Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructing learning models from data : the dynamic catalog mailing problem

The catalog industry is a large and important industry in the US economy. One of the most important and challenging business decisions in the industry is to decide who should receive catalogs, due to the significant mailing cost and the low response rate. The problem is a dynamic one — when a customer is ready to purchase, s/he may order from a previous catalog if s/he does not have the most recent one. In this sense, customers’ purchasing behavior depends not only on the firm’s most recent mailing decision, but also on prior mailing decisions. From the firm’s perspective, in order to maximize its long-term profit it should make a series of optimal mailing decisions to each customer over time. Contrary to the traditional myopic catalog mailing decision process that is generally implemented in the catalog industry, we propose a model that allows firms to design optimal dynamic mailing policies using their own business data. We constructed the model from a large data set provided by a catalog mailing company. The computational results from the historical data show great potential profit improvement. This application differs from many other applications of (approximate) dynamic programming in that an underlying Markov model is not a priori available, nor can it be derived in a principled manner. Instead, it has to be estimated or “learned” from available data. The thesis furthers the discussion on issues related to constructing learning models from data. More specifically, we discuss the so called “endogeneity problem” and the effects of inaccuracy in model parameter estimation. The fact that the model parameter estimation depends on data collected according to a specific policy introduces an endogeneity problem. As a result, the derived optimal policy depends on the original policy used to collect the data. In the thesis we discuss a specific endogeneity problem, “attribution error. ” We also investigate whether online learning can solve this problem. More specifically, we discuss the existence of fixed point policies for potential on-line learning algorithms.
Sistema interactivo de búsqueda de respuestascon sugerencia de términos

This paper analyzes the user behavior in a interactive search of answers that includes mechanisms suggested terms. The analysis was performed using assessment methodologies applied in such experiments. It organized a group of 16 users, each of them should find the answer to eight questions, plus two training, only half applied the suggestion mechanism terms. The results show that the ability to add terms related to the question was highly valued by users, who considered it useful, and which were obtained more precise answers. So far we have used relations of co-occurrence of words to create a thesaurus of terms related to the question, which is displayed to the user through a floating layer, if desired, add to your question, but we are also working on techniques information extraction.
LUNAR: Lightweight Underlay Network Ad-hoc Routing

In this paper we present an new ad hoc routing system based upon simple principles regarding the routing strategy and the implementation approach. In the routing area we (re-)introduce the end-to-end principle, letting the communicating end nodes make the decisions concerning the behaviour of intermediate nodes. We adopt a routing strategy that is a mixture of on-demand and pro-active routing in order to minimize the possible down-times of communication paths. Implementation-wise we use explicit ”resolution commands” sent to neighbour nodes to provide LUNAR functionality. A freely available implementation has been produced that includes auto-configuration of IP network addresses and default gateway routing, making LUNAR a fully self-configuring ad-hoc routing solution which supports both unicast and broadcast styles of communication. In a direct comparison LUNAR matched or outperformed the available Linux implementations of AODV and OLSR.
Computer-aided nonlinear simulation at the system level

A computer-aided technique (the discrete technique) for nonlinear simulation at the system level is presented in this paper. The basis of the discrete technique is representation of the equivalent block diagram of a system or subsystem as linear filters and memoryless nonlinear elements. Linear filters are simulated in the frequency domain; nonlinear memoryless elements are simulated in the time domain; the transition from the time domain to the frequency domain and vise versa is made with the use of the fast Fourier transform. The methods of high-order polynomial synthesis, an automatic identification of nonlinear interference sources as well as detector simulation have also been discussed.
Computing near-optimal schedules

We survey a number ofresults on computing near-optimal solutions for . N'P'-hard scheduling problems. For many . N'P'-hard optimization problems there are polynomial-time approximation algorithms for finding solutions that are provably quite close to the optimum, whereas for others no such algorithm is known. We concentrate on results that state that certain performance guarantees are unlikely to be attained, in the sense that if there is such a good algorithm, then P'= N P. In particular, we survey results for multiprocessor scheduling and shop scheduling problems.
Hierarchical modulatory and intermodule optimization

Separate compilation is an important tool for coping with design complexity in large software projects. When done right it also can be used to create software libraries, thus promoting code reuse. But separate compilation comes in various flavors and has many facets: namespace management, linking, optimization, dependencies. Many programming languages identify modular units with units of compilation, while only a few extend this to permit hierarchies of language-level modules within individual compilation units. When the number of compilation units is large, then it becomes increasingly important that the mechanism of separate compilation itself can be used to control namespaces. The group model implemented in SML/NJ's compilation manager CM provides the necessary facilities to avoid unwanted interferences between unrelated parts of large programs. Compilation units are arranged into groups, and explicit export interfaces can be used to control namespaces. When there are many groups, then they can be organized into super-groups, and so on, thus forming a hierarchical modular structure. CM provides automatic dependency analysis, but automatic dependency analysis is NP-hard for general SML code. We show two simple restrictions that avoid intractability. To remove the penalties for efficiency usually incurred by modularization and separate compilation we designed an algorithm for automatic inline expansion across compilation unit boundaries that works in the presence of higher-order functions and free variables; it rearranges bindings and scopes as necessary to move non-expansive code from one module to another. We describe--and implement--the algorithm as transformations on $\lambda$-calculus. Our inliner is efficient, robust, and practical enough for everyday use in the SML/NJ compiler. It preserves separate compilation and has been integrated with CM. We briefly investigate macro systems as an alternative approach--driven by programmer directives--to achieve cross-module inlining and discuss a variety of problems that arise. We find a solution to the problem of integrating macro systems with ML-style modules that use long identifiers and show an implementation technique for reliable name resolution during linking. But we also discover that other problems continue to impede large-scale programming.
Analizar el liderazgo distribuido en entornos virtuales de formación.

We propose a coding scheme for the analysis of distributed leadership in virtual learning environments. The tool is designed for the analysis of synchronous and asynchronous textual communications. The tool is built by a process based on previous literature and the content analysis of the researchers. We obtain realibility of coding scheme through the intraclass correlation coefficient reaches a value of . 878. We conclude that the proposed coding scheme can be used for coding virtual communication through chats, forums and emails to obtain reliable results that facilitate understanding of distributed leadership in teaching and learning in virtual environments.
A novel adaptive control approach for nonlinearly parameterized systems

Nonlinearly parameterized systems are commonly encountered in control of practical systems. However, the conventional adaptive estimation and control strategies, based on the essential assumption of linear parameterization, are incapable of dealing with this class of systems. This incapability in turn becomes a bottleneck for prevalent applications of adaptive control. In literature, there have been some attempts to break through this bottleneck by investigating the characteristics of nonlinearities. However, it is still open for an implementable strategy that is powerful for nonlinearly parameterized systems as the certainty equivalence principle for linearly parameterized systems. This paper aims to contribute an attempt to this open problem by proposing a novel adaptive control approach. On the one hand, the controller is conceptually simple, and it does not explicitly rely on the expression of system nonlinearities. On the other hand, the controller is able to achieve system stability and parameter convergence. Copyright © 2013 John Wiley & Sons, Ltd.
Human factors for informatics usability

Human factors are a critical issue in informatics or information technology systems as the computer industry realizes the need to change from technology-dominated goals to the needs of computer users. The study of human factors can help to improve the usability of information systems and to help reduce the huge costs of human-computer interactions. However, information technology equipment is not easy to use. Even specialists in computing and information technology have difficulty with equipment produced by other experts. This book shows how knowledge and methods from the field of ergonomics can be used to help make information technology equipment easier to use. The principal audience is the many designers, software and hardware engineers, system design managers, management service managers, and user managers who are now becoming aware of the importance of usability. This book provides not only an introduction and overview but guidance on what they can do and how they can approach the problems of usability in informatics equipment.
Automating the Computation of Nested Abnormality Theories

Nested Abnormality Theories (NATs) were introduced by Lifschitz to use circumscription for representing knowledge. We describe a program CS (Circumscription Simpli er) for computing NATs. The main part of CS is SCAN, developed by Engel and Ohlbach for the elimination of second-order quanti ers. Our addition to SCAN is a new interface that allows us to use it to simplify NATs. CS takes a NAT as input and if it terminates, the output is a set of formulas whose conjunction is logically equivalent to the NAT we used as input. In many cases, the resulting formulas are rst-order.
Cluster Based on Demand Routing Protocol for Mobile Ad Hoc Network

Mobile adhoc network (MANET) is a collection of wireless nodes that dynamically create a wireless network among them without using any infrastructure. Nodes are free to move, independent of each other which makes routing much difficult. The routing protocols in MANET should be more dynamic so that they quickly respond to topological changes. Mobile ad hoc network is a collection of mobile nodes communicating through wireless channels without any existing network infrastructure or centralized administration. Due of the limited transmission range of wireless network, multiple "hops" are needed to exchange data across the network. In order to facilitate communication within the network, a routing protocol is used to discover routes between nodes. The primary goal of such an adhoc network routing protocol is efficient route establishment between a pair of nodes so that messages may be delivered in a timely manner. Route construction should be done with a minimum of overhead and bandwidth consumption. This paper mainly focuses on cluster-based routing on demand protocol. In this we use clustering's structure for routing protocol. Clustering is a process that divides the network into interconnected substructures, called clusters. ODRP creates routes on demand so they suffer from a route acquisition delay, although it helps reduce network traffic in general.
Time-varying network tomography: router link data

In a computer network, the traffic matrix or the origin-destination (OD) byte counts are important statistics needed for design, routing, configuration debugging, monitoring and pricing. However, they are not easily available. For a fixed routing scheme, a statistical inverse algorithm is proposed and validated to estimate the traffic matrix from the easily collectable link counts which are aggregations of the origin-destination counts.
Interaction and Nonlinear Effects in Structural Equation Modeling

Contents: Preface. E.E. Rigdon, R.E. Schumacker, W. Wothke, A Comparative Review of Interaction and Nonlinear Modeling. F.Y. Jonsson, Modeling Interaction and Nonlinear Effects: A Step-by-Step LISREL Example. M.C. Neale, Modeling Interaction and Nonlinear Effects With Mx: A General Approach. R.A. Ping, Jr., EQS and LISREL Examples Using Survey Data. P.K. Wood, D.J. Erikson, Estimating Interaction and Nonlinear Effects With SAS. K.A. Bollen, P. Paxton, Two-Stage Least Squares Estimation of Interaction Effects. F. Li, P. Harmer, Modeling Interaction Effects: A Two-Stage Least Squares Example. R.L. Tate, Effect Decomposition in Interaction and Nonlinear Models. B. Laplante, S. Sabourin, L-G. Cournoyer, J. Wright, Estimating Nonlinear Effects Using a Structured Means Intercept Approach. K. Schermelleh-Engel, A. Klein, H. Moosbrugger, Estimating Nonlinear Effects Using a Latent Moderated Structural Equations Approach. K.G. Joreskog, Interaction and Nonlinear Modeling: Issues and Approaches.
Hybrid neural network and pattern classification learning algorithms

Some key research issues in learning for feedforward networks are addressed. Some results from learning from examples are discussed, and how this relates to learning in networks is pointed out. Some limitations of algorithms and alternative strategies that involve changing network architectures or input data transformations are discussed. An example of how a self-organizing feature map can be used in conjunction with a feedforward network to achieve good results in isolated word recognition is given. <<ETX>>
Improving Position Estimation of the RFID Tag Floor Localization with Multiple Recognition Ranges

This chapter introduces the RFID tag floor localization method with multiple recognition ranges and its mathematical formulation to improve position estimation accuracy. Using the multiple recognition ranges of RFID reader, the reader can obtain more information about the distances to the tags on the tag floor. The information is used to improve the position estimation performance. At first, this chapter reviews the RFID tag floor localization methodwith single recognition range formobile robots(Park et al., 2010) and The performance measure based on the position estimation error variance for the localization method. For the second, this paper extends the mathematical formulation of the localization method and the performance measure for the case of multiple recognition ranges. This work is related to the previous work(Park et al., 2009) that used multiple powers to improve position estimation performance. However, previous work lacks analysis and mathematical formulation of general RFID tag recognition models. We extend the mathematical formulation and the analysis of the single recognition range RFID tag floor localizationmethod (Park et al., 2010) to the multiple recognition range case. Then the minimum error variance of multiple recognition range is introduced as a lower bound of position estimation error variance. Finally, it presents performance improvement of proposed localization method via the Monte-Carlo simulation and simple experiments. The analysis for the simulation and experimental results and the consideration for real application will be given. This chapter is organized as follows; This section discusses sensor systems used in the mobile robot localization. Then the advantages of the RFID systems as sensor systems for localization are discussed and the researches on the systems are reviewed. Section 2 introduces the RFID tag floor localization, its mathematical formulation and its performance index. Section 3 represents the motivation of introducing the use of multiple recognition ranges for the RFID tag floor localizationmethod, and extend themathematical formulation and the error variance for the multiple recognition range case. Section 4 conducts the Monte-Carlo simulation to show the improvement of the position estimation performance when the multiple recognition range is used. Section 5 represents experimental results that support the simulation results. In Section 6, the minimum error variance(Park et al., 2010) as a lower bound of error variance is extended to the multiple recognition range case. Section 7 gives the conclusions, discussions and tasks for the further researches. Youngsu Park, Je Won Lee, Daehyun Kim, Sang-woo Kim Electronic and Electric Engineering department, POSTECH Korea, South Improving Position Estimation of the RFID Tag Floor Localization with Multiple Recognition Ranges 10
Kinematics of human motion

This work describes how to study human body position and displacement without regard to time, velocity or acceleration. It goes on to "add" these variables in simple and complex biokinematic chains and by adding the variable of three-dimensional movement to the study of multilink chains. The book also includes the three-dimensional analysis of 26 specific human joints. While the work is advanced and assumes a knowledge of calculus and matrix algebra, the emphasis is on explaining movement concepts, not mathematical formulae. The text features 23 refreshers of the basic concepts and many practical examples. The author integrates mechanical models with biological experiments. This work is intended as an undergraduate text and as a reference for biomechanists, sports biomechanists, motor behaviour specialists, ergonomists, orthopaedic surgeons, neuroscience specialists, physical therapists and rehabilitation specialists.
Effective content drifting method on content-based network using game theory

Content distribution networks (CDNs) are well known to be able to distribute many kinds of content on the Internet, where caches and mirror servers are used to store and distribute content. In this paper, we propose novel network architecture to distribute content, called a content-based network (CBN). Each unit of content in the CBN has meta-data including keys to retrieve content If meta-data has a parameter that indicates how often the content has recently been retrieved, we can select adequate operation ("store content", "delete content", "move content", "divide content", and "merge content") considering network traffic, capacity in each node, and also the meta-data parameters. To achieve the above, we used the game theory. In this paper, two game players and gain are defined; "content group" player and "neighboring nodes group" player. Computer simulation revealed that the proposed algorithm has the capability of minimizing the number of hops to retrieve target content.
Synthesis of self-adaptive software

Embedded applications are constantly being pushed toward achieving autonomy, allowing them to function reliably in all circumstances and under extreme design constraints. Our approach to embedded systems introduces a feedback loop characterizing adaptive systems: the adaptation mechanism monitors system performance and changes the structure accordingly to optimize performance. These self-adaptive systems can be designed and implemented using model-integrated computing. To represent dynamic software architectures, the system is modeled in a generative manner. Here, the components of the architecture are prepared, but their number and connectivity patterns are not fully defined at design time. Instead, an algorithmic description and architectural parameters are provided that specify how the architecture could be generated "on-the-fly". These design-time models are then embedded in the run-time system along with generators that configure/reconfigure the system by changing certain architectural parameters.
On Diagnosis and Intervention: Helping Students with Special Needs Learn Fraction Ideas Involving Decimal Numbers.

Despite the emphasis that children should have a robust sense of number and a thorough understanding of fraction (National Mathematics Advisory Panel, 2008), many students continue to struggle with these concepts. Booker Diagnostic Assessment Framework (Booker, 2011) can inform decision about teaching that improves students' learning outcomes. Focusing on decimal numbers, this paper reports how effective use of the framework and instructional materials can help three teachers challenge their students' misconceptions with mathematics, leading to improved learning outcomes.
Short-length Low-density Parity-check Codes: Construction and Decoding Algorithms

Error control coding is an essential part of modern communications systems. LDPC codes have been demonstrated to offer performance near the fundamental limits of channels corrupted by random noise. Optimal maximum likelihood decoding of LDPC codes is too complex to be practically useful even at short block lengths and so a graph-based message passing decoder known as the belief propagation algorithm is used instead. In fact, on graphs without closed paths known as cycles the iterative message passing decoding is known to be optimal and may converge in a single iteration, although identifying the message update schedule which allows single-iteration convergence is not trivial. At finite block lengths graphs without cycles have poor minimum distance properties and perform poorly even under optimal decoding. LDPC codes with large block length have been demonstrated to offer performance close to that predicted for codes of infinite length, as the cycles present in the graph are quite long. In this thesis, LDPC codes of shorter length are considered as they offer advantages in terms of latency and complexity, at the cost of performance degradation from the increased number of short cycles in the graph. For these shorter LDPC codes, the problems considered are: First, improved construction of structured and unstructured LDPC code graphs of short length with a view to reducing the harmful effects of the cycles on error rate performance, based on knowledge of the decoding process. Structured code graphs are particularly interesting as they allow benefits in encoding and decoding complexity and speed. Secondly, the design and construction of LDPC codes for the block fading channel, a particularly challenging scenario from the point of view of error control code design. Both established and novel classes of codes for the channel are considered. Finally the decoding of LDPC codes by the belief propagation algorithm is considered, in particular the scheduling of messages passed in the iterative decoder. A knowledge-aided approach is developed based on message reliabilities and residuals to allow fast convergence and significant improvements in error rate performance.