Reviewerly/exHarmony huggingface dataset:
BATOR's Changes and input files used

1/ Since CY42 some changes have been made in BATOR : 'ficdate' file which describe timeslots is deprecated. 'refdata' files are replaced by 'batormap' ones 2/ How to write a param_bator.cfg input file (from CY43) 3/ namelist entities used as input in Bator 4/ how Bator does read OPERA radar files
Framework For A Computer Based Corrosion Course

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Session 3213 Session 3213 Framework for a Computer Based Corrosion Course M.A.A. Tullmin and P.R. Roberge Department of Chemistry and Chemical Engineering Royal Military College of Canada, Kingston, Ontario, Canada, K7K 7B4 Abstract A framework for a computer based corrosion course has been developed, with a view to distance learning applications. Potential advantages of the computer based learning approach over a conventional course offering include access to a larger target population and optimization of the shrinking expert instructor pool. However, experience has shown that, despite advances in software applications, an enormous investment in professional time in planning and developing the course material is required. This computer based corrosion course is unique, in that emphasis has been placed on quantitative material, rather than on more descriptive subject matter often found in existing corrosion education products. The course was also designed to be fundamentally interactive in nature, with the use of situational case studies and assignments, in direct contrast to some approaches of re-creating books in hypertext format. Course modules have been created initially in paper based format, to place the scientific/technical course content on a sound footing. Selected case studies and assignments have subsequently been designed in electronic format to develop skills in applying the knowledge and understanding gained from the paper based course notes. Following detailed planning, additional work is underway to present further selected material in electronic format. 1. Introduction Corrosion Science and Engineering (CSE) is an important element of chemical engineering education, at both the university student and practicing professional levels. For the purposes of this paper these two populations will simply be referred to as “the students”. While not all chemical engineering university students receive formal education in this field, most chemical engineers can be expected to have to deal with corrosion damage in technical and/or managerial capacities. At the Royal Military College of Canada (RMC), CSE is an integral part of the Chemical and Materials Engineering program in the Department of Chemistry and Chemical Engineering.
Functional Interactions Between Memory and Recognition Judgments

One issue facing agents that accumulate large bodies of knowledge is determining whether they have knowl- edge that is relevant to its current goals. Performing comprehensive searches of long-term memory in every situation can be computationally expensive and disrup- tive to task reasoning. In this paper, we demonstrate that the recognition judgment — a heuristic for whether memory structures have been previously perceived — can serve as a low-cost indicator of the existence of potentially relevant knowledge. We present an approach for computing both context-dependent and context- independent recognition judgments using processes and data shared with declarative memories. We then de- scribe an initial, efficient implementation in the Soar cognitive architecture and evaluate our system in a word sense disambiguation task, showing that it reduces the number of memory searches without degrading agent performance.
Sistema de informação especializado em transporte urbano : proposta de Base de Dados para a Associação Nacional das Empresas de Transporte Urbanos (NTU)

Research that presents a proposal for the development of a database specialized in urban transport, which references information available on the web for use by employees of the National Association of Urban Transport Companies, in order to contribute to decisions. It is based on urban transport, information systems, database and data modeling. The objective is to propose a reference database on urban transport to be adopted in the provision of informational services developed by the institution, in a case study characterized as applied, bibliographical and exploratory. It presents, as research results, an application developed through the Microsoft Access 2013 Database Management System, offering registration (reference) of materials, such as articles, videos, presentations, book chapters, newspaper articles, among others, and queries, which can be performed by searching by title, author or subject. It concludes that the librarian can act in the process of building the NTU reference database, based on a data modeling that considered attributes mirrored in the Anglo-American Cataloguing Rules (second edition), for the registration of materials, and defined the types of data in the system and the database model for prototyping, which made it possible to provide and retrieve relevant information from searches by title, author and subject, and direct users to the original and complete source.
A Natural Click Interface for AR Systems with a Single Camera

Clicking on a virtual object is the most fundamental and important interaction in augmented reality (AR). However, existing AR systems do not support natural click interfaces, because head-mounted displays with only one camera are usually adopted to realize augmented reality and it is difficult to recognize an arbitrary gesture without accurate depth information. For the ease of detection, some systems force users to make unintuitive gestures, such as pinching with the thumb and forefinger. This paper presents a new natural click interface for AR systems. Through a study investigating how users intuitively click virtual objects in AR systems, we found that the speed and acceleration of fingertips provide cues for detecting click gestures. Based on our findings, we developed a new technique for recognizing natural click gestures with a single camera by focusing on temporal differentials between adjacent frames. We further validated the effectiveness of the recognition algorithm and the usability of our new interface through experiments.
Towards Deeper Understanding

A new way of learning helped nursing students to promote better mental health and gain valuable experience.
Artificial Parts, Practical Lives

From the wooden teeth of George Washington to the Bly prosthesis, popular in the 1860s and boasting easy uniform motions of the limb, to today's lifelike approximations, prosthetic devices reveal the extent to which the evolution and design of technologies of the body are intertwined with both the practical and subjective needs of human beings. The peculiar history of prosthetic devices sheds light on the relationship between technological change and the civilizing process of modernity, and analyzes the concrete materials of prosthetics which carry with them ideologies of body, ideals, body politics, and culture. Simultaneously critiquing, historicizing, and theorizing prosthetics, Artificial Parts, Practical Lives lays out a balanced and complex picture of its subject, neither vilifying nor celebrating the merger of flesh and machine.
Rapid application development (RAD)

Rapid application development (RAD) is a system development methodology that employs joint application design, prototyping, computer aided software engineering (CASE) technology, application generators, and similar tools to expedite the design process. RAD promotes fast, efficient, accurate program and/or system development and delivery. RAD focuses on four major components: tools, people, methodology, and management. Compared to other methodologies, RAD generally improves user/designer communication, user cooperation, and user commitment, and promotes better documentation. J. Martin suggests four phases to implement RAD: requirements planning, user design, construction, and cutover. There are several variations and/or extensions to the RAD methodology. RAD is an alternative to the traditional system development life cycle. RAD is a system development methodology that employs joint application design, prototyping, CASE technology, application generators, and similar tools to expedite the design process. ASE tools are used extensively during this phase. The system design can be planned as a series of iterative steps or allowed to evolve.
Context Steering

Steering behaviors are extremely common in the games industry. Context steering behaviors are small and stateless and guarantee any desired movement constraint. Steering behaviors remains extremely useful in many situations. For games that can be represented in two dimensions, context steering offers strong movement guarantees and simple, stateless, decoupled behaviors. A single steering behavior component is asked to return a vector representing its decision, considering the state of the world. This chapter starts with two simple steering behaviors: chase, for approaching targets, and avoid, for not hitting obstacles. The context steering framework deals in the currency of context maps. Internally, the context map is an array of scalar values, with each slot of the array representing a possible heading, and the contents of the slot representing how strongly the behavior feels about this heading. The racing line behavior maps interest all across the track, with a peak around the racing line.
Access and Usage of E-Journals by Research Scholars in National Institute of Technology (NIT) Rourkela, Odisha: A Case Study

The purpose of this study is to investigate different aspects such as awareness, access and usage of e-journals among the research scholars at Biju Patnaik Central Library (BPCL) of National Institute of Technology (NIT) Rourkela, Odisha. The scope of this paper limits to: (i) E-Resources: Only e-Journal is considered among the various types of e-resources subscribed by library; (ii) Respondents: Only Research scholars are taken into consideration; and (iii) Questionnaires: 150 questionnaires collected from 700 research scholars. This paper also reveals the problems and suggests some solutions. The study shows that User Education Programmes (UEP), stable high-speed internet supply and adequate number of computers should be provided to ensure constant access that can effectively enhance the usage of e-journals.
Deadline Flow Scheduling in Datacenters with Time-Varying Bandwidth Allocations

Many production datacenters nowadays service multiple applications with dynamically allocated network bandwidth, and some applications are time-critical so their data transfers or flows are constrained by deadlines. To meet deadlines, several flow scheduling schemes for datacenter networks are proposed, but most of them are unaware of bandwidth variations, leading to suboptimal throughputs. In this paper, we present a flow scheduling scheme, called UBAS, to improve deadline-meeting throughputs for time-critical applications with uncertain time-varying bandwidth allocations. First, we model an optimization problem of scheduling deadline-constrained flows under uncertain time-varying bandwidth allocations to maximize the expected deadline-meeting throughput. The problem is NP-hard. Then, we propose an approximation algorithm under a mild condition for the problem in a special case, where bandwidth allocations are certain, as well as a conditional approximation algorithm for the problem in general. To adapt to practice, scalable and online variants of the algorithm are also presented. In evaluation, we conduct simulations based on a real traffic trace in a production datacenter. The results demonstrate that, with severe practical settings, UBAS still achieves nearly optimal deadline-meeting throughputs. Moreover, the throughput improvements of UBAS against existing bandwidth-agnostic schemes are more substantial when the variance of bandwidth allocations over time increases.
A necessary and sufficient condition for an algebraic integer to be a Salem number

We present a necessary and sufficient condition for a root greater than unity of a monic reciprocal polynomial of an even degree at least four, with integer coefficients, to be a Salem number. This condition requires that the minimal polynomial of some power of the algebraic integer has a linear coefficient that is relatively large. We also determine the probability that an arbitrary power of a Salem number, of certain small degrees, satisfies this condition.
Fuzzy Systems Are Universal Approximators for Random Dependencies: A Simplified Proof

In many real-life situations, we do not know the actual dependence $$y=f(x_1,\ldots ,x_n)$$ between the physical quantities $$x_i$$ and y, we only know expert rules describing this dependence. These rules are often described by using imprecise (“fuzzy”) words from natural language. Fuzzy techniques have been invented with the purpose to translate these rules into a precise dependence $$y=\widetilde{f}(x_1,\ldots ,x_n)$$. For deterministic dependencies $$y=f(x_1,\ldots ,x_n)$$, there are universal approximation results according to which for each continuous function on a bounded domain and for every $$\varepsilon >0$$, there exist fuzzy rules for which the resulting approximate dependence $$\widetilde{f}(x_1,\ldots ,x_n)$$ is $$\varepsilon $$-close to the original function $$f(x_1,\ldots ,x_n)$$. In practice, many dependencies are random, in the sense that for each combination of the values $$x_1,\ldots ,x_n$$, we may get different values y with different probabilities. It has been proven that fuzzy systems are universal approximators for such random dependencies as well. However, the existing proofs are very complicated and not intuitive. In this paper, we provide a simplified proof of this universal approximation property.
Face2Face: Real-time facial reenactment

Abstract This article summarizes the dissertation “Face2Face: Realtime Facial Reenactment” by Justus Thies (Eurographics Graphics Dissertation Online, 2017). It shows advances in the field of 3D reconstruction of human faces using commodity hardware. Besides the reconstruction of the facial geometry and texture, real-time face tracking is demonstrated. The developed algorithms are based on the principle of analysis-by-synthesis. To apply this principle, a mathematical model that represents a face virtually is defined. Utilizing this model to synthesize facial imagery, the model parameters are adjusted, such that the synthesized image fits the input image as good as possible. Thus, in reverse, this process transfers the input image to a virtual representation of the face. The achieved quality allows many new applications that require a good reconstruction of the face. One of these applications is the so-called “Facial Reenactment”. Our developed methods show that such an application does not need any special hardware. The generated results are nearly photo-realistic videos that show the transfer of the expressions of one person to another person. These techniques can for example be used to bring movie dubbing to a new level. Instead of adapting the audio to the video, which might also include changes of the text, the video can be post-processed to match the mouth movements of the dubber. Since the approaches that are shown in the dissertation run in real-time, one can also think of a live dubber in a video teleconferencing system that simultaneously translates the speech of a person to another language. The published videos of the projects in this dissertation led to a broad discussion in the media. On the one hand this is due to the fact that our methods are designed such that they run in real-time and on the other hand that we reduced the hardware requirements to a minimum while improving the resulting quality. In fact, after some preprocessing, we are able to edit ordinary videos from the Internet in real-time. Amongst others, we impose a different mimic to faces of prominent persons like former presidents of the United States of America. This led inevitably to a discussion about trustworthiness of video material, especially from unknown source. Most people did not expect that such manipulations are possible, neglecting existing methods that are already able to edit videos (e. g. special effects in movie productions). Thus, besides the advances in real-time face tracking, our projects raised the awareness of video manipulation.
Kidney Detection in 3-D Ultrasound Imagery via Shape-to-Volume Registration Based on Spatially Aligned Neural Network

This paper introduces a computer-aided kidney shape detection method suitable for volumetric (3D) ultrasound images. Using shape and texture priors, the proposed method automates the process of kidney detection, which is a problem of great importance in computer-assisted trauma diagnosis. This paper introduces a new complex-valued implicit shape model, which represents the multiregional structure of the kidney shape. A spatially aligned neural network classifiers with complex-valued output is designed to classify voxels into background and multiregional structure of the kidney shape. The complex values of the shape model and classification outputs are selected and incorporated in a new similarity metric, such as the shape-to-volume registration process only fits the shape model on the actual kidney shape in input ultrasound volumes. The algorithm's accuracy and sensitivity are evaluated using both simulated and actual 3-D ultrasound images, and it is compared against the performance of the state of the art. The results support the claims about accuracy and robustness of the proposed kidney detection method, and statistical analysis validates its superiority over the state of the art.
Bridging the Gap between Service Oriented Architecture and Cloud Software as a Service

Nowadays, Cloud Software as a Service (SaaS) and Service Oriented Architecture (SOA) have received increased attention as approaches to software development in distributed systems. Cloud SaaS is the most common model in cloud computing that provides software as service over internet to support the availability and scalability of services. While SOA is an architectural style that focuses on loosely coupled interaction between services to provide the reusability. In SaaS model, applications suffer from functions customization and reusability. On the other hand, SOA architecture suffers from many scalability issues. There is a need for a new model that tackle these issues. This research aims to bridge the gap between SOA and SaaS through designing a new model as an attempt to combine SOA and SaaS in one model and then leverage from SOA reusability and SaaS scalability. The proposed model has the structure of SaaS multi-tenant’s applications with modified in computing and application code structure by applying the SOA concepts. The research followed an empirical study and case study methodology. The evaluation is carried out through designing a healthcare information system based on the proposed model. According to the evaluation results, the implementation of the proposed model on healthcare information system has increased the reusability and scalability of system.
Verb Phrases Alignment Technique for English-Malayalam Parallel Corpus in Statistical Machine Translation Special issue on MTIL 2017

Abstract Machine translation (MT) from English to foreign languages is a fast developing area of research, and various techniques of translation are discussed in the literature. However, translation from English to Malayalam, a Dravidian language, is still in the rising stage, and works in this field have not flourished to a great extent, so far. The main reason of this shortcoming is the non-availability of linguistic resources and translation tools in the Malayalam language. A parallel corpus with alignment is one of such resources that are essential for a machine translator system. This paper focuses on a technique that enables automatic setting up of a verb-aligned parallel corpus by exploring the internal structure of the English and Malayalam language, which in turn facilitates the task of machine translation from English to Malayalam.
Framework of Randomized Distribution Features for Visual Representation and Categorization

This paper introduces a framework to deal with the distribution of descriptive features, which preserves the advantages of the vectorial representation and computational efficiency of histogram-based techniques, and inherits the rigorous theoretical guarantee and competitive performance of metric-based ones. The methods developed under this framework describe the underlying distribution of a set of features as a vectorial feature by utilizing random features. Moreover, the proposed methods asymptotically converge to metric-based methods in terms of the similarity and distance and, depending on a specific kernel function, reduce to histogram-based methods. The experimental results show the benefits of a comparable performance on categorization tasks compared to conventional metric-based methods at a significantly reduced computational cost.
Hybrid BATGSA: a metaheuristic model for classification of breast cancer data

Nature-inspired algorithms have a vast range of applications. One such application is in the field of medical data mining where, major focus is on building models for the classification and prediction of various diseases. Breast cancer has grabbed the interest of numerous researchers because, it is the major killer disease, killing millions of women across the globe. In this paper, we propose a hybrid diagnostic model which is a fusion of Bat algorithm (Bat), Gravitational Search Algorithm (GSA), and Feed-Forward Neural Network (FNN). Here, the potential of the FNN and the advantages of nature inspired algorithms have been exploited to build a hybrid model used for classification of breast cancer data. The proposed model consists of two modules. First, is the training module where the data is properly trained using a feed-forward neural network and the second, is an error minimising module, which is built using Bat and GSA metaheuristic algorithm. The hybrid model minimises the error thus, producing better classification results. The accuracy obtained for Wisconsin Diagnostic Breast Cancer Diagnostic (WBCD) data set is found to be 94.28% and 92.10% for training and testing respectively.