Miracle-dz/UniFAR-FTUs huggingface dataset:
An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity

The adaptive cubic overestimation algorithm described by Cartis, Gould and Toint (RAL-TR2007-007) is adapted to the problem of minimizing a nonlinear, possibly nonconvex, smooth objective function over a convex domain. Convergence to first-order critical points is shown under standard assumptions, but without any Lipschitz continuity requirement on the objective’s Hessian. A worst-case complexity analysis in terms of evaluations of the problem’s function and derivatives is also presented for the Lipschitz continuous case and for a variant of the resulting algorithm. This analysis extends the best known bound for general unconstrained problems to nonlinear problems with convex constraints. 1 School of Mathematics, University of Edinburgh, The King’s Buildings, Edinburgh, EH9 3JZ, Scotland, EU. Email: coralia.cartis@ed.ac. uk . 2 Computational Science and Engineering Department, Rutherford Appleton Laboratory, Chilton, Oxfordshire, OX11 0QX, England, EU. Email: nick.gould@stfc.ac. uk . Current reports available from “http://www.numerical. rl.ac. uk/reports/reports.shtml”. 3 This work was supported by the EPSRC grants EP/E053351/1 and EP/F005369/1. 4 Department of Mathematics, Facultés Universitaires ND de la Paix, 61, rue de Bruxelles, B-5000 Namur, Belgium, EU. Email : philippe.toint@fundp.ac.be . Current reports available from “http://www.fundp.ac.be/∼phtoint/pht/publications.html”. 5 This work was supported in part by the EPSRC grant EP/G038643/1 and by the European Science Foundation through the OPTPDE program. Computational Science and Engineering Department Atlas Centre Rutherford Appleton Laboratory Oxfordshire OX11 0QX February 20, 2009 Adaptive cubic regularisation for nonconvex optimization with convex constraints 1
SalGAN: visual saliency prediction with adversarial networks

Recent approaches for saliency prediction are generally trained with a loss function based on a single saliency metric. This could lead to low performance when evaluating with other saliency metrics. In this paper, we propose a novel data-driven metric based saliency prediction method, named SalGAN (Saliency GAN), trained with adversarial loss function. SalGAN consists of two networks: one predicts saliency maps from raw pixels of an input image; the other one takes the output of the ﬁrst one to discriminate whether a saliency map is a predicted one or ground truth. By trying to make the predicted saliency map indistinguishable with the ground truth, SalGAN is expected to generate saliency maps that resembles the ground truth. Our experiments show that the adversarial training allows our model to obtain state-of-the-art performances across various saliency metrics.
Incorporating rich features into Deep knowledge tracing 1

The desire to follow student learning within intelligent tutoring systems in near real time has led to the development of several models anticipating the correctness of the next item as students work through an assignment. Such models have included Performance Factors Analysis (PFA), Bayesian Knowledge Tracing (BKT), and more recently with developments in deep learning, Deep Knowledge Tracing (DKT). This DKT model, based on the use of a recurrent neural network, exhibited promising results. Thus far, however, the model has only considered the knowledge components of the problems and correctness as input, neglecting the breadth of other features collected by computer-based learning platforms. This work seeks to improve upon the DKT model by incorporating more features at the problem-level. With this higher dimensional input, an adaption to the original DKT model structure is also proposed, incorporating an auto-encoder network layer to convert the input into a low dimensional feature vector to reduce both the resource requirement and time needed to train. Experiment results show that our adapted DKT model, observing more combinations of features, can effectively improve accuracy.
HARD Track Overview in TREC 2005 High Accuracy Retrieval from Documents

TREC 2005 saw the third year of the High Accuracy Retrieval from Documents (HARD) track. The HARD track explores methods for improving the accuracy of document retrieval systems, with particular attention paid to the start of the ranked list. Although it has done so in a few different ways in the past, budget realities limited the track to “clarification forms” this year. The question investigated was whether highly focused interaction with the searcher be used to improve the accuracy of a system. Participants created “clarification forms” generated in response to a query—and leveraging any information available in the corpus—that were filled out by the searcher. Typical clarification questions might ask whether some titles seem relevant, whether some words or names are on topic, or whether a short passage of text is related.
Agile Software Development with SCRUM

From the Publisher: “Agile development methods are key to the future of flexible software systems. Scrum is one of the vangards of the new way to buy and manage software development when business conditions are changing. This book distills both the theory and practive and is essential reading for anyone who needs to cope with software in a volatile world. ” —Martin Fowler, industry consultant and CTO, ThoughtWorks “Most executives today are not happy with their organization's ability to deliver systems at reasonable cost and timeframes. Yet, if pressed, they will admit that they don't think their software developers are not competent. If it's not the engineers, then what is it that prevents fast development at reasonable cost? Scrum gives the answer to the question and the solution to the problem. ” —Alan Buffington, industry consultant, former Present, Fidelity Systems Company Arguably the most important book about managing technology and systems development efforts, this book describes building systems using the deceptively simple process, Scrum. Readers will come to understand a new approach to systems development projects that cuts through the ocmplexity and ambiguity of complex, emergent requiremetns and unstable technology to iteratively and quickly produce quality software. BENEFITS Learn how to immediately start producing software incrementally regardless of existing engineering practices or methodologies Learn how to simplify the implementation of Agile processes Learn how to simplify XP implementation through a Scrum wrapper Learn why Agile processes work and how to manage them Understand the theoretical underpinnings of Agile processes
A Comparison of File System Workloads

In this paper, we describe the collection and analysis of file system traces from a variety of different environments, including both UNIX and NT systems, clients and servers, and instructional and production systems. Our goal is to understand how modern workloads affect the ability of file systems to provide high performance to users. Because of the increasing gap between processor speed and disk latency, file system performance is largely determined by its disk behavior. Therefore we primarily focus on the disk I/O aspects of the traces. We find that more processes access files via the memory-map interface than through the read interface. However, because many processes memory-map a small set of files, these files are likely to be cached. We also find that file access has a bimodal distribution pattern: some files are written repeatedly without being read; other files are almost exclusively read. We develop a new metric for measuring file lifetime that accounts for files that are never deleted. Using this metric, we find that the average block lifetime for some workloads is significantly longer than the 30-second write delay used by many file systems. However, all workloads show lifetime locality: the same files tend to be overwritten multiple times.
FOR CLOSENESS : ADJUSTING NORMALIZED MUTUAL INFORMATION MEASURE FOR CLUSTERING COMPARISON

Normalized mutual information (NMI) is a widely used measure to compare community detection methods. Recently, however, the need of adjustment for information theory-based measures has been argued because of the so-called selection bias problem, that is, they show the tendency in choosing clustering solutions with more communities. In this article, an experimental evaluation of these measures is performed to deeply investigate the problem, and an adjustment that scales the values of these measures is proposed. Experiments on synthetic networks, for which the ground-truth division is known, highlight that scaled NMI does not present the selection bias behavior. Moreover, a comparison among some well-known community detection methods on synthetic generated networks shows a fairer behavior of scaled NMI, especially when the network topology does not present a clear community structure. The experimentation also on two real-world networks reveals that the corrected formula allows to choose, among a set, the method finding a network division that better reflects the ground-truth structure.
Convergence of stochastic gradient descent on parameterized sphere with applications to variational Monte Carlo simulation

We analyze stochastic gradient descent (SGD) type algorithms on a high-dimensional sphere which is parameterized by a neural network up to a normalization constant. We provide a new algorithm for the setting of supervised learning and show its convergence both theoretically and numerically. We also provide a proof of convergence for the unsupervised setting, which corresponds to the widely used variational Monte Carlo (VMC) method in quantum physics.
Actors: A Model of Concurrent Computation in Distributed Systems

Gul A. Agha’s Actors: A Model of Concurrent Computation in Distributed Systems (The MIT Press, Cambridge, Mass., 1987, 144 pages, $25.00, ISBN O-262 010925) is part of the MIT Press Series in Artificial Intelligence. This volume is edited by Patrick Winston, Michael Brady, and Daniel Bobrow. In the actor formalism, pioneered by Carl Hewitt (1977), one perceives abstract computational agents, called actors, that are distributed in space. Each actor has a mailbox (and a mail address) and associated with each actor is a behavior. One actor can influence the actions of another actor only by sending it a communication. An actor can send another actor a communication only when it knows the address of the second actor. An actor can (should be able to) receive more than one message simultaneously (in some sense). In case of synchronous communication in nonactor paradigms, this simultaneous communication requires the sender to wait until the recipient of the communication is ready to accept it. Once the recipient starts processing a given communication, it is blocked from accepting any other messages until after it is done with the message-all for the sake of maintaining the integrity of communications, no doubt. The actor model achieves the same effect through buffering. A recipient’s mailbox is always ready to receive messages. Furthermore, in the actor framework, there are no restrictions on freely communicating mail addresses; thus, the interconnections of the actors can be dynamically modified, and resource management is more flexibly done. Should the reader begin pondering the difference between actors and objects (as found in object-oriented programming), I would like to make a few clarifying observations. Objects
Retail Geography and Intelligent Network Planning

INTRODUCTION TRENDS IN RETAILING Introduction Demand--Side Changes Trends in Distribution and Retail Supply The Regulatory Environment Conclusion RETAIL LOCATIONS AND DISTRIBUTION CHANNELS:PAST,PRESENT AND FUTURE Introduction The High Street or Town Centre The Superstore and Hypermarket The Discount Store The Shopping Centre or Mall The Retail Warehouse and Retail Park New Retail Locations New Retail Formats and Distribution Channels The Old versus the New Conclusion SPATIAL RETAIL GROWTH STRATEGIES Introduction Organic Growth Mergers and Acquisitions Franchising Joint Ventures and Strategic Alliances Warehouse LocationConclusion SPATIAL RETAIL GROWTH STRATEGIES Introduction What is E--Commerce/Internet Retailing? Who Makes Money from the Internet? Understanding Consumer Preferences Examples of Internet Retailing in Different Sectors Geography,the Internet and E--Commerce Conclusion TERRITORY PLANNING Introduction Territory Management Balanced Workloads Ef . cient Organization Conclusion METHODS FOR SITE SELECTION Introduction An Inductive Approach to Site Selection A Deductive Approach to Site Selection Applied Location Modelling The Simplicity Spectrum SPATIAL INTERACTION MODELS FOR RETAIL SITE ASSESSMENT The Model and its Development Estimating the Small Area Demands for Products and Services The Supply Side Customer Flows and Store Revenues Providing a Decision--Support Capability The Development of a Cross Channel Management Planfor the City of Vienna for a Major Automotive Manufacturer Conclusion NETWORK REPRESENTATION PLANNING Introduction Case Study 1:Automotive Network Optimization Case Study 2:Financial Services Network Optimization Post--merger Network Optimization Retail network optimization Conclusion DIRECT MARKETING AND DISTRIBUTION CHANNEL MANAGEMENT Introduction Geodemographics Enhancement of Geodemographics Lifestyle Databases Other Micro--Modelling Strategies A Financial Services Channel Simulation Model MEASURING THE BENEFITS OF SPATIAL MODELLING Introduction Returns on Capital Operational Ef . ciency Improved Competitiveness Strategic Value Applications to Market RegulationConclusion CONCLUSION BIBLIOGRAPHY
The Cambridge Handbook of Multimedia Learning: Principles of Multimedia Learning Based on Social Cues : Personalization, Voice, and Image Principles

Abstract Social cues may prime social responses in learners that lead to deeper cognitive processing during learning and hence better test performance. The personalization principle is that people learn more deeply when the words in a multimedia presentation are in conversational style rather than formal style. This principle was supported in 10 out of 10 experimental tests, yielding a median effect size of 1.3. The voice principle is that people learn more deeply when the words in a multimedia message are spoken in a standard-accented human voice rather than in a machine voice or foreign-accented human voice. This principle was supported in four out of four experimental comparisons, with a median effect size of 0.8. The image principle is that people do not necessarily learn more deeply from a multimedia presentation when the speaker's image is on the screen rather than not on the screen. This principle was based on nine experimental tests with mixed results, yielding a median effect size of 0.2. What Are the Personalization, Voice, and Image Principles? Definitions The goal of this chapter is to examine the research evidence concerning three principles for multimedia design that are based on social cues – personalization, voice, and image principles. The personalization principle is that people learn more deeply when the words in a multimedia presentation are in conversational style rather than formal style.
Information Technology & People Examining Explorative and Exploitative Uses of Smartphones: a User Competence Perspective for Authors Examining Explorative and Exploitative Uses of Smartphones: a User Competence Perspective

(2015),"Examining explorative and exploitative uses of smartphones: a user competence perspective", Information Technology & People, Vol. 28 Iss 1 pp. (2015),"Building brand loyalty through user engagement in online brand communities in social networking sites", Information (2015),"Managing work-life boundaries with mobile technologies: An interpretive study of mobile work practices", Aurélie Leclercq-Vandelannoitte, (2015),"Managing BYOD: how do organizations incorporate user-driven IT innovations? ", If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight. com/authors for more information. Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. Abstract Purpose – The purpose of this paper is to investigate the effects of user competence on two different usage variables related to information systems (IS) infusion: explorative use and exploitative use. Design/methodology/approach – Structural equation modeling is used to construct a predictive model of user competence toward IS infusion. Individuals' responses to questions about attitude and intention to use smartphone were collected and analyzed. Findings – The results showed that all first-order factors of user competence were significantly linked to the second-order factor. User competence is then significantly related to IS infusion, both explorative use and exploitative use. Research limitations/implications – This study discusses individual usage behavior related to IS infusion usage. The authors conceptualized that exploitative use is different from explorative use. The findings in this study suggest that user competence must be included in IS usage models, especially IS infusion model. Practical implications – The results associated with exploitation are more certain and closer in time, while those associated with exploration are more variable. That is, users are likely to innovate through their smart devices related to IS infusion. Smartphone developers and the relevant service providers should decide which factors are more important along the stages of the information technology implementation process. As indicated in this study, knowledge-based user competence together with perceived …
Detection of pesticide (Cyantraniliprole) residue on grapes using hyperspectral sensing

Pesticide residues in the fruits, vegetables and agricultural commodities are harmful to humans and are becoming a health concern nowadays. Detection of pesticide residues on various commodities in an open environment is a challenging task. Hyperspectral sensing is one of the recent technologies used to detect the pesticide residues. This paper addresses the problem of detection of pesticide residues of Cyantraniliprole on grapes in open fields using multi temporal hyperspectral remote sensing data. The re ectance data of 686 samples of grapes with no, single and double dose application of Cyantraniliprole has been collected by handheld spectroradiometer (MS- 720) with a wavelength ranging from 350 nm to 1052 nm. The data collection was carried out over a large feature set of 213 spectral bands during the period of March to May 2015. This large feature set may cause model over-fitting problem as well as increase the computational time, so in order to get the most relevant features, various feature selection techniques viz Principle Component Analysis (PCA), LASSO and Elastic Net regularization have been used. Using this selected features, we evaluate the performance of various classifiers such as Artificial Neural Networks (ANN), Support Vector Machine (SVM), Random Forest (RF) and Extreme Gradient Boosting (XGBoost) to classify the grape sample with no, single or double application of Cyantraniliprole. The key finding of this paper is; most of the features selected by the LASSO varies between 350-373nm and 940-990nm consistently for all days. Experimental results also shows that, by using the relevant features selected by LASSO, SVM performs better with average prediction accuracy of 91.98 % among all classifiers, for all days.
GENERALIZED WIKI OBJECT MODEL 3 . 1 From Wiki Markup to an Object Model

The organic growth of wikis requires constant attention by contributors who are willing to patrol the wiki and improve its content structure. However, most wikis still only offer textual editing and even wikis which offer WYSIWYG editing do not assist the user in restructuring the wiki. Therefore, “gardening” a wiki is a tedious and error-prone task. One of the main obstacles to assisted restructuring of wikis is the underlying content model which prohibits automatic transformations of the content. Most wikis use either a purely textual representation of content or rely on the representational HTML format. To allow rigorous definitions of transformations we use and extend a Wiki Object Model. With the Wiki Object Model installed we present a catalog of transformations and refactorings that helps users to easily and consistently evolve the content and structure of a wiki. Furthermore we propose XSLT as language for transformation specification and provide working examples of selected transformations to demonstrate that the Wiki Object Model and the transformation framework are well designed. We believe that our contribution significantly simplifies wiki “gardening” by introducing the means of effortless restructuring of articles and groups of articles. It furthermore provides an easily extensible foundation for wiki content transformations.
TINGKAT HASIL DAN KOMPONEN HASIL SISTEM INTENSIFIKASI PADI (SRI) TANPA PUPUK ORGANIK DI DAERAH CURAH HUJAN TINGGI

Actually, the system of rice intensifications (SRI) have been encouraging the international researchers, included Indonesians, to intensively increase the yield. The system, such as regulations of planting points, numbers of seedling in each crop point, and planting time were applied here. The research was conducted in Limau Manis, aside the UNAND campus, from January to June 2005 used the varieties of Cisokan. The split plot design was applied in the research. The fertilizers were applied according to the recommended 200 kg urea, 200 kg SP-36, and 150 kg KCl. The research variables are harvest time, productive tillers, numbers of grain per panicle, grain weight, yield component, and yield. The data shows that relatively higher of monthly rainfalls and lower sunny days along the research periods have been the constrains in maximizing the crop production. Simply, the SRI application in the region was significantly useful due to the higher of both crop yield and yield component.
T-FINDER: A highly sensitive, pan-HLA platform for functional T cell receptor and ligand discovery

Effective, unbiased, high-throughput methods to functionally identify both class II and class I HLA-presented T cell epitopes and their cognate T cell receptors (TCRs) are essential for and prerequisite to diagnostic and therapeutic applications, yet remain underdeveloped. Addressing this bottleneck, we established T-FINDER (T cell Functional Identification and (Neo)-antigen Discovery of Epitopes and Receptors), a platform that rapidly deconvolutes CD4 and CD8 TCR reactivities to targets physiologically processed and presented by an individual’s unmanipulated, complete HLA haplotype. By using a highly sensitive TCR signaling reporter capable of detecting even low-affinity TCR:ligand interactions, T-FINDER not only robustly identifies unknown peptide:HLA ligands from complex antigen libraries, but also rapidly screens and functionally validates the specificity of complex TCR libraries against known or predicted targets. To demonstrate its pan-HLA presentation capacity, we apply the platform to multiple TCR-based applications, including glioma, celiac disease, and rheumatoid arthritis, providing unique biological insights and showcasing T-FINDER’s potency and versatility.