Reviewerly/exHarmony huggingface dataset:
Teachers’ Perception Toward The Use of English Textbook in Teaching English at Eighth Grade of SMPN 23 Banjarmasin

This research describes the problem of teachers’ perception toward the use of English textbook in teaching English at eight grade of SMPN 23 Banjarmasin. Textbook is important material to help the process of teaching and learning in the classroom, so that an appropriate textbook can be conducted by the perception of the teachers as well because they know what the students need more than anybody else.The participants in this research was two English teachers at eight grade of SMPN 23 Banjarmasin. The object was teachers’ perception toward the use of English textbook in teaching English at eight grade of SMPN 23 Banjarmasin. In data collection, researcher used interview techniques. Then all of data that have collected were analyzed in decriptive qualitative method.The result of this research indicated the teachers’ perception toward the use of English textbook in teaching English were the English textbook should be learned by the teachers to prepare themselves for teaching English in better way, but according to T1, she wanted her students learned the textbook by themselves too at their home so if they did not understand, they would ask her in the classroom activities. According T2, she would learned other English textbook and another sources because she wanted herself ready to teach her students with great preparation to make her students understood the lesson topic.Based on the result the researcher hopes teachers can say louder about this stuff to the public, so the developer can make an appropriate textbook for students because they are the only one who know their students need and want to learn English, and make English fun not fear of it.
A View-invariant Skeleton Map with 3DCNN for Action Recognition

Skeleton based human action recognition is a challenging task in the field of computer vision, which is easily affected by variant camera viewpoint. A novel view-invariant feature is proposed in this paper. We encode the spatial-temporal information of skeleton joint points sequences into a view-invariant skeleton map (VISM), and employ a 3D convolutional neural network (3DCNN) to exploit features from VISM for 3D action recognition. Experimental results on the NTU RGB+D dataset have demonstrated the efficacy of the proposed method, and the robust to the variant viewpoint problem.
A Survey on Cloud Security Issues and Challenges

Cloud computing is a paradigm that provides high quality services with improved performance which enables users to store their data in remote servers that are operated by the third party. Cloud computing is a new concept for providing flexible infrastructure and ease of access but it is still lacking due to its security issues. The main objective of our research is to understand the cloud architecture, cloud models, security issues and challenges. In this paper, we have studied the detail analysis of cloud security issues along with the three main cloud security aspects: Confidentiality, Integrity and Availability and have also discussed approaches in order to enhance and to preserve security aspects.
A new Arabic stemming algorithm

Text processing is a vital step in the information retrieval process, text mining, and natural language processing. It includes several stages, such as normalization, stop word removal, and stemming. Stemming is the process of reducing the lexicon to its root. Due to the different structures and rules in languages, the task of stemming is language-dependent. This research introduces a new stemming algorithm for the Arabic Language. Arabic is one of the most complex languages, both spoken and written. However, it is also one of the most common languages in the world. It is the base from which many other languages are derived. Despite the wide usage of the language, technology and development for Arabic has been limited. The main reason lies within the formulation rules of Arabic, as Arabic language exhibits a very complicated morphological structure. Existing Arabic stemmers suffer from high stemming error-rates. They blindly stem all the words and perform poorly, especially with compound words, proper nouns and foreign Arabized words. The main cause of this problem is the stemmer’s lack of knowledge of the word lexical category (i.e. noun, verb, proposition, etc.) This paper presents a new stemming algorithm that relies on Arabic language morphology and Arabic language syntax. The automated addition to the syntactic knowledge reduced both stemming error and stemming cost. Additionally, the new Algorithm automatically creates it is own list of proper nouns, and compound words based on the processed corpus.
Analysis of Distracted Driver Behaviour Using Self-Organizing Maps

This work studies driving under different distractions and how they affect driver's behaviour. Driving patterns are studied by constructing Self Organizing Maps and training it on the data for multiple drivers. This results in a structure that maps each driver under a particular distraction to their behaviour. The map is then analyzed by labeling features from the datasets. These labels serve to examine different behaviour of each driver.
Pfeiffer Library: Cyber Security: Government Information

Resources in the field of Cyber Security Provides links to government websites, law, and law citation resources.
Blockchain-based Digital-Voting: Effectiveness and Challenges in Afghanistan

In today's world, the democratic process of voting is made more critical as this process usually interfered by power hungry actors, especially in corrupted governments. People mistrust the government as their human rights and fundamental constitutional freedoms are violated. In such an environment, providing a transparent and secure voting system is a key to gain back the of the citizens. The traditional paper-based or digital voting system has several problems encountered as it is managed by a single organization having fully control of the system and database. This organization can tamper with the database, and can easily eliminate the traces. Furthermore, these systems have also encountered problems like security of people, security and privacy of data, time consumption, and potential system attacks. In modern world it is possible to build a transparent voting system to address these security credentials of current voting systems. The technology which paves the ground for this new generation voting system is called Blockchain. Blockchain is a distributed, transparent and unchangeable database of continually growing data records that ensures the truth of data by providing public inspection of votes cast for a candidate in a secure, anonymous and verifiable way. Core tent of this voting system is to remove all need for trust and place strong emphasis on open End to End verification of the process and votes. The implementation of proposed system will result to higher voter turnout as it has substantial benefits and brings more easing to cast a vote. The implementation of proposed system in Afghanistan may also encounter some challenges such as cyber security hacks, digital devices and internet access requirement, and low literacy rate. To avoid these obstacles the government can make some alternate arrangements to make it more secure and reliable. This research focused on effectiveness and challenges of this new generation voting system in Afghanistan.
Users Experience with VR System: Current State and Development Directions

Virtual Reality (VR) system is at its maturity to practice within many fields of studies. It is already recognized internationally and it’s a reliable system to achieve user sense of presence and level of engagement among the users. However, the system still needs further advancement, as there are still numbers of concerns within the system itself that can demote user experience value. This paper attempted to classify the presented studies by researchers from articles sightings between years of 2007 to 2017 into three main components namely the technologies application platform, design of the application systems and construction of virtual environment (VE) for the application system. Then the review of design and development issues that concerns on users experience within the area of VE exploration and creation are also included. The filtration of selection papers is not discussed here, and in this review process, there is no empirical assessment. The objective of this paper is to point out and learn about the current state of VR and the issues faced in order to further promote the connection between user experiences with the system itself. Moreover, it is to level up the acceptance practices among users and continues publicizing the benefits of this complex system in various fields of use. Finally, with the review findings, this paper recommended VR trends for future research, design and development directions.
On the Lower Bound of the Number of Abelian Varieties Over 𝔽<i>p</i>

Abstract In this paper, we prove that the number $B(p,g)$ of isomorphism classes of abelian varieties over a prime field $\mathbb{F}_p$ of dimension $g$ has a lower bound $p^{\frac{1}{2}g^2(1+o(1))}$ as $g \rightarrow \infty$. This is the 1st nontrivial result on the lower bound of $B(p,g)$. We also improve the upper bound $2^{34g^2}p^{\frac{69}{4} g^2 (1+o(1))}$ of $B(p,g)$ given by Lipnowski and Tsimerman [ 7] to $p^{\frac{45}{4} g^2(1+o(1))}$.
(1904-5132) General Definitions for the Union and Intersection of Ordered Fuzzy Multisets

Since its original formulation, the theory of fuzzy sets has spawned a number of extensions where the role of membershipvalues in the real unit interval [0; 1] is handed over to more complex mathematical entities. Amongst the many existingextensions, two similar ones, the fuzzy multisets and the hesitant fuzzy sets, rely on collections of several distinct valuesto represent fuzzy membership, the key difference being that the fuzzy multisets allow for repeated membership valueswhereas the hesitant fuzzy sets do not. But in neither case are these collections of values ordered, as they are simplyrepresented through multisets or sets. In this paper, we study ordered fuzzy multisets, where the membership valuecan be an ordered n-tuple of values, thus accounting for both order and repetition. We present some basic definitionsand results and explore the relation between these ordered fuzzy multisets and the fuzzy multisets and hesitant fuzzysets.
ELÉXICO : diseño de un prototipo de juego para el aprendizaje de léxico de ELE de nivel A2

The use of mobile applications as well as games has been widespread over the last few years, there are more and more options for students who want to learn a language as independent users or to complement their process in a language school. This paper aims at enhancing the way those applications are designed and implemented in the learning process; therefore, some previous research papers were analyzed in order to identify what other authors identified as aspects to improve when designing such type of material. As a result, it was identified that not only did they ignore some or all of the principles of the lexical approach such as providing meaningful activities that could lead to communicative uses, but also those related to gamification, which contain the guidelines to set parameters as well as assessment criteria that can allow students to keep track of their process and to make it more meaningful.After studying how the lexical approach, vocabulary learning and gamification principles should be implemented, a prototype for a mobile game was proposed. It was designed by taking into consideration the theoretical and methodological aspects that would aim at enhancing the learning process of vocabulary, it is intended to be used with students who are taking an A2 level of Spanish as a Foreign Language (SFL) and who are studying collocations related to free time activities in the Latinamerican and Colombian context.Once the prototype was designed, it was evaluated by two experts on teaching SFL in the Pontificia Universidad Javeriana of Bogota. They pointed out how this material could be a useful complement to the learning process in the proposed level, yet they suggested some areas that need to be reinforced in order to guarantee the application serves its main purpose which is to provide students with some complementary material that can enhance students’ learning process, this by following principles of both the lexical approach and gamification.This research allowed us to propose some material that complements the learning process of vocabulary, particularly collocations. The implementation of the lexical approach as well as gamification led us to propose more meaningful and communicative-oriented activities.
Combination filter for keypoint detection and pattern recognition in traffic visual surveillance

The detection of keypoints is very important for several computer applications. There are several ways for keypoint detection and pattern recognition. Earliest work proposes a trainable filter called COSFIRE filter which is a combination of bank of log gabor filters. This proposesd work interested in configuration of more sophisticated combination filter using bank of log gabor filters with bigger support. The specific function that use here to combine filter response is weighted geometric mean, essentially multiplication, which has specific advantages regarding shape recognition and robustness to contrast variations. The proposed work tends to demonstrate the effectiveness of filter in traffic visual surveillance including detection and recognition of traffic signs in complicated scenes.
Status of Library 2.0 Model in Cape Town Public Libraries

The Library 2.0 model is one of many library service models. It has its origin in and has borrowed concepts from Web 2.0, which is associated with web applications that facilitate participatory information-sharing, interoperability, user-centred design and collaboration on the World Wide Web. The focus of Library 2.0 is on user-centred change and participation in the creation of content. The purpose of this study was to investigate the implementation of Library 2.0 in the libraries of the City of Cape Town Metropolitan Municipality (hereafter City of Cape Town) and the challenges they encountered in using Library 2.0 technologies to deliver services. The website of the City of Cape Town Library and Information Services Department was visited to explore the implementation and usage of Web 2.0 tools, including blogs, really simple syndication (RSS), wikis, social networking, and social bookmarking. In addition, data were obtained from an interview conducted with the manager at the said department in charge of technical services, which included the implementation of new technologies. It was found that City of Cape Town libraries were slow in adopting Library 2.0 technologies in their services—there was no evidence on the website of the use of popular Web 2.0 tools such as blogs, wikis, video- and photo-sharing/-streaming, RSS, social bookmarking, and mash-ups. The research shed some light on the Web 2.0 tools used by public libraries other than those in Cape Town and it also highlighted how they were used and what their benefits were. More importantly, the research demonstrated the need for public libraries to embed Web 2.0 tools in their services and to keep abreast with and embrace emerging technologies.
Privaros: A Framework for Privacy-Compliant Drones.

We present Privaros, a framework to enforce privacy policies on drones.Privaros is designed for commercial delivery drones, such as the ones that willlikely be used by Amazon Prime Air. Such drones visit a number of hostairspaces, each of which may have different privacy requirements. Privarosprovides an information flow control framework to enforce the policies of thesehosts on the guest delivery drones. The mechanisms in Privaros are built on topof ROS, a middleware popular in many drone platforms. This paper presents thedesign and implementation of these mechanisms, describes how policies arespecified, and shows that Privaros's policy specification can be integratedwith India's Digital Sky portal. Our evaluation shows that a drone runningPrivaros can robustly enforce various privacy policies specified by hosts, andthat its core mechanisms only marginally increase communication latency andpower consumption.
Recognition of the landslide disasters with extreme learning machine

The geological disasters of landslides induced by the Wenchuan earthquake are great in number so landslide disaster recognition and investigation must be conducted in the early stage of large construction planning in the disaster area. In recent years, the studies on image recognition focus on the extreme learning machine algorithm. Based on the preprocessing of remote sensing images, this paper conducts landslide recognition with remote sensing images through the extreme learning machine classification combined with colour and texture features of ground objects. The comparison experiments of landslide recognition with the support vector machine algorithm shows that the recognition accuracy of the extreme learning machine algorithm is not much different from that of the SVM algorithm, but the extreme learning machine takes short time in training with absolute advantage.
Pattern-Based Semantic and Temporal Exploration of Social Media Messages

Social media is a valuable source for emergency workers and first-responders due to its wide use. Unfortunately, the number of posts poses a challenge to quickly find relevant and trustworthy information. We propose a text pattern-based approach to gain insights from large micro-document collections, including temporal and semantic relationships. In this work, we apply our method to the fictional data set of the VAST 2019 Mini-Challenge 3 that deals with the aftermath of an earthquake. We present major findings we could deduct using our visual analytics approach.
Adaptive Person-Specific Appearance-Based Gaze Estimation

Non-invasive gaze estimation from only eye images captured by camera is a challenging problem due to various eye shapes, eye structures and image qualities. Recently, CNN network has been applied to directly regress eye image to gaze direction and obtains good performance. However, generic approaches are susceptible to bias and variance highly relating to different individuals. In this paper, we study the person-specific bias when applying generic methods on new person. And we introduce a novel appearance-based deep neural network integrating meta-learning to reduce the person-specific bias. Given only a few person-specific calibration images collected in normal calibration process, our model adapts quickly to test person and predicts more accurate gaze directions. Experiments on public MPIIGaze dataset and Eyediap dataset show our approach has achieved competitive accuracy to current state-of-the-art methods and are able to alleviate person-specific bias problem.
Information resource description: creating and managing metadata

In this second edition of his 2012 work, Hider provides a comprehensive description of the history and practice of metadata and information resource description. Hider’s writing is clear, fluent an...
State Estimation for Non-linear Sampled-Data Descriptor Systems: A Robust Extended Kalman Filtering Approach

This paper proposes a state estimation method for a class of norm-bounded non-linear sampled-data descriptor systems using the Kalman filtering method. The descriptor model is firstly discretized to obtain a discrete-time non-singular one. Then a model of robust extended Kalman filter is proposed for the state estimation based on the discretized non-linear non-singular system. As parameters are introduced in for transforming descriptor systems into non-singular ones, there exist uncertainties in the state of the systems. To solve this problem, an optimized upper-bound is proposed so that the convergence of the estimation error co-variance matrix is guaranteed in the paper. A simulating example is proposed to verify the validity of this method at last.
Optical Equalization using Photonic Reservoir Computing with Optical Analog Signal Injection

Photonic reservoir computing with optical pre-processing enables equalization of the signal entirely in the optical domain. We compare the performance of reservoir computing-based estimation of 28GBd PAM-4 transmission over 100km SSMF with Kramers-Kronig DSP results.
Practical Privacy Measures in Blockchains

The Blockchain Technology has recently been a hot topic proposed in many industries such as Financial, Healthcare, Business, E-Government, Education, etc. The Blockchain can simply be defined as a distributed database or public ledger that contains records of all digital transactions/events that have transpired amongst the parties involved. The technology itself is comprised of other more fundamental knowledge namely: cryptography, distributed system, network and game theory. Thus at the more basic level, the blockchain components include functions such as hash, asymmetric cryptography, digital signatures, peer-to-peer network protocols and some elements of a “proof of correctness/work” resulting from a game-like setup. Against a backdrop of such a mixture of functions, “privacy” has emerged to be one of the new challenges in any Blockchain implementation. This research aims to investigate the techniques that can be used to successfully manage privacy in the blockchains. The work has identified the requirements and analyzed the techniques that can be used. Finally, the work was also extended to an analysis on the performance evaluation of blockchains in managing privacy albeit focusing on a specific blockchain—the Hyperledger fabric platform.
Cyber risk governance should take centre stage in financial services

It feels as though cyber risk has crept up on us without warning and with great intensity. We have come a long way from the days when our palm pilots had to be hot-sync’d through a docking station and the occasional hazard was from viruses transmitted as email attachments. Over the years, we have embraced extreme connectivity combined with extreme automation in a never-ending drive towards convenience and costefficiency. However, even as banks continue to nudge, cajole (and perhaps occasionally threaten) their customers towards impersonal e-channels, we learn about record amounts of losses from online fraud and theft. Furthermore, all of us – not just the specialists – are asked to act as conscription soldiers in the fight against this threat. According to a report by Accenture, almost eight out of ten business leaders believe that they are adopting new technologies faster than they can address related security issues. It also estimates that nearly $350 billion of value could be lost by the banking sector to cybercrime in the next five years.
Spegel, spegel på skärmen där … Hur tre författare framställer sig själva genom digitala plattformar

This essay is concerned with three authors' projection of self and their personal trademarks within various digital platforms. The authors' posts on social media are examined on the basis of how they relate to the authors' trademarks. Viveca Sten and Katarina Wennstam’s websites and Denise Rudberg’s podcast participation are analysed based on how these platforms present a projection of the authors' self. The analysis is based on different theoretical perspectives such as marketing theory, brand studies, performativity and celebrity studies.