Reviewerly/exHarmony huggingface dataset:
Asic Implementation of 12-Bit Radix-8 Booth Multiplier

Multipliers are playing a vital role in DSP and Neural Networks applications. Many methods have been introduced to work on multipliers that offer high speed, less power consumption and reduced area. Booth Algorithm demonstrates an efficient way of signed binary multiplication. In this paper, physical design of 12-bit radix-8 booth multiplier for signed multiplication is presented with an aim to improve the performance metrics such as power, area and delay. The performance of 12-bit radix-8 booth multiplier is compared with the 64-bit radix-16 booth multiplier.
Temporal Pattern Detection to Predict Adverse Events in Critical Care: Case Study With Acute Kidney Injury (Preprint)

<sec> <title>BACKGROUND</title> More than 20% of patients admitted to the intensive care unit (ICU) develop an adverse event (AE). No previous study has leveraged patients’ data to extract the temporal features using their structural temporal patterns, that is, trends. </sec> <sec> <title>OBJECTIVE</title> This study aimed to improve AE prediction methods by using structural temporal pattern detection that captures global and local temporal trends and to demonstrate these improvements in the detection of acute kidney injury (AKI). </sec> <sec> <title>METHODS</title> Using the Medical Information Mart for Intensive Care dataset, containing 22,542 patients, we extracted both global and local trends using structural pattern detection methods to predict AKI (ie, binary prediction). Classifiers were built on 17 input features consisting of vital signs and laboratory test results using state-of-the-art models; the optimal classifier was selected for comparisons with previous approaches. The classifier with structural pattern detection features was compared with two baseline classifiers that used different temporal feature extraction approaches commonly used in the literature: (1) symbolic temporal pattern detection, which is the most common approach for multivariate time series classification; and (2) the last recorded value before the prediction point, which is the most common approach to extract temporal data in the AKI prediction literature. Moreover, we assessed the individual contribution of global and local trends. Classifier performance was measured in terms of accuracy (primary outcome), area under the curve, and F-measure. For all experiments, we employed 20-fold cross-validation. </sec> <sec> <title>RESULTS</title> Random forest was the best classifier using structural temporal pattern detection. The accuracy of the classifier with local and global trend features was significantly higher than that while using symbolic temporal pattern detection and the last recorded value (81.3% vs 70.6% vs 58.1%; &lt;i&gt;P&lt;/i&gt;&lt;.001). Excluding local or global features reduced the accuracy to 74.4% or 78.1%, respectively (&lt;i&gt;P&lt;/i&gt;&lt;.001). </sec> <sec> <title>CONCLUSIONS</title> Classifiers using features obtained from structural temporal pattern detection significantly improved the prediction of AKI onset in ICU patients over two baselines based on common previous approaches. The proposed method is a generalizable approach to predict AEs in critical care that may be used to help clinicians intervene in a timely manner to prevent or mitigate AEs. </sec>
Grid Partitioning For Anomaly Detection (Gpad) In High Density Distributed Environment For Mining Techniques

Anomaly detection is the most important task in data mining techniques. This helps to increase the scalability, accuracy and efficiency. During the extraction process, the outsource may damage their original data set and that will be defined as the intrusion. To avoid the intrusion and maintain the anomaly detection in a high densely populated environment is another difficult task. For that purpose, Grid Partitioning for Anomaly Detection (GPAD) has been proposed for high density environment. This technique will detect the outlier using the grid partitioning approach and density based outlier detection scheme. Initially, all the data sets will be split in the grid format. Allocate the equal amount of data points to each grid. Compare the density of each grid to their neighbor grid in a zigzag manner. Based on the response, lesser density grid will be detected as outlier function as well as that grid will be eliminated. This proposed Grid Partitioning for Anomaly Detection (GPAD) has reduced the complexity and increases the accuracy and these will be proven in simulation part.
Letters

Early Years EducatorVol. 21, No. 2 LettersLettersJonathan BroadberyJonathan BroadberyHead of policy and external relations at National Day Nurseries Association (NDNA)Search for more papers by this authorJonathan BroadberyPublished Online:30 Apr 2019https://doi.org/10.12968/eyed.2019.21.2.12AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article FiguresReferencesRelatedDetails 2 June 2019Volume 21Issue 2ISSN (print): 1465-931XISSN (online): 2052-4617 Metrics History Published online 30 April 2019 Published in print 2 June 2019 Information© MA Education LimitedPDF download
Exchange woes continue

More details are emerging about attacks against the zero-day flaws found in Microsoft Exchange servers, even as organisations around the world frantically patch their systems.
Organizational Climate and Effectiveness Relationship in IT Sector: Mediating Effect of Organizational Commitment

Human resource of an organization is considered as a central variable which affects the effectiveness of an organization. In this competitive era employees are considered as an asset to the organization and it is the only resource which can use all other resources within organization in an effective way. Human resource with its skills, capability, talent and intelligence can help an organization to achieve its objectives. The performance of employees will only be high when a favourable environment with growth opportunities will be provided to them. The present study focuses on the effect of organizational climate on organizational effectiveness of IT sector with organizational commitment as a mediator. Data was collected through structured questionnaire with the help of convenient sampling from 350 employees from Delhi and NCR. Process macro along with AMOS was used to measure the mediating effect of commitment between organizational climate and organizational effectiveness. A significant partial mediation using Bootstrapping was found with an indirect effect of organizational climate on organizational effectiveness (β= .32, Boot (LLCI= .8678, ULCI= 1.599). Total effect of organizational climate on Organizational effectiveness was .71, whereas direct effect was .39.
Using text and acoustic features to diagnose Mild Cognitive Impairment and Alzheimer’s disease

Abstract The authors have requested that this preprint be removed from Research Square.
Gaussian Processes

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Extreme learning machine-based investigation on automated detection of architectural distortion in mammograms

Breast cancer, having its origin from the breast tissue is usually detected by mammographic screening. The early detection of breast cancer reduces the mortality rate. A subtle type of breast cancer that often leads to misinterpretation by radiologists is architectural distortion. Though the existing computer aided diagnosis systems efficiently and effectively detect the presence of micro-calcification and masses, the diagnosis of architectural distortion lacks a promising method. This project attempts to detect and classify the regions of mammograms having architectural distortion. MIAS and DDSM database images are enrolled in this research work. 350 region of interests (ROIs) of each architectural distortion and normal cases were extracted. They were subjected to a filtering process, followed by contrast enhancement. Application of Gabor filter to the images resulted in orientation differences between the normal and abnormal images. Statistical features extracted from the resulting images were classified using extreme learning machine classifier. The experimental results obtained from extreme learning machine in comparison with support vector machine had an accuracy of 98.49% and 87.21% for MIAS and DDSM respectively. The accuracy of combined database of which is 85.38%.
Anonymous Functions

In Dart, most of the functions we have seen so far are named functions, which are similar to functions in languages like C# and Java. Still, the function syntax of Dart has more similarities with JavaScript than in many strongly typed languages like C# or Java.
Wavelets and Subband Decomposition

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Assessing Decadal Predictability in an Earth-System Model Using Explainable Neural Networks

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Geophysical Research Letters. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]Assessing Decadal Predictability in an Earth-System Model Using Explainable Neural NetworksAuthorsBenjamin ATomsiDElizabeth A.BarnesJames WilsonHurrelliDSee all authors Benjamin A TomsiDColorado State UniversityiDhttps://orcid.org/0000-0001-7982-5491view email addressThe email was not providedcopy email addressElizabeth A. BarnesCorresponding Author• Submitting AuthorColorado State Universityview email addressThe email was not providedcopy email addressJames Wilson HurrelliDColorado State UniversityiDhttps://orcid.org/0000-0002-3169-6384view email addressThe email was not providedcopy email address
ASPEK-ASPEK AUDIT SISTEM INFORMaSI

AbstractThe audit of information system was conducted at Library and archive in Salatiga Dictrict, applying ISO 9001:2015 standard method that focusing on environmental control, physical control, logical controls, and IS operation, collecting the result. The library has already had access right division for the users, policy that rule, and security based on the standard. Based on the result of asset management information system audit done previously stated that library management has never conducted any information system audit toward the performance of information system owned to ensure information system performance is based on ISO 9001:2015 standard. Keywords: Information System Audit, Library, ISO
Research on Hybrid Teaching Mode Based on "Cloud Class Intelligent Vocational Education" --- Take "Introduction to Internet of Things" as An Example

The advent of the era of ＂Internet+＂has made intelligent classroom an inevitable trend of current education. Based on the cloud class intelligent vocational education platform, this paper takes the course "Introduction to Internet of things" as an example, and constructs a hybrid teaching mode through the integration of online and offline resources. Through the actual classroom teaching, this paper analyzes the traditional teaching and hybrid teaching, and discusses their possible shortcomings. By reflecting on its shortcomings, new ideas are put forward for the innovation and practical application of hybrid teaching mode in vocational education in the future. This paper mainly introduces the application advantages of the "cloud class intelligent vocational education" hybrid teaching mode in the "Introduction to the Internet of Things", analyzes the problems in the application of the hybrid teaching mode in the course of "Introduction to the Internet of Things", and studies the specific problems and countermeasures.
Preface

International Journal of Modern Physics AVol. 35, No. 34n35, 2002004 (2020) No AccessPrefacehttps://doi.org/10.1142/S0217751X20020042Cited by:0 Next This article is part of the issue: Special Issue on New Frontiers in Physics — Selected Papers from ICNFP2019 (Part 1) Guest Editors: L. Bravina, S. Kabana, V. Volkova and V. I. Zakharov AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail You currently do not have access to the full text article. Recommend the journal to your library today! FiguresReferencesRelatedDetails Recommended Vol. 35, No. 34n35 Metrics History PDF download
David Weiss

David Weiss performed as principal oboe with the Los Angeles Philharmonic from 1973 to 2003. He taught at the University of Southern California and the Music Academy of the West in Santa Barbara and was also a published photographer. In this chapter, he discussed his early career, teaching, tone, and auditions. He told stories from his performances on the musical saw.
Preface

We are delighted to introduce the proceedings of the 2nd Workshop on Engineering, Education, Applied Sciences, and Technology (WEAST 2020) and joint conference with The 4th International Conference on Mathematics, Science, Technology, Education and their Applications (ICMSTEA). The event is organized by a Faculty of Mathematics and Natural Sciences Universitas Negeri Makassar. The technical program has brought researchers and practitioners around the world to a good forum for discussing, leveraging and developing all scientific and technological aspects that are relevant to digital society. This event that discussed the development of the era of industrial revolution 4.0 and how to anticipate this era in various fields of science. Due to Covid-19 outbreak, the event has been successfully held virtual and non-virtual (for authors from Makassar or near of the event with Health Protocol of COVID-19 in Opening Ceremony) on October 5, 2020. Total more than 100 participants in the plenary room were enthusiastic about listening to the keynote speakers. We hope that the future 2 nd WEAST and 4 th ICMSTEA will be as successful and stimulating, as indicated with the contributions presented in this volume. In closing, we would like to thank the all parties, for supporting the successful conference. We would also like to thank all contributors for your good cooperation. Special thanks for OC members for their hard work and patience. International Scientific Committee, Reviewer, Committee, Adminitration Committee, Program Committee, Editing and Punlication Committee, Logistic and Decoration Committee, Fund and Sponsorhip Committee and this titles are available in this pdf.
Wait Statistics Internals

SQL Server wait statistics are an important tool you can use to analyze performance-related problems or to optimize your SQL Server’s performance. They are, however, not that well known to many database administrators or developers. I believe this has to do with their relatively complex nature, the sheer volume of the different types of wait statistics, and the lack of documentation for many types of wait statistics. Wait statistics are also directly related to the SQL Server you are analyzing them on, which means that it is impossible to compare the wait statistics of Server A to the wait statistics of Server B, even if they had an identical hardware and database configuration. Every configuration option, from the hardware firmware level to the configuration of the SQL Server Native Client on the client computers, will have an impact on the wait statistics!
efektivitas dan efisiensi pembiayaan pendidikan

This research based on the problem of lack of clarity in the allocation of funds effectively, efficiency in implementing the educational process. Research objectives to be achieved is “formulation of the effectiveness and efficiency of financing”.
Reporting the findings

This chapter describes ways to present usability test findings. Topics include writing an informal or formal report in document style or presentation style, using tables, charts and graphs, screenshots, participant quotes, and video clips to illustrate the findings, and presenting the posttask and posttest results. Ways to present recommendations are included. The chapter also describes the key factors in preparing and presenting an oral report, from planning to practice to delivery to handling questions. The chapter concludes by emphasizing the need to advocate for more user-centered design research.
Snakes and Ladders Game: An Alternative Instructional Strategy to Enhance the Learners’ Grammatical Proficiency

This present study reports on the findings related to the use of the snake and ladder game as a strategy to enhance the learners’ grammatical proficiency in mastering simple future tense. The participants were 27 eleventh graders of SMK Asrama Pembina Masyarakat. A number of instruments used in this study. The developments of the students’ grammatical proficiency were collected through the two sets of pre-test and post-test. The data related to the students’ attitude toward grammatical problems and the implementation of snake and ladder game were collected through questionnaires. Observation was employed to record the students’ participation during the lesson. The findings revealed that the students’ grammatical proficiency significantly improved. There were 20 (74.07%) out of 27 students who passed the criterion of minimum completeness of 75. The average score of students showed 77.26. Through the distributed questionnaires, the findings also demonstrated the positive thoughts and attitudes related to the game they played during the lesson. The students’ participation to the use of the snake and ladder game in teaching-learning activity in the classroom was also pleasing. It can be concluded that the application of this game can meet the all criteria of success of cycle. In other words, it can play positive role in developing the learners’ grammatical proficiency.
On Computing Digraph Kernels

We illustrate in this chapter, first, the concept of graph kernel, i.e. maximal independent set of vertices. In non-symmetric digraphs, the kernel concept becomes richer and separates into initial and terminal kernels. In, furthermore, lateralised outranking digraphs, initial and terminal kernels become separate and may deliver suitable first and, respectively, last choice recommendations. After commenting the tractability of kernel computations, we close the chapter with the solving of bipolar-valued kernel equation systems.
Relation between Katsaridaphobia and Blood Glucose Level

Blood glucose refers to the amount of sugar (glucose) in your blood, also known as Serum Glucose Level. Increased blood sugar level for a long time can damage the blood vessels. Normal Fasting Glucose level in blood is 70 – 100 mg/dl, while sugar level after two hours of eating (Random) must be below 140 mg/dl. In this project, we are discussing about phobia of cockroaches named as Katsaridaphobia. Main objective behind this study was to find interrelation between katsaridaphobia and blood glucose level. This project was carried out by conducting a questionnaire in 130 students of university. A simple glucometer was used to measure sugar levels of students. . Student’s t-test was performed for statistical analysis.
LETTER FROM THE ASSOCIATED EDITOR

In this letter, the number 3 of 2020 of the Journal of Management and Business Education is introduced. A brilliant article and a suggestive line of research by Professor Enrique Bigne head the number. His work introduces us to a new perspective, current, and with a great projection of the future, which is the necessary customization of the teaching-learning process in Business and Management, assisted by technology and the constant innovations in teaching and learning. In addition, the number includes a relevant contribution by the professors of the University of the Basque Country UPV-EHU, with its IKASEKIN model, formulated as an integral learning for the development of innovative capacity, and which received the Educational Innovation Award of XXXIII AEDEM Annual Congress, held in June 2019 in Seville. Other interesting contributions included in the number refer to the implications of new methodological tools that increasingly appear as protagonists in our classrooms, such as gamification or interactive digital applications to maintain attention and the motivation of the students in their learning.
International Symposium on Frontier of Applied Physics

International Symposium on Frontier of Applied Physics is organized annually by Research Center for Physics-Indonesian Institute of Sciences. The 4th ISFAP 2018 conference is part of Indonesian Science Expo 2018 which disseminates current technology progress initiated by researchers in Indonesian Institute of Sciences.
DAG-CPM Scheduler for Parallel Execution of Critical Jobs

Map Reduce applications having multiple jobs may be dependent on each other such as iterative Page View application [2] performs the required operation in several iterations before generating the result. Each iteration is considered as single job. Conventional Hadoop MapReduce schedules the jobs sequentially, but not customized to handle multi job application. Also, it will not perform the parallel execution of the dependent jobs. This prolongs the execution time to complete all the jobs. Therefore a new scheduler DAG–CPM Scheduler uses the critical path job scheduling model, to identify the jobs present in the critical path. Critical path job scheduling is optimized to offer support for multi job applications, critical path job is a series of jobs, if execution of a job is delayed, then time required to execute all jobs will be prolonged. DAG–CPM Scheduler schedules multiple jobs by dynamically constructing the job dependency in DAG for the currently running job based on the input and output of a job. DAG represents the dependency among the jobs, this dependency graph is used to insert a pipeline between the output of one job as input for map tasks of another job and it executes the dependent jobs in parallel which results into a substantial reduction in the execution time of an application. Experimental analysis on the proposed approach has been carried out on Page View application on Academic and research web server log file, such as, NASA and rnsit.ac.in of 10 GB data set. PigMix2 is executed on 8GB data set. Experimental results reveal that the average execution time is decreased by 41% compared to Hadoop in respect Page View application and Execution speed is 37.7% faster compared to Pig and DAG–CPM Scheduler can run 24.3% faster when compared to DAG–CPM Scheduler without pipeline.
China: Lomon Billions – TiO2

Over the last years complex data (e.g. images) have been growing in a very fast pace. This demands the ability to describe and to categorize them. To solve this problem it is essential to develop efficient and effective vision-based expert techniques. Hence, the cornerstone of our work is to propose a new methodology, called BoVW-CN, that combines Bag-of-Visual-Words and complex networks for describing keypoints detected in a given image. Our insight is that describing just the relevant points of an image we can achieve a more cost-effective and better image description. The obtained results testify that BoVW-CN, applied to public image datasets, outperforms the widely used state-of-the-art methods. We not only obtained good accuracies (e.g. 78.18%), but also performed analyses to find the best trade-off between computational cost and accuracy. Besides, to the best of our knowledge, our work is the first one to propose such integration of Bag-of-Visual-Words and complex networks through a texture-based focus.