Reviewerly/exHarmony huggingface dataset:
An Interpretive Saga of SQL Injection Attacks

Web applications security is indeed the most talked about and a vital topic of discussion in cyber security world. In the recent years, websites have become a main target for hackers. Attackers exploit vulnerabilities present in the web applications. Application level attacks are increasing day by day in websites. Some of the main application level attacks are SQL injections, cross-site scripting attacks, cookie poisoning attack, command injection attack, etc. According to OWASP, injection attacks occupy first place in breaching website security. There are several government, private and e-commerce websites that become victim of SQL injection attack each year. This paper includes the detailed study of mitigation strategies proposed by various researchers related to SQL injection attack. Furthermore, defence mechanism to safeguard web applications from SQLi attacks and future research directions is also indicated.
Assessing Metacognitive Online Reading Strategy Usage among EFL Teachers in Indonesia

A significant amount of research on Metacognitive Online Reading Strategies (MORS) is currently focused on EFL/ESL students, and only a few studies have examined the participation of EFL teachers. This quantitative study, therefore, aimed at assessing the use of these strategies among EFL teachers in Indonesia. Analyses of the strategy usage was based on factors of gender, teaching status, and internet literacy levels. Via a Google form application, a MORS survey was employed as the data collection instrument. The gathered data were analyzed descriptively and inferentially using t-tests, Pearson correlation, and linear regression. The results showed that in reading online academic materials, the teachers used support strategies more frequently than problem-solving strategies and global strategies. Overall, the teachers employed these strategies at a moderate to high level. Based on gender and internet literacy, significant differences in the overall and strategy category uses were discovered. There were significant correlations between the teachers’ internet literacy levels and their use of the overall strategies, the support strategies, and the global strategies, but no correlation between the internet literacy levels and the problem-solving strategies. The internet literacy levels were found to be strong predictors of the overall and category strategy uses. The findings of this research offer a wide variety of educational implications for EFL reading. Keywords: metacognitive online reading strategies; EFL teachers; gender; internet literacy; teaching status
Developing a Conceptual Model: Integrating CALL in TBLT

Over the last 20 years, task-based language learning (TBLT) has gained immense recognition from linguists all over the world. With the seamless assimilation of technology in the lives of educators and learners, a strong and growing body of literature has supported the efficacy of computer-assisted language learning (CALL) over the last decade. Recent research has
Source Area Weathering and Tectonic History Inferred from the Geochemistry of the Maastrichtian Sandstone from Patti Formation, Southern Bida Basin, North Central Nigeria

Sandstones sampled from Patti Formation, Southern Bida Basin, were studied geochemically using Inductively Coupled Plasma Atomic Emission Spectrophotometer (ICP-AES) and an Inductively Coupled Plasma Mass Spectrometry (ICP-MS) technique to evaluate their weathering and tectonic setting as well as to deduce the paleo-climatic conditions that existed during their deposition. Geochemically, SiO2 range from 73.9% to 86.2%, Al2O3 (6.7%~17.1%), Fe2O3 (1.1%~1.9%), K2O (0.1%~0.7%) while MgO, CaO, Na2O, P2O5, MnO and TiO2 were &lt;1%. Enriched in Ba (Av. 622.94), Sr (Av. 153.63), Rb (Av. 55.08) and Zr (Av. 51.86) relatively similar in composition to UCC. High SiO2 but low other major oxides signify high mobility during processes of weathering. This was confirmed by high value (&gt;80%) for indices like chemical index of alteration, chemical index of weathering, plagioclase index of alteration, mineralogical index of alteration and relatively lower values for weathering index of parker, recently used alpha indices (αAl E) of sodium (326.17αΑl Na&lt;344.40), magnesium (100.54αΑl mg&lt;398.55), calcium (12.07αΑl Ca&lt;198.99), potassium (4.43αΑl K&lt;64.33), strontium (0.84αΑl E&lt;21.40), barium (0.45 αΑl Ba&lt;10.52) and rubidium (0.0008αΑl Rb&lt;0.06), supported by AI2O3-(CaO*+Na2O)-K2O and CIA vs. SiO2 plots that imply intense weathering in the source area. The obtained high CIA values (&gt;80) indicates a steady-state of weathering under a warm/humid climate as confirmed by the SiO2 vs. Al2O3+ K2O + Na2O plot. High average SiO2 (75.41wt%) with K2O/Na2O ratio &gt;1 (15.63), low Fe2O3 (1.27wt %), Al2O3 (15.82wt%) and TiO2 (0.46) suggest passive margin tectonic setting. This is supported by enriched ΣREE (209.64 ppm), ΣLREE (195.78), LREE/HREE (27.78) and negative Eu/Eu* (0.68), plots of log (K2O/Na2O) vs. SiO2 and SiO2/Al2O3 vs. K2O/Na2O. Major elements discriminant-function multi-dimensional diagram, DF1 (arcrift-col) vs. DF2 (arc-rift-col), for high-silica sediments revealed a continental rift tectonic setting. Thus, the Patti Formation sandstone underwent a high degree of weathering under a humid climatic condition within a continental rift tectonic setting.
Design of a CHSE Information System to Expand Tourism Market Segmentation

The destination of this research is to produce a CHSE (Cleanliness, Health, Safety, and Environment Sustainability). Pariwisata information system to expand the tourism market segmentation to make it easier for tourists who have limited time and have difficulty finding information about tourist attractions to no longer experience obstacles. This online site has special specifications by offering several advantages, including being able to see CHSE practices and marketed tourist attractions. This study uses the Waterfall Method a sequential software development process, passing through the phases of planning, modelling, implementation, and testing. In its development, the waterfall method has several stages such as a waterfall from top to bottom while from bottom to top coherently: requirements, system design, coding, testing, implementation and maintenance. The results of this study meet the need for information on recreational areas that are healthy and safe, good, conducive, and not only limited to certain locations making this CHSE information system an important contribution to expanding tourism market segmentation. It is easy to get and reach the information needs of recreational offerings for people who come from outside the city of East Java. For the realization of the CHSE information system, its application requires the readiness of human resources and the availability of information technology infrastructure for smooth transactions and personal interaction with buyers (customers). Future research needs to complement the e-payment payment system to provide convenience in conducting transactions.
The Use of Youtube in Teaching Speaking : A Systematic Literature Review

The era of the COVID-19 pandemic has hampered the conventional learning process or face to face learning in schools. Of course, it is necessary to find a solution to overcome these obstacles. Through online learning is one way that can be used by teachers and students to overcome these problems. English subject is one of the subjects at the junior high / high school level. However, some students find this subject difficult to reach for students who have never studied English in schools before. The purpose of this research is to find out the benefits can be taken from YouTube for bold English learning media in the midst of the covid 19 pandemic. This research is a qualitative research in which the author uses the SLR method. The results of this study indicate that by using YouTube media, it is able to increase students' understanding so that students' learning achievement increases when using other media such as using e-books or WhatsApp, but things that do not need to be constrained are less than optimal supervision of teachers and other people. Parents to students, poor signal or internet network, and high quota even there are still students who don't have Android phones, which is an obstacle in using YouTube as a learning medium. Challenges in the world of education in meet the needs of the internet generation is quite large. This is due to experience those who differ in particular their life experience in using technology. Internet itself opens up many possibilities for integrating technology in learning in the classroom. Youtube is one of the learning media that can be integrated in learning English subjects that are considered difficult by students. Research purposes This is to see to what extent Youtube can be used as a learning medium in English eyes. The results showed that the videos on Youtube can be used as a learning medium.
Recent advances of research on power supply restoration of distribution network under extreme events

In recent years, the probability of large-scale power outage in distribution network caused by extreme events continues to increase, which poses a serious threat to people's life, market economy and social stability. With the continuous development of renewable energy, more and more distributed power sources are connected to the distribution network, which significantly improves the power supply reliability of the distribution network and also provides a way to ensure the continuous power supply of key facilities in extreme events. Based on the analysis of the severe damage caused by extreme events to distribution network, this paper summarizes the current power supply recovery ideas, power supply recovery model and power supply recovery algorithm of distribution network under extreme events, and finally prospects the development trend of power supply recovery problem of distribution network under extreme events.
Attention-based semi-supervised partial label learning on web image classification

Partial label learning s a type of weakly supervised learning, which learns to predict one label as the correct answer from a given candidate label set. It is a great challenge to improve the accuracy of recognition because of the combination of the two difficult learning conditions, partial supervised learning and partial supervised learning. However, these methods all use similar matrices for tag propagation. We introduced the attention mechanism, proposed a attention-based semisupervised partial label learning (ASPLL) method to address the label contamination issue in PLL through reliable label propagation. Using attention mechanism instead of similarity matrix can significantly improve the accuracy of the algorithm. We evaluate the performance of our method on real-world web image datasets. The experimental results on the web image dataset show that in the semi supervised partial labeling web image classification, ASSPL algorithm is significantly better than the mainstream semi-supervised partial labeling learning algorithms, such as SSPL, PARM.
A document-level summary extraction model based on BigBird

Traditional single-model document-level summary extraction methods lack a multi-level representation of features and cannot extract feature information from documents well. To this end, the text uses the BigBird model and Transformer model to extract the sentence features and document features of the document respectively, to obtain a more comprehensive multi-level feature representation of the document and extract a more accurate document summary. In addition, the BigBird model for the sentence encoding layer, which increases the length of the input text sequence through a sparsity attention mechanism, solves the problem that traditional single-model document-level summary extraction methods cannot focus on more comprehensive contextual information and reduces the model time and space complexity. Comparative experiments are conducted on a generic dataset, and the experimental results demonstrate the effectiveness of the proposed method.
Real time video pedestrian detection based on improved SSD in edge environment

Object detection is an essential subject in the field of computer vision. It is widely used in various scenes and greatly shares the work of human beings. In view of the lack of real-time performance of pedestrian detection in the field of object detection and the excessive load of data returned by the central server in the cloud computing environment, this paper proposes an improved SSD model under the edge computing architecture. The intelligent mobile terminal completes the real-time data collection, and the edge server undertakes the preliminary calculation, The cloud server is responsible for complex computing and model training. The SSD algorithm is lightweight improved to better adapt to the performance of the edge server. The idea of feature pyramid is introduced to fuse the semantic information carried by the deep feature map with the shallow feature map to improve the detection accuracy of small objects. Through experiments, the model has achieved about 0.72 map and about 0.034s single frame processing speed, which can be applied to real life.
ALIVE: Avatar Learning Impact assessment for Virtual Environments

Currently, accurate representation of physical spaces and, especially, human interactions in Virtual Reality (VR)can often feel clunky, unrealistic and require specialist knowledge and development. Our project explores avatar use through the Unreal Meta Humans tool (an extraordinary new 3D character creation technology), specifically, testing the use of realistic avatars in soft skills training and social interactions. This is a proof-of-concept project to generate ideas that address this gap in knowledge, do fast, low-cost prototyping and user testing to further our understanding of the field. We built and tested the recognition of basic emotions in Meta Humans and cartoon avatars in VR. The aim was to understand whether the realism of the avatar impacts our perception of basic human emotion and the sense of immersion in VR. This work aims to advance the study of artificial social interactions, and guide industry practice.
Moving Object Detection Based on 3D Scene Flow for Autonomous Vehicles

The precise perception of moving objects in a dynamic environment is an essential task for autonomous vehicles. Inspired by the excellent performance of the optical flow method in moving objects’ detection in the image domain, we adopt optical flow method for point cloud data and propose a new moving object detection method using point clouds. The proposed new method contains semantic constraints and a scene flow module. In detail, we first fuse semantic information to judge static objects, such as ground and buildings, and exclude these points of static objects; then we apply the scene flow module to estimate the motion vector field of two consecutive point clouds and predict moving or static labels to each point. At the end, exhaustive experiments with a public SemanticKITTI data set are conducted for validation and evaluation. The results demonstrate the competitive performance of the proposed method compares to the existing state-of-the-art methods.
Designing a Blockchain Application

Chapter 8 is the first of three chapters in this book that deal with blockchain application design, development and testing. The chapter begins with an outline of a series of considerations that blockchain application developers must assess during the design process. These include questions such as whether the application needs to be feature-heavy or feature-light; to what extent the application needs to be specialized; whether support for the app needs to be centralized or decentralized; or to what extent the application needs to be scalable. Moreover, this chapter provides an introduction to a fictional case study, comprised of two personas and their user story in order to familiarize readers with the need to create personas, and their user stories as first to determine the functional requirements for an application. Functional requirements are subsequently translated to technical requirements, which lead to the process of creating the specific tasks and steps associated with completing the application design process. The second part of this chapter briefly discusses some popular application design approaches, such as the Ancile, ontology-driven and model-driven approaches. The chapter discussion concludes with a table outlining eight important blockchain design considerations, including attributes and/or issues.
Blockchain Application Development

Following the previous blockchain application design discussions, Chapter 9 focuses on a discussion of fundamental blockchain application development considerations and presents readers with some basic tools and techniques required during the development phase. This chapter begins with a discussion of the necessity to get things right the first time, by explaining some reasons that blockchain application developers are well advised to adopt a firmware versus a software approach. Next, a few popular blockchain frameworks are presented and discussed. While an in-depth discussion of the Ethereum, Hyperledger and Corda frameworks was the sole focus of Chapter 7, this chapter also introduces two additional blockchain development frameworks, Quorum and Ripple. The chapter discussions continue with an explanation of the main layers of a typical blockchain application, namely, the application, service, semantic, network and infrastructure layers. Readers are also provided with an introduction to the various blockchain application tools and techniques, as well as a tool download link table for easy access. Finally, the use of an Integrated Development Environment is introduced and discussed. The final section of the chapter presents and discusses several blockchain application development good practices. While this chapter is not meant to provide advanced training for blockchain application professionals, novice blockchain enthusiasts and information systems auditors should find its content both interesting and useful.
Blockchain Risk, Governance Compliance, Assessment and Mitigation

This chapter discusses a total of seventeen blockchain-related risks, four major regulations/standards and ten COSO-based blockchain good practices. The risks, regulations and good practices presented in this chapter should enable assurance professionals to conduct more relevant and effective blockchain-related risk assessments. Topics covered in this chapter include:
Blockchain Tokens and Cryptocurrencies

The first three chapters of this book aim at providing readers with a fundamental understanding of the various attributes and components of blockchain technology. For many public blockchain implementations, the use of tokens or cryptocurrencies constitutes a major benefit. As such, this chapter aims at first familiarizing readers with various blockchain governance types and considerations in order to explain the concept of a ‘fork’ in a blockchain. It is also important to note that a permanent or hard blockchain fork often results in the creation of a new type of cryptocurrency. The chapter provides several examples of such occurrences. The various types of blockchain token types such as equity and utility tokens, as well as current token standards, such as ERC 20, 223 and 721 are also discussed in this chapter. The last major section of this chapter provides readers with an overview of some more popular cryptocurrency types such as Bitcoin, Ether, Ripple, Litecoin and Monero, to name a few. Finally, a brief discussion of some major, current crypto exchange platforms, such as Bittrex, Coinbase and Bitfinex, is also provided. As mentioned in the chapter, as of February 2020, there were close to 5,400 cryptocurrencies created with a total market capitalization of over $200,000,000. While the long-term performance and sustainability of most cryptocurrencies currently on the market remain highly uncertain, it is important for auditors and aspiring blockchain professionals to be familiar with the basic attributes of the more popular cryptocurrencies discussed in this chapter.
Tutorial on Explainable Deep Reinforcement Learning: One framework, three paradigms and many challenges.

Interpretability, explainability and transparency are key issues to introducing Artificial Intelligence closed—box methods in many critical domains: This is important due to ethical concerns and trust issues strongly connected to reliability, robustness, auditability and fairness, and has important consequences towards keeping the human in the loop in high levels of automation, especially in critical cases for decision making. Reinforcement learning methods, and especially their deep versions, are closed-box methods that support agents to act autonomously in the real world. This tutorial will provide a formal specification of the deep reinforcement learning explainability problems, and will present the necessary components of a general explainable reinforcement learning framework. Based on this framework will provide distinct explainability paradigms towards solving explainability problems, with examples from state-of-the-art methods and real-world cases. The tutorial will conclude identifying open questions and important challenges. The tutorial is based on the survey paper on “Explainable Deep Reinforcement Learning” State of the Art and Challenges” [1].
AI and Games: The Virtuous Cycle

Ever since the birth of the idea of artificial intelligence (AI), games have been helping AI research to advance. Games not only pose interesting and complex problems for AI to solve, they also offer a rich canvas for creativity and expression. This rare domain where science meets art and interaction offers unique properties for the study of AI and is the key driver of technical progress and AI breakthroughs including deep learning and artificial general intelligence. It is not only AI that advances through games, however; AI has been helping games to advance across several fronts: in the way we play them, in the way we understand their inner functionalities, in the way we design them, and in the way we understand play, interaction and creativity. As games get increasingly richer and more complex through creative AI processes, AI advances further and in turn, it advances the environments it is trained in a continuous virtuous cycle. Video games are arguably the most important domain to develop AI for, while AI is arguably the most important technological leap forward for games.
Accessibility in Spanish Universities, evaluation through their policies

This research analyzes the announcements issued by Spanish universities during the COVID-19 pandemic relating to students with special needs, to offer a new vision, complementary to existing audits conducted on university websites about technical accessibility compliance. The study approaches the evaluation of accessibility from the point of view of organizational support. The identified measures are mapped onto Universal Design Learning guidelines to give them context and to analyze their coverage. The research shows a landscape with an uncoordinated and uncollaborative approach, with negative consequences in the tackling of remote emergency teaching..