Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study on the Performance of CT-APRIORI and CT-PRO Algorithms usingCompressed Structures for Pattern Mining

Many algorithms have been proposed to improve the performance of mining frequent patterns from transaction databases. Pattern growth algorithms like FP-Growth based on the FP-tree are more efficient than candidate generation and test algorithms. In this paper, we propose a new data structure named Compressed FP-Tree (CFP-Tree) and an algorithm named CT-PRO that performs better than the current algorithms including FP-Growth and Apriori. The number of nodes in a CFP-Tree can be up to 50% less than in the corresponding FP-Tree. CT-PRO is empirically compared with FP-Growth and Apriori. CT-PRO is also extended for mining very large databases and its scalability evaluated experimentally. All these results point CT-PRO as the right candidate for generating a compact version of the original transaction database, which is small in size and which performs frequent pattern mining in a fast and efficient manner
Interacting with Text:The Role of Dialogue in Learning to Read and Write

English language teachers in China are expressing growing interest in the model of language provided by systemic functional linguistics and genre theory. This paper offers further insights into the methods developed in this framework,for teaching reading and writing in school and academic contexts. These methods involve carefully planned interactions between teachers and students,that enable all students in a class to successfully practise skills in academic reading and writing. The paper outlines the models of language and language learning that underpin the methods,and illustrates the kinds of classroom interactions used for writing and reading. It concludes with a discussion of the implications of these methods for language teaching in China.
Sampling Function of Degree 2 for DVD-Audio

Authors have been studying Fluency Information Theory that generalizes Shannon’s sampling theorem and its applications. Among the practical application of the research, the Fluency DAC that is developed as the Digital-to-analog converter for CD audio could have received objective valuation including receipt Golden Sound Award in 1988. In recent, DVD-Audio that deal with maximum sampling rate of 192 kHz has appeared. Due to the introduction of DVD audio that requires four times the sampling rate of nowadays CD audio, the request for developing a new Fluency DAC for DVD audio was initiated. From such requirements, the research for developing the Fluency DAC for DVD-Audio has been started. The result of the research could revive awards in local contest in Japan audio apparatus at 2000 and 2001. As the initial report on our project in developing the Fluency DAC that is capable of dealing with a maximum sampling rate of 192kHz, in this paper we aimed to derive the sampling function that acts as the impulse response for such a D/A converter.
Implementation of Anomaly Based Network Intrusion Detection by Using Q-learning Technique

Network Intrusion detection System (NIDS) is an intrusion detection system that tries to discover malicious activity such as service attacks, port scans or even attempts to break into computers by monitoring network traffic. Data mining techniques make it possible to search large amounts of data for characteristic rules and patterns. If applied to network monitoring data recorded on a host or in a network, they can be used to detect intrusions, attacks or anomalies. We proposed “machine learning method”, cascading Principal Component Analysis (PCA) and the Q-learning methods to classifying anomalous and normal activities in a computer network. This paper investigates the use of PCA to reduce high dimensional data and to improve the predictive performance. On the reduced data, representing a density region of normal or anomaly instances, Q-learning strategies are applied for the creation of agents that can adapt to unknown, complex environments. We attempted to create an agent that would learn to explore an environment and collect the malicious within it. We obtained interesting results where agents were able to re-adapt their learning quickly to the new traffic and network information as compare to the other machine learning method such as supervised learning and unsupervised learning. Keywords: Intrusion, Anomaly Detection, Data Mining, KDD Cup’99, PCA, Q-learning.
Research on Sequence Query Processing Techniques over Data Streams

Due to the great progress of computer technology and mature development of network, more and more data are generated and distributed through the network, which is called data streams. During the last couple of years, a number of researchers have paid their attention to data stream management, which is different from the conventional database management. At present, the new type of data management system, called data stream management system (DSMS), has become one of the most popular research areas in data engineering field. Lots of research projects have made great progress in this area. Since the current DSMS does not support queries on sequence data, this project will study the issues related to two types of data. First, we will focus on the content filtering on single-attribute streams, such as sensor data. Second, we will focus on multi-attribute streams, such as video films. We will discuss the related issues such as how to build an efficient index for all queries of different streams and the corresponding query processing mechanisms.
Adaptive view synthesis for aliasing artifact reduction

In recent years, the scan speed of computed tomography (CT) has increased significantly. Not long ago, the state-of-the- art CT was only capable of completing a single scan in 1.0 s per gantry rotation. Nowadays, 0.5 s per revolution is nearly an industry standard. Faster scan speeds demand faster sampling of the projections to combat aliasing artifacts, and higher x-ray tube output to ensure sufficient x-ray photon flux delivered to the scan. These demands often exceed the technological capability of these components. In this paper we performed a detailed analysis on the characteristics of the view aliasing artifact. Based on our analysis and clinical observations, we propose an adaptive view synthesis (AVS) scheme that effectively reduces the demands on the data acquisition system. Detailed performance comparison between the full view sampling and the adaptive view synthesis are performed through computer simulations and phantom experiments. Our analysis indicates that AVS is adequate for routine clinical applications.
On LISP: Advanced Techniques for Common LISP

1. The Extensible Language. 2. Functions. 3. Functional Programming. 4. Utility Functions. 5. Returning Functions. 6. Functions as Representation. 7. Macros. 8. When to Use Macros. 9. Variable Capture. 10. Other Macro Pitfalls. 11. Classic Macros. 12. Generalized Variables. 13. Computation at Compile-Time. 14. Anaphoric Macros. 15. Macros Returning Functions. 16. Macro-Defining Macros. 17. Read Macros. 18. Destructuring. 19. A Query Compiler. 20. Continuations. 21. Multiple Processes. 22. Nondeterminism. 23. Parsing with ATNs. 24. Prolog. 25. Object-Oriented Lisp. Appendix: Packages. Notes. Index.
Towards semi-supervised learning of semantic spatial concepts for mobile robots

The ability of building robust semantic space representations of environments is crucial for the development of truly autonomous robots. This task, inherently connected with cognition, is traditionally achieved by training the robot with a supervised learning phase. We argue that the design of robust and autonomous systems would greatly benefit from adopting a semi-supervised online learning approach. Indeed, the support of open-ended, lifelong learning is fundamental in order to cope with the dazzling variability of the real world, and online learning provides precisely this kind of ability. Here we focus on the robot place recognition problem, and we present an online place classification algorithm that is able to detect gap in its own knowledge based on a confidence measure. For every incoming new image frame, the method is able to decide if (a) it is a known room with a familiar appearance, (b) it is a known room with a challenging appearance, or (c) it is a new, unknown room. Experiments on ImageCLEF database and a subset of the challenging COLD database show the promise of our approach.
Reinforcement Learning: A Tutorial.

Abstract : The purpose of this tutorial is to provide an introduction to reinforcement learning (RL) at a level easily understood by students and researchers in a wide range of disciplines. The intent is not to present a rigorous mathematical discussion that requires a great deal of effort on the part of the reader, but rather to present a conceptual framework that might serve as an introduction to a more rigorous study of RL. The fundamental principles and techniques used to solve RL problems are presented. The most popular RL algorithms are presented. Section (1) presents an overview of RL and provides a simple example to develop intuition of the underlying dynamic programming mechanism. In Section (2) the parts of a reinforcement learning problem are discussed. These include the environment, reinforcement function, and value function. Section (3) gives a description of the most widely used reinforcement learning algorithms. These include TD(lambda) and both the residual and direct forms of value iteration, Q-learning, and advantage learning. In Section (4) some of the ancillary issues of RL are briefly discussed, such as choosing an exploration strategy and a discount factor. The conclusion is given in Section (5). Finally, Section (6) is a glossary of commonly used terms followed by references and bibliography.
Efficient localization methods for wireless sensor networks based on received signal strength = Metodos de localizacion eficiente para redes de sensores basados en la medida de la potencia de señal recibida

The localization of the nodes in ad hoc and sensor networks has an enormous value and utility in the context of Ambient Intelligence, since it enables a great number of applications in which the position of the nodes that collect the measurements is needed to correctly interpret the gathered information and act accordingly. Some of these applications could be emergency management, traffic monitoring, precision agriculture, domotic control, in-hospital patient and equipment monitoring, etc. Furthermore, disregarding the specific application for which the network is deployed, knowing the position of the nodes enables the development of algorithms that leverage this information to optimize some functional aspects of the network (such as routing or in-network data compression), reducing the energy consumption during communications. It is well known that energy is a scarce resource in wireless devices, since they are powered by batteries with limited life-time. For this reason, it is very important to manage the energy consumption in an efficient way, as this will impact directly on the autonomy of the nodes and, therefore, of the network. The great number of studies that deal with the topic of energy efficiency from different points of view (hardware optimization, routing optimization, etc.) is an indicative of the significance of this issue for ad hoc and sensor networks. However, little work has focused on studying the energy consumption during the process of localizing the nodes of the network. The localization of the nodes in a wireless network embraces two different steps. First, the nodes exchange a series of messages and perform measurements of some parameters of the radio signals that receive from their neighboring nodes, such as the Time of Arrival or the Received Signal Strength. Then, these measurements are processed in order to calculate the position of the nodes. Clearly, there is some energy consumption during the localization of the nodes, given that the nodes must communicate and perform some processing operations. Therefore, it is essential to perform the localization in an efficient way, that is, consuming a small amount of energy, so that the life of the network can be as long as possible. This thesis contributes to this idea of energy-efficient localization by conceiving, designing, developing and evaluating new localization strategies and algorithms for ad hoc and sensor networks that are efficient regarding the energy consumption and capable of
Modeling Discourse Topic: Sequential Relations and Strategies in Expository Text

Introduction BRINGING THE TOPIC UP: FACETS OF TOPIC Thematics: The State of the Art Topic as a Discrete Element Topic as a Structuring Frame The Need for a Model Topic as a Sequential Structure Summary TRACING THE TOPIC: SEQUENTIAL RELATIONS AND STRATEGIES The Problem of Topic as a Sequential Structure Strategies of Sequentiality Sequential Techniques in Expository Text The Signals of Topic Structure Summary MODELING SEQUENTIAL TOPIC The Patterning of Topic Structure Framing the Analysis Topic Structure Heuristics The Hierarchy and Synergy of Signals Text Boundaries THE TOPIC MODEL IN ACTION Texts in English English and Greek Texts in Contrast THE TOPIC MODEL IN PERSPECTIVE: TOWARD A MULTIPLANE DESCRIPTION OF DISCOURSE Text Organization and Sequential Relations The Interaction of Topic Structure with Other Text Relations The Multifunctionality of Topic Signals The Contribution of Topic Structure to Text Organization and Coherence ROUNDING THE TOPIC OFF: CONCLUSIONS The Modeling of Discourse Topic Connections and Implications Sequential Relations and Beyond Appendices Bibliography Index
G-Language Genome Analysis Environment Version 2

G-language Project of Institute for Advanced Biosciences aims to introduce higher efficiency in genome analysis by: 1. Constructing an integrated environment for the development of analysis software. 2. Systematically accumulating existing analysis software, methodologies for analysis and their results. 3. Constructing generic analysis packages that allow users to avoid redundancy in the process of analysis. We are currently developing G-language Genome Analysis Environment (G-language GAE)[1] version 2 which will be publicly released in Q2 of 2004. G-language GAE version 2 aims to provide a more flexible and sophisticated workbench for different layers of life sciences, including genome, transcriptome, proteome, metabolome, and systeome. Software download is available at http://www. g-language.org/.
DESCRIPTION OF THE MIKE2 ALGORITHM FOR PRESENTATION MINING

This paper describes a keyphrase extraction algorithm in Presentation Mining called MiKe 2 . The algorithm extracts keyphrases and keywords from a collection of presentation slides to be generated into a visual knowledge display looks like a mind map. MiKe 2 takes a statistical approach by combining the n-grams frequency count and weight from the C-Value approach . The algorithm is hoped to improve performance in Presentation Mining by automatically generating a high quality mind map that could improve teaching and learning in general.
2D and 3D-superimposition of cardiac SPECT and coronarography data

This contribution deals with the diagnostic aid for cardiovascular diseases using a simultaneous exploitation of Nuclear Medicine Imaging and X-ray Cine Angiography. The aim of this work is to superimpose the myocardial perfusion images on the coronarography ones as well as to reconstruct the coronary tree and set it on the perfusion volume. The final objective is to present in a synthetic way the information provided by both modalities. This data superimposition makes the diagnosis easier since the conjoint analysis of both modalities leads to a better visualization and understanding of the relationship between the stenosis on coronary arteries and their consequences on perfusion. Furthermore, these methods use standard modalities without strong constraints, and do not need any calibration procedure. That makes this solution easy and flexible to distribute. This paper presents a segmentation method of myocardial boundaries with deformable models, a registration of both modalities and a 3D-reconstruction technique of coronary vessels based on homologous points.
Stepping-stone Network Attack Kit (SNEAK) For Evading Timing-based Detection Methods Under The Cloak Of Constant Rate Multimedia Streams

STEPPING-STONE NETWORK ATTACK KIT (SNEAK) FOR EVADING TIMING-BASED DETECTION METHODS UNDER THE CLOAK OF CONSTANT RATE MULTIMEDIA STREAMS Jaideep D. Padhye, M.S. The University of Texas at Arlington, 2008 Supervising Professor: Matthew Wright With the advent of the Internet, network-based security threats have been constantly on the rise. The source of an attack could be traced by studying the system logs and the source IP address of the attack can be used to identify and prosecute the attacker. To avoid getting traced and to mislead the forensic investigators, attackers usually compromise weaker nodes on less secure networks and use them as stepping stones to attack the victim. This technique makes it difficult for the investigators to trace the real source of attack. Hence, it is important to research the stepping stone detection techniques so that the attackers can be apprehended. An interesting approach towards detecting stepping stones is to correlate incoming and outgoing streams at the stepping stone. A popular way of achieving this is to watermark packet streams as it is effective against a wide range of evasion techniques. Previous investigators have described a promising technique by which an attacker could effectively evade any timing-based detection technique, includ-
Performance Analysis of Digital Transmission Systems

If you want to get Performance Analysis of Digital Transmission Systems pdf eBook copy write by good author William Turin, you can download the book copy here. The Performance Analysis of Digital Transmission Systems we think have quite excellent writing style that make it easy to comprehend. Data transmission, digital transmission, or digital communications is the physical transfer of data (a digital bit stream) over a point-to-point or point-to-multipoint communication channel. Examples of such channels are copper wires, optical fibres, wireless communication channels, and storage . This book describes mathematical methods for analyzing digital transmission system performance. In contrast with publications that use an idealistic model of channels with independent errors, this book shows how to evaluate performance characteristics of information transmission systems in real .
Rent a Car in Just 0, 60, 240 or 1,217 Seconds? - Comparative Usability Measurement, CUE-8

This paper reports on the approach and results of CUE-8, the eighth in a series of Comparative Usability Evaluation studies. Fifteen experienced professional usability teams simultaneously and independently measured a baseline for the usability of the car rental website Budget.com. The CUE-8 study documented a wide difference in measurement approaches. Teams that used similar approaches often reached similar results. This paper discusses a number of common pitfalls in usability measurements. This paper also points out a number of fundamental problems in unmoderated measurement studies, which were used by 6 of the 15 participating teams.
The roles and values of personal knowledge management

Purpose – This paper aims to describe the roles and values of personal knowledge management (PKM). It seeks to investigate the roles of PKM in the KM process cycle and assess the values for improving the competences of both individuals and organizations.Design/methodology/approach – A research model was developed based on a critical review of KM and the PKM literature, followed by a survey of the KM participants in KM associations/interest groups/societies. The results and conclusions were made based on the quantitative analysis approach.Findings – The results indicate that PKM is playing important roles in the KM process and both individuals and organizations are benefitting by PKM in improving their competences. The roles of PKM are positively correlated to the values of PKM for individuals and organizations. It is also found that the values of PKM for individuals are correlated to the values of PKM for the organization.Research limitations/implications – This study is intended as a starting point for e.
Measuring the performance of geosimulation models by map comparison

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Implementation of an interactive visualization tool for analyzing dynamic hierarchies

Many real world examples can be found that deal with hierarchical data. Software systems typically consist of packages, directories, subdirectories, files, classes, and functions. Phylogenetic trees structure biological species into a hierarchical organization. Visualizing such static hierarchical data has been in focus of Information Visualization for many years. Visually encoding and understanding of evolving hierarchies still remains a challenging task. Since hierarchies may grow huge and may evolve over a long time producing many time steps, we make use of a side-by-side and aligned representation of Indented Pixel Tree Plots. To achieve a mental map preserving overview-based diagram we show the dynamics of a hierarchy by a static representation and illustrate the changes between subsequent hierarchies by special links. Interactive features make the data manipulable and navigable in all dimensions.
An application of H/sub /spl infin// optimization to IQ modulator digital compensation

A technique is developed to design IIR filters to compensate digitally for the imperfections caused by signal reconstruction filters in an IQ modulation system. These IIR filters are obtained by posing the problem as an unconstrained optimization problem and solving it via H/sub /spl infin// optimization, for which there is ready-made software in MATLAB. The simulation results show that this technique is simple, efficient, and leads to substantial improvement of output envelope ripples.
The Quadratic Assignment Procedure (QAP)

Some data sets contain observations corresponding to pairs of entities (people, companies, countries, etc.). Conceptually, each observation corresponds to a cell in a square matrix, where the rows and columns are labelled by the entities. For example, consider a square matrix where the rows and columns are the 50 U.S. states. Each observation would contain numbers such as the distance between the pair of states, exports from one state to the other, etc. The observations are not independent, so estimation procedures designed for independent observations will calculate incorrect standard errors. The quadratic assignment procedure (QAP), which is commonly used in social network analysis, is a resampling-based method, similar to the bootstrap, for calculating the correct standard errors. This talk explains the QAP algorithm and describes the -qap- command, with syntax similar to -bstrap- command, which implements the quadratic assignment procedure and allows running any estimation command using QAP samples.