Reviewerly/exHarmony huggingface dataset:
Integrated-Block: A New Combination Model to Improve Web Page Segmentation

Context: Web page segmentation methods have been used for different purposes such as web page classification and content analysis. These methods categorize a web page into different blocks, where each block contains similar components. Objective: The goal of this paper is to propose a new segmentation approach that semantically segments web pages into integrated blocks and obtains high segmentation accuracy. Method: In this paper, we propose a new segmentation model that semantically segments web pages into integrated blocks, where (1) it merges web page content into basic-blocks by simulating human perception using Gestalt laws of grouping; and, (2) it utilizes semantic text similarity to identify similar blocks and regroup these similar basic-blocks as integrated blocks. Results: To verify the accuracy of our approach, we (1) applied it to three datasets, (2) compared it with the five existing state-of-the-art algorithms. The results show that our approach outperforms all the five comparison methods in terms of precision, recall, F-1 score, and ARI. Conclusion: In this paper, we propose a new segmentation model and apply it to three datasets to (1) generate basic-blocks by simulating human perception to segment a web page, (2) identify semantically related blocks and regroup them as an integrated block, and (3) address limitations found in existing approaches.
Analysis of Most Common Encryption Algorithms

As the things are settled down after the emergence of technology, and this is the decade of professionalism as far as technology is concerned, security of data is the major hurdle in this race. This is the era in which data is one click away from the users, so data needs to be more secured so that it can be avoided unauthorized access. For this purpose, different data security fields have also emerged to ensure data security and confidentiality. In this survey paper we will look up all the techniques used for data encryption and after that, we compare those techniques to provide the best algorithm to ensure that data is secured. We go categorically, as in most of the cases, symmetric encryption technique is applicable and, in a few cases, asymmetric is recommended. Firstly, in our study, we compare both the techniques with each other and then compare all the algorithms working under the above-mentioned categories concerning their time, efficiency, memory usage, latency, key size, and several rounds which will result in showing the best algorithm according to input data.
Multiscale ship detection based on cascaded dense weighted networks in synthetic aperture radar images

The sizes of ships vary by type in synthetic aperture radar (SAR) images, and this multiscale problem degrades the accuracy of ship detection. We present a multiscale ship detection method based on cascaded dense weighted networks in SAR images. Dense weighted fusion is performed in the feature extraction module and feature fusion module by cascading, i.e., feature weighting is achieved by embedding a convolutional block attention module after feature layers at different scales, followed by dense connection to fuse features at different scales. This makes it possible to refine the cascaded feature mapping, enhance the information transfer of shallow and deep features, and build a multiscale feature representation model. Experiments on the extended high-resolution SAR images dataset show that the accuracy of this method is 74.87% in inshore scenes, and 97.39% in offshore scenes, which exceeds that of other ship detection methods. In addition, in two SAR images from TerraSAR-X, the detection accuracy of multiscale ships reaches 86.63%, which indicates the method’s better robustness.
Understanding Pelger Huët Cell

The Pelger-Huët anomaly (PHA), an autosomal dominant condition is characterized by morphologically abnormal neutrophil. This abnormal neutrophil has an unique morphological appearance called as Pelger-Heut cell (PHC) .Understanding &nbsp;this special type of cell is essential as it demands a diagnostic challenge to differentiate it from its mimickers. This article summarises the history of PHA, pathogenesis, and guidance for distinguishing between congenital and acquired PHA, as well as their various morphological variants. We present an intriguing case of pseudo-PHA in a 70-year-old male with Leptospirosis who had spectrum of dysplastic neutrophils with unilobed, unilobed intended, and bilobed pelgeroid cells in the peripheral smear.
The Need for Speed: From Electric Supercars to Cloud Bursting for Design

Our industry has insatiable need for speed. In addition to fast products for consumer electronics, medical, mil-aero, security, smart sensors, AI processing, robots, and more, we also continuously push for higher performance for the processing and communication infrastructure needs for true hyper-connectivity.
A dense vehicle target detection method based on CSAR image

The traditional synthetic aperture radar (SAR) image can only detect a piece of target area, but can not accurately locate a single vehicle target in the target group. In order to improve the accuracy and efficiency of dense vehicle detection in SAR images, a method of segmentation detection for dense vehicle targets was proposed to make full use of the advantages of CSAR (Circular SAR) in acquiring target scattering information from all directions. The method separates the entangled adjacent targets through image segmentation, and then uses the clustering method based on azimuth angle to locate the target precisely. Experimental results show that the detection probability of the proposed method is 93.18% and 91.84% respectively for high-frequency and low-frequency CSAR image dense vehicle targets, which can locate the densely packed vehicle targets in the scene more accurately, reduce the false alarm rate, and realize the detection of dense vehicle targets. Compared with other dense vehicle target detection methods, the detection performance of this method is better.
IVAN ALEXEYEVICH DVIGUBSKY: ON THE 250TH ANNIVERSARY OF HIS BIRTH

The article discusses the scientific biography of Ivan Alexeyevich Dvigubsky (1771/72-1839/40), Moscow State University’s provost (1826-33), dean of the Department of Physical and Mathematical Sciences, honorary professor (1830) and honorary member of the university, an eminent teacher and naturalist.
A Study on the Multi-Dimension of ㅂ Irregular Inflexion

ㅂ irregular inflexion is a phenomenon that occurs very frequently in Korean. Many researchers have been interested in this because the phenomenon is not simple. As a result, ㅂ irregular inflexion has long been the subject of interest with various people such as phonology, morphology, and syntax. Unlike this situation, language regul- ations and grammar textbooks treat ㅂ irregular inflexion too simply. It is difficult to fully understand the multidimensions of ㅂ irregular inflexion only with the content of the grammar textbook and the language regulations. There- fore, this study pointed out the problems of grammar textbooks and language regulations related to ㅂ irregular inflexion. In addition, various research results on the characteristics of ㅂ irregular inflexion were reviewed. Finally, all words listed in the Open Dictionary, <Urimalsaem> were reviewed. Through this, we tried to get closer to the practical knowledge of ㅂ irregular inflexion. This paper is expected to provide meaningful information for Korean language education and Korean language education as a foreign language in the future.
A Survey on Virtual Machine Migration in Cloud Computing

Cloud computing provides multiple services to users through the internet and these services include cloud storage, applications, servers, security and large network access. Virtual Machine allows the user to emulate multiple operating systems on a single computer; with the help of virtual machine migration users can transfer operating system instances from one computer to multiple computer machines. In this paper we will be discussing VM migration in cloud and also I will explain the whole procedure of VM migration. The two methods through which we can perform VM migration are Live VM migration and NON-live VM migration.VM migration also helps in managing the loads of the multiple machines and with VM we can save power consumption. People have written about cloud computing and virtual machines in previous studies, but in this research, we'll speak about virtual machine migration in cloud computing, as well as the techniques that are used in the VM migration process. I have used table to show the differences between VM migration techniques.
Fourier attack – a more efficient adversarial attack method

As neural networks have made remarkable achievements in the field of image classification, a variety of adversarial attack methods have appeared to interfere with neural networks. Adversarial samples apply a tiny perturbation to the original image, which would not make much sense to the human eye, but would produce a massive error to the neural network. In recent years, many articles have made contributions to adversarial sample attack and defense, which aim to generate a maximum classification error while minimizing the perturbation. However, former attacks are focused on the spatial domain. We find that separated attacks based on different components in the frequency domain are more effective. The contribution of this article is: (1) compute the gradient of the neural network for image classification after the discrete Fourier transform. (2) design a stationary filter to generate the adversarial sample according to frequency component and gradient. (3) conduct experiments show that the adverasial samples generated by our method achieve the same attack effect on the premise that they are closer to the original picture.
Two-way machine translation model of notices to navigation based on transfer learning and back translation

In order to improve the professionalism and accuracy of machine translation in the field of notice to air navigation, a twoway machine translation model of notice to air navigation based on transfer learning and back translation is proposed to solve the problem of the parallel corpus of machine translation in the field of air notice. On the basis of training the machine translation of People’s Daily, the parameters obtained from the training are transferred to the encoding end and the decoding end of the machine translation model of the partly back-translated announcements to initialize the parameters at both ends, and adjust the parameters at both ends through experiments. Obtain the two-way machine translation model of the notice of air travel. Experiments show that the introduction of the data enhancement strategy of transfer learning and partial back translation improves the robustness of the model and improves the translation quality. The BLEU value of the translation evaluation index of the Chinese-to-English model has increased by 2.08%. The BLEU value of the translation evaluation index increased by 3.12 percentage points
L’empathie en réalité virtuelle comme posture d’auteur : Une étude québécoise

For certain authors, virtual reality (VR) is an effective media to gain user empathy, in part because of its immersive and interactive properties. How do VR work creators consider empathy? When they seek to stimulate empathy through their works, what mechanisms do they implement? Conversely, do they care little about it or do they reject it categorically? Is there a specifically Québécois use of empathy in virtual-reality creations? The analysis of Québec VR works undertaken to try and answer those questions confirms a definite interest towards empathy in VR, an interest encouraged by funding bodies. Furthermore, two trends can be noted: certain VR authors seek individualized empathy (relating to personal stories), while others pursue non-individualized empathy (relating to a group of people or a human archetype). Our study did not identify specific Québec characteristics for the use of empathy in VR, but does allow us to conclude that empathy in VR is an author’s choice, perhaps even creator posturing, with an ethical purpose.
DevOps Security and Privacy in the Development of Multicloud Applications

There are many different types of services that can be provided to cloud computing consumers, such as on-demand services, flexible pricing, and risk transfer during resource sharing. The security of data, energy consumption, and server consolidation are all issues that cloud computing is now grappling with. There has been some research on enhancing security at several levels, including application, operating system, VM, and hardware. An innovative DevOps framework and methodology are presented in this thesis to help rationalize and systematize security and privacy analyses in multiCloud so that an informed decision-process for risk-cost balanced selection of the protections of system components and the protections requested from Cloud Service Providers can be enabled. MultiCloud application development is the primary emphasis of the work being done at this time.
Grammatical Generalizations in Neural Language Models Trained on L2 Textbooks

Recent studies employing state-of-the-art neural network language models (NLMs) have reported their human-like performances in ‘understanding’ various linguistic phenomena particularly through the Benchmark of Linguistic Minimal Pairs (BLiMP), which is a challenge test dataset of sentences to be used for evaluating the linguistic knowledge of NLMs on major grammatical phenomena in English (Warstadt et al., 2020). Adopting the methodology at hand, this paper aims to assess the level of linguistic knowledge acquired by L2-NLMs trained on English textbooks (alias the K-English datasets) published in Korea and compare it with the corresponding different levels in English native speakers and L1-NLMs. Assuming that an NLM is also a language learner, we used the BLiMP to evaluate the grammaticality rating performances of L2-NLMs based on Generation Pre-trained Transformer-2 (GPT-2) and Long Short-Term Memory (LSTM). In conclusion, this study demonstrates that the L2-NLMs have attained a substantially lower level of grammatical generalization than L1 counterparts as well as English native speakers. The results imply that the K-English training datasets are not robust enough for L2 NLMs to make substantial grammatical generalizations.
A Novel Framework for Selecting Elicitation Technique based on Attribute Mapping

The software development process is completely based on the requirements of stakeholders. If the requirements of stakeholders are being integrated into the proposed system, then it can be assumed that the end product is going to be optimal and successful. To achieve a successful product, different Requirement Elicitation Techniques (RET) are being practiced. The selection of a suitable RET is based on the nature of the product being developed. So, a single RET doesn’t fit all products. In this paper, we differentiate all RETs from each other which makes it easier for an analyst to choose suitable RET from the available ones. We further designed a novel mapping framework that extracts the best suited RET to any software based on its attributes. We have further implemented the proposed framework by using an online vehicle booking system as a running example.
Evaluation of Urban Drainage System as a Flood Control in Klitren Urban Village

Flooding that often happens during the rainy season in Klitren urban village is caused by reducing open space as water catchment areas [1]. It happens due to several factors, including a large amount of land that has been converted into residential areas and unsustainable existing drainage systems. To evaluate the amount of runoff produced by the area, the writer conducted a simulation using EPA SWMM 5.1 software. The simulation is conducted to compare how much runoff is generated by the area and how much water is collected according to the drainage system's capacity. Modeling alternatives used including the existing condition and other alternatives such as implementing green infrastructure installations. From the results of the analysis conducted in the study location, the runoff decreased from 3,09 m3/s to 2,92 m3/s, and the runoff decreased by 5,5%. Then, it can be used as a reference for implementing green infrastructure in urban areas.
A Virtual Book based on Human Anatomy

—Over the last few decades, the educational field has seen an major change from the traditional usage of books in school to virtually learning. The world-wide pandemic has enabled teaching and learning methods to be conducted virtually for the benefit of the students from home. The proposed application allows the students to learn by logging into the application and go through and select various available human organs/systems and view them in 3-D Augmented Reality (AR) world. Developing such an Android based application on Human Anatomy and additional features such as YouTube video lectures with deep concept explanation for more interactive learning will be helpful. This project is implemented in Android Studio. A 3D framework called SceneForm was used to build this AR application. It enables to readily render 3-D models. The mobility of mobile application allows students to learn interactively and also it helps to learn to concepts and build their interest for their future career.
Handling Heterogeneous Data in Knowledge Graphs: A Survey

In this era of information where everything is digital, data tends to be ubiquitous. Data Analytics is a term that covers all the areas that deal with the logical analysis of raw data Graph analytics is one of the emerging domains of data analytics that represents and analyses data in the form of knowledge graphs. Knowledge graphs play a vital role in analysing and processing data in order to make decisions. In knowledge graphs the data is stored in the form of entities, relationships between the entities and the attributes of entities as well as attributes of relationships. Construction of knowledge graph and its analytics face multiple challenges like data redundancy, heterogeneity of data, missing data, dynamic nature of real-world data etc. This paper focuses on the issue related to heterogeneity of data while constructing a knowledge graph, and it provides a systematic literature review over construction of knowledge graphs from heterogeneous data sources. This review compiles state-of-the-art knowledge fusion techniques. To conduct this systematic literature review, an exhaustive approach has been adopted to identify various procedures and algorithms included and adapted by different research works for knowledge graph construction.
Web-Based Recommender System for High School Major Decision Using Forward Chaining

Education is a learning process for students to develop their potential skills. One of the vocational schools is the State Vocational High School (SMK) 05 Bekasi, that educates students to have high expertise in industrial fields. However, not every student can choose the right major, there are students who choose majors based on the wishes of their parents, and do not know their real potential and abilities, so that the abilities of students are not in accordance with the majors they have chosen. One way that can be used to help choose the right major is to take a preference test that is assessed by a psychologist or the Counseling Guidance section. This method is quite effective, but it takes time especially for large numbers of student. Therefore, the researcher created a website-based recommendation system to identify majors using the Forward Chaining method. The purpose of the research is to make a recommendation system to determine the majors that students will choose. The application are developed using the System Development Life Cycle.
Successful charitable challenge

Veterinary RecordVolume 190, Issue 8 p. iii-iii People Successful charitable challenge First published: 14 April 2022 https://doi.org/10.1002/vetr.1726Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume190, Issue816–30 April 2022Pages iii-iii RelatedInformation
Power and Energy-efficient VM scheduling in OpenStack Cloud Through Migration and Consolidation using Wake-on-LAN

On-demand provisioning of computing resources using the network over the Cloud consumes a tremendous amount of energy. The energy consumed does not scale out efficiently with the computational use of the resources. A large portion accounts for the power consumption to drive the hardware and cooling facilities for the hardware resources. Nowadays, energy and power consumption have become the most critical concerns in data centers. This work highlights a novel technique to achieve energy efficiency through server consolidation to address the abovementioned situations by effectively scheduling Virtual Machines (VMs) onto the servers and rescheduling active VMs upon deletion of existing VMs through cold migration. An advanced technology, i.e. Wake on LAN (WoL), is employed through power wake for dynamic and wake up of the servers on private Cloud. Compared to existing models, the proposed approach's maximum estimated energy and power saved are experimentally verified to be 54% and 50%, respectively.
Impact of Glass Ceiling (GC) on Organizational Performance (OP): Moderating Role of Employee Satisfaction(ES)

The study focuses on employee satisfaction, as it is one of the major ingredients for better performance.In business originations, performance of overall organizations depends on the satisfaction level of employees, however various techniques have been applied to enhance the satisfaction, but couldn't succeed completely.Workforce includes female population as well, and one of the issues they face is Glass Ceiling and that leads to low satisfaction and hence towards below average organizational performance.A sample of 225 was selected, and through a valid and reliable instrument, data were collected.The data were screened and then analysis was carried out through applying various tests.The results show significant impact of the contributing variables including glass ceiling on the dependent variable.
Uplifting Interviews in Social Science with Individual Data Visualization: the case of Music Listening

Collecting accurate and fine-grain information about the music people like, dislike and actually listen to has long been a challenge for sociologists. As millions of people now use online music streaming services, research can build upon the individual listening history data that are collected by these platforms. Individual interviews in particular can benefit from such data, by allowing the interviewers to immerse themselves in the musical universe of consenting respondents, and thus ask them contextualized questions and get more precise answers. Designing a visual exploration tool allowing such an immersion is however difficult, because of the volume and heterogeneity of the listening data, the unequal "visual literacy" of the prospective users, or the interviewers' potential lack of knowledge of the music listened to by the respondents. In this case study we discuss the design and evaluation of such a tool. Designed with social scientists, its purpose is to help them in preparing and conducting semi-structured interviews that address various aspects of the listening experience. It was evaluated during thirty interviews with consenting users of a streaming platform in France.