Reviewerly/exHarmony huggingface dataset:
Improvement of the performance of optical handwritten digit recognition by incorporating cross-domain autoencoder-based image to image translation technique

The paper represents a novel approach that improves the performance of optical handwritten digit recognition incorporating image to image translation technique in a way - that it translates the input image of handwritten domain to some model domain so that the performance of any specified classier improves. In this paper, we have done image to image translation using two pretrained autoencoders, one of them is an autoencoder of a handwritten domain and other is an autoencoder of a model domain. We have bonded together the encoder of handwritten domain and the decoder of model domain and a neural network for feature translation in between in order to train the whole neural network for the translation of an image from handwritten domain to the image of a model domain. Also, an analysis has been shown regarding how well our method improves the performance of optical handwritten digit recognition for both Bengali and English digits.
A Framework for Cyber-Physical System Security Situation Awareness

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Systematic Approach to Analyze Attacks on SCM: using Blockchain

Smart contracts are programs, which are stored in a decentralized network i.e. Block chain. These are written by users to develop decentralized applications using different platform like Ethereum and bitcoin. In current scenario, even though blockchain support features like security and transparency. Because of solidity language vulnerability, there is a possibility of attacks on smart contracts in blockchain. So, to avoid those attacks like i.e. Locked Ether, Transaction order dependency and Time stamp dependency. We discussed, analyzed and tested these attacks in this paper. Further, in our project supply chain management for textile industry using block chain technology, we have developed smart contract using solidity language on Ethereum Platform. With the aim of protecting our project from these attacks, we are thoroughly and experimentally analyzed. And based on the experimental observations, we are going to protect our project from these attacks. All the above mentioned attacks are thoroughly studied and experimentally tested on Ganache, Ropston test network, Rinkeby test network using Remix IDE in JVM, injectedweb3and web3 provider environments. Finally, we have suggested security measures to protect from these attacks
Training of pedagogical staff for rural underfilled school

The level of training of pedagogical personnel plays an important role in the development of the education system in the region. Therefore, the paper considers the problem of forming the professional competence of the future teacher. The main goal of the research is to improve the activities of the Pedagogical University in developing a system for training a young specialist for a rural underfilled school, as well as creating conditions for their consolidation in an educational organisation of rural areas. The authors presented the experience of the Altai State Pedagogical University in training pedagogical staff for a rural underfilled school, a system of graduate support of the professional development of young professionals. It is established that 89.8% of Altai Territory teachers from the number involved in the diagnosis of professional activity on the basis of identified deficiencies of competences have prepared plans for their professional development. The authors believe that a necessary and sufficient condition for the expansion of the highway for professional growth is the need for constant improvement in the special competencies of a teacher in a rural underfilled school.
Card cloning fuels fraud spree

In its latest ‘Quarterly Financial Crime Report’, risk management firm Feedzai says that there has been a 30-37% increase in card not present (CNP) transactions, not least because of people being trapped at home by Covid regulations. This has helped fuel an increase in fraud based around card cloning.
Dynamic Key Switching Integrated Scenarios for Performance Aware Implementations in Cloud and Integrated Internet of Things

With the adoption and wide usage of smart gadgets and devices for multiple applications, the association of advanced technologies is quite prominence and needs higher degree of accuracy and performance. These are legitimately connected with the advanced innovations including Internet of Things, Internet of Everything, Internet of Vehicles, Internet of Cloud Apps and numerous others. This original copy is therefore displaying the enormous issues and research focuses in this area with the associated streams so the different elements of IoT, IoE, IoX, IoV and others can be broke down with the examination openings and the portions for various streams. In the present situation, the IoT based coordination of digital forms of money is very unmistakable whereby the distributed system is pursued and it goes under the innovation of blockchain. The blockchain innovation is likewise connected with the shrewd advances. In the present period, Blockchain Technology is one of the key territories of research just as execution explicitly in the space of cryptocurrency. Presently days, various computerized cryptographic forms of money are very conspicuous and shared all through the world in spite of tremendous analysis and discussions. Other than these purposes of research, the vehicular mix of IoT is very conspicuous that is tended to utilizing IoV that is Internet of Vehicles in the keen traffic observing and brilliant transportation. Presently days, the IoT is moving towards IoE or IoX which alludes to Internet of Everything and this is additionally tended to in this composition. The manuscript is presenting the scenarios for the implementation patterns associated with the security and dynamic key based environment.
Robot intelligence for real-world applications

In this chapter, we will look into how robots can, have and will benefit the wider human community in tasks that perhaps were taken for granted. More specifically, we review and analyse state-of-the-art work in robotic locomotion, robotic manipulation with and without human supervision. We hope to assist readers in having a thorough related work as a basis of their research with the current state-of-the-art approaches in the aforementioned fields as well as the importance of robots today.
Ferring B.V. v. Allergan, Inc. United States Court of Appeals of the Federal Circuit, 2020 980 F.3d 841

Biotechnology Law ReportVol. 40, No. 1 As presented by Chris HolmanFerring B.V. v. Allergan, Inc. United States Court of Appeals of the Federal Circuit, 2020 980 F.3d 841Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:3 Feb 2021https://doi.org/10.1089/blr.2020.29214.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 40Issue 1Feb 2021 InformationCopyright 2021, Mary Ann Liebert, Inc., publishersTo cite this article:Ferring B.V. v. Allergan, Inc. United States Court of Appeals of the Federal Circuit, 2020 980 F.3d 841.Biotechnology Law Report.Feb 2021.43-53.http://doi.org/10.1089/blr.2020.29214.cmhPublished in Volume: 40 Issue 1: February 3, 2021Online Ahead of Print:January 12, 2021PDF download
Abstractive summarization of long texts based on BERT and sequence-to-sequence model

Manual summarization of long text is labor-costing and time-consuming. Therefore, the automatic text summarization methods are necessary for information retrieval, text semantic mining, and question answering. In this paper, we propose an end-to-end automatic text summarization model (BSSA) based on the Bidirectional Encoder Representations from Transformers (BERT) and sequence-to-sequence model. First, the BERT model extracts the text feature as a part of the encoder. Second, the long short-term memory network generates the semantic feature of the text as another main part of the encoder. Finally, the decoder with an attention mechanism generates the abstractive summaries. The experimental results on both the Chinese and English datasets show that the BSSA model achieves significant improvements over the baseline models.
Importance Sampling

SummaryRoughly speaking, a particle filter is an algorithm that iterates importance sampling and resampling steps, in order to approximate a sequence of filtering (or related) distributions. This chapter covers the basics of importance sampling; resampling will be treated in the following chapter. We describe in particular the two versions of importance sampling (normalised and auto-normalised), we make a connection with the probabilistic notion of change of measure, we derive the variance of importance sampling estimators, we describe different empirical measures of efficiency such as effective sample size, we discuss the inherent curse of dimensionality of importance sampling, and we extend importance sampling to situations where importance weights are randomised.
Web services classification via combining Doc2Vec and LINE model

Classifying web services with similar functionality from tremendous amount of web services can significantly improve the efficiency of service discovery. Few of the web services classification researches integrate the independent mining of the content semantic information and network structure information hidden in the web service characterisation documents. Therefore, we propose a web service classification method combining them. So, the Doc2Vec algorithm is firstly exploited to deeply mine the functional semantics of web service characterisation documents and obtain web service's content semantic representation. Then, the LINE algorithm is adopted to embed the web service information network which is constructed by utilising web service characterisation documents and word information. Subsequently, the content semantic representation and network structure representation of web service are integrated as the input of the logistic regression classifier to perform web service classification. The experimental results on the ProgrammableWeb dataset verify that the proposed method outperforms to baseline methods.
An Examination of Threats facing Assets in Use in Kenyan Public Universities

Globally universities are increasingly dependent on information and communication technology to execute their core operations and functionalities, thus getting exposed to increasing cyber threats and consequently unprecedented security risks.
A Fuzzy Analytic Network Process for Security Risk Assessment of Web based Hospital Management System

Software applications have revolutionized human lives. As healthcare industry becomes digitalized, more and more hospitals are now dependent on effective and user-friendly software applications for efficacious management. However, this progressive increase in the use of software applications has led to several security issues. Security risk has probably become the biggest and most sensitive concern in this era for hospital management systems. Assessment of security risk may help in acquiring the level of security that the end user wants. Security assessment needs identification and prioritization of its attributes for publishing guidelines to maintain that level, as security risk is a multidimensional problem. This study has used the Fuzzy ANP methodology to solve this multi criteria based problem. This work also emphasizes on increasing security by assessing the security risk in hospital management system. A real time case study of hospital management system has also been used for validating the results. The acquired results will help in mapping the guidelines and developing new mechanism as per the high prioritized attributes of security risk.
Analisis K-Means Clustering pada Data Sepeda Motor

K-Means is a data mining algorithm that can be used to grouping or clustering data. This research using k-means for clustering the data of motorcycle based on consumer needs. The dataset used in this research is Honda and Yamaha motorcycle which taken from the dialers in Dewantara District, Aceh. The data tested by grouping 300 data of motorcycle with different attributes into 3 clusters, which are cheap, normal, and expensive. The distribution of the data we separate it using 45 data in 15 times of test. Each test used 3 different data randomly selected on each test. To calculate the distance of each motorcycle data that have been inputted to each centroid, we used the Euclidean Distance formula. Data in this cluster system can be used as a recommendation for users in selecting the motorcycle that they interest the most. The results of the performance on each test finished in 15 times shown that the average value of Precision by 76%, Recall by 76% and the accuracy by 81%.
Global $9.5 bn refinery catalyst market to 2027 by material (zeolites, metallic, chemical compounds), &amp;application (FCC, alkylation, hydrotreating, hydrocracking)

This study presents the air-borne geophysical Gamma Ray Spectrometry data have been used for detecting the alteration zones related to hydrothermal activity. Areas enriched in potassium may indicate the existence of potassic alteration zone that is often associated with hydrothermal alteration accompanied by economic mineral deposits. The radioelements (K (%), eTh (ppm), and eU (ppm)) concentration distribution and the ratios of (K/eTh and K/eU) over the study area were presented. A Potassium Point anomaly map was obtained from the statistical treatment of the K (%), K/eU, and K/eTh spectrometric data. Anomalously High (X+3σ or more) areas were delineated and considered the most preferred areas for potassic alteration. If the maximum values exceed the (X+3σ) threshold, then (X+2σ) or (X+σ) is applied instead. Sixteen areas were delineated and suggested for the presence of potassic alteration. The F-Parameter of Efimov (K*(eU/eTh)) was also implemented as proved approach for delineating the most preferred areas for hydrothermal alteration. The result of the Potassium point anomaly mapping was compared to that of the F-Parameter technique that was used as reference for validating the results. The sixteen anomalous areas revealed from the Potassium point anomaly technique showed perfect correlation with the areas of highly anomalous F-parameter.Remote sensing study supported by field data and laboratory spectral analyses was also implemented in this study as another useful powerful cost-effective approach for alteration mapping. A field study was conducted; samples from the different observed alterations were collected. The spectral signatures of these samples were measured using the “ASD TerraSpec Halo mineral identifier” hand-held spectroradiometer. Spectral analyses were performed to obtain the spectral characteristics of the alteration zones of the study are. The end-members were identified through comparing the measured spectra against the United States Geological Survey (USGS) spectral library in ENVI v.5.1. software. The identified end-members include; Kaolinite, Sericite, Montmorillonite, Chlorite, Epidote and iron oxides. Subpixel Mixture Tuned Matched Filtering (MTMF) mapping technique was finally used for mapping the distribution of these end-members on ASTER nine Visible Near Infra-Red (VNIR) and Short Wave Infra-Red (SWIR) bands. The remote sensing data were validated as Semna gold mine and the identified alterations during the field study were successfully mapped by the remote sensing technique. Finally; Most of the delineated areas using the proposed Potassium point anomaly technique were also evidenced by the approached remote sensing technique. Moreover remote sensing suggested more alteration areas than did the gamma ray spectrometry data.
Towards a Comprehensive Façade Inspection Process: An NLP based Analysis of Historical Façade Inspection Reports for Knowledge Discovery

Towards a Comprehensive Façade Inspection Process: An NLP based Analysis of Historical Façade Inspection Reports for Knowledge Discovery Zhuoya Shi, Keundeok Park and Semiha Ergan Pages 433-440 (2020 Proceedings of the 37th ISARC, Kitakyushu, Japan, ISBN 978-952-94-3634-7) Abstract: Façade condition assessment for buildings is essential to public safety in cities. Currently, twelve major cities across the U.S. ensure the building façade safety with mandatory façade inspection programs. Even in major cities with the façade inspection programs, there have been seventeen falling debris accidents reported in 2019, three of which were fatal. These accidents indicate a need to improve the current façade inspection practice. Shadowing work conducted by the research team with expert inspectors on three buildings, and analysis of façade inspection programs and guidelines show that inspectors check façades based on defect types or on façade components, whereas existing documentation to guide inspectors are based on major material types. This mismatch results in inspectors checking façade components based on their experience, which might not align well with the expectations of agencies. Systematic and detailed assessment guidance is necessary to get a comprehensive and consistent façade inspection. Towards such systematic guidance and to understand the underlying reasons for continuing accidents, this paper provides the details of an approach to identify generic vocabularies and the relationships between major entities that play a role in the inspection domain for systematic inspection processes. To identify these, we developed a data-driven approach that analyzed around 100 façade inspection reports that were filed to the NYC Department of Buildings (DOB) during the past inspection cycle (2014-2019). Among the twelve major cities, New York City (NYC) has the longest history of façade inspection, and most buildings (14,000) enrolled in the façade inspection program. We believe that study about NYC buildings can provide a general understanding of inspection requirements in other cities where similar problems exist. The developed mechanism is based on natural language processing and unsupervised machine learning techniques and is used to extract the vocabularies of façade elements, defect types, associated defect attributes, and mapping between them. The results also provide the mapping relationship of façade components and defect types for a specific façade type (e.g., stone/limestone). This work provides the foundation for an ontology to be used to systematically guide façade inspection for any given building. Keywords: Façade inspection; Report analysis; Natural Language Processing (NLP); Unsupervised learning DOI: https://doi.org/10.22260/ISARC2020/0061 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
People, Politics and Interpersonal Relationships

looks at the part emoji play in interpersonal communication. One of the aims behind their initial development was to provide a way to express those things that gestures, facial expressions, and tone of voice do in face-to-face conversation but that get lost in written communication. Emoji were seen as a way of diminishing the possibility of accidental conflict by signalling the emotional frame in which a message was meant. But they also allow for a great deal of ambiguity, and as their popularity has grown they’ve started to be used in an increasingly broad range of contexts. The chapter considers what it’s appropriate to express via emoji (and who makes these decisions). Is it deemed appropriate to use them to break up with someone? Or to send condolences about the death of a loved one? Drawing on discussions of their use by legal and political commentators, the chapter looks at how emoji have been used as evidence in legal cases and co-opted into the world of politics - so that, despite their seemingly frivolous and light-hearted roots, they’re now at the front line of debates about everything from the alt-right to post-truth politics.
Multimodal BCIs–the hands-free Tetris paradigm

In this chapter, we will explore ways to integrate three natural sensory modalities, i.e. vision, brain commands and stress levels into a single visceral experience that allows simultaneous control of various interface options. In this direction, we present MM-Tetris, the multimodal reinvention of the popular Tetris game, modified to be controlled with the user&apos;s eye-movements, mental commands and bio-measurements. MM-Tetris is intended for use by motor -impaired people who are not able to operate computing devices through the regular controllers (i.e. mouse and keyboard). In the proposed version of the game, the use of eye -movements and mental commands works in a complementary fashion, by facilitating two different controls, the horizontal movement of the tiles (i.e. tetriminos) through the coordinates of the gaze and the tile rotation through sensorimotor rhythm (SMR) signals detection, respectively. Additionally, bio-measurements provide the stress levels of the player, which in turn determines the speed of the tiles&apos; drop. In this way, the three modalities smoothly collaborate to facilitate playing a game like Tetris. Eventually, the design of the game provides a natural gamified interface for user training in generating more discriminative SMR signals for better detection of imaginary movements.
Gaming Technologies in Professional Education

The specificity of modern higher education is the organization of the learning process, as close as possible to the real professional conditions of future graduates, which is based on the actual achievements of science and practice, including various pedagogical technologies. The paper presents gaming technologies as one of the most effective in the process of organizing successful training of students in higher education. The purpose of the article is to consider the possibilities of formation of competencies of future teachers of vocational training. The paper presents the experience of the implementation of game technologies of training of students of higher educational institutions in the field of training "Vocational training (by industry)". The requirements for conducting business games taking into account the specifics of "Labor law" and "Civil law" are disclosed. The structure of games in these disciplines, as well as the functions and process of use, the criteria for assessing the activities of students in the implementation of business games. The use of business games as one of the components of gaming technologies allows improving the process of formation of competencies of future teachers of vocational training.