Reviewerly/exHarmony huggingface dataset:
Classification of Web History Tools Through Web Analysis

Web pages may contain various types of sensitive information exposed, such as user login information. Even after these pages have been corrected, the sensitive information, once exposed, can be found through the web history tools. These tools make snapshots of web pages, that is, capture the state of the pages in the most varied periods. Although these tools are widely used, it is not known which web history tool is the most accessed. A method to find out which web history tool is the most accessed is by means of classification using the web analytics technique. Therefore, in view of this scenario, the objective of this work was to classify web history tools through web analysis. The methodology used was the descriptive with quantitative approach. As for the technical procedures, this work is characterized as experimental to verify if the technique of web analysis is able to classify web history tools. The results show that the technique of web analysis produces indicators capable of classifying the web history tools by the total number of accesses received.
Developing an effective scheme for translation and expansion of Persian user queries

Abstract This study aims at introducing a new source for translation and expansion of user queries in Persian language in order to develop a bilingual dictionary. For the purpose of this study, required data were extracted and processed from English and Persian bibliographic information of journal articles to develop a dictionary for query translation and expansion, denoted as Query Expansion Assistant Database (QEAD). In this study, psychology and educational sciences journals have been selected as the sample with the potential of extension to other domains. Persian–English authors’ keywords were used for translation part and titles of English references were used to extract phrases using natural language processing techniques for the expansion part. The proposed algorithm is demonstrated. Then we evaluated this approach using human evaluation by using Google translate (GT) and Google scholar. Although the evaluation of translation part indicated 60% match between GT and QEAD, in 40% of unmatched translations, QEAD showed a better performance according to expert evaluators. Expansion part of QEAD was compared with Google scholar suggestions, which indicated that the expanded words of QEAD can equalize with Google scholar suggestions. Persian as a low resource language needs more qualified lexicon translation. In addition, using the English–Persian bibliographic information of scientific journals to mine lexicon translation is conducted for the first time. Since these journals are peer-reviewed, they can be a valuable source for translation of user’s query. Users can be informed of the most prevalent and up-to-date words or phrases among scientists, because journals are published frequently.
A Hybrid Methodology of Effective Text-Similarity Evaluation

In this paper, an effective methodology which hybridizes a LCS finding algorithm and SimHash computation is presented for evaluating the text-similarity of articles. It reduces the time-space scale needed by the LCS algorithm by breaking the articles into word subsequences of sentences, managing and pairing them by SimHash comparisons, and reaching the goal of evaluating long-length articles rapidly, with the similar parts and similarity score of compared articles figured out exactly.
Mind Maps in Requirements Engineering: A Systematic Mapping

Many of the mistakes that can be found in software products have their origin in the requirements definition and preliminary design stages; likewise, the correction of these demands a greater effort than those generated in the following stages. The lack of effective and transparent communication between those involved in the process (users, experts in the business domain, analysts, developers, etc.) is one of the main causes for the introduction of these errors, which is why a well-defined method and information exchange are necessary. In this way, a validation and early correction of the requirements could be done with the help of those involved, so that the functionalities implemented can be verified in later instance. Through the process of systematic mapping of the literature, fifteen research studies that consider the use of mind maps as facilitators in the exchange of communications of ideas developed in the requirements engineering processes were selected. Concluding that, the inclusion of the development of mental maps is evidenced more frequently in the processes of elicitation, analysis and validation of the requirements, this as a result of the activities developed in these processes involve a constant interaction and communication between expert users of the business domain and the analysts.
Research on Content Extraction of Rich Text Web Pages

Obtaining effective information from Web pages has become a hot topic in the Internet data processing industry. Based on this, this paper studies the extraction of rich text Web pages. First, this paper designs a method to extract rich text page titles and release times. After a large number of data sets statistics, it is found that almost all the body titles are in the title tag, so a tag-based regular matching algorithm is designed. By writing the code to test the algorithm, the average extraction accuracy is more than 80%. For the extraction of release time, a common regular expression is used to match the full text of a web page and filter according to the position difference of each timestamp in the web page. Set the rule to filter the first occurrence of the timestamp is the release time. Test the algorithm, and the average extraction accuracy of the local data set is over 75%. Secondly, this paper designs a method to extract the text of rich text web pages. On the basis of the training data set, the logical regression model, random forest model and support vector machine model were respectively trained through the cross validation of ten folds. Model fusion was performed on the three models to identify the class tag of the body. Again tested on the test data set, the experimental results show that the average accuracy is 95.6%, the recall rate index was 0.948, 0.923, f1 to further determine the web page text in class labels can be 100% extraction. Finally, this paper evaluates the proposed algorithm and proposes corresponding improvements.
A tracking method combines with detection algorithm based on deep separable convolution network

Abstract With the emergence of a large number of artificial intelligence technologies, deep learning has become the key technology in computer vision area. Object tracking is one of the most important technology in the field of computer vision. Thus we studied about tracking algorithms and proposed a method mainly hopes to solve the occlusion problem in complex tracking scene. Using object detection algorithms based on deep learning to increase the speed of associations and improve tracking effect. It can return the position of the tracking object unsupervised. Then extract features to store in features library, so that the prediction of trajectory whose features can highly be matched is more accurate and the associations are more reliable. Experiment shows our tracking algorithm combines with detection algorithm based on depthwise separable convolution networks not only has a smaller and faster model but also achieved a robustness and real-time tracking in scene where objects are under occlusions.
Development of Automated Platform for Image Capturing and Counting Algorithm for Viral Plaque

Automatic analyzing tools are essential for biomedical research such as evaluating quantitation of virion. Counting dengue 96-well plaque assay with automated analysis system is one of the interesting and important applications since it can reduce researchers' burden and help researchers analyze the results quickly. Thus, automated platform for image capturing and counting algorithm for viral plaque have been developed. The automated platform for image capturing consists of xy-table, which have work space of 220 mm x 220 mm,accuracy of 0.05 mm, and vertical z-axis for image focusing. With the automated platform, each well of 96-well plate can be automatically captured with high resolution. Next, the counting algorithm is a program for counting and analyzing the images. The algorithm is developed from Halcon library. The results show that the accuracy of the counting algorithm is good enough for the application. Moreover, with this system, there is no additional process of nontransparent liquid to achieve contrast-enhanced image during image capturing. Thus, this system can reduce workload of researchers during assay preparation.
An Dynamic Protocol for the Quantum Secure Multi-party Summation Based On Commutative Encryption

A dynamic protocol for the quantum secure multi-party summation based on commutative encryption is proposed. Without using the entangled character, joint measurement, n parties can encrypt their private information and privately get the summation of their private information using commutative encryption. Any m parties can dynamically participate and drop out the proposed protocol. Correctness analysis shows that the proposed protocol can be used to get the summation of their private information correctly. Security analysis shows that the proposed protocol can resist the general active attacks from an outside eavesdropper. And it can overcomes the problem of information leakage. In theory, our protocol can be used to build complex secure protocols for other multiparty computations and also lots of other important applications in distributed networks.
Crowd-sourcing the sounds of places with a web-based evolutionary algorithm

The sounds we associate with particular places are tightly interwoven with our memories and sense of belonging. We describe a platform designed to assist in gathering the sounds a group of people associate with a place. A web-based evolutionary algorithm, with human-in-the-loop fitness evaluations, ranks and recombines sounds to find collections that the group rates as familiar. An experiment covering four geographical locations shows that the process does indeed find sounds deemed familiar by participants.
An Improved WNNM Algorithm for Image Denoising

Abstract The traditional weighted nuclear norm minimization (WNNM) has excellent performance for the removal of non-sparse noise such as Gaussian noise, but attains bad performance for the removing of salt&amp;pepper noise and mixed noise of Gaussian noise and salt&amp;pepper noise. This paper proposes an improved WNNM image denoising algorithm. WNNM can effectively remove non-sparse noise such as Gaussian noise and adaptive median filtering algorithm can effectively remove sparse noise such as salt and pepper noise; the improved algorithm combines the characteristics of WNNM and adaptive median filtering. The experimental data demonstrate that the improved WNNM algorithm has better denoising effect than WNNM algorithm.
Reducing ambiguity during enterprise design

Requirements elicitation is one of the most important phases in the design process and applied by many engineering disciplines. A more recent application of the design process is to design the enterprise as an artefact, also called enterprise engineering (EE). Even though there are limits to formal enterprise design due to enterprise complexity, strategic intentions are not realised spontaneously or accidently. Intentional enterprise design is required, starting with the strategic context, eliciting enterprise intentions. Similar to the ad hoc evolution of enterprises, EE as a discipline also developed in a fragmented way with enterprise design knowledge mostly encapsulated in several enterprise design approaches. A previous study analysed eight different enterprise design/alignment approaches, inductively developing a common framework to represent and compare these approaches in terms of four main components. One of the components represents the scope of enterprise design/alignment in terms of three dimensions: design domains, intentions and constraints, and enterprise scope. Since existing approaches use inconsistent means of defining the first dimension, namely the design domains, previous work already provides some guidance on demarcating design domains in a more consistent way. This article focuses on the second dimension, i.e. intentions and constraints, and the need to distinguish between different intention-related concepts to reduce possible ambiguity. The study applies design science research to develop a method for enterprise intentions concept clarification (MEICC) as a theoretical contribution. The study also offers a practical contribution, demonstrating how the MEICC was used to clarify intention-related concepts that feature within a specific approach, namely Hoogervorst’s approach. A coding strategy (including coding conditions, a refined codebook and a coding method), developed for Hoogervorst’s approach via MEICC, is presented as a secondary contribution, since the coding strategy will also be useful to practitioners that use Hoogervorst’s approach.
How “Friendly” Integrated Development Environments Are?

Programmers and software developers are using different Integrated Development Environments (IDEs) to perform their daily work. IDEs are often complex applications, not friendly for novice programmers, with a learning process of several weeks and with usability and satisfaction of use not always as good as expected. The Programmer eXperience (PX) is a particular case of User eXperience (UX), based on the use of the IDEs and other artifacts. We have found studies about the programmer's behavior and work, and also articles addressed the usability and new tools proposals for IDEs. In this work, we conducted a survey to evaluate the usability of several IDEs. The survey was based on the System Usability Scale (SUS), which we adapted for the purpose of our research. We focus the study on popular IDEs such as Dev-C++, Eclipse and NetBeans. The survey was conducted in two Chilean universities and one Spanish university, with students enrolled in two undergraduate programs in Informatics Engineering. The results obtained show that the IDEs evaluated have several issues related to the usability perceived by our participants. An interview was conducted with six experienced programmers that are working in different programming environments, in order to consult them on what aspects they would like to improve the IDEs. Their comments indicate that IDEs should incorporate connection with other programmers, and also, they claim for more intuitive interfaces and understandable error messages.
Analysis of Segmentation and Identification of Square-Hexa-Round-Holed Nuts Using Sobel and Canny Edge Detector

In the existing real-time automobile shop, it is difficult to trace an object and identify its presence. The failure may happen due to its absence or improper match of shape as its identity. So to overcome this, we propose a method which can be used for the automatic identification of vehicular nuts based on the input image that contains a nut with square, hexa, rounded-head and pinned-bolt shapes. The application even works with the nut having clear view or any entity added like mud, noise, colour, etc. on the surface of nut. For the identification process the database has been designed to store different shapes for selected number of nut-shapes. By applying median filter during pre-processing stage, the Sobel-edge-detector and Canny-edge-detector; segmented and identified the captured images by identifying the edges to ascertain shape of the input. With the experimentations carried the method results with an accuracy of 86.1875%
Bitcoin’s Decentralized Decision Structure

With the introduction of bitcoin, the world got not just a new currency, it also got evidence that a decentralized control structure could work in practice for institutional governance. This Commentary discusses the advantages and disadvantages of centralized and decentralized control structures by examining the features of the bitcoin payment system. We show that while the decentralized nature of the Bitcoin network "democratizes" payments, it is not obvious that the approach increases the equity or efficiency of markets or that the costs of the decentralized control structure won’t outweigh the benefits in the long run.
Face Rotation via VAE-CapsuleGAN

High-quality image reconstruction and generating the new image by learning the distribution from the image are very popular in computer vision field. Nevertheless, some promising results have been reported in the literature recently. In this work, we propose a VAE-CapsuleGAN network which can generate high-quality face image with modified rotation angle. We show promising results in our experiment on the CAS-PEAL-R1 face dataset.
Research on the Design of Cloud Computing Platform in Intelligent Campus

Abstract Constructing intelligent campus is the inevitable trend of educational informationization development. With the development of technology and the deepening of application, users demand a more humane and intelligent user experience, and put forward new functional requirements for the construction of intelligent campus. The construction of cloud-based IT system platform and its application mode can solve the above problems fundamentally, so as to promote the leap-forward development of educational informationization construction.
Inception Network-Based Weather Image Classification with Pre-filtering Process

Visual data (e.g., images/videos) captured from outdoor visual devices are usually degraded by turbid media, such as haze, rain, or snow. Hence, weather conditions would usually disrupt or degrade proper functioning of vision-based applications, such as transportation systems or advanced driver assistance systems, as well as several other outdoor surveillance-based systems. To cope with these problems, removal of weather effects (or the so-called deweathering) from visual data has been critical and received much attention. Therefore, it is important to provide a preprocessing step to automatically decide the current weather condition for input visual data, and then the corresponding proper deweathering operations (e.g., removals of rain or snow) will be properly triggered accordingly. This paper presents an inception network-based weather image classification framework relying on the GoogLeNet by considering the two common weather conditions (with similar characteristics), including rain and snow, in outdoor scenes. For an input image, our method automatically classifies it into one of the two categories or none of them (e.g., sunny or others). We also evaluate the possible impact on image classification performance derived from the image preprocessing via filtering. Extensive experiments conducted on open weather image datasets with/without preprocessing are conducted to evaluate the proposed method and the feasibility has been verified.
JPEGCNN: A Transform Domain Steganalysis Model Based on Convolutional Neural Network

Convolutional Neural Network (CNN) has gained an overwhelming advantage in many fields of pattern recognition. Both excellent data learning ability and automatic feature extraction ability of CNN are urgently needed in image steganalysis. However, the application of CNN in image steganalysis is still in its infancy, especially in the field of JPEG steganalysis. In this paper, a steganalysis model based on CNN in gray image transform domain is proposed, which is called JPEGCNN. At the same time, on the basis of JPEGCNN, JPEGCNN is extended to the transform domain of color image by researching and designing different methods of feature extraction. RGBMERGE-JPEGCNN and RGBADD-JPEGCNN are proposed respectively, which make up for the lack of research on steganalysis model based on convolution neural network in the transform domain of color image. Experiments show that JPEGCNN, RGBMERGE-JPEGCNN and RGBADD-JPEGCNN proposed in this paper have good detection ability for steganography algorithm in transform domain.
A Breath Switch for Secure Password Input

One of the most popular authentication methods in information security is the use of passwords. However, people who cannot use typical keyboards, like those having physical disabilities, cannot input their passwords efficiently. With assistive technologies, they can move a cursor and/or hold a pointer in their mouth to enter characters shown on a screen keyboard. However, if someone is next to them and is looking at the screen, they can easily see the characters being entered. We propose a breath-based password input system, in which characters can be entered via exhalation. This will allow people with severely limiting physical disabilities to securely input their secret information.
Short tightly secure signatures for signing a vector of group elements: A new approach

We give a new approach to build tightly secure signatures for signing a vector of group elements in a bilinear group. We illustrate its usefulness to construct efficient signature schemes by giving two new constructions of partially structure preserving signature schemes, a weaker version of structure preserving signatures which are still compatible with Groth-Sahai Non-Interactive Zero-Knowledge Proofs. The first scheme is simpler to analyze, while the second scheme is more efficient and has a signature size of only 3 group elements. This is comparable to the state-of-the art in tightly secure signatures in bilinear groups without the partial structure preserving property. We finally give a third construction using the same ideas, a tightly secure signature scheme in bilinear groups which is comparable with the state-of-the-art.
The Systematic Discovery of Services in Early Stages of Agile Developments: A Systematic Literature Review

In recent years, agile methodologies have been consolidated and extended in organizations that develop software in Web environments.For this reason, the development methodology of these organizations will not only be related to Services, but also to the Web Engineering paradigm.These organizations are heading for incorporating software development methodologies whose paradigm can allow integration, naturally and in the earlier stages of Web applications develop with the services of the organization that described and published in the Services Portfolio.The aim of this study will be to analyze the current state of the art in the process of discovering services in early stages of agile software development with focus on those identified requirements that could be covered with the services included in the Service Portfolio.We have identified 20 relevant papers through conducting a double systematic literature review (SLR).It is concluded that no study has been found that can solve the entire process of discovering candidate services within an organization that cover the requirements of a new application developed with agile methodologies.At the same time, guidelines have been found to formalize the solution to this problem and fill in that gap of knowledge by proposing in a single process, the formalization of a requirement based on agile techniques, which can be managed against a Services Portfolio.