Reviewerly/exHarmony huggingface dataset:
Managing Applications

The previous chapters have described how to build applications. Applications are the largest building blocks in Visual Builder Cloud Service, and within one VBCS instance, you can have many applications. This chapter is about how to work with and manage entire applications.
The Alignment Between Business Objectives Clarity and Software ObjectivesThe Alignment Between Business Objectives Clarity and Software Objectives

This paper aims to highlight a very important concept and plays a key role in the success of software development, which is the alignment between business objectives and software objectives.In this research we refer to most of the literature that dealt with this subject.The researcher designed a questionnaire and conducted field interviews with software project managers.This study concluded with a set of recommendations and found that the alignment between business objectives and software goals plays a prominent role in software development and has a positive impact on the success of the software.
Factors that Generate Labor Commitment in the Human Capital of an Institution of Higher Education

The objective of this research is to determine if training is a factor for the administrative staff working in the HEIs to feel committed to their work, it is developed in a Higher Education Institution (HEI), the hypothesis states that there is a direct relationship of training with commitment, considering the questionnaire as a tool to detect the needs of workers in terms of their personal or professional training and if, as they develop, they feel more attached to the place where they work.The results mention that the workers know that they have complications in various aspects within their workplace that have not allowed them that growth, therefore 50% of those interviewed mention not having a complete feeling of belonging.It is also detected that, despite the lack of training courses, many of them feel proud of the way in which they work, they do not discredit their efforts so that they are giving the results that are in their departmental objectives, taking into account the lack of equipment in some cases (knowing that their objectives are achieved), the pride of being part of this Institution is not lost.
Group Recommendation for Cold Start Users Using Hybrid Recommendation Technique

Recommender system is an data retrieval system that gives customers the recommendations for the items that a customer may be willing to have. It helps in making the search easy by sorting the huge amount of data.We have progressed from the era of paucity to the new era of plethora due to which there is lot of development in the recommender system. In today’s scenario the interaction between the groups of friends, family or colleagues has increased due to the advancement in mobile devices and the social media. So, group recommendation has become a necessity in all kinds of domains. In this paper a system has been proposed using the group recommendation system based on hybrid based filtering method to overcome the cold start user issue which arises when a new user signs in and he/she doesn’t have any past records. So, the recommender system does not have enough information related to the user to recommend an item which will be of his/her interest. The dataset has been taken from the MovieLens is used in the experiment.
Art Approach and Framework for HCI Research

The chapter presents the specific art approach to HCI research, including an illustration from the literature. The latter claims that empirical investigations of videogame play and videogame engagement are often delimited along demographic or genre lines. In contrast, the illustration proposes a theory of players engaging with games, if they can find a sense of net personal cultural value. The chapter then presents the specific art framework for HCI research, comprising art as discipline, general problem, particular scope, research, knowledge and practices. The specific art framework is followed by the art design research exemplar, as the art design cycle and the art design research cycle. The lower-level art framework comprises the art application, the art interactive system, and the art interactive system performance. Both the exemplar and the lower-level framework are applied to the same illustration of the art approach taken from the literature, which proposes a theory of players engaging with games, if they can find a sense of net personal cultural value.
Guest Editor’s Introduction

International Journal of Semantic ComputingVol. 14, No. 02, pp. 169-171 (2020) No AccessGuest Editor’s IntroductionDaniela D’AuriaDaniela D’AuriaFree University of Bozen-Bolzano, Italyhttps://doi.org/10.1142/S1793351X2002002XCited by:0 Next This article is part of the issue: Special Issue – Selected Papers from 14th IEEE International Conference on Semantic Computing (ICSC2020)Guest Editor: Daniela D’Auria AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Remember to check out the Most Cited Articles! Check out our titles in Semantic Computing! FiguresReferencesRelatedDetails Recommended Vol. 14, No. 02 Metrics History PDF download
Comprehensive Analysis of Web Page Classifier for Fsocused Crawler

Focused Crawler collects domain specific web page from the internet. However, the performance of focused web crawler depends upon the multidimensional nature of the web page. This paper presents a comprehensive analysis of recent web page classifiers for focused crawlers and also explores the impact of web-based feature in collaboration with web classifier. It also evaluates the performance of classification technique such as Support vector machine, Naive Bayes, Linear Regression and Random Forest over web page classification. Along with that it examines the impact of web feature i.e. anchor text, Page content and link over web page classification. Finally the paper yield interesting result about the collective response of web feature and classification technique for web page classification as a relevant class and irrelevant class.
Acute Myelogenous Leukemia Detection using Circumventing Ant Colony Optimization based Convolutional Neural Network

Acute Myelogenous Leukemia (AML) is a type of disease associated with acute leukemia which is getting increased in both children’s and adults. AML falls under the category of cancer disease. The term acute in AML indicates rapid progression of disease in human body. The main challenge of medical field in vision of computer and multimedia is texture and color between various categories. The variation in texture and color attributes makes the classification task a tedious. Deep learning has shown its dazzling performance in various streams, which includes classification too. The objective of image classification is to differentiate the subcategories that belong to same basic-level category. The main objective of this paper is to propose bioinspired based on convolutional neural network to classify the microscopic blood images for AML. This paper has utilized bioinspired concept to extract the features more reliably. Bench mark performance metrics were chosen to evaluate the proposed classifier against the previous classifiers based on two parameters. The results indicate that the proposed classifiers has outperformed the previous works towards the classification of AML.
SISTEMATIZAÇÃO DA ASSISTÊNCIA DE ENFERMAGEM COM ALUNOS DO PRIMEIRO SEMESTRE DE ENFERMAGEM FACE À PANDEMIA

Develop the Systematization of Nursing Assistance with students in the first semester of the nursing course in view of the social isolation caused by COVID-19.Method: This is an educational investigative narrative, developed based on the stages of the Nursing Care Systematization with students of the nursing course.Results: Through the Systematization of Nursing Care, it was possible to verify that even in the face of difficulties encountered in the face of social isolation and remote academic adaptations, students are concerned about their mental health and seek alternatives to promote their wellbeing.Conclusion: It became evident that the Nursing Care Systematization can be understood as an educational tool to apprehend the weaknesses and enhance the initiatives in the face of the COVID-19 pandemic.
Perception and Satisfaction with Non-face-to-face Lectures among Dental Hygiene Learners

Objectives:The purpose of this study was to evaluate dental hygiene learners' perception and satisfaction level with the non-face-to-face lecture in each of the theory and practical courses.Method: Data were collected from 190 dental hygiene students using an online survey system.The questionnaires consisted of satisfaction level, learning achievement, and advantages and disadvantage of non-face-to-face lecture, as well as preferred teaching methods in both courses.Variables of each teaching method were compared using ANOVA.Results: Among the teaching methods that learners experienced, non-face-to-face recording lecture (theory course) and blending lecture (practical course) were the highest at 33% and 25%, respectively.The highest satisfaction levels were with non-face-to-face recording lectures in the theory course (p=0.006), and face-to face lectures in the practical course (p<0.001).The learning achievement level of the non-face-to-face practical course was below the average level.Further, the face-to-face teaching method scored the highest in terms of effective communication with professors and was considered the most preferred teaching method in both courses after COVID-19 recover. Conclusion:The satisfaction level was highest with face-to-face lectures, and the non-face-toface lectures were the lowest at a sub-average level in practical courses.In theory courses, the satisfaction level was the highest in the non-face-to-face recording lecture.
Enhancing Security in Cloud Computing using Playfair and Ceasar Cipher in Substitution Techniques

Cloud Computing is playing the significant role in the existent submissions the humans life. Cloud computing is an extravagant set of conveniently and operative virtualized assets, like as hardware, evolution platforms and utility. Cloud computing is a exclusive generation of the parallel conception. The cloud computing extensibility is a concern of the allotment of revenue on mastery demand. Cloud computing accommodate the operation of uniting. The elevation of the cloud automation also raises the security controversy twice. So, there is a need to solve the security contention in the cloud automation. Reasons for maturity of cloud security for disparate inhabitants and disparate prospect depend upon the exaction. The main trouble correlate with cloud computing is data confidentiality, preservation, data stealing, data breaches etc. In this research work, it is proposed to use a new level of data security solution using Playfair cipher and Ceasar cipher algorithm. Both the algorithms are encrypted by the full set of 256 ASCII characters. A new encryption algorithm for security is implemented in this work. The main aim of this research work is to clarify the security issues in both cloud providers and cloud consumers using cryptography encryption methods.
Library projects, programs, contests and actions: An ecological element. The experience of Moscow A. P. Gaidar Central City Children’s Library

The ecological projects, programs, contests and actions comprise information on environmental protection and ecology, promote ecological culture and support ecological education of juvenile users and those who are to guide children’s reading.
A Simple Semantic Web Crawler for Intelligent Information Retrieval from Academic Websites

In various applications data is shared and reused through a common framework like Semantic Web. In essence, in the ever-expanding sphere of the web, huge quantities of web content is created and made available for men and machines for their interpretation and application. In the present paper, an attempt has been made to develop a “scutter”, other wisely known as semantic crawler that essentially collects and stores information in a centrally-located database by crawling through the semantic content. The projected ‘scutter’ is based on Jena 3.0 Framework, which is a freely downloadable language software available on https://jena.apache.org/download/. In this process, a RDF file is taken as the seed input file after which the ‘scutter’ accesses other RDF documents by crawling through ‘rdfs:seeAlso’ property, thereby designated as an automatic extraction of semantic information emanating from various websites. Also, certain privacy related issues, especially in FOAF metadata is discussed in this paper.
An Enhancement of Svm Based Semantically Enriched Variable Length Confidence Pruned Markov Chain Model Based Web Page Recommendation System

Semantic Variable Length Markov Chain Length Model (SVLMC) is a web page recommendation system which combined the fields of semantic web and web usage mining by the Markov transition probability matrix with rich semantic information extracted from web pages. Though it has high prediction accuracy, it has problem of high state space complexity. The high space complexity reduce the execution speed and reduce the performance of the system, which was resolved by Semantic Variable Length confidence pruned Markov Chain Model (SVLCPMC) model that provides high user satisfied recommendation and Confidence Pruned Markov Model (CPMM). The time consumption of CPMM was reduced by Support Vector Machine (SVM). But still the recommendation accuracy is still below the user satisfaction. So in this paper, quickest change detection using Kullback-Leibler Divergence method is introduced to improve the accuracy of recommendation generation by developing a scalable quickest change detection schemes that can be implemented recursively in a more complicated scenario of Markov model and it is included in the training data of SVM. Then the performance of web page recommendation is improved by ranking the web pages using page ranking technique. Thus the performance of web page recommendation generation system has been improved. The experiments are conducted to prove the effectiveness of the proposed work in terms of prediction accuracy, precision, recall, F1-measure, coverage and R measure.
AN ANALYSIS OF THE MOBILE READINESS OF THE U.S. STATE GOVERNMENT WEBSITES

Mobile technologies using cellular communication have evolved rapidly over the past few years.More and more people prefer a smart phone or a tablet computer to a laptop due to a portability and ease of use.Organizations who utilize their websites to provide important information with users are compelled to rethink their website designs for drastically increased mobile device users.This paper exams mobile readiness of 50 government websites of the United States.The performance of a web page for mobile devices is measured using 1) Alexa 1000 benchmark, which benchmarks the government websites' mobile ready score against the distribution of the top 1000 Alexa sites, 2) a Google PageSpeed Insights tool, which analyzes the contents of a web page and generates a performance report that shows whether a page utilizes best common practices, 3) MobyReady, which measures a page weight in terms of the number of bytes, and finally 4) 38 technical check points, which are tested and grouped into three categories such as major failure, minor failure, and passes.The research results reveal that the majority of the U.S government websites have a lot of room to be improved for mobile device users.
Generalized Parikh matrices of picture array

The theory of Parikh matrices and subword occurrences has led to extensive research in combinatorics on words. The extension of Parikh matrix of a word into picture array is an another interesting problem. Since the Parikh matrix does not say about the number of subword occurrences in the array. Therefore, in this paper we introduce the generalized Parikh matrix of a picture array which gives the number of subwords occurrences in the array. We also discuss some properties of generalized Parikh matrices.
知覚の記憶-痕跡理論Ⅰ：時間間隔について

A memory-trace theory of perception (TToP) is developed for sequentially presented stimuli; here, temporal intervals. Duration is estimated based on the memorial strength of the stimuli that signal the initiation of an interval at the time of its termination. Memory persistence depends on modality and character of the signals. When the constant difference limen on the memorial continuum is reflected back to the temporal domain it yields a generalized Weber function. Memory traces interact through generalization gradients: Memories of stimuli that are similar are aggregated—feature-bound. The resulting representations may be judged in a discrimination paradigm, or translated back to the physical domain as reproductions. The presentation of a standard stimulus affects the perception of the comparison stimulus, warping the ruler that measures it. Complementary effects are predicted for discrimination and adjustment paradigms. The TToP accounts for multiple anomalies observed with classical psychophysical methods：Scalar and non-scalar timing, modality effects, time-order errors, masking, time warping, lengthening, and Vierordt’s law.
Preface

Editorial International Conference on Advanced Information Scientific Development (ICAISD) 2020 ICAISD 2020, INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION SCIENTIFIC DEVELOPMENT and all this titles are available in this PDF.
Le Lettere del beato Colombini come esempio di dialetto senese secondo Giovan Girolamo Carli

Giovan Girolamo Carli, a Sienese scholar (1719-1786), focused on the language of the Letters, usually considered a secondary aspect compared to their historical and theological value. Probably pushed by an anonimous client, Carli was planning to publish the first critical edition of the Letters, strictly philological, supported by insights on the life of the Blessed and a dictionary. His manuscript drafts, even incomplete, are however a precious source for reconstructing the original documents tradition, since he directly consulted and compared different and authoritative copies. Carli's purpose was to celebrate a fellow citizen, but also to prove the Sienese linguistic primacy instead of the Florentine one – as in art historiography –, and propose an authentic style against the contemporary mediocrity.
Multi-robot Cooperative Search Method Based on Biological Heuristic Algorithm

The multi-robot search problem is one of the key issues in the research of multi-robot systems. In order to find the target effectively, an improved multi-robot collaborative search method based on Beetle Antennae search (BAS) algorithm is proposed. First, the left and right whiskers in Beetle Antennae search algorithm can correspond to the two robots one by one. According to this feature, the position of this group of robots is continuously updated according to the algorithm, and finally the target search task is completed. On this basis, considering the cooperation between multiple groups of robots, the collaborative method of particle swarm optimization (PSO) algorithm is introduced, and a multi-robot collaborative search method based on the improved beetle algorithm is proposed. Simulation shows that the improved algorithm can be effectively completed for static targets Target search task, and the target search success rate is significantly better than particle swarm optimization algorithm when the number of robots is small.
Optimized Wavelet Decomposition and Gaussian interpolation based Satellite Image Enhancement

Satellite images (SI) play a vital role in various remote sensing applications like geoscience, geographical studies, observing the earth's atmosphere, monitoring natural disasters, etc. The SI are used in these applications require high-resolution. The performance of the wavelet transforms based resolution enhancement methods depends on the type of the mother wavelet used and it varies with image to image. The novel robust SI resolution enhancement technique including Optimized wavelet transform based image decomposition and Gaussian interpolation is proposed in this paper. Optimized wavelet decomposition is obtained using the Stochastic Diffusion Search algorithm and the Gaussian distribution function is used for interpolation. The proposed method is compared with the Discrete wavelet decomposition and Gaussian interpolation resolution enhancement method and proved that the proposed method gives the best results for any image.
ACM/IEEE SYMPOSIUM ON LOGIC IN COMPUTER SCIENCE (LICS 2019) SUPPORTED BY THE ASSOCIATION FOR SYMBOLIC LOGIC Vancouver, Canada June 24–27, 2019

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8th International Conference on Natural Language Processing (NLP 2019)

We aim to model unknown file processing.As the content of log files often evolves over time, we established a dynamic statistical model which learns and adapts processing and parsing rules.First, we limit the amount of unstructured text by focusing only on those frequent patterns which lead to the desired output table similar to Vaarandi [10].Second, we transform the found frequent patterns and the output stating the parsed table into a Hidden Markov Model (HMM).We use this HMM as a specific, however, flexible representation of a pattern for log file processing.With changes in the raw log file distorting learned patterns, we aim the model to adapt automatically in order to maintain high quality output.After training our model on one system type, applying the model and the resulting parsing rule to a different system with slightly different log file patterns, we achieve an accuracy over 99%.
Information Extraction using User Opinion Procedure

Increasing in the demand of informaiton extraction content based image retrieval play and vital role. Extracting image information is not an easy process because of the image attribute nature. From the availiable huge data sets extracting the particular image frame or image content really big challenge for many researchers. To address is issue in this paper a propsed relevance feedback image system is developed. This system reduce the complex image search operation and the same time brings the more relavant outputs. Experimental results shows that the proposed system reduces the number of inteion compare to the exsiting image reterival operations and improve the effeciency campare with the exisiting technqiues.
Performance Comparison of SVM and its Variants for the Early Prognosis of Breast Cancer

Breast cancer has become a leading cause of women death in this era. Breast cancer is very common in various countries including Pakistan. Early identification of the breast cancer or tumor is the only way for the rapid treatment and cure. An imaging approach named as mammography has performed tremendous job in the field of medical to detect the cancer tumors on early basis with less false alarm rate. Breast cancer has two types of tumors a) Benign and b) Malignant. Malignant is acknowledged as cancer tumor as it spread and grow rapidly inside the tissues. Detection of Malignant tumor is very complex in dense breast as it is covered and linked with the milk glands, ducts and other related tissues. Therefore, machine learning and artificial intelligence approaches were needed as mammographic images required edge detection, image enhancement and image processing. Various Artificial Intelligence based algorithms have been applied to the clinical breast cancer data set for the early detection of breast tumor. In this research work the clinical data has been collected from the UCI machine learning repository for the classification of breast cancer tumor a) Benign and b) Malignant. Support Vector machine with its variants Kernel, Gaussian Kernel and Sigmoid Kernel have been applied to the linearly separable breast cancer data set for comparative analysis. Results proved that all the variants of SVM performed better for the breast cancer classification.&nbsp