Reviewerly/exHarmony huggingface dataset:
A_CenterNet: Object as a Point by Attention

In this paper, in view of the insufficiency of the CenterNet detector’s inability to achieve high real-time performance with high accuracy when performing object detection, we designed a new detector called A_CenterNet. In the detector, we use our newly designed lightweight Hourglass-256 model, and we also use the feature map fusion method we designed, as well as our improved attention mechanism. Through the experimental results on multiple datasets, it can be known that the A_CenterNet proposed in this paper has a competitive advantage compared with some existing classic detectors. A_CenterNet achieves the best speed-accuracy trade-off on the MS COCO dataset, with 44.6 AP at 36 FPS. Compared with CenterNet, A_CenterNet greatly improves the detection speed without loss of detection accuracy.
Professionally Oriented Tasks in the System of Professional Training of Musical Art Teachers

The relevance of the chosen topic of the article is determined by the need of definition of the tasks in the system of professional training of musical art teachers, that are focused on work, as the integration of higher musical and pedagogical education of Ukraine in the world educational and cultural space based on the principles of national and ethno cultural interests, preservation and development of the Ukrainian intellectual potential of the nation, peacekeeping orientation of international cooperation, tolerance and adaptation in the assessment of mastering and achievements in the field of art culture of different nationalities, puts forward new requirements for the training of future musical art teachers (FMAT) in the field of higher education institutions (HEI).The article analyzes the theoretical developments on the topic, specifies the tasks in the system of vocational training of musical art teachers in the works of researchers and scientists, the experience of future musical teachers in higher educational institutions. These conditions include: ensuring the motivation of students to professionally solve educational problems by immersing FMAT in an innovative professional educational environment; application of innovative methods of design of educational activities of students in the process of studying the disciplines "Pedagogy", "Musical Pedagogy" to enrich the technical knowledge of the FMAT; to help students to realize the need for continuous professional self-improvement in the process of passing various types of educational practice. The implementation of a certain educational factor was aimed at forming a specific component of the phenomenon under study.
Adversarial Machine Learning: A Blow to the Transportation Sharing Economy

Adversarial machine learning has indicated that perturbations to a picture may disable a deep neural network to correctly qualify the content of a picture. The progressing research has even revealed that the perturbations do not necessarily have to be that tremendous in size. This research has been transplanted to traffic signs. The test results were disastrous. For example, a perturbated stop sign was recognized as a speeding sign. Because visualization technology is not able to overcome this problem yet, the question arises who should be liable for accidents caused by this technology. Manufacturers are being pointed at and for that reason it has been claimed that the commercialization of autonomous vehicles may stall. Without autonomous vehicles, the sharing economy may not fully develop either. This Chapter shows that there are alternatives for the unpredictable financial burden on the car manufacturers for accidents with autonomous cars. This Chapter refers to operator liability, but argues that for reasons of fairness, this is not a viable choice. A more viable choice is a no-fault liability on the manufacturer, as this kind of scheme forces the car manufacturer to be careful but keeps the financial risk predicable. Another option is to be found outside law. Engineers could build infrastructure enabling automation. Such infrastructure may overcome the problems of the visualization technology, but could potentially create a complex web of product and service providers. Legislators should prevent that the victims of an accident, if it were still to occur, would face years in court with the various actors of this complex web in order to receive compensation.
Sqoop usage in Hadoop Distributed File System and Observations to Handle Common Errors

The Hadoop framework provides a way of storing and processing the huge amounts of the data. The social media like Facebook, twitter and amazon uses Hadoop eco system tools so as to store the data in Hadoop distributed file system and to process the data Map Reduce (MR). The current work describes the usage of Sqoop in the process of import and export with HDFS. The work involves various possible import/export commands supported by the tool Sqoop in the eco system of Hadoop. The importance of the work is to highlight the common errors while installing Sqoop and working with Sqoop. Many developers and researchers were using Sqoop so as to perform the import/export process and to handle the source data in the relational format. In the current work the connectivity between mysql and sqoop were presented and various commands usage along with the results were presented. The outcome of the work is for each command the possible errors encountered and the corresponding solution is mentioned. The common configuration settings we have to follow so as to handle the Sqoop without any errors is also mentioned.
Amgen Inc. v. Sanofi, Aventisub LLC United States Court of Appeals of the Federal Circuit, 2021 987 F.3d 1080

Biotechnology Law ReportVol. 40, No. 3 Case in PointAmgen Inc. v. Sanofi, Aventisub LLC United States Court of Appeals of the Federal Circuit, 2021 987 F.3d 1080Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:8 Jun 2021https://doi.org/10.1089/blr.2021.29228.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:Amgen Inc. v. Sanofi, Aventisub LLC United States Court of Appeals of the Federal Circuit, 2021 987 F.3d 1080.Biotechnology Law Report.Jun 2021.191-196.http://doi.org/10.1089/blr.2021.29228.cmhPublished in Volume: 40 Issue 3: June 8, 2021Online Ahead of Print:April 26, 2021PDF download
systemd

We’ve explored looking at processes directly using tools like ps; another way to look at the processes running on a system is from the daemon perspective. A daemon is a long-running process which operates in the background of a system; often they’re automatically started on system start by an init program like systemd. The “d” in systemd comes from the concept of daemon, as it acts as a controller for all daemons running on the system.
Question Classification using a Rule based Model

Question Answering is one of the most common applications for data acquisition. Although the majority of text-mining applications strive to improve the user experience and the tools used to find appropriate answers, the problems still exist because the web content is constantly increasing. The Questions Classification (QC) task is one of the main tasks in improving the classification system is to classify types of questions in the text mining application. A large number of QC methods are introduced to help resolve classification problems, most of which are bag of words approaches. In this project, we propose a QC system that uses Parts of Speech (POS) Tagger and Named Entity Recognition (NER) Tagger from the Stanford core Natural Language Processing (NLP) to classify the questions correctly. We started by cleaning the data by removing the available labels in the questions then we proceed by tagging the questions by splitting words and tagging each and every words in the input question with the POS Tagger. After this step, we will convert them into a pattern without changing the structure of the question. Then we proceed by tagging the question with NER Tagger. Finally, we will do confirmation process for certain question types which is performed by confirming question type module to make the system work efficiently.
Design and Analysis of 32 bit R evers e C onverter based on low power Parallel Prefix A dder

The Residue Number System (RNS) based reverse converter can play as main role in Parallel arithmetic operations of Digital Signal Processing (DSP) applications and VLSI technologies. Normally, by the use of carry adders, the reverse conversion design gives high delay and high power consumption. Due to resolve of above problem, the design of reverse converter is proposed by the use of familiar high speed (less propagation delay) Parallel Prefix - Kogge Stone Adder (PP- KSA). This paper describes the design of 32-bit Reverse converter with regular PP-KSA and proposed MUX (Multiplex) logic of PP-KSA with Hybrid Modular Parallel Prefix structure (HMPE) separately. In addition to that, the performance of that designs are analysed based on area, delay and power independently. The Performance results of proposed MUX logic of PP-KSA Reverse converter design yields low power than the other design which uses the regular PP-KSA. The simulation and synthesis effects can be done in Xilinx ISE 14.2i tool.
Quantum computers

In a quantum computer, the elementary units of information are qubits, which replace the classical two-valued bits, usually designated 0 and 1. A qubit is a coherent quantum superposition of the 0 and 1 states. Just as in the classical case, quits can be manipulated using circuits composed of quantum gates. With n qubits one could, in principle, perform n simultaneous computations, giving the equivalent of massively parallel capability. Quantum gates can be represented by unitary matrices. Thus, in contrast to classical gates, quantum gates are reversible. Some very efficient algorithms have been proposed for quantum computers for fast Fourier transform and for factorization of large integers. Applications to large scale quantum computations on molecules are at an early stage of development.
Implementation of Double Fold Text Encryption Based on Elliptic Curve Cryptography (ECC) with Digital Signature

As the internet provides access to millions of communications in every second around the world, security implications are tremendously increasing. Transfer of important files like banking transactions, tenders, and e commerce require special security and authenticated mechanism in its journey from the sender to the receiver. Recent attention of cryptography is mainly focused on use of elliptic curves in public key cryptosystems. The present paper explains an innovative public key cryptographic scheme for protecting sensitive of critical information using elliptic curve over finite field. This mechanism besides providing the robustness of the cipher contributes the authentication of the message with digital signature.
Container Overview

This first chapter will introduce readers to the world of containers, microservice applications, and their associated monitoring and management tools ecosystem. We will also look into how containers and the ecosystem around them are assembled. The chapter will cover the following topics:
Efficient search for top-&lt;i&gt;k&lt;/i&gt; discords in streaming time series

The problem of anomaly detection in streaming time series has received much attention recently. The problem addresses finding the most anomalous subsequence (discord) over a time-series stream, which might arrive at high speed. The fact that finding top-k discords is more useful than finding the most unusual subsequence since users might make a choice among the top-k discords instead of choosing only one. Hence, an efficient method of search for top-k discords in streaming time series is proposed in the paper. The method uses a lower bound threshold, a lower bounding technique on a common dimensionality reduction transform, and a state-of-the-art technique of the distance computation between two time-series subsequences to prune off unnecessary distance calculations. The three techniques are arranged in a cascading fashion to speed up the performance of the method. Furthermore, the proposed method can return a set of top-k discords on the fly. The experimental results show that the proposed method can acquire quality discords nearly identical to those obtained by HOT SAX, a well-known method of anomaly detection. Remarkably, our proposed method demonstrates a fast response in handling time-series streams at high speed.
TEACHING EFL USING MEDIA VIDEO OFFLINE FROM YOUTUBE

English is a foreign language that must be studied, there are four skills that students must master, namely writing, speaking, reading and pronouncation. The development of technology in the learning process of teachers is required to use media not only using books, markers, or other things that are not related to technology that will make teachers or students miss technological development. The current era of globalization is a lot of media or tools for teaching teachers, namely using smartphones, laptops, one of them is a website, application, social media such as facebook, instagram, twitter, line or other social media, and the last is YouTube. In this study we use YouTube video offline media as a teaching process. Using the media in the learning process and YouTube include new media or ways in the learning process and using YouTube definitely brings impact. Of course a positive impact for students or teachers in the learning process. This study will tell so much about the use of YouTube as a medium for teacher learning in learning English.
PetroLogistics II to build new PDH plant at undecided location on the Gulf Coast

Information security violations have negative organizational and personal impacts. Studies that examine key factors to motivate individuals to change their security-related behaviours are important to promote safe and secure computing. Drawing on protection motivation theory (PMT), this research aims to investigate the antecedents of threat and coping appraisals in relation to the individuals' information security protection intention among university students. It contributes to a better understanding of users' information security awareness through an examination of the impact of security education, training and awareness (SETA) programme on information security threat and countermeasures awareness and the role of information security awareness as an antecedent to the cognitive processes associated with coping and threat appraisals. In addition, this research contributes to extend PMT by investigating the role of fear and maladaptive rewards in explaining information security behaviours.
Research on the Application of Intelligent Learning Algorithms in Network Security Situation Awareness and Prediction Methods

As the core hotspot of network information security, network security situational awareness has received more and more attention. In order to explore the application effect of intelligent learning algorithm, this study takes Radial Basis Function (RBF) as the main research object, optimizes RBF by Simulated Annealing (SA) algorithm and Hybrid Hierarchy Genetic Algorithm (HHGA), constructs RBF neural network prediction model based on SA-HHGA optimization, and carries out relevant experiments. The results show that the predicted situation value of the optimized RBF in 15 samples is very close to the realistic situation value. RBF has good prediction effect and can provide assistance for the maintenance of network security.
Implementation of Security Enhancement in AES by Inducting Dynamicity in AES S-Box

Advance Encryption Standard (AES) supersedes Data Encryption Standard (DES) and is the best known and most widely used block cipher. As for now, there are no known practical attacks that would allow anyone to read correctly implemented AES encrypted data. However, several theoretical attacks have been announced until now. A theoretical attack called Biclique Attack is known to have broken Full AES and requires 2126.1, 2189.7, 2254.4 operations to recover an AES-128, AES-192, AES-256 respectively. Biclique Attack is faster than Brute force attack by a factor of four. As such, these theoretical attacks are of high computational complexity; they do not threaten the practical use of AES in any way. However, attacks always get better; they never get worse. As the technology evolves, successful attacks (using Quantum Computing and faster GPU) against AES may turn up, and they may be difficult to ignore. In this study, we aim to enhance the security prospects of AES with the inclusion of Dynamicity character in AES S-Box for increased resilience against Brute Force Attack and Biclique Attack, and hashing technique is combined with AES algorithm to achieve variance in security using MD4, SHA3 or SHA5. The novel key dispersion technique is introduced to increase the avalanche effect of AES algorithm.
Network technologies in preparing high school students for database management

The article shows the importance of network technologies in teaching schoolchildren. The analysis of textbooks of informatics on the subject of teaching a topic related to the maintenance of databases is given, and the features of its presentation are highlighted. On the example of the implementation of the project “Entering the University”, it is shown how students of grade 11 can be taught to work with network databases. In particular, create and maintain them, use them in professional activities. A step-by-step description of the actions of schoolchildren when creating a network database is given (creating a table structure, fi lling the database with information, selecting information through the formation of a query, working with reports). A business game through which students better understand the purpose of database management systems is described. Examples of a possible violation of information security when working with documents of applicants in the university selection committee are given.
Business Intelligence for Evaluating the Intangible Benefits of On-Shelf High Utility Itemset from the Temporal Transaction Database

Utility Mining is the progression of identifying High Utility Itemsets (HUI’s) from enormous transaction data. Utility mining plays a decisive role in the inspection of the data or giving actionable information to help managers, sales executives, and other commercial end-users to generate versed business decisions. In the hypermarkets, the showcase period of every item in display will vary such as new products, seasonal products, and so on. Itemsets with time period are not retrieved by existing utility mining algorithms. Hence, On-Shelf Utility Mining algorithms were proposed to discover HUI’s and a general on-shelf period of all items in temporal databases is considered. Research work aims to propose an algorithm called LOSUM (List On-Shelf Utility Mining) to retrieve on-shelf HUI’s from a temporal transaction database by reducing the data stores scan. The algorithm is enhanced by implementing a list structure to store utility information of every itemset. The candidate itemsets are generated from the list itself. This reduces the supplementary scan of a database. The LOSUM is compared with FOSHU using Chess, Accident, Kosarak, and Mushroom datasets. The experimental results illustrate that the LOSUM is efficient than the existing algorithm FOSHU (Fast On-Shelf High Utility itemset mining) algorithm.
Selection and Manipulation Whole-Body Gesture Elicitation Study in Virtual Reality

We present a whole-body gesture elicitation study using Head Mounted Displays, including a legacy bias reduction technique. The motivation for this study was to understand the type of gesture agreement rates for selection and manipulation interactions and to improve the user experience for whole-body interactions. We found that regardless of the production technique used to remove legacy bias, legacy bias was still found in some of the produced gestures.
Amerigen Pharm. Ltd. v. UCB Pharma GmbH United States Court of Appeals of the Federal Circuit, 2019 913 F.3d 1076

Biotechnology Law ReportVol. 38, No. 2 Case in PointAmerigen Pharm. Ltd. v. UCB Pharma GmbH United States Court of Appeals of the Federal Circuit, 2019 913 F.3d 1076Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:15 Apr 2019https://doi.org/10.1089/blr.2019.29110.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 38Issue 2Apr 2019 InformationCopyright 2019, Mary Ann Liebert, Inc., publishersTo cite this article:Amerigen Pharm. Ltd. v. UCB Pharma GmbH United States Court of Appeals of the Federal Circuit, 2019 913 F.3d 1076.Biotechnology Law Report.Apr 2019.116-121.http://doi.org/10.1089/blr.2019.29110.cmhPublished in Volume: 38 Issue 2: April 15, 2019PDF download
NLP Algorithms Endowed f or Automatic Extraction of Information from Unstructured Free Text Reports of Radiology Monarchy

Natural Language Processing (NLP) Algorithms are the key factors for automatic information extraction form the unstructured free-text radiology reports .To extract clinically important findings and recommendations, various NLP algorithms are used . A rule-based NLP system is used in most of the automated IE applications in medical domain; whereas some applications are using Random Forest classifier, PageRank Algorithm, clustering algorithm, Conditional Random Fields (CRF) algorithm, and deep learning-based approaches. Some papers found with methods used for IE like, Support Vector Machines (SVMs), linear-chain conditional random fields (LC-CRFs), k-means or k-medoids algorithm ,Affinity Propagation (AP) clustering algorithm , supervised machine learning algorithm and many more. Thus through this survey we can say that, NLP methods used to extract information ,brings new insights into already known clinical evidences. It also helps to identify previously unknown treatment and causal relations between biomedical entities .Therefore NLP algorithms has empowered Radiology monarchy.
KONSEP DASAR SISTEM INFORMASI MANAJEMEN DAN PENGARUHNYA DALAM DUNIA PENDIDIKAN

Management information system in an operasional system that carries out a variety of functions to produce outputs that are useful for the implementation of operations and management of the relevant organization. The application of management information system in daily life is now increasingly found as in business, nanking, goverenment, or hospitality. In the world of education management information system and information technology are very supportive to improv the quality of education. With a school management information system, it can determine, the right approach in planing an education management information system at school and can collect data comprehensively.
STAD vs. conventional and learning modality towards English speaking pronunciation learning outcome

The design of this study is quasi-experimental research designs (quasi-experiment) with the model design is Nonequivalent Pretest - Posttest Control Group Design. Based on data analysis, the results of the study (1) there are differences in learning outcome between groups of English speaking students taught by STAD learning strategy with a group of students who are taught by conventional learning strategies (F = 38.999, p = 0.000), (2) there are differences in English speaking learning outcome between the students who have different learning modalities (F = 99.063, p = 0.000), and 3) there are interaction effect between STAD and conventional learning strategy and learning modalities (visual, auditory and kinesthetic) on English speaking pronunciation learning outcome (F = 3.729, p = 0.126).