the feature extraction phase that requires many computational resources in the CNN algorithm. The model of transfer learning that is used is the Inception V3 model. This project is to prove that the concept of new orchid species recognition can be done. The web application that created using HTML and Flask was able to recognize new species based on existing species. In this project, 10 existing species with 100 images each was selected in training, validating, and testing phase. The training accuracy reached 97% and the functional testing of orchid recognition results shows 83% accuracy with 1000 datasets. In conclusion, the use of a web system as a prototype tool for the recognition of new orchid species is helpful for the unlicensed persons/organization.
Research on the Project Management of Thermal Pipe Network Engineering Based on Cs Mode

In the steady development of national economic construction, the level of urbanization is getting faster and faster. Optimizing the function and quality of the city has become the main task of practical innovation and development. In order to alleviate the development pressure of urban environment and meet the increasing living standard of people, the development mode of central heating is put forward for the construction of thermal pipe network project based on the understanding of their own energy advantages. Under the background of comprehensive promotion of central heating projects in various regions, effective treatment of thermal pipe network project can be carried out by combining modern project management concept and CS mode architecture. On the basis of improving operation efficiency, multi-angle management and control can be carried out from the whole process of the project. In this article, therefore, understand the current status of the development of urban central heating, on the basis of meaning, along with the development of the thermal engineering construction project management discussed cs mode and the importance of modern project management concept, and then from the project preparation, implementation, completion inspection and acceptance, project evaluation through the validation of the multi-stage degree analysis. The final results show that the advanced management concept and mode can effectively utilize the resources of all parties and strengthen the project management level of thermal pipe network construction.
An Improved Semi-Global Stereo Matching Algorithm Based on Multi-cost Fusion

As the matching accuracy of the traditional Semi Global Matching (SGM) algorithm is not satisfactory in illumination and weak texture areas, a SGM algorithm based on multi-cost fusion is proposed. Initially, gradient information and truncation coefficient are added to the Absolute Differences (AD) measure function to highlight the image edge, avoiding the excessive value caused by pixel outliers; Then, a fast Census transform method is proposed to work out the problem of high computational complexity of the traditional Census transform; Finally, the improved AD function constructs a cost calculation function incombination with the fast Census transform, which can strength for the robustness of traditional Semi Global Matching (SGM) algorithm in illumination noise and weak texture regions, and is capable to enhance the disparity map quality. Experimental results reveal that the average error matching rate of the improved approach is effectively reduced in comparison with traditional SGM matching algorithm, which settles the matter that the SGM algorithm at a single matching cost is arduous to obtain higher matching accuracy.
Recognizing daily-life activities using sensor-collected data in a kitchen

This paper focuses on the recognition and classification of Activities of Daily Living (ADLs) that are carried out in a kitchen. To do this, a Recurrent Neural Network architecture of the Long-Short Term Memory (LSTM) type is implemented as a classifier. The ARAS dataset is used for training and evaluation. A classifier is obtained with an average value in the F1 metric of 95.33% for the chosen data set
Short Term Prediction of Electrical Load Using Artificial Neural Network with Backpropagation Algorithm

Artificial neural network is one of the machine learning algorithms that can perform a regression or classification with supervised learning. In principle, artificial neural network has the same way of working as the system network in the human brain, which has the ability to learn from past experiences. In this paper, it will be proposed to design an artificial neural network model to be able to determine the amount of electrical load generated from a building in Telkom University for the next 7 days. The purpose of predicting this electrical load is to be able to plan of using electrical energy for the future. So that the waste from electrical energy can be minimized by making a prediction of the electrical load made from an artificial neural network model. Prediction of electrical load is done by predicting the last 7 days in January 2020 with training data for 24 days in the same month. The results of the research that has been done during weekend have a larger error than weekdays marked on the 26th has the largest error of 12.123&#x0025; and the lowest error occurs on the 29th with an error value of 5.737&#x0025;
Implementation of Arithmetic Operations in the Residue Numeral System

To improve the performance of computer systems, special number systems can be used, for example, the residue numeral system (RNS). Replacing integers with their values modulo several pairwise coprime integers (called the moduli) can significantly reduce the complexity of arithmetic operations. However, the different way of representing numbers makes it difficult to use RNS in practice. For example, integers represented in a positional numeral system need to be quickly converted to RNS and vice versa. In addition, the implementation of computing devices operating in the RNS must also take into account the peculiarities of representing numbers as residuals on coprime bases. In this article, we look at the various structures of computing devices in RNS. In particular, we present the arithmetic operations of addition modulo and give examples of adders.
Design of the Residual Adder of Two Numbers

It is known that an important and topical scientific and applied problem is the problem of constructing the structure of an adder operating in the residual number system (RNS). Such a non-positional adder for an arbitrary value <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$m_{i}$</tex> of the RNS modulus is a sequential set of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n=[\log_{2}(m_{i}-1)+1]$</tex> binary one-bit adders (OBA), united by connections, like connections of positional binary adders. The use of additional connections made it possible to create an adder that implements the operation of adding two residues. A set of k adders modulo is an adder of two numbers in RNS. Specific examples of constructing structures of binary adders for various values of the RNS moduli are given.