Reviewerly/exHarmony huggingface dataset:
ENCAPSULATION OF IMAGE METADATA FOR EASE OF RETRIEVAL AND MOBILITY

Increasing proliferation of images due to multimedia capabilities of hand-held devices has resulted in loss of source information resulting from inherent mobility. These images are cumbersome to search out once stored away from their original source because they drop their descriptive data. This work, developed a model to encapsulate descriptive metadata into the Exif section of image header for effective retrieval and mobility. The resulting metadata used for retrieval purposes was mobile, searchable and non-obstructive.
A Study on Literature Obsolescence in Agricultural Biotechnology

Obsolescence or decline stage of research may encourage towards further research to overcome gaps or a development of new knowledge. This study aims to investigate growth and obsolescence of literature in agricultural biotechnology. 3064 references of 21 research publications from “Emerging Technologies and Management of Crop Stress Tolerance Vol. 1” for the period of 2011–2015 have been taken as a sample to know the obsolescence and growth rate in the field of agriculture biotechnology with the application of Brooke’s formula to calculate Annual Aging Factor (AAF) and Utility Factor (UF) through synchronous method. Web of Science (WOS) citation database used as a tool to collect sample data which was analysed and plotted on semi logarithmic graph. This study resulted that more number of citations (79% of total) have been published in last 15 years, which interprets that latest publications have more chances to be cited as compared to older publications. On the bases of analysed data, half-life was observed as 14.5 years, Annual Aging Factor (AAF) as 0.986 and Utility Factor (UF) as 71.42. Obsolescence study helps for taking decision of subscription or renewal of subjective journals as well as future prospects for particular research area and its popularity among researchers. Core values and principle theories are less affected with age and latest researches get more benefited because of open accessibility and easy availability. Keywords: Growth of literature, obsolescence of literature, half-life, Annual Aging Factor (AAF), agricultural biotechnology, Utility Factor (UF) Cite this Article Shukla Svetal H, Lalitha Poluru. A Study on Literature Obsolescence in Agricultural Biotechnology. Journal of Advancements in Library Sciences . 2019; 6(2): 9–15p.
Intraoperative Ultrasound-based Augmented Reality Guidance

This paper presents an ultrasound-based augmented reality framework for minimally invasive surgery. We achieved high accuracy in each calibration step. The frame-work was evaluated by localizing a hidden target in a soft tissue phantom.
Implementation of HOG algorithm on eye controlled wheelchair using Python language

The eye-controlled wheelchair is a flexible device for persons with restrained or severe locomotor disabilities, ameliorating movement further for the aged. There are numerous interfaces for wheelchair obtainable within the market, but still, they continue to be under-utilized because they require the presence of mind, ability, and power to control them. The proposed model is an alternative that tries to form the lives of those individuals easy by helping them move around as they wish and not a burden on others. An individual littered with paralysis will move his eyes and may tilt his head partially. Thus, A wheelchair that is totally controlled with eye movements and blinks has been designed in which python software is used & processing of eyeball movement is done which employs the Histogram of Oriented Gradients (HOG) algorithm. The Arduino drives the motor driver circuit. The motors connected to the wheelchair support differential steering that avoids clumsy motion. The wheelchair has been supplied with a joystick to make sure safe movement just in case of tired vision and with a security stop button, which is able to prevent the wheelchair movement at his own case.
Two deep learning classifiers for human expression with emoji replacement

Author(s): Fang, Jingyi | Advisor(s): Wu, Yingnian | Abstract: Machine learning and deep learning techniques currently are leveraged by various practi- tioners in computer vision field. This thesis proposes an application of two different machine learning models to classify facial expressions of human and replace them with emojis accord- ingly.The first model is based on fisher-face algorithm which is used for face recognition, the second one is a simplified version of prevalent Convolution Neural Network model utilized by many researchers: VGGNet network. The former model is implemented on OpenCV library, whereas convolutional neural network is builded with help of Keras. I trained both models by an open source dataset (JAFFE) which divides its facial expression images into seven classes. Both models are tested with randomly selected images of facial expression from internet.
ANALISA DAN PERANCANGAN LAYANAN JASA SETTING ATAU EDITTING DAN DIGITAL PRINTING BERBASIS WEB STUDI KASUS : CV. KARYA CIPTA MANDIRI

This research was conducted to develop an information system in the form of a web-based application on CV. Karya Cipta Mandiri in analyzing and designing service requests for setting or editing and digital printing services, because all this time it only displays information about the company and all the processes are done manually, so customers often find it difficult to order. The purpose of this study is to help or facilitate digital printing CV.Karya Cipta Mandiri in developing requests for setting or editing and digital printing services to customers, so that the company is able to get new customers and utilize customer information that is useful for increasing transaction value and maintaining customer loyalty. This research was developed through a method of collecting data in the form of observation, interviews and literature. Data were analyzed using the PIECES framework (Performance Information Economic Control Efficiency Service). While the methodology used by the author in developing the system is the Waterfall method. While the analysis and design of the application is described using the UML (Unifed Modeling Language) method. This method was chosen because it can make a complete and precise design of the application implementation. It is expected that the relationship between the company and the customer can be established well, which in turn brings benefits to the company and so this system can help all parts in the ordering service
ESTIMASI DAYA BEBAN LISTRIK PADA GARDU INDUK CENGKARENG DENGAN MENGGUNAKAN METODE TIME SERIES MODEL DEKOMPOSISI

In this research, Cengkareng substation serves the burden which in every year is increasing. So in this study a system of estimating the load power at the substation was made as a result of forecasting for the following year using the Time Series Decomposition model method which was then analyzed from the existing transformer capacity. The Time Series Decomposition model method is a method of combining Trend, Seasonal and Cycle to predict the electrical load power of a substation. In this study, the development of the system uses the CRISP-DM method so that the work becomes more ordered and the testing is done with MAD, MSE and MAPE to verify the error value in the forecasting results. From this study, it produces an error value of MAD and MAPE of 9.11%. These results, prove that the Time Series Decomposition model method can be used to assist in estimating the Power Load in Cengkareng Substation.
The Use of List-Group-Label (LGL) Strategy in Teaching Vocabulary (A Pre-Experimental Research to the second semester Students of Islamic Education Department of Teacher Training and Education Faculty of IAIN Pontianak in the Academic Year of 2017/2018)

The aim of this research was to find out the effectiveness of List-Group-Label (LGL) strategy in teaching vocabulary and how significant the effect of List-Group-Label (LGL) strategy was in teaching vocabulary to the second semester Students of Islamic Education Department of Teacher Training and Education Faculty of IAIN Pontianak in the Academic Year of 2017/2018.The research design employs a pre-experimental research in form of one group Pretest- Posttest design and had no control group. The population of this research was all of the second semester Students of Islamic Education Department of Teacher Training and Education Faculty of IAIN Pontianak in the Academic Year of 2017/2018 consisted of 317 students and the chosen sample was class B. The sample was taken by apllying Cluster random sampling technique. The research was conducted at IAIN Pontianak.The technique of data collection in this research was measurement. The data were collected with essay test. The pre-test and post-test were distributed in order to get the data from the students. The data were analyzed by using t test. The result revealed that List-Group-Label (LGL) strategy was effective on students’ vocabulary mastery because the mean score in pretest and posttest were different and the difference were considered significant. The effect size calculation revealed that List-Group-Label (LGL) strategy gave strong effect to the students’ vocabulary mastery. It could be inferred that List-Group-Label (LGL) strategy was significantly effective in teaching vocabulary to the second semester Students of Islamic Education Department of Teacher Training and Education Faculty of IAIN Pontianak in the Academic Year of 2017/2018 and the treatments gave strong effect to the students in learning vocabulary. List-Group-Label (LGL) strategy can be implemented in teaching vocabulary in order to improve students’ vocabulary mastery.
SENPAI: Supporting Exploratory Text Analysis through Semantic & Syntactic Pattern Inspection

Analyzing language for social computing tasks requires looking beyond individual words. For example, the word “please” generally signals politeness, but more so together with modal verbs (“could you please...”) than without (“please do this.”). Combining semantics and syntax into rich textual patterns is essential to capturing these nuances. What are the relevant patterns for a task, and how to find them? NLP practitioners choose patterns informed by theory, and find them through computational models. However, few tools allow identifying rich patterns without NLP expertise. We introduce SENPAI, a novel tool that discovers combined semantic and syntactic patterns. SENPAI fuses neural embeddings, dependency parsing, and graph mining to surface patterns directly from data. We apply SENPAI to measure credibility, politeness, and sentiment in text. Quantitatively, models powered by SENPAI perform similarly to theoretically-motivated ones. Qualitatively, SENPAI discovers patterns that are interpretable and meaningful. SENPAI enables building computational models without NLP expertise and discovering new linguistic constructs.
Deformable Models and Image Segmentation

This chapter focuses on deformable-model based segmentation, due to the many advances it has made in the field of medical imaging analysis, the ease of integrating its concepts in any framework, and the high efficiency it provides in convergence to solutions. It provides an overview of the advances in image segmentation using deformable models, which have been extensively used in literature for image segmentation. The chapter presents a variety of energy functions and numerical schemes to solve their associated partial differential equations. It reviews the parametric deformable models in literature and the geometric deformable models that were designed to overcome the limitations of the classical parametric representation. The chapter explores basics of the level sets method and some of its important concepts and numerical schemes for solving the level sets equation. It discusses some of the popular guiding forces in literature, such as the Chan-Vese model that is widely applied in image segmentation techniques, along with some improvements of it.
The Use of Video in Teaching Speaking

The research problem of this study that does the use of video in teaching speaking improve students’ speaking skill at the VIII 4 Graders of SMPN 1 Peukan Bada Aceh Besar. The objective study is to find out the use of video in teaching speaking improve students’ speaking skill at the VIII 4 Graders of SMPN 1 Peukan Bada Aceh Besar. It is focused on the use of video to improve students’ speaking ability, especially on vocabulary at the VIII 4 Graders of SMPN 1 Peukan Bada. The method used was descriptive quantitative research. The population was the second year students of SMPN 1 Peukan Bada Aceh Besar. The sample was 19 students of class VIII 4 by using purposive sampling. The data was pre-test and post-test. Based on the calculation of the data, it can be seen that there was significant difference between the result of pre test and post test. The mean of pre-test result was 67 and the post-test result was 76,47. In this case, the result of test indicated that the achievement of students in post test is higher than that of pre test. It means video can improve students’ speaking ability, especially at the VIII 4 Graders of SMPN 1 Peukan Bada Aceh Besar.
Research Guides: Past FUAM Exhibition-A French Affair: Featured Artists

All patrons are welcome to visit the DiMenna-Nyselius Library to view the library resources on this guide. Only Fairfield University students, faculty and staff are able to view some of the links & resources remotely by authenticating with a current NetID
Distributed Gaussian Granular Neural Networks Ensemble for Prediction Intervals Construction

To overcome the weakness of generic neural networks (NNs) ensemble for prediction intervals (PIs) construction, a novel Map-Reduce framework-based distributed NN ensemble consisting of several local Gaussian granular NN (GGNNs) is proposed in this study. Each local network is weighted according to its contribution to the ensemble model. The weighted coefficient is estimated by evaluating the performance of the constructed PIs from each local network. A new evaluation principle is reported with the consideration of the predicting indices. To estimate the modelling uncertainty and the data noise simultaneously, the Gaussian granular is introduced to the numeric NNs. The constructed PIs can then be calculated by the variance of output distribution of each local NN, i.e., the summation of the model uncertainty variance and the data noise variance. To verify the effectiveness of the proposed model, a series of prediction experiments, including two classical time series with additive noise and two industrial time series, are carried out here. The results indicate that the proposed distributed GGNNs ensemble exhibits a good performance for PIs construction.
SISTEM REKOMENDASI TEMPAT WISATA PADA INDUSTRY PARIWISATA DENGAN MENGGUNAKAN PRINCIPAL COMPONENT ANALYSIS

The creative economy and the tourism sector are two things that are mutually influential and can work together if managed properly (Ooi, 2006). The concept of tourism activities can be defined by three factors, namely there must be something to see, something to do, and something to buy (Yoeti, 1985). Something to see related to attractions in tourist destinations, something to do related to tourist activities in tourist areas, while something to buy is associated with special souvenirs purchased in tourist areas as personal memorabilia  tourists. When you want to introduce and travel in the Depok area, tourists will always be influenced by their emotions and feelings. Therefore, tourist attractions must consider this. One important aspect is introduction. Tourist attractions must now have many sales tasks ranging from attracting tourists, introducing facilities to attracting tourists. But tourist attractions in the Depok area are still very unpopular. In this research, the Principal Component Analysis method will be applied to identify the tourist's desire for tourist attractions to be visited as well as the use of information systems to help researcher determine what tourist attractions are in accordance with the wishes of tourists. The results of the research produced 5 of the most popular tourist attractions based on questionnaires and words that represented feelings when traveling. Based on the calculation of the linear regression equation, get the criteria for tourist attractions in accordance with the wishes of tourists
A Framework for Evaluating Extensibility in an Aspect-oriented Software System and its Validation

Background: Modern day software applications involve management and processing of huge amount of data, originating from a variety of sources such as Internet of Things. Such data may be dynamic, homogenous or heterogeneous. Such data is processed by the users according to their own specific needs through programming code. The coding tool should be such that it is extensible and appropriate to manage such data. The aspect-oriented approach of programming can be a good option to handle such data for extracting useful and timely information. Aspect-oriented approach can contribute positively in extending the software design and code dynamically. Objective: The aim of the research is to provide a formal framework for evaluating the extensibility of the software. Methods: In order to design a framework for extensibility, a maintainability model is used. By applying the maintainability model, a novel framework for evaluating the extensibility characteristic is exhibited. The proposed framework is tested for a set of aspect-based software. Also, validation of the proposed extensibility metric is done by applying Karl Pearson Product Moment Correlation method. Finally, a comparison is made between software built using object-oriented approach and aspect-oriented approach. Results: Results suggest that novel framework for extensibility is a valid framework. Further, the findings reveal a strong positive relation between the selected attributes and extensibility. Also, after comparison it was found that, software built using aspect-oriented approach is more extensible than the one built using object-oriented approach. Conclusion: The experimental results show that the level of sub-attributes can contribute effectively to determine the level of extensibility, with design size being the top contributor, followed by complexity, coupling and cohesion. And the proposed framework is found to help software developers in selecting software that can be easily extensible.
PND55 SOCIETAL BURDEN OF MULTIPLE SCLEROSIS IN THE BRAZILIAN SOCIAL SECURITY SYSTEM

Multiple sclerosis is a chronic inflammatory disease of the central nervous system that affects young adults. It represents a major burden for patients as it is debilitating and impairs the quality of life. The objective of this study is to evaluate the impact of the work absence and early retirement in the Brazilian Social Security System. A literature review on the societal burden of multiple sclerosis in Brazil and worldwide was performed. Data was obtained from the Brazilian Social Security Aeps Infologo System. The analyses included the amount and total value of the benefits granted for disability (permanent) and sickness (temporary) by the Brazilian Social Security System, filtered by International Classification of Diseases of benefits, ICD G35 “Multiple Sclerosis”, between 2008 and 2017. Nine studies were found in the following countries: Italy, Netherlands, Sweden, Spain, Austria, Switzerland, Germany, United Kingdom and Brazil. From 2008 to 2017, total 8,664 benefits were granted for multiple sclerosis. Annually, the median number of monthly benefits granted was 864 and ranged between 680 and 1019. In 2017, median 81 benefits were granted monthly. Total 2,937 early retirements due to multiple sclerosis were registered from 2008 to 2016. Multiple sclerosis represented a significant burden to the Brazilian Social Security System due to short-term absence, long-term sick leave and early retirement benefits constantly granted to patients over a 9-year period.
Investigating Whether Clean Code Helps Developers in Understanding a New Project

When developers enter a project, often a vast amount of existing code exists for them to understand. Improving the understandability of the code should help them in getting up to speed. This study researches two methods that could improve the understandability of the code for newcomers: Refactoring the code to adhere to Clean Code guidelines and providing an introductory document. The effect is measured by performing a controlled experiment in which the participants are given small tasks to complete. The results show an increase in productivity for the participants working in the refactored code, and no effect for the participants who had received the introductory document. This suggests that refactoring the code can be used to aid new developers in projects.
Getting on board with REF requirements: games for early career researchers

A growing number of card and board games have been developed to enable early career researchers (ECRs) to engage with key concepts or elements of the research lifecycle. These games vary in complexity, the time needed to play them, and the required preparation time. However, most are free or low-cost and thus valuable for academic libraries seeking to engage with early career researchers, either to introduce or reinforce understanding of a topic, often as part of a training session. Links to a number of these research games have been collected at http://wke.lt/w/s/4dJ0w This workshop will introduce delegates to a range of physical games related to research and publishing, review these in relation to the Vitae Researcher Development Framework (RDF), and consider the potential of these games in supporting researchers in their own library setting.
Interlingua : Linking textbooks across different languages

Increasing numbers of students enrol in formal and informal courses taught in a foreign language. Studying a course from an unfamiliar university/program is difficult enough, but the difficulties multiply when the transition to new course requirements is exacerbated by the necessity to learn course material in a foreign language. This paper describes Interlingua a platform where students can study textbooks in a foreign language supported by on-demand access to relevant reading material in their mother tongue. Interlingua automatically recognises important terminology within textbooks content, extracts structural models of textbooks and links sections and subsections across textbooks in different languages covering the same academic subject. The interface and architecture of Interlingua as well as the technologies underlying the platform are described.