Reviewerly/exHarmony huggingface dataset:
A Survey and Comparative Study for Connecting 2D points

Reconstruction from noisy point sets has many ap-plications in the areas of science and engineering. Research effort in reconstructing shape from noisy point sets. Reconstruction on planar point including shape, surface, curve and manifold recon-struction. Good algorithms are required to create a good shape from a given point set. Better local and global sampling conditions form the base of these algorithms. Reconstruction from noisy point set is not extensively studied and therefore the researchers do not have a successful algorithm. Reconstruction from the stage is begun before many decades and these activities are now being extended for a few days. Extending any older reconstruction algorithms needs a good understanding and comparison of all previous algorithms. This survey is spamming on different reconstruction algorithms, various local sampling conditions, extension of different works and their working conditions and reconstruction implementation from point sets. Survey begins after 1997 and compares various extension works. The sampling condition for all these algorithms contributes significantly to the construction of algorithms, thus different local sampling conditions are investigated. During this study, all algorithms for reconstruction are tabulated and different parameters for these algorithms are compared. This survey is concluding with several promising directions for the future works on reconstruction.
Discovering Seminal Works with Marker Papers.

Bibliometric information retrieval in databases can employ different strategies. Commonly, queries are performed by searching in title, abstract and/or author keywords (author vocabulary). More advanced queries employ database keywords to search in a controlled vocabulary. Queries based on search terms can be augmented with their citing papers if a research field cannot be curtailed by the search query alone. Here, we present another strategy to discover the most important papers of a research field. A marker paper is used to reveal the most important works for the relevant community. All papers co-cited with the marker paper are analyzed using reference publication year spectroscopy (RPYS). For demonstration of the marker paper approach, density functional theory is used as a research field. Comparisons between a prior RPYS on a publication set compiled using a keyword-based search in a controlled vocabulary and three different co-citation RPYS analyses show very similar results. Similarities and differences are discussed.
Numerical methods for neural networks and applications

Neural Networks have been a trending topic in the latest years, because oftheir incredible capability of approximating any function.They could be considered big optimization problems, but their highcomplexity does not allow to use powerful algorithms, because of theircomputational cost. Thus the strategy adopted in Neural Networks' theory isto modify the classic Gradient Descent with some advices, deriving fromheuristics. However this brings this family of problems to a not so rigorousenvironment. Thus the purpose of this work is to investigate the behaviourand results of Neural Networks through DLTI systems, that are well knownmathematical models.
LibGuides: 52nd Annual CBHL 2020 Meeting: Financial Support

Program and schedule for the 52nd meeting of the Council on Botanical and Horticultural Libraries in Washington D.C. and Beltsville, Maryland
LibGuides: Introduction to Academic Writing: e-learning and eBooks (30 mins+)

Our online guide to academic writing covers the key skills for writing at university level, including style, structure and how to develop your academic voice.
Effect of Concentration Training on Cognitive Ability

Purpose: The objective of this study was to determine the effects of concentration training on cognitive ability. Methods: For this study, 30 subjects were randomly assigned to experimental and control groups. The experimental group received concentration training using a computerized cognitive rehabilitation program. The intervention was performed three times a week for four weeks. The period of each session was 10 minutes. The control group received the training with a virtual driving simulator. To assess cognitive ability, a virtual driving simulator was used. Results: This study shows the following results. First, the control group showed a significant increase in interference task 1 compared with the experimental group. The control group displayed statistically significant speed increases in interference task 1 compared with the experimental group. Third, the experimental group showed significant increases in the score and the speed of the ability to stay in one’s lane compared with the control group. Conclusion: This study showed that concentration training had positive effects on cognitive ability, but the learning effect of the virtual driving simulator influenced the score and speed of interference task 1.
LibGuides: Web of Science Core Collection: Saving, Alerting, and Managing Results

Web of Science Core Collection is a painstakingly selected, actively curated database of the journals that researchers themselves have judged to be the most important and useful in their fields. How to create a 'Marked List', view your Search History and Export records
Ensembling and transfer learning for multi-domain microscopy image segmentation

A lot of imaging data is generated in medical, and particularly in the microscopy ﬁeld. Researchers spend a lot of time analyzing this data due to slow algorithms and exhaustive manual work. Recent advancements in machine learning and especially deep learning areas resulted in methods that could be used to efﬁciently solve challenges in the microscopy imaging ﬁeld. Image segmentation is one of the most common labor-intensive tasks that could be automated with deep learning approaches. One of the biggest challenges for computer algorithms in this domain is the problem of domain shift. The domain shift is the difference between the distribution of the data used for training and the distribution of the new upcoming data. In this work, we show that deep neural networks could efﬁciently segment microscopy images with the domain shift present. Moreover, we show that transfer learning from other medical tasks is an effective strategy to reduce the amount of required annotated data, whereas ﬁne-tuning ImageNet models for microscopy segmentation gain little beneﬁt.
Engaging JROTC Youth in CS Pathways

CSforALL is collaborating with the US Air Force JROTC HQ and additional partners to launch JROTC-CS, a demonstration project to design and test implementation models for the long-term scale up of CS and cybersecurity education programs within the Junior Reserve Officers Training Corps (JROTC). There are approximately 500K Junior Reserve Officer Training Corps (JROTC) cadets at 3,400 partner high schools across the US. The JROTC represents a significant pool of public service oriented talent. The JROTC program is comprised of a highly diverse population, with a majority-minority student population and 40% of the JROTC being female, and JROTC is strongly represented in schools serving economically disadvantaged populations (over 50% Title 1 schools). The JROTC infrastructure is under-leveraged as a technology talent development opportunity, and represents an accessible, high ROI/low cost opportunity to accelerate preparation of the future workforce in critical areas such as computing, cybersecurity, defense technologies, AI and more. The JROTC-CS Demonstration project aims to design and test experiences for the participating districts, schools, teachers, JROTC instructors, and cadets that lead to a comprehensive implementation model for future scale across the JROTC infrastructure. An estimated additional 60K students will benefit from this project, as capacity for CS and cyber security is increased at their schools.
LibGuides: 52nd Annual CBHL 2020 Meeting: Sponsors

Program and schedule for the 52nd meeting of the Council on Botanical and Horticultural Libraries in Washington D.C. and Beltsville, Maryland
Pedagogical Techniques Teachers Use to Bolster Extensive Reading Habits in Secondary Schools in Kenya

This study addresses the issue of pedagogical techniques for extensive reading in secondary schools in Kenya at a time when concern is being expressed about declining reading habits in the institutions of learning.Learners nowadays have taken to social and mass media and rarely read anything extra outside the prescribed texts.Even the wide spread national examination malpractice witnessed recently could be traced to the decline in reading interest and poor reading habits among secondary school learners.Effective use of pedagogical extensive reading techniques can greatly improve learners' achievement in English and also enhance their reading habits.This study was prompted by the observed poor reading in English by secondary schools learners in Laikipia County in Kenya.Among some of the possible explanations for this scenario are that students in the County did not adequately read books extensively coupled with other determinants that influence their performance in English.The study investigated the pedagogical techniques used by teachers to bolster extensive and pleasure reading habits.The study was guided by The Schema Theory.The descriptive survey research design was used for this study.Fifteen secondary schools in Laikipia County were sampled by proportional stratified sampling technique in five subcounties across the county.Purposive sampling was used to sample 30 out of 80 (37.5%)English language teachers.Simple random sampling was used to sample 327 students out of about 2670 students (12.24%) in form 2 and 3 in the County.The research instruments used for data collection included: questionnaire for students, interview guides for teachers and documents analysis guide.The instruments were pilot tested to ensure validity and reliability in a co-educational secondary school in the neighbouring county that was not included in the study.The reliability of the questionnaire and interview guide was estimated using Cronbach's alpha coefficient which was 0.871 which met the recommended threshold of 0.7 and above.Analysis of data was done using descriptive statistics such as frequency, tables and percentages.Qualitative data were organized according to the study themes and presented descriptively on the basis of the study objectives.The analyzed data revealed various reading pedagogical techniques which included analysis of the title and the blurb before reading, formation of mental images while reading and writing book reviews after reading.Acute shortage of reading resources was a major hindrance to engagement in extensive reading in schools.The study recommended that schools should ground learners on reading techniques and also come up with strong extensive reading policy to promote independent reading.
The Influence of Corporate Social Relations on the Stability of Strategic Alliances

Our study aims to verify the effects of social relations, opportunistic behavior and trust among partners on the stability of strategic alliance.In order to test the hypotheses, 221 valid questionnaires collected from top managers of 50 strategic alliances in China.Moreover, the results also indicate that contractual governance can moderate the influence of high-level social relations on opportunistic behavior and trust between partners.It is found that the social relationship of senior managers cannot directly affect the stability of the alliance but can negatively affect the opportunistic behavior and positively affect the trust between partners.Opportunistic behavior and trust among alliance partners affect the stability of strategic alliance negatively and positively, respectively.Contract governance can enhance the influence of senior managers' social relationships on opportunistic behavior.In addition, contract governance shows the inverted U-shaped moderating effects on the relationship between senior managers' social relations and trust.
TRANSLATION SHIFT ANALYSIS OF THEMATIC STRUCTURE IN PRINTED POLITICAL NEWS REPORTS OF INDONESIAN LOCAL NEWSPAPER

This study aims to investigate translation shifts of textual metafunction in printed news reports of the Pikiran Rakyat newspaper. This study used a descriptive-qualitative method to investigate the consistency of the alignment from the news writers in translating articles. The data were taken from five printed political news articles along with its translation published from 19th March to 21st March, 2018. The data were analyzed by using Hallidayan framework of Systemic Functional Grammar and Newmark’s Translation Shift. The findings show that in terms of thematic structures, there were found 29.1% theme shifts of 79 clauses. It is found that the translators are manage to maintain the objectivity in the news reports. Further, this study discovers that the combination of structure and unit shift recurred frequently for 49.5% in translation. Then, it is followed by unit shift 21.5%, structure shift 10.2%, and the combination of class and unit shift 8.7%. The translation shift from the data shows that almost 50% of structure and unit shift are used frequently. It is concluded that Pikiran Rakyat tried to translate the contextual meaning in the source text, both in aspects of language and its content, so that readers can accept and agree with what being delivered.
Katalogisering i Libris XL : En studie om katalogisatörers praktik, kunskap och lärande

The aim of the study was to investigate catalogers’ practice, knowledge and learning, and if and how previous experience makes a difference and also investigate the need for knowledge in underlying ...
Research on Improvement of Parallel Apriori Algorithm Based on Boolean Matrix and Weight

Aiming at the defect that Apriori algorithm needs to traverse the database multiple times, an improved algorithm based on Boolean matrix and weight WF_Apriori(Weight Function Apriori) is proposed. This algorithm will add weight rows to the matrix to trim out duplicate transactions and compress the stored matrix, saving the time to scan the transaction set, making full use of the intersection between rows and rows, avoiding the k-1 item set The self-joining operation of the k-item set enables one of the required k-term frequent sets to be obtained at one time. Based on Hadoop, the improved algorithm is parallelized. The large matrix is divided into small matrices, parallelizing the processing of small matrices, reducing the time complexity of the algorithm, making the algorithm more efficient and increasing the practicability of the algorithm. The experimental results show that the improved algorithm greatly shortens the processing time in the big data environment, improves the mining efficiency of the algorithm, and achieves the expected goal.
Subject and Course Guides: Your Personal Librarian: Questions?

Your Personal Librarian is your own information concierge service. Use this guide to learn about the program and to connect with Your Personal Librarian to get the most out of your UTA Libraries experience.
Teaching Open Science

In this episode, we are discussing how to teach open science to PhD students. Helene N. Andreassen, head of Library Teaching and Learning Support at the University Library of UiT the Arctic University of Norway shares her experiences with the integration of open science in a special, tailor-made course for PhD's that have just started their project. An interdisciplinary, discussion-based course, "Take Control of Your PhD Journey: From (P)reflection to Publishing" consists of a series of seminars on research data management, open access publishing and other subject matters pertaining to open science.&#x0D; First published online February 26, 2020.
Kamil Khalili garnered Outstanding Student Award in Academic and Intellectual Development Cluster for STEM category for the year 2019

Universiti Malaysia Pahang (UMP)’s Mechanical and Automotive Engineering undergraduate Kamil Khalili Haji Abdullah’s deep interest in Science, Technology, Engineering and Mathematics (STEM) and active involvement in various STEM-related programmes earned him the Outstanding Student Award in Academic and Intellectual Development Cluster for STEM category for the year 2019.
Colour Image Search for Graphical Design Inspiration

This thesis project aims to develop a search algorithm which uses the colour information in uncompleted graphical work to find inspirational images that utilizes similar colour schemes. The dominan ...
LibGuides: 52nd Annual CBHL 2020 Meeting: Transportation

Program and schedule for the 52nd meeting of the Council on Botanical and Horticultural Libraries in Washington D.C. and Beltsville, Maryland
NVU Libraries Research Guides: Business and Economics: Welcome

This guide provides access to library materials on topics regarding business and economics.
LibGuides: 53rd Annual CBHL 2021 Meeting: Program

Program and schedule the 53rd meeting of the Council on Botanical and Horticultural Libraries in Washington D.C., May 5-7, 2021
BAYESIAN NETWORKS FOR IMPROVED ESTIMATION OF PADDY CROP PRODUCTION

In India’s food security, Paddy crop production has a prominent role by dispensing more than 40% of production of crop. Depends on climatic situation, paddy crop gives better production. Changes in seasonal climatic situations like low temperature or rainfall have negative impact of crop yielding. For improving the decision making capacity of farmers and stakeholders by considering the agronomy and crop choice, effective methods are developing for predicting the crop productivity under different climatic situation. The aim of this paper is estimating the paddy crop yield of Anantapur district, India. Anantapur was selected for this report accordingly considering the information existing in the Indian administration chronicles with different atmospheric and production predications like area production, precipitation, rainfall, minimal temperature, intermediate temperature, maximal temperature, evapotranspiration of crop and production from 2007 to 2012 of the Kharif season which is from June to November are selected. The dataset utilizing was processed usingalled the tool WEKA. Clustering is performed by using k-means cluster. Classifiers named naivebayes and bayesnet are used in this report. Proposed methodology gives better performance using bayesnet instead of naivebayes classifier for the dataset.
”I skottgluggen” (In the Crenel)

As higher education learning environments need to become increasingly flexible, podcast technology is a creative way to entwine new pedagogical methods with ICT.1&#x0D; For academic libraries a podcast, unlike textual content, can be beneficial as it keeps users in touch with library activities while doing something else.This is also perceived by students as useful, to be able to cover course content out of the classroom for example during their daily commute.2&#x0D; In 2019, the Anna Lindh library podcast ”I skottgluggen” (”In the Crenel”) was launched as a joint project between ICT educators and librarians. With a targeted audience of students studying the newly introduced higher military programme at the Swedish Defence University, the primary aim of the podcast was to increase awareness and contextualize information literacy within warstudies. A second goal was to provide a successful example for teachers interested in exploring new technology in their own practice. This PechaKucha presentation will exemplify how an academic library incorporated creativity with new technologies to stimulate flexible learning. Our synopsis is to show the planning, production and experiences of a library podcast in information literacy education.
ANALISIS DAN DESAIN SISTEM PENCATATAN DATA MANIFES KAPAL PENYEBERANGAN MENGGUNAKAN METODE PIECES DAN UML

Crossing ships  are the main transportation in several tourism areas, including on Lake Toba and become the main choice of people around Lake Toba and Samosir Island. The Manifest Data is a very important document in the process of transportation, especially airplanes and ships, including crossing ships on Lake Toba. The manifest contains data on passengers, crew members and various items transported by the mode of transportation. Manifest documents are also useful for the process of disbursing insurance for transportation accidents. Passenger Manifest data using crossing ship s on Lake Toba currently only records the number of passengers and the number of vehicles boarding the ship, but does not record details of the identity of the passenger and vehicle. The application of recording passenger manifest data is needed to manage the manifest data of crossing ship passengers on Lake Toba, with the aim of facilitating monitoring of crossing activities and the process of identifying passenger crossing ships. This research will conduct an analysis and design of the crossing vessel Manifest Passenger Manifest recording system in Lake Toba. The system is made web-based, so it will be easily accessed anywhere, and can only be accessed by the North Sumatra Transportation Office. This application can be used to make it easier for the parties involved in supervising and controlling the list of boat passengers who travel on Lake Toba, so that it can reduce the risk of accidents and misuse of the number of boat loads from the permit
Deep Learning Guided Undersampling Mask Design for MR Image Reconstruction.

Magnetic resonance imaging (MRI) is mainly limited by long scanning time and vulnerable to human tissue motion artifacts, in 3D clinical scenarios. Thus, k-space undersampling is used to accelerate the acquisition of MRI while leading to visually poor MR images. Recently, some studies 1) use effective undersampling patterns, or 2) design deep neural networks to improve the quality of resulting images. However, they are considered as two separate optimization strategies. In this paper, we propose a cross-domain network for MR image reconstruction, in a retrospective data-driven manner, under limited sampling rates. Our method can simultaneously obtain the optimal undersampling pattern (in k-space) and the reconstruction model, which are customized to the type of training data, by using an end-to-end learning strategy. We propose a 2D probabilistic undersampling layer, to obtain the optimal undersampling pattern and its probability distribution in a differentiable way. We propose a 2D inverse Fourier transform layer, which connects the Fourier domain and the image domain during the forward pass and the backpropagation. In addition, by training 3D fully-sampled k-space data and MR images with the traditional Euclidean loss, we discover the universal relationship between the probability distribution of the optimal undersampling pattern and its corresponding sampling rate. Experiments show that the quantitative and qualitative results of recovered MR images by our 2D probabilistic undersampling pattern obviously outperform those of several existing sampling strategies.
THE IDEOLOGY OF TRUMP ON HIS SPEECH ABOUT JERUSALEM: FAIRCLOUGH'S MODELS OF CDA

This research investigates the ideology of Trump on his speech about Jerusalem. This research was aimed to analyze illocutionary acts and the ideology of Trump.. This research used qualitative approach. The design of this research is Critical Discourse Analysis (CDA). This research used Fairclough’s three models of CDA, those are textual analysis, discursive practice and social practice The result that showed that there are five types of illocutionary acts expressed, those are representatives, directives, commissives, expressives and declaratives. Representatives was mostly expressed by Trump. Therefore, the result showed that Trump expressed all types of illocutionary act. The ideology on the speech about Jerusalem showed that Trump intended to use his power to create peace in Jerusalem.
Research Sources & Guides: Remote Access to Library Resources and Services: Library Resources

The majority of the Stanford GSB Library's resources and services are available to current Stanford faculty, students, and staff online from any location.