Reviewerly/exHarmony huggingface dataset:
La constitución de una memoria terminológica: elaboración de terminologías bilingües en programas de memoria de traducción

Computer-aided translation systems (CAT) based on Translation Memories (TM) are a widely diffused technology that uses database and code-protection features to improve the quality, efficiency and consistency of the human translation process. These systems basically consist of a textual database in which each source sentence of a translation is stored together with the target sentence (this is called a translation memory “unit”). New and changed translation proposals will then be stored in the database for future use. This textual database – the kernel of the system – is combined with a terminological database (TDB), which is used by translators to store independently, terminological equivalences or translation units of particular value.In this paper the authors outline a first draft of a methodology that describes the preparation of a bilingual terminology from – and within – TM applications. The bilingual corpus produced is called the ‘terminological memory’ of the translator.
Process Implementation—The Key to Quality Documentation

The process NCR defined for its publications organizations is called the Quality Documentation Process (QDP). Initially, several senior consultants from corporate publication services worked with Edmond Weiss, an independent consultant, to establish and define the QDP. The process we developed to actively validate usability and satisfaction is a practical validation testing method that does not require specialized personnel, equipment, or facilities as some other methods do. The decisions involving manufacturing and distribution were made in the analysis subprocess and are documented in the official information products plan. Manufacturing and distribution involve multiple supplier/customer relationships and various quality checks. The phase reviews occur after four points in the process: design, implementation, validation, and production. Process implementation is not only the key to producing quality documentation, it is also a tool for use in other departmental activities, such as training new employees or acquainting people with an aspect of the job with which they are unfamiliar.
Review of (): A Bibliographical Data Bank on the Language Laboratory and Related Fields in Language Teaching Technology

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Finite Fields and their Applications

Article history: We present a study of the factorization of the polynomial X m − 1 in M2(F2)(X) and we determine the period of any reversible polynomial of this polynomial ring by using skew polynomial rings. These results are applied to the construction of the class of quasi- cyclic codes Ω(P ) introduced by Cayrel et al. Furthermore, we present a new construction of the self dual subclass.
Can Cpi Be Applied To Projects That Are Temporary And Unique?

Projects are defined as temporary and unique by the Project Management Institute Body of Knowledge (PMI BoK).Continuous Process Improvement (CPI) assumes incremental improvements over time.If a project is temporary and unique, how can we incrementally apply CPI over time?How do we develop lessons learned from a temporary project and how and when do we apply them?
Finite Mixtures of Multivariate Skew Laplace Distributions

In this paper, we propose finite mixtures of multivariate skew Laplace distributions to model both skewness and heavy-tailedness in the heterogeneous data sets. The maximum likelihood estimators for the parameters of interest are obtained by using the EM algorithm. We give a small simulation study and a real data example to illustrate the performance of the proposed mixture model.
Optimizing Data Center Redundancy

Jakob Carenmark is the head of SKANSKA's Mission Critical Center of Excellance (COE).Jakob developed this team to showcase SKANSKA's expertise in constructing Mission Critical facilities and to share best practices among various regions.Within this CEO team, Jacob leads some of the most creative and innovative minds in the data center construction industry.Mr. Carnemark has a degree in Civil Engineering from the University of Virginia, as well as 25 years of experience.
Content based video retrieval system using principal object analysis

Video retrieval is a searching problem on videos or clips based on the content of video clips which relates to the input image or video. Some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. We propose a content based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is evaluated on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show.
Occurrence of the term Library and Information Science on Facebook: A Study

Examines the occurrence of the term ‘Library and Information Science’ on the Facebook. As many as 768 groups were discovered, out of which those   being maintained properly have been identified. The nature / structures of groups were analyzed to conduct various studies.
Nonparametric, Computer Intensive Statistics: A Primer

The authors have developed a first course in statistics for engineers based on nonparametric, computer-intensive (NPCI) statistical methods.These methods do not rely on calculus or knowledge of statistical distribution theory, and as such can be taught earlier in a curriculum, are more intuitive, are less-recipe driven, and can be retained longer than traditional parametric statistics.In this paper, we provide a primer on NPCI methods.Basic NPCI concepts of bootstrapping and permutation are described.These concepts are then applied to confidence interval construction and hypothesis testing.Several examples taken from the course are worked to elucidate the methods.
Quality Control in the Construction of Water Supply and Drainage Pipeline of Municipal Engineering

Taking the water supply and drainage pipeline of municipal engineering as the research target,this article analyzes and describes how to control construction quality of water supply and drainage pipeline of municipal engineering in detail,and discusses he significant role and meaning of optimizing construction quality of water supply and drainage pipeline of municipal engineering for ensuring the security,stability,and high-efficient operation of water supply and drainage system of overall municipal engineering.
An Effective Strategy For Dynamic Mapping Of Peer Reviewers

Although much work has been done on peer review in an academic setting, virtually no work has been done on strategies for mapping reviewers.In most cases, an instructor merely collects papers, shuffles them, and passes them out to students for peer review.When peer review is electronic and asynchronous, better strategies are needed.A random mapping, arranged statically in advance, is frustrated by students who drop the course during the assignment period, or who do not submit their assignments.The result is that some students get reviewed by more reviewers than other students, and some students do not get reviewed at all.We have developed a dynamic strategy that adapts to situations like students dropping the course or not doing their assigned reviews, to ensure that all students' work is reviewed by approximately the same number of other students, and that no students are assigned to review their own work.The strategy is very similar to the Banker's Algorithm for allocating resources in a computer system.It assigns reviewers in such a way as to maximize the chance that all future mapping assignments will be able to be assigned successfully (i.e., without assigning a student to review him/herself) The strategy has been extended to second-level reviews-that is, where one student reviews another student's review, to give students an incentive to do a careful job of reviewing It has also been extended to the situation where team projects are reviewed by individual students This strategy offers great advantages for peer review of student work, and opportunity for extension to other problems like asynchronous review periods, where students themselves negotiate review deadlines.
EXPERIMENTAL EVIDENCE OF BANDGAP STRUCTURES IN THE LOWER JAW OF THE BOTTLENOSE DOLPHIN (TURSIOPS TRUNCATUS)

Previous studies using the TLM numerical modelling technique have demonstrated the potentialexistence of bandgap structures within the lower jawbone of the Atlantic Bottlenose dolphin(Tursiops truncatus). The study presented here shows experimental evidence of the existence ofthese bandgaps within a 2-D structure that mimics the prinnciple dimensions of the lower teeth andjawbone of the Bottlenose dolphin. The bandgap present is due to the tooth structure in the lowerjaw forming a periodic array of scattering elements, which results in the formation of an acousticstop band that is angular dependent.
Tree Similarity Measure-based Recommender Systems

The rapid growth of web information provides excellent opportunities for developing e-services in many applications but also caused increasingly severe information overload problems whereby users are not able to locate relevant information to exactly meet their needs efficiently by using the current Internet search functions. A personalised recommender system aims to handle this issue.A big challenge in current recommender system research is: the items and user profiles in many recommender system applications nowadays, such as the e-business and e-learning recommender systems, are so complex that they can only be described in complicated tree structures. Therefore, the item or user similarity measure, as the core technique of the recommendation approach, becomes a tree similarity measure, which existing recommender systems cannot provide. Another challenge is that in many real life situations, online recommendations to customers in selecting the most suitable products/services are often made under incomplete and uncertain information, which needs fuzzy set theory and techniques to deal with. Thus, how to use fuzzy set techniques to handle data uncertainty issues in tree-structured items or user profiles needs to be investigated.This research aims to handle these two challenges in both theoretical and practical aspects. It first defines a tree-structured data model, which can be used to model tree-structured items, user profiles and user preferences. A comprehensive similarity measure on tree-structured data considering all the information on tree structures, nodes’ concepts, weights and values is then developed, which can be used to compute the semantic similarity between tree-structured items or users, and the matching degree of items to tree-structured user requests. Based on the tree-structured data model, the tree-structured items and user requirements are modelled as item trees and user request trees respectively. An item tree and user request tree-based hybrid recommendation approach is then developed. To model users’ fuzzy tree-structured preferences, a fuzzy preference tree model is proposed. A fuzzy preference tree-based recommendation approach is then developed. Experimental results on an Australian business dataset and the Movielens dataset show that the proposed recommendation approaches have good performance and are well-suited in dealing with tree-structured data in recommender systems. By use of the proposed tree similarity measure and recommendation approaches based on that, two real world applications, a business partner recommender system, Smart BizSeeker, and an e-learning recommender system, ELRS, are designed and implemented, which demonstrate the applicability and effectiveness of the proposed approaches.
Expectation Propagation

This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This second volume, Inference, builds on the foundational topics established in volume I to introduce students to techniques for inferring unknown variables and quantities, including Bayesian inference, Monte Carlo Markov Chain methods, maximum-likelihood estimation, hidden Markov models, Bayesian networks, and reinforcement learning. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including solutions for instructors), 180 solved examples, almost 200 figures, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference.
The Effect of Sample Composition on Inference for Random Effects Using Normal and Dirichlet Process Models

Good inference for the random effects in a linear mixed-effects model is important because of their role in decision making.For example, estimates of the random effects may be used to make decisions about the quality of medical providers such as hospitals, surgeons, etc.Standard methods assume that the random effects are normally distributed, but this may be problematic because inferences are sensitive to this assumption and to the composition of the study sample.We investigate whether using a Dirichlet process prior instead of a normal prior for the random effects is effective in reducing the dependence of inferences on the study sample.Specifically, we compare the two models, normal and Dirichlet process, emphasizing inferences for extrema.Our main finding is that using the Dirichlet process prior provides inferences that are substantially more robust to the composition of the study sample.
6 Some thoughts about the future

there hadbeenachange inemphasis inmy experimental work.When GarryBoring wrotetoMikeElliott tosupport my appointment atMinnesota, hesaid that Ihad beensheltered byfive years ofresearch fellowships. Iwasonly just beginning tosee animportant effect. Almost alltheexperimentsreported inTheBehavior ofOrganismsweredonetofollow upleads arising fromtheworkitself. Ianswered questions, clarified points, andsolved practical problemsraised bymyownresearch. Onceout ofmyshelter andincontact withother people, Iturned toother questions: atMinnesota, tohowfast ratspressed atmaximal hunger, whether maze-bright andmaze-dull ratsdiffered inextinction, whether a rat could usetokens, andwhateffect drugs had onbehavior; andatIndiana, reaction time, choice, andmatching tosample. Thesewere akindoftechnological application ofthe operant methodology. Iwasusing anexperimental analysis ofbehavior rather than furthering it.Theresults wereinteresting tomanymorepeople, butthey weredigressions. (p.343) AtHarvard, incollaboration withCharles B. Ferster, Ireturned tobasics, butschedules of reinforcement proved almost toofascinating, andwhatIshould havecalled central issues onlyoccasionally brokethrough. Recently, in abrief return tothelaboratory Ionceagain considered issues thatcamenotfromtheresearch itself butfromanapplication-to the simulation ofso-called cognitive processes. Ourresearch onProject Pigeon during the Second WorldWarwasalso atechnological application oftheoperant analysis. My colleagues andIhadtoconvince someveryskeptical engineers thataliving organism wasat least asreliable asanyother partofthemissile theywereworking on.We didnotconvince theengineers, butwe ourselves were morethansatisfied withthecontrol we achieved. Oneepisode inparticular madea great difference inlater years. We discovered theeasewithwhichwecould shapethebehavior ofapigeon simply byoperating areinforcing device withahandswitch atappropriate times. Ihadbeentalking about control formany years, butnowIbegantodosoinearnest. Witha groupofphilosophers andliterary critics Idiscussed manyoftheimplications of ascientific analysis ofhumanbehavior. Much ofWalden Twoislittle morethanarehash of those discussions. Whattheprotagonist in WaldenTwocalled abehavioral technology wasatthetimestill science fiction, butitsoon movedinto thereal world. Curiously enough, there does notseemtohavebeenacomparable interest intotal control inbasic research.
The Security in Private Cloud Computing

Cloud computing security (sometimes referred to simply as security) is an evolving sub-domain of computer security, network security, and, more broadly, information security. It refers to a broad set of policies, technologies, and controls deployed to protect data, applications, and the associated infrastructure of cloud computing. Private Cloud computing has elevated IT to newer limits by offering the market environment data storage and capacity with flexible scalable computing processing power to match elastic demand and supply, whilst reducing capital expenditure. However the opportunity cost of the successful implementation of Cloud computing is to effectively manage the security in the cloud applications. Security consciousness and concerns arise as soon as one begins to run applications beyond the designated firewall and move closer towards the public domain. The purpose of the paper is to provide an overall security perspective of Cloud computing with the aim to highlight the security concerns that should be properly addressed and managed to realize the full potential of Cloud computing. Gartner's list on cloud security issues, as well the findings from the International Data Corporation enterprise panel survey based on cloud threats, will be discussed in this paper.
Quasielastic scattering

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FACE IDENTIFICATION USING BACK-PROPAGATION ADAPTIVE MULTIWAVENET

Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a recognition rate of 97.75% in the presence of facial expression, lighting and pose variations. Results are compared with its wavelet-based counterpart where it obtained a recognition rate of 10.4%. The proposed multiwavenet demonstrated very good recognition rate in the presence of variations in facial expression, lighting and pose and outperformed its wavelet-based counterpart.
A Systematic Approach for Development and Simulation of Digital Control Algorithms using SIMULINK

A Systematic Approach for Development and Simulation of Digital Control Algorithms using SIMULINK Prof. Matthew G Feemster, U.S. Naval Academy Matthew Feemster received his Ph.D in Electrical Engineering from Clemson University in 2000. From 2000 to 2002, he was the lead Controls Engineer at WaveCrest Laboratories based in Dulles, VA. In 2002, he accepted a position at the U.S. Naval Academy where he is currently an Associate Professor. His current research interests include nonlinear/adaptive control techniques applied to marine applications.
Elliptic Curve Cryptography

Public key cryptography systems are based on sound mathematical foundations that are designed to make the problem hard for an intruder to break into the system. The major approaches that since 1976 have withstood intruder attacks, are the discrete logarithm Mr. Raja Ghosal PhD Student, Auto-ID Lab, ADELAIDE School of Electrical and Electronics Engineering, The University of Adelaide Prof. Peter H. Cole Research Director, Auto-ID Lab, ADELAIDE School of Electrical and Electronics Engineering, The University of Adelaide Contact: rghosal@eleceng.adelaide.edu.au or cole@eleceng.adelaide.edu.au. Internet: www.autoidlabs.org
A research study of relationship between strategic human resource management and employee innovation (from the employee's perspective, Islamic Azad University of Urmia)

Strategic human resource management is an approach to the formulation and implementation of human resource strategies; in such a way that it blends with the strategies of the organization and to assist it to achieve its objectives. In fact, the nature of the strategic management of human resource has a conceptual aspect and a general attitude about how to achieve fusion or combination of organization strategies and human resource strategies, long term benefits to where human resources should go and how to get there and finally the way of formulation and implementation of strategies related to human resources, also, innovation is important for many companies and organizations. Because it can provides a sustainable competitive advantage for them. Many organizations that face many problems in the competitive environment will be able to get rid of these problems. The population in this study consists of all employees and managers of Islamic Azad University of Urmia, and according to the official statistics, 213 patients were considered as the entire population of this study and according to Cochran's formula the sample size of 137 was determined and 130 questionnaires were distributed among the sample and the data from the questionnaires were analyzed using Spss 18 software and the results of the study proved a significant relationship between the intended HRM strategies to demonstrate staff innovation, therefore the research hypothesis were confirmed.
Object Video Tracking using a Pan-Tilt-Zoom System

This paper implements object video tracking system that represents object location in subsequent video frames. A closed-circuit television (CCTV) camera mounted on a rotating system is used for capturing video while the object of interest always kept at the centre of the screen. Three tracking algorithms were selected and implemented: template matching, contour matching and optical flow. Measures of their accuracy and speed were taken for comparison. The software was implemented in a personal computer with C# programming language, with the aid of EmguCV which is a wrapper for OpenCV, a famous image processing library. The system implemented for this study is able to successfully track a rigid body, discernible from the background objects with size up to 400×300 pixel for the Phase Alternate Line (PAL) system of 720×576 pixel frame size. Tracking was stable even with the existence of rotation and scaling. Some faults were observed when occlusion was present or when the target was moving with a speed faster than that of the rotation system of 30 degrees/s horizontal and 15 degrees/s vertical.