Reviewerly/exHarmony huggingface dataset:
A Survey: XSS Attack On Web Applications

These days the web applications are profoundly valuable and amazing for utilization in many fields, for example, fund, web-based business, human resource, etc so it must be all around verified. Applications may be susceptible, hence get abused by assailants to take the client's credentials. Cross scripting (XSS) is a significant risk to web applications as it is the fundamental and simple assault on web applications. Xss layout the platform for assaults such as Cross-Site Request Session Hijacking, Forgery ...etc. An XSS assault is an infusion assault in which vindictive content is infused into the site by the assaulter in the user-side in the client's program or on the server-side in the database. The malicious code is basically a JavaScript code and is performed on an input field in web applications. Kinds of XSS assaults are i.e. nonpersistent (or reflected) XSS, persistent (or stored) XSS, and DOM-Based vulnerabilities. The main cause of Cross-site scripting (XSS) weakness is failing to sanitize user inputs implanted in web pages. Despite adopting secure coding techniques and using vulnerability detection tools XSS remains in many web applications because the method is quite complex, improper implementation of methods, lack of knowledge of vulnerabilities. In this paper, we have surveyed on XSS attack, causes, and approaches for the prevention of stored based XSS and DOM based XSS.
Numerical Simulation of Stratified Values of the Vertical Gravity Gradient Generated by a Pair of Closely Spaced Isolated Inhomogeneities with Excessive Density

Abstract In the article is presented a mathematical model and a computational algorithm for solving the inverse problem of gravity gradiometry – a problem of localization (separability) of a pair of gravitational inhomogeneities – isolated ore bodies (oil and gas domes) with excessive positive (negative) density based on the gravitational anomalies generated by them. Anomalies are empirical data for solving the inverse problem, which is relevant for geological exploration, monitoring and geophysical support of developed fields, as well as for practical problems of engineering geology.
Investigation and Research on the Status Quo of Informatization Development at Home and Abroad

Abstract With the further advancement of the digital age, informatization has become the current most mainstream trend and has attracted widespread attention from the public. As a decisive measure for the country to increase its talent pool and cultivate innovative talents, it plays a vital role in promoting national development and enhancing international competitiveness. This article draws on the strategic measures and policies of French education informatization to analyze the current situation of education informatization in China and look forward to the prospects of the education informatization industry.
Model of preparing children with delayed mental development to school in conditions of preschool educational institutions

The article discusses the need to build a model of preparation for school education working in preschool educational institutions. The proposed model is based on the direction of work that makes it possible to identify multi-level, systemic relationships between the components of the model, as well as problems that hinder the effective professional activity of a teacher in preschool education.
Implementing Data Privacy of Cloud Data on a Remote Server using Symmetric Cryptographic Algorithms

Cloud Computing is an excellent technology for Micro Medium and Small Enterprises, which operate under budget shortage for setting up their own Information Technology infrastructure that requires capital investment on resources such as computers, storage and networking devices. Now-a-days, major Cloud Providers like Google and Amazon provide cloud services to its customers for managing their email, contact list, calendar, documents, and their own websites. MSME can take advantage of the cloud-based solutions offered by various Cloud Service Providers for equipping their own employees in doing their day to day activities more effectively and on the cloud. Though cloud computing promotes less expensive and collaborative work environment among a group of employees, it involves risks in keeping the resources such as computing and data secured. Different mechanisms are available for securing the data on the cloud among which encryption of data using cryptographic algorithm is the widely used one. Among various encryption symmetric algorithms, Advanced Encryption Standard is the more secured symmetric encryption algorithm for implementing data privacy on the cloud. In this paper, the authors have discussed some of the issues involved in adopting the cloud in an organization and proposed solutions that will benefit an organization while uploading and managing data in files and databases on the cloud.
LibGuides: Education: More Help

This Library Guide will help students find the resources they need for their education research.
Sequence Embedding for Zero or Low Resource Knowledge Graph Completion

Knowledge graph completion (KGC) has been proposed to improve KGs by filling in missing links. Previous KGC approaches require a large number of training instances (entity and relation) and hold a closed-world assumption. The real case is that very few instances are available and KG evolve quickly with new entities and relations being added by the minute. The newly added cases are zero resource in training. In this work, we propose a Sequence Embedding with Adversarial learning approach (SEwA) for zero or low resource KGC. It transform the KGC into a sequence prediction problem by making full use of inherently link structure of knowledge graph and resource-easy-to-transfer feature of adversarial contextual embedding. Specifically, the triples $$(<\!\!h,r,t\!\!>)$$ and higher-order triples $$(<\!\!h,p,t\!\!>)$$ containing the paths $$(p= r_1 \rightarrow \cdots \rightarrow r_n)$$ are represented as word sequences and are encoded by pre-training model with multi head self-attention. The path is obtained by a non-parametric learning based on the one-class classification of the relation trees. The zero and low resources issues are further optimizes by adversarial learning. At last, our SEwA is evaluated by low resource datasets and open world datasets.
Analisa Perbandingan Fungsi Efektivitas Cloud Management Platform OpenNebula Dan Eucalyptus

Cloud Management Platform or CMP have an important role to provide maximum services for management device on premises and virtualization devices at utmost efficiency and under control. There are many types of CMP that can be use in any Cloud Computing Provider. However, choosing the right CMP, can provide accessibility on system management, such as expandability, cost, resource management, system durability and performance produced by the system. This analysis study is using Literature Review method to provide theoretical comparisons through the studies that have been researched by previous researchers. With this research study, Cloud Service Manager can choose the right CMP that suits their needs.
Level alert classification of dengue hemorrhagic fever cases in DKI Jakarta with the implementation of the random forest algorithm

Abstract In 2007, the capital district, DKI Jakarta had one of the worst floods that submerged nearly 60% of the area. One of the causes was heavy rainfall. Two months after the incident, the Governor of DKI Jakarta stated that the capital district was affected by an outbreak of dengue fever. From these two incidents, there are some indications of dengue hemorrhagic fever cases related to weather. In this research, a random forest classification algorithm was used to build a model that could classify the level alert of dengue fever for each district in DKI Jakarta into three categories: safe, moderately safe, and unsafe. The results and the accuracy of the classification model for the level alert of cases of dengue hemorrhagic fever for East Jakarta, North Jakarta, South Jakarta, Central Jakarta, and West Jakarta are 94.51%, 86.81%, 81.32%, 80.22%, and 80.22% respectively.
Pitch Contour Stylization by Marking Voice Intonation

The stylization of pitch contour is a primary task in the speech prosody for the development of a linguistic model.The stylization of pitch contour is performed either by statistical learning or statistical analysis.The recent statistical learning models require a large amount of data for training purposes and rely on complex machine learning algorithms.Whereas, the statistical analysis methods perform stylization based on the shape of the contour and require further processing to capture the voice intonations of the speaker.The objective of this paper is to devise a low-complexity transcription algorithm for the stylization of pitch contour based on the voice intonation of a speaker.For this, we propose to use of pitch marks as a subset of points for the stylization of the pitch contour.The pitch marks are the instance of glottal closure in a speech waveform that captures characteristics of speech uttered by a speaker.The selected subset can interpolate the shape of the pitch contour and acts as a template to capture the intonation of a speaker's voice, which can be used for designing applications in speech synthesis and speech morphing.The algorithm balances the quality of the stylized curve and its cost in terms of the number of data points used.We evaluate the performance of the proposed algorithm using the mean square error and the number of lines used for fitting the pitch contour.Furthermore, we perform a comparison with other existing stylization algorithms using the LibriSpeech ASR corpus.
The Effectiveness of Colour-Coded Dominoes in Enhancing Simple Sentence Construction

Writing is considered one of the most arduous language skills to master by English as a Second Language (ESL) learners.Hence, this study aims to investigate the effectiveness of colour-coded Dominoes in enhancing simple sentence construction among year three pupils.Twenty pupils from a national school in Johor Bahru district who had obtained Band 2 in School-Based Assessment (SBA) were selected as the participants of this action research.The data were collected through pre-test, post-test, Focus Group Interview (FGI) and field notes on classroom observation.The findings revealed that colour-coded Dominoes had enhanced simple sentence construction among the participants effectively.This study has impacted the pupils by elevating their learning motivation in a fun and conducive learning atmosphere with its attractive features to construct simple sentences.Thus, language games such as colour-coded Dominoes should be incorporated into English lessons to facilitate teaching and learning.
Culture and Language Use

The chapter discusses how cultural institutions and artefacts affect the shared workspace framework. We first consider the integration of linguistic and non-linguistic information in the shared workspace when interlocutors do such things as jointly constructing flat-pack furniture. We show how the framework is ideally suited for such integration of signs and non-signs as part of the activity. We then consider how different activity types serve to refine dialogue games. Finally we consider how cultural artefacts augment the shared workspace to support alignment. We consider the role of illustration, recording and other communication technologies.
Network-Based Hiring: Local Benefits; Global Costs

Entrepreneurs, particularly in the developing world, often hire from their networks: friends, family, and resulting referrals. Network hiring has two benefits, documented extensively in the empirical literature: entrepreneurs know more about the ability of their network (and indeed they are often positively selected), and network members may be less likely to engage in moral hazard. We study theoretically how network hiring affects the size and composition (i.e., whether to hire friends or strangers) of the firm. Our primary result is that network hiring, while locally beneficial, can be globally inefficient. Because of the existence of a network, entrepreneurs set inefficiently low wages, firms are weakly too small, rely too much on networks for hiring, and resulting welfare losses increase in the quality of the network. Further, if entrepreneurs are uncertain about the true quality of the external labor market, the economy may become stuck in an information poverty trap where forward-looking entrepreneurs or even entrepreneurs in a market with social learning never learn the correct distribution of stranger ability, exacerbating welfare losses. We show that the poverty trap can worsen when network referrals are of higher quality.
Message from the General and Program Chairs

Welcome to the 2011 International Conference on Cloud and Service Computing (CSC2011) and the city of Hong Kong. In the past several years, cloud and service computing have attracted a lot of attention from both academics and industrial communities. Cloud computing is an important transition and paradigm shift in IT service delivery driven by economies of scale. It enables a shared pool of virtualized, dynamically configurable, and managed computing resources to be delivered on demand to customers over the Internet and other available networks. As such and with the “pay-asyou-go” business model, cloud computing also leads to changes and transformation of many other industries. Closely related to cloud computing, service computing has become a cross-discipline area bridging the gap between Business Services and IT Services.
LibGuides: Living Poets: Fairfax County Poet Laureate 2020-2022 Nicole Tong

Come celebrate National Poetry Month with resources about Living Poets! Explore resources here at NOVA Libraries, online and in our local communities. Try your hand at a Haiku with our annual Haiku Contest! Happy Spring! Explore NOVA's own Nicole Tong, Professor of English and the Fairfax County Poet Laureate 2020-2022!
Insufficiency and Improvement of Online Teaching in the Context of the Covid-19 Pandemic

In the face of the sudden outbreak of COVID-19 virus, the Ministry of Education requires schools to postpone the opening, but calls for “ensuring learning undisrupted when classes are disrupted” at the same time. Online teaching has been widely used during the epidemic, but there are still many shortcomings, which limit the effectiveness of online teaching. Based on the current development of online teaching, this paper analyzes the main existing problems and puts forward some improvement measures in order to give full play to the advantages of online teaching and promote the teaching reform of combining online and offline in colleges and universities.
Novel method for sql injection prevention

Novel method for sql injection prevention - Web security is a set of procedures, practices, and technologies for protecting
Role of Internet of Things and Machine Learning in Finding the Optimal Path for an Autonomous Mobile Robot

Path planning for the mobile robot is an emerging area in today’s world; the development of autonomous vehicles like driverless cars and mobile robots has tremendously enhanced researchers to work more on path planning strategies using emerging technologies, like the Internet of things and machine learning. These technologies will provide optimal solutions than classical problem-solving algorithms. The article deals with path planning for mobile robots in an unknown environment using deep learning and the Internet of things. These technologies are adopted to work in different strategies like environmental prediction, object detection/ obstacle detection, and finding a path. For this, an innovative model is proposed to detect static and dynamic obstacles from the input data and finding a path from one point to another point.
Corpus of Croatian news portals ENGRI (2014-2018)

The corpus consists of texts collected from the most popular (based on the Reuters Institute Digital News Report for 2018, retrieved from http://www.digitalnewsreport.org in April, 2019) news portals in Croatia in the period from 2014 to 2018: Direktno, Dnevno, Net Hr, Hrt, Index_Hr, Jutarnji, Novilist, Rtl, SlobodnaDalmacija, Vecernji, Tportal, Dnevnik. Web browsing and web crawling were used to select and store the texts with their useful HTML information (publication date of the article, its URL, and title). The linguistic processing of the corpus was performed with the CLASSLA package (https://pypi.org/project/classla/) on the levels of tokenization, sentence splitting, morphosyntactic tagging, lemmatization, dependency parsing and named entity recognition.This corpus is a linguistically-processed version of the original corpus published at https://repository.pfri.uniri.hr/islandora/object/pfri%3A2156 and is distributed in the CoNLL-U format (https://universaldependencies.org/format.html).
Structural design of microscopic 3D measurement system based on dual-telecentric optical path

Most of the traditional microscopic systems are based on the structural design of a single telecentric camera combined with a single projector. The projector in such system needs to be accurately calibrated as an additional view to complete the 3D measurement with the camera. However, it is difficult to achieve high-accuracy calibration due to problems such as gamma, lens distortion, and additional lenses that are difficult to accurately align. In this work, we present a structural design of microscopic 3D measurement system based on dual-telecentric optical path, which contains two camera that can be accurately calibrated and a projection light path. Our design can make full use of the advantages of the full-field structured light projection and is convenient to calibrate. Two different perspectives can provide 3D data from different depth and multiple angles simultaneously so that measurement volume can be enlarged by superimposing the data.
Does the Legal Form Matter for Firm Performance in the MENA Region?

This paper attempts to study the relationship between firm legal form and firm performance in the Middle East and North Africa Region (MENA) using the World Bank Enterprise Survey (WBES) database. Our analysis shows that open shareholding, closed shareholding, partnership, and limited partnership companies demonstrate an advantage in terms of annual sales and annual productivity growth rates over sole proprietorship firms, and that medium-sized and large-sized firms also demonstrate an advantage over small ones. Our analysis also shows that foreign ownership, exporting activities, the usage of the web in communication with clients and suppliers, and the presence of full-time workers positively affect firm performance. These findings are robust when running the analysis for firms with female participation in ownership. This paper provides directions for strategists targeting at improving the performance of firms.
KU_NLP@LT-EDI-EACL2021: A Multilingual Hope Speech Detection for Equality, Diversity, and Inclusion using Context Aware Embeddings

Hope speech detection is a new task for finding and highlighting positive comments or supporting content from user-generated social media comments. For this task, we have used a Shared Task multilingual dataset on Hope Speech Detection for Equality, Diversity, and Inclusion (HopeEDI) for three languages English, code-switched Tamil and Malayalam. In this paper, we present deep learning techniques using context-aware string embeddings for word representations and Recurrent Neural Network (RNN) and pooled document embeddings for text representation. We have evaluated and compared the three models for each language with different approaches. Our proposed methodology works fine and achieved higher performance than baselines. The highest weighted average F-scores of 0.93, 0.58, and 0.84 are obtained on the task organisers’ final evaluation test set. The proposed models are outperforming the baselines by 3%, 2% and 11% in absolute terms for English, Tamil and Malayalam respectively.
KEYWORD ANALYSIS WITH USING STATISTICAL METHODS

There are currently more than a billion websites worldwide. In so many websites, everyone wants to be visible to search engines through the keywords that people search for. The article deals with the process of creating keywords, through which we can identify the intention of the searcher. The process of creating keywords consists of several steps, namely the collection of keywords, subsequent cleaning of keywords, their categorization and the last step is the interpretation of keywords. The paper focuses mainly on the categorization of keywords, which we obtain through the use of statistical methods, which includes a method of visualizing relationships between keywords by determining the strength of the association between words called concept linking or term map.
Deprecating FFDH(E) Ciphersuites in TLS

This document deprecates and discourages use of finite field andelliptic curve Diffie Hellman cipher suites that have knownvulnerabilities or improper security properties when implementedincorrectly.
Product Evaluation on the Chinese Language Program for International Students in a Chinese University

HanyuShuipingKaoshi (HSK) is an international standardized test, which means Chinese Proficiency Test in English. A minimum of HSK level 4 is needed for an international student to apply for an academic programme taught in Chinese language in the universities of China. Guided by product evaluation of Context, Input, Process, Product (CIPP) model, the test scores of HSK level 4 of the international students in a Chinese university are analyzed using effect size. Feedbacks from the international students who failed in the test of HSK level 4 are collected based on a questionnaire formulated by the researchers. The strengths, weaknesses, causes of failure and improving direction of the one academic year’s Chinese language program in this Chinese university are identified through the evaluation. The research aims to provide references for the improvement of Chinese language teaching in this Chinese university and universities with the same context. The research enriches the literature concerning the evaluation on Chinese language teaching and learning for international students in China.
International Activities - Scholarship for Students

Scholarship for Students by The Advisory Board of the Foundation of Szechenyi Istvan University
Acquiring Event-Specific Semantics from English Online News Corpus: A Study of Computational Linguistics

The paper explored algorithm for automatic extension in English language. The automation was for the event-specific semantics which was unsupervised in the cluster of terms. The algorithm was tested in the particular language i-e English to acquire words which were necessary for detection of displacement and evacuation events. These events were constituted as significant factor for developing the humanitarian problems, clashes and natural or artificial catastrophe. The paper demonstrated acquisition of algorithm, semantic classes besides from grammar extension as an inception for semi-automation. This semi-automation was based on the construction of domain-specific ontology of fiasco. The experiment was carried out in English language which acquired a conclusive support.