Reviewerly/exHarmony huggingface dataset:
Nalpropion Pharm., Inc. v. Actavis Labs. FL, Inc. United States Court of Appeals of the Federal Circuit, 2019 No. 2018-1221, 2019 WL 3819335

Biotechnology Law ReportVol. 38, No. 5 As presented by Chris HolmanNalpropion Pharm., Inc. v. Actavis Labs. FL, Inc. United States Court of Appeals of the Federal Circuit, 2019 No. 2018-1221, 2019 WL 3819335Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:11 Oct 2019https://doi.org/10.1089/blr.2019.29142.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 38Issue 5Oct 2019 InformationCopyright 2019, Mary Ann Liebert, Inc., publishersTo cite this article:Nalpropion Pharm., Inc. v. Actavis Labs. FL, Inc. United States Court of Appeals of the Federal Circuit, 2019 No. 2018-1221, 2019 WL 3819335.Biotechnology Law Report.Oct 2019.332-338.http://doi.org/10.1089/blr.2019.29142.cmhPublished in Volume: 38 Issue 5: October 11, 2019PDF download
Purple Teaming

The purple teaming concept is essentially any method, process, or activity that leverages collaboration between the red and blue facets of organizational security. By “red,” I mean any attack emulation or offensive security effort in general. “Blue” refers to any effort that involves the defensive efforts undertaken by an organization. It is my belief that when offensive and defensive capabilities are used in concert in a purple teaming engagement, it represents the penultimate improvement capability to organizational security. This is not accomplished without challenges, and there are many shades of purple team activities—some more reddish and some closer to blue. In this chapter I discuss purple teaming challenges and provide examples of different types of purple teaming activities that I feel are effective.
The role of augmented reality-based unplugged computer programming approach in the effectiveness of computational thinking

Recently, pedagogical approaches to promote computational thinking among 21st century learners have increasingly become a topic of interest in educational research. Studies revealed that unplugged computer programming, learning coding without a computer, can enhance students' computational thinking and positive attitudes towards computer programming. However, when dealing with complex computer science concepts, they face limitations. This study therefore developed a solution adopting unplugged coding using flowcharts integrated with Augmented Reality (AR) technology to help scaffold students (called AR semi-unplugged coding). It recruited 120 secondary students for data collection, divided into an experimental group and a control group (unplugged coding). It showed that although both exhibited improved computational thinking and increased self-efficacy after participating in their assigned activity, those in the experimental group outperformed their counterparts statistically. Moreover, the developed solution attracted a greater level of perceived usefulness by users which shows its potential to become an effective approach for promoting computational thinking.
TensorFlow Datasets

We introduce TensorFlow Datasets by discussing and demonstrating their many facets with code examples. Although TensorFlow Datasets are not ML models, we include this chapter because we use them in many of the chapters in this book. These datasets are created by the TensorFlow team to provide a diverse set of data for practicing ML experiments.
DCGAN Model Used to Generate Body Gestures on a Human-Humanoid Interaction System

The current availability of the humanoid robots opens up a wide range of applications, for instance, in the domain of hospitality the humanoids can be programmed to behave autonomous ways to provide help to people. The aspect of the humanoids and the humanness of interaction are key components of success. We developed a system to endow the humanoid robot Pepper, from SoftBank Robotics, with the capability of both: identify the emotion state of the humans and exhibiting emotional states via gestures and postures generated using a DCGAN model to learn from the human body language and to create originals body expressions to exhibit like-human movements.
The rapid development of knowledge bases using UML class diagrams

The knowledge bases design that employs conceptual models and their transformations is one of the most interesting areas of knowledge engineering and it remains critical. This paper presents an approach to the rapid development of knowledge bases for rule-based expert systems on the basis of the model-based generation of program codes. The approach proposed uses conceptual models in the form of UML class diagrams as a source of knowledge. In accordance with the technique that we propose, diagram concepts and relationships are extracted, mapped to the ontology of a subject domain and represented in the form of fact and rules templates. The original notation, namely the rule visual modelling language (RVML), is used to visualise and modify mapped elements. The CLIPS is used as the targeted knowledge base programming language. This approach does not eliminate errors due to conceptual models; but provides minimisation of programming errors resulting from hand coding.
The roles of uncertainty avoidance and strategic agility in cloud storage adoption among multinational manufacturing companies in Malaysia

Cloud technology adoption is becoming a key sustainable information technology (IT) strategy for companies in developing countries with an investment potential of US$900 million by 2020. This study examined the antecedents and outcome of cloud storage adoption among multinational manufacturing companies (MNCs) in Malaysia. A total of 122 responses were collected and analysed with SmartPLS 3.2.7. Results show that relative advantage, top management support, technology readiness, cost saving and stakeholder pressure significantly influence cloud storage adoption; while uncertainty avoidance moderates the relationship between technology readiness and adoption. Interestingly, cloud storage adoption impacts firm performance while strategic agility enhances this relationship. This study provides a new perspective by examining the influence of national culture and strategic agility in the context of cloud storage adoption and its outcome among MNCs in Malaysia. In conclusion, this study contributes holistic and meaningful insights to IT practitioners and researchers in adopting cloud technology as a sustainable IT strategy.
An efficient privacy solution for electronic health records in cloud computing

Cloud computing is generally seen as the most practical and efficient way to build and deploy electronic medical records (EMR) due to advantages such as scalability and cost savings. However, existing solutions are not mature enough to protect patient data. Besides, traditional security countermeasures should be tailored to achieve the right balance between performance and security. In this respect, we propose a highly secure framework to boost remote image processing. Concretely, we rely on the segmentation method to break up the secret image into small portions; thereby optimising the overall execution time. Additionally, we propose a novel access control based on users' trust and user-managed access (UMA). More interestingly, the trust-aware model can reduce the heavy computational overhead of authorisation decisions in comparison to other checking methods. The implementation results prove the accuracy of this approach to meet the stringent security standards and performance requirements.
Eye Blink Detection System for Paralyzed Patients

Paralysis of an human being is caused due to the degeneration of motor neurons which weakens the muscle, so that it does not allow patient to move, speak, breathe , and loss in the voluntary actions. It is an incurable disease. To understand the feelings of a paralyzed patients Brain wave technique and Electro-oculography techniques were used. These techniques are afflictive, discomfortable and leads to unconsciousness of the paralyzed patient. The real time video oculography system fills the communication gap between the patient and the world. Video Oculography (VOG) is video-based method of measuring the vertical, torsional and horizontal position components of both the eye blinks with the help of small cameras placed in the head-mounted mask .This paper presents different visual technologies, such as eye blink detection, eye center localization and conversion of the eye blink to speech. The video oculography could achieve accuracy of 0.968.
Benefits and Challenges of Cloud Computing Adoption and Usage in Higher Education

The aim of this article was to provide evidence pertaining to cloud computing (CC) adoption in education, namely higher education institutions (HEIs) or Universities. A systematic literature review (SLR) of empirical studies exploring the current CC adoption levels in HEIs and the benefits and challenges for using CC in HEIs was performed. A total of 20 papers were included in the SLR. It was discovered that a number of universities have a keen interest in using CC in their institution, and the evidence indicates a high level of successful CC adoption in the HEIs reviewed in the SLR. In conclusion, the SLR identified a clear literature gap in this research area: there exists limited empirical studies focusing on CC utilisation in HEIs.
Governance

Higher Education AbstractsVolume 56, Issue 2 p. 136-136 GOVERNANCE Governance First published: 22 June 2021 https://doi.org/10.1111/hea.25_12166Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume56, Issue2April 2021Pages 136-136 RelatedInformation
Sentiment Recognition in Customer Reviews Using Deep Learning

Deep learning has become popular in all aspect related to human judgments. Most machine learning techniques work well which includes text classification, text sequence learning, sentiment analysis, question-answer engine, etc. This paper has been focused on two objectives, firstly is to study the applicability of deep neural networks strategies for extracting sentiment present in social media data and customer reviews with effective training solutions. The second objective is to design deep networks that can be trained with these weakly supervised strategies in order to predict meaningful inferences. This paper presents the concept and steps of using deep learning for extraction sentiments from customer reviews. The extraction pulls out the features from the customer reviews using deep learning popular methods including Convolution neural networks (CNN) and Long Short-Term Memory (LSTM) architectures. The comparison of the results with tradition text classification method such as Naive Bayes(NB) and Support Vector Machine(SVM) using two data sets IMDB reviews and Amazon customer reviews have been presented. This work mainly focused on investigating the merit of using deep models for sentiment analysis in customer reviews.
An Research on the Effectiveness of the Different Algorithms and the Scheduling in Improving the Performance of Cloud Computing by using Cloud Analyst Simulator

Cloud computing can be defined as a computing paradigm, where the various systems and large pool are connected to each other in private or public networks. The aim for that is to provide a dynamically scalable infrastructure, where it is used for applications, data and file storage. Cloud computing reduced the cost of computation and application hosting so that content storage and delivering services are handled faster and more flexibility. Load balancing is one of the challenges that affect the performance of cloud computing and the overcome it leads to better resource utilization and response time. The service broker policy plays an important role in accelerating the response time of customer requests by locating data centers or optimize the pattern of access to them. The contribution of this paper investigates the effectiveness of using the different algorithms and the approaches to improve the performance of cloud computing as it has been shown that there is a possibility to increase the performance of cloud computing by relying on certain criteria described in this paper. The results, which are presented in this paper were obtained using the cloud analyst simulator, where this simulator contains (Time duration, Load balancing algorithms, and Service Broker Algorithms, etc).
AI Technology and Biological Research Use in Cultural Practices

The article is a comprehensive analysis of projects aimed at studying AI technologies and culture interaction. The author examines the specifics and uniqueness of art works created through AI-technologies using examples of projects from “Thought Works Arts Global Research”, “Innovation Laboratory of New Technologies”, “Isolation Foundation” and “IZONE Creative Association”. The article analyzes the principle of selection of materials, algorithmic analysis of data, the interdependence of digital data received from the user’s brain impulses with audiovisual content, the possibility of instant data processing in the process of creating an artistic product. The author explores the principles of tracking brain function and decoding human genetic data, which are used to create art projects. The article assesses the potential that AI possesses and explains the conditions necessary for the implementation of AI-technology in culture. As a result of the study, the author revealed that through algorithmic analysis it is possible to transform digital data into a system of expressive signs of visual and sound arts, to broadcast the received audiovisual content. The author finds out that through these technologies it is possible to create interactive art forms (interactive film, installations, immersive presentations, etc.)
Educational virtualization model in initial teacher training

As a consequence of social isolation the initial teacher training institutions had to establish a recovery plan in the remote mode to guarantee the continuity of their professional careers. The objective of this article is to build a theoretical modeling of educational virtualization from the holistic dialectical method that allows to support new strategies in initial teacher training. The results obtained allowed an epistcmic construct of the initial scientific categories and their resignification as configurations dimensions and link of a new theoretical model. It is concluded that the formative model of the dynamics of educational virtualization in IDF is composed of ten related configurations that are expressed in three dimensions: the technological contextual dimension the sociocultural axiological dimension and the pedagogical praxiological dimension. The dimensions mentioned in a new succession of synthesis that are expressed in the teaching competence of educational virtualization constitutes the link of the model id a higher stage.
Knowledge management practices as an antecedent for enabling work performance of employees: empirical evidence from pump and motor manufacturing cluster in India

Organisations are continuously striving to improve the work performance of employees. The comprehensive literature review identified the importance of knowledge management practices including creation, acquisition, sharing, storage and use of knowledge. The aim of this study is to understand the relationship between knowledge management practices and work performance of employees. The study was conducted among 102 firms in the pump and motor manufacturing cluster. A 70-item questionnaire was administered among the middle level managers. The data was analysed using partial least squares. The results revealed that there is positive relationship among the five knowledge management practices except the knowledge that is created is not effectively stored in repositories. The results further found that knowledge management practices positively influence the work performance. This study posited strong evidence for academicians and practitioners that prevalence of knowledge management practices can be leveraged for the betterment of employees' performance.
Performance Evaluation of Various Machine Learning Techniques for Human Activity Recognition using Smartphone

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Bayer Healthcare LLC v. Baxalta Inc. United States Court of Appeals of the Federal Circuit, 2021 989 F.3d 964

Biotechnology Law ReportVol. 40, No. 3 As presented by Chris HolmanBayer Healthcare LLC v. Baxalta Inc. United States Court of Appeals of the Federal Circuit, 2021 989 F.3d 964Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:8 Jun 2021https://doi.org/10.1089/blr.2021.29229.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 40Issue 3Jun 2021 InformationCopyright 2021, Mary Ann Liebert, Inc., publishersTo cite this article:Bayer Healthcare LLC v. Baxalta Inc. United States Court of Appeals of the Federal Circuit, 2021 989 F.3d 964.Biotechnology Law Report.Jun 2021.197-205.http://doi.org/10.1089/blr.2021.29229.cmhPublished in Volume: 40 Issue 3: June 8, 2021Online Ahead of Print:April 26, 2021PDF download
Critical Success Factors and Knowledge Management Process in Indian Nationalised Bank

Knowledge management is now becoming the driving force for the success of any business. This paper presents the framework for understanding the critical success factor that impact the execution of knowledge management in a bank. We had entered the era where future will depend on the creation, acquisition, integration and application of knowledge at right time to innovate and take competitive edge. Knowledge can be used as asset, resource or strategy. The motivation of this study is to identify the impact of critical success factors on knowledge management process in Indian nationalised banks. The construct identified as critical success factors such as information technologies, leadership in knowledge management, knowledge management culture, and measurement of knowledge management were tested using structural equation model. 236 response were collected from the respondent employed in Indian nationalised bank in Gorakhpur with the help of questionnaire as a data gathering instrument. The finding of the study reveals that all the critical success factors used in the proposed model significantly influence the knowledge management process. Leadership in knowledge management is identified as most important predictor among the critical success factor.
A Novel Integrated Framework for Sarcasm Detection in Social Platform

Sarcasm is a form of speech which transforms the verbatim meaning of a sentence into its antonym. Sarcasm identification in social media is a crucial facet of the sentiment analysis process, since it deals with texts whose polarity is completely opposite from its utterance. Our paper provides an exhaustive review of the existing methodologies dedicated to the task of detecting sarcasm in texts posted on an online forum. A comparative analysis of the existing techniques, mentioning the datasets and the performance measure, is also provided. This paper also introduces a novel integrated framework for identifying sarcastic clues in tweets, and recognizing sarcastic users.
Implementing Item-Based Collaborative Filtering System in Requirement Elicitation

In Requirement Engineering, Gathering Requirements plays a vital role in the Software Development Process. There are lot of processes available to gather requirements i.e. Brainstorming, Interview, Observation. This process takes lot of time and effort for the developer to gather and continue the development, and if the requirements which are analyzed are not up to the satisfaction of the user, it will cause issues in end product resulting in loss of human effort, time and cost. To overcome this issue faced by the developers we have developed a tool using item-based collaborative algorithm for users which will recommend users the required set of functional and nonfunctional requirements based upon the questionnaire given tothe user and produce a software requirement specification (SRS).
A COMPARISON STUDY: TEACHER, PEER AND SELF-FEEDBACK ON STUDENTS ESSAY WRITING

The aim of this research was to know whether there are significant affection of reduction language error in students essay writing by using peer, teacher and self-feedback and to investigate which the best one of the strategies on reduction language error in students essay writing. The 126 tenth grade students of one senior high school in Tangerang were chosen as the sample which taken by non-random using purposive sampling. This research used experimental method with three experimental groups design. Students’ test for pre-test and post-test were used by the researcher to collect the data. The hypothesis data was tested using formula of t-test. The result showed that there was a significant effect used peer, teacher and self-feedback on reduction language error in students writing essay at the tenth grade of senior high school, but teacher feedback is better strategy than peer and self-feedback. It means that the three feedback strategies in reducing language error are effective on improving students writing skill and the teacher feedback strategy is the most effective one among the other strategies