Miracle-dz/UniFAR-FTUs huggingface dataset:
Reinforcement learning for ART-based fuzzy adaptive learning control networks

This paper proposes a reinforcement fuzzy adaptive learning control network (RFALCON) for solving various reinforcement learning problems. The proposed RFALCON is constructed by integrating two fuzzy adaptive learning control networks (FALCON), each of which is a connectionist model with a feedforward multilayered network developed for the realization of a fuzzy logic controller. An online structure/parameter learning algorithm, called RFALCON-ART, is proposed for constructing the RFALCON dynamically. The proposed RFALCON also preserves the advantages of the original FALCON, such as the ability to do online partition the input/output spaces, tune membership functions, and find proper fuzzy logic rules. In its initial form, there is no membership function, fuzzy partition, and fuzzy logic rule. They are created and begin to grow as the first reinforcement signal arrives. The users thus need not give it any a priori knowledge or even any initial information on these. <<ETX>>
A Review on Text Sanitization

is essential for all purpose of activities such as research, business decision making, etc. In this internet technology age there is no scarcity of information also. But if the information reveals the identity of a person or if it discloses confidential matters, then such information is a serious threat to privacy. So before publishing or sharing documents, the sensitive information should be removed or masked. This is the major goal of Text sanitization. Several semi-automatic and automatic methods are used for identifying sensitive information and thereby sanitizing the document by removing such terms. This broadens the users using the document due to their lowered classification level and also privacy is preserved.
Current Experimental, Bioinformatic and Statistical Methods used in NMR Based Metabolomics

The aim of this contribution is to familiarize the reader with experimental, bioinformatic and statistical strategies currently used in the field of solution NMR based metabolomics. Special emphasis is given to methods that have worked well in our hands. Methods covered include sample preparation, acquisition and processing of NMR spectra, and identification and quantification of metabolites. Further consideration is given to data normalization and scaling, unsupervised and supervised statistical data analysis, the biomedical interpretation of results, and the centralized community-wide storage and retrieval of NMR data.
Knowledge Discovery by Combination of Indexes for Signal Detection for Economic Time Series Data

There are many types of Evolutionary Algorithm. Genetic Programming has the rich expression of the solution for a lot of problems, and Genetic Algorithm is good for the tuning of parameters for the array. However, when we apply each of them to the extraction of investment rule, it needs a lot of searching for useful solution in the ﬁeld of foreign exchange. So we introduce the diversiﬁed investment using multiple solutions, and even if the searching is not good, we can decrease the risk with the diversiﬁed investment. In the numerical example, we compare the proposed hybrid algorithm of Genetic Programming including Genetic Algorithm with the island model in the layer of Genetic Programming which are diﬀerent 3 tournament sizes without migration. It is shown our model has higher performance to economic time series data rather than others. Furthermore, it can be shown that our model can detect signal by the combination of indexes as the knowledge discovery.
Fraud Detection: Using Data Analysis Techniques to Detect Fraud

A new approach being used for fraud prevention and detection involves the examination of patterns in the actual data. The rationale is that unexpected patterns can be symptoms of possible fraud. A simple example of the application of this technique is the search for duplicate transactions, such as the same invoice number-vendor number: Ordinarily, one would expect that invoice number-vendor number combinations, would be unique. Therefore, the existence of transactions with the same invoice number-vendor number combinations would be an unexpected pattern in the data. The identification of possible duplicate transactions would be a possible symptom of fraud that should be examined. However, fraud symptoms are only that – symptoms-and care should be taken to properly investigate the transactions before jumping to conclusions. Transactions that look like duplicates may simply be progress payments or equal billing of monthly charges. It is possible to search for duplicates on one or more key fields. Even Amounts Another digital analysis technique is to identify even dollar amounts, numbers that have been rounded up, such as $200.00 or $5,000.00. The existence of even amounts may be a symptom of possible fraud and should be examined. The MOD() function in ACL can easily identify these types of even numbers. For example: MOD(Amount,100) = 0 will identify transactions that are a multiple of 100, Travel expenses had always be a concern for the auditors as controls were a weak. Employees had a maximum per diem rate when traveling, but had to submit actual receipts to cover the expenses. Maximums were also established for meals: Breakfast $10.00, Lunch $20.00 and Dinner $30.00 and for Hotel $100.00. The auditors used the MOD() function to identify transactions that were multiples of $10.00 or multiples of $100.00. These transactions were compared to the manual receipts to ensure that the amounts expensed were appropriate.
Solving a Five-linked Robotic Manipulator CNC Problem Using Direct Collocation with Nonlinear Programming

Computer numerical control (CNC) and robotic welding have long been applied to industrial manufacturing in production lines. This paper introduces optimal control to layout the maneuvering sequence for a five-linked manipulator arm. Two- point boundary-value problem (TPBVP) is inevitable in most of the dynamic optimal control problem. Direct collocation with Nonlinear Programming (DCNLP) converts a TPBVP into a nonlinear programming problem. DCNLP has been extensively applied in solving the space and aircraft control problems but is not much adopted in solving robotic optimization problems. The paper requires a manipulator to weld up two cylinders which are intersecting and perpendicular to each other. A least energy maneuvering sequence is expected.
motion synthesis by combining motion models and PIK

This paper explores the issue of interactive low-dimensional human motion synthesis. We compare the performances of two motion models, i.e. Principal Components Analysis (PCA) or Probabilistic PCA (PPCA), for solving a constrained optimization problem within a low-dimensional latent space. We use PCA or PPCA as a first step of preprocessing to reduce the dimensionality of the database to make it tractable, and to encapsulate only the essential aspects of a specific motion pattern. Interactive user control is provided by formulating a low-dimensional optimization framework that uses a Prioritized Inverse Kinematics (PIK) strategy. The key insight of PIK is that the user can adjust a motion by adding constraints with different priorities. We demonstrate the robustness of our approach by synthesizing various styles of golf swing. This movement is challenging in the sense that it is highly coordinated and requires a great precision while moving with high speeds. Hence, any artifact is clearly noticeable in the solution movement. We simultaneously show results comparing local and global motion models regarding synthesis realism and performance. Finally, the quality of the synthesized animations is assessed by comparing our results against a per-frame PIK technique. Copyright © 2007 John Wiley & Sons, Ltd.
Path-based timing optimization by buffer insertion with accurate delay model

With progress in VLSI sub-micron technology, interconnect delay has become a dominant factor in chip timing, and interconnect optimization has become a critical step in the high performance design of VLSI. In this paper, an algorithm of path-based timing optimization by buffer insertion is presented. The algorithm adopts a high order model to estimate interconnect delay and a nonlinear delay model based on look-up table for gate delay estimation. And heuristic method of buffer insertion is presented to reduce delay. The algorithm is tested by industrial circuit case. Experimental results show that our algorithm can optimize the timing of circuit efficiently and the timing constraint is satisfied.
The Designing of Data Acquisition Card through PIC18F4550 and an Interface Study

Since automatic control is used in every field, there is almost no industrial application system which doesn’t employ the sensors. It makes correctly reading the data obtained from sensors in the system with sensors and transmitting this data into the computer more important. In this executed study, a design for an interface which can be easily used with a low cost data processing card and with flexible structure was performed. In the executed system, the PIC18F4550 microcontroller was used and data can be accurately read from 10 different channels. The data read from the designed data acquisition card was transferred into a computer interface program prepared in C# program using a USB and recorded into the database in the Microsoft Access program. The designed interface, the values of read signals and their graphs may be displayed on the screen. Thus, the interface screen may be used as both an indicator and oscilloscope screen.
Collective Intelligence: An Agent-Based Approach to Programmatic Organization in Architecture

Architectural programming is the research and decision-making process that identifies the scope of work to be designed. Programming is difficult because it involves identifying, collecting, analyzing and updating information from different sources such as engineers, clients, users, consultants, and others. In this paper I propose a computational model for programming and describe its implementation, a tool called PENA that allows a programming expert to represent different processes and people involved in a project using intelligent agents. By delegating responsibility to agents, a programming expert can better organize and manage project data as well as find creative solutions to conflicting issues through agent negotiation. As a proof-of-concept, I show how an agent, called the Arch-Learner, manages adjacencies of rooms in a simple program for a house by clustering them into public and private rooms. I conclude with a discussion of future work and development of PENA.
Android malware detection through permission and package

Malicious Android applications are a seriously problem due to the large share of the Android operating system market and also the flexibility of Android. An application should be checked before installing to a phone to avoid the privacy information leak. This paper proposes a static android malware detection method by using not only the permission but also the package of an Android application. The experimental results show the proposed method can detect the malicious software effectively. It suggests that the information provided by the package is useful for detection.
It's All Academic: Google Scholar, Scirus, and Windows Live Academic Search

SUMMARY In April 2006 and again in November 2006, Google Scholar, Scirus, and Windows Live Academic Search were searched for a set of 39 citations found in databases covering science, computer science, electrical engineering, and physics, along with the British Library OPAC and WorldCAT. The functionality and coverage of each engine are compared. Changes in results and functionality between April and November 2006 are also noted. Google Scholar retrieved the most citations, followed by Scirus, and then by Microsoft's engine. Libraries should link to these engines and enable OpenURL and other link resolving systems to ease retrieval for their users.
A Procedure For Correcting Readings InChemiluminescence Nitrogen Oxide AnalyzersDue To The Effect Of Sample Pressure

The influence of sample pressure on chemiluminescence nitrogen oxides analyzers is studied in this paper. Although both of the employed analyzers comply with the requirements established in the standard EN 14211:2005 for this performance feature, it is advisable to make corrections to ensure a better quality of the data. The proposed procedure reduced to ± 1.5% the mistakes caused by the effect of sample pressure.
Ubiquitous map-image access through wireless overlay networks

With the availability of various wireless link-layer technologies, such as Bluetooth, WLAN and GPRS, in one wireless device, ubiquitous communications can be realized through managing vertical handoff in the environment of wireless overlay networks. In this paper, we propose a vertical handoff management system based on mobile IPv6, which can automatically manage the multiple network interfaces on the mobile device, and make decisions on network interface selection according to the current situation. Moreover, we apply our proposed vertical handoff management with JPEG-2000 codec to the wireless application of map image access. The developed system is able to provide seamless communications, as well as fast retrieve any interested map region with any block size, in different resolutions and different color representations directly from the compressed bitstream.
Statistical Analysis of Forming Processes as a First Step in a Process-Chain Analysis: Novel PRO-CHAIN Components

This paper presents a new approach for statistical analysis of process chains, including a parameter sensitivity analysis of each process step as a basis for dimension reduction, and an efficient interpolatory metamodel in order to predict new designs. A Monte Carlo alike evaluation of this metamodel results in the requested statistical information, e.g. quantiles of the output functionals. Numerical results are presented for the forming process of a ZStE340 metal blank of a B-pillar. Additionally, a brief overview of results of the process chain forming to crash is given.
Functional programming for loosely-coupled multiprocessors

From the Publisher: Recent progress in VLSI provides massive parallelism but general purpose parallel computers remain elusive due to limited communications performance. This book proposes a new high level approach to programming that addresses the pragmatic issue of how a computation is distributed across a machine. The book's approach is based on functional programming and has significant advantages over existing comparable approaches, extending the domain of functional programming to include computer architectures in which communication costs are not negligible. It looks at how high-level functional programming languages can be used to specify, reason about, and implement parallel programs for a variety of multiprocessor systems, but in particular a class of loosely coupled multiprocessors whose operation can be described by a process network In these networks the nodes correspond to processes and the arcs to communications channels. A simple language called Caliban is described in which the functional program text is augmented with a declarative description of how processes are partitioned and mapped onto a network of processing elements. The notation gains expressive power by allowing these annotations to be generated by predicates defined in the functional language. Thus, common communications structures have simple and concise definitions as "network forming operators. " The main objective of these annotations is to provide an abstract description of the process network specified by the program so that an efficient mapping of processes to processors can be carried out by the compiler. Paul H. J. Kelly is Research Assistant in the Department of Computing at ImperialCollege, London Functional Programming for LooselyCoupled Multiprocessors is included in the series Research Monographs in Parallel and Distributed Computing, copublished with Pitman Publishing.
How similar do songs sound? Towards modeling human perception of musical similarity

Human listeners have a well-developed feeling for identifying "whether two songs sound similar" or whether they do not. Even though this type of judgment usually also involves a considerable amount of the listener's background knowledge, it has been demonstrated that an algorithmic model of this type of similarity can be achieved by merely evaluating the signal's low-level acoustic features. The paper describes a system for assessing subjectively sound similarity between pairs of musical items by using a number of such signal features. The system's performance is assessed by means of a subjective listening test that is based on a modification of a test methodology originally standardized for subjective sound quality evaluation. A number of interesting applications for such a technology are described.
Development support for content-based image retrieval systems

It is very hard to realize a general purpose, domain independent content-based image retrieval system. To implement a CBIR system rapidly for some specific purpose, tools that support application development are needed. The objective of this study has been to design a framework for content-based image retrieval application development. With this environment it is fast and easy to implement prototype systems and test their performance and usability. In order to speed up experiments, a compete computational chain has been implemented in such a way that rapid changes are possible. This has been realized utilizing atomic, re-usable software components. The designed framework permits the development of new CBIR systems by utilizing existing components and by building new standardized components.
An Exploration of the Literature of Instructional Technology through Citation Analysis

The field of Instructional Technology/Educational T echnology (IT) is at a crossroads with respect to how to define itself. An AECT panel (the Definitions and Terminology committee, chaired Al Januszewski) was formed in 2002 to repla ce the current definition, dating from 1994. Robert Reiser’s (1997) excellent history of formal definitions in the field shows a wide range of ideas about “what we are,” with various definitions including or excluding explicit references to specific media, systematic processes, and management as part of the core of the field.
A parallelizable load balancing algorithm

We present a parallelizable load balancing algorithm for grid-based problems that employs a give and take concept among neighboring subdomains. The algorithm is found to converge very quickly to almost perfect load balance while minimizing the surface-to-volume ratio of the domains. The algorithm can be used for problems whose volume cost grows nonlinearly with the number of elements, because it measures continuously the computational cost to be incurred for each subdomain. This is an advantage over most algorithms currently in use (e.g., recursive subdivision), which assume a linear relationship between the computational cost and the number of elements. 10 refs.
Video indexing based on image and sound

Video indexing is a major challenge for both scientific and economic reasons. Information extraction can sometimes be easier from sound channel than from image channel. We first present a multi-channel and multi-modal query interface, to query sound, image and script through 'pull' and 'push' queries. We then summarize the segmentation phase, which needs information from the image channel. Detection of critical segments is proposed. It should speed-up both automatic and manual indexing. We then present an overview of the information extraction phase. Information can be extracted from the sound channel, through speaker recognition, vocal dictation with unconstrained vocabularies, and script alignment with speech. We present experiment results for these various techniques. Speaker recognition methods were tested on the TIMIT and NTIMIT database. Vocal dictation as experimented on newspaper sentences spoken by several speakers. Script alignment was tested on part of a carton movie, 'Ivanhoe'. For good quality sound segments, error rates are low enough for use in indexing applications. Major issues are the processing of sound segments with noise or music, and performance improvement through the use of appropriate, low-cost architectures or networks of workstations.
A new error backpropagation learning algorithm for a layered neural network with nondifferentiable units

This paper proposes a new error backpropagation method (DBP) for a three-layered neural network containing a nondifferentiable binary output unit. In contrast to the conventional simple perceptron, in which the teacher signal is given only to the output layer, in the DBP method the teacher signal is also given to the middle layer so that the output error is decreased. Consequently, it is possible in the DBP method to correct the coupling weights in both the lower layer and the upper layer. This makes it easy to construct a network composed only of binary output units, which results in high-speed operation and is suitable for hardware implementation. When the DBP method is applied to linearly inseparable tasks such as XORing, the learning performance is greatly improved compared to learning by the simple perceptron, and almost the same learning performance as the conventional BP is obtained. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 90(5): 40– 49, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20318
Image search engine with selective filtering and feature-element-based classification

With the growth of Internet and storage capability in recent years, image has become a widespread information format in World Wide Web. However, it has become increasingly harder to search for images of interest, and effective image search engine for the WWW needs to be developed. We propose in this paper a selective filtering process and a novel approach for image classification based on feature element in the image search engine we developed for the WWW. First a selective filtering process is embedded in a general web crawler to filter out the meaningless images with GIF format. Two parameters that can be obtained easily are used in the filtering process. Our classification approach first extract feature elements from images instead of feature vectors. Compared with feature vectors, feature elements can better capture visual meanings of the image according to subjective perception of human beings. Different from traditional image classification method, our classification approach based on feature element doesn't calculate the distance between two vectors in the feature space, while trying to find associations between feature element and class attribute of the image. Experiments are presented to show the efficiency of the proposed approach.
Design of multishell sampling schemes with uniform coverage in diffusion MRI

In diffusion MRI, a technique known as diffusion spectrum imaging reconstructs the propagator with a discrete Fourier transform, from a Cartesian sampling of the diffusion signal. Alternatively, it is possible to directly reconstruct the orientation distribution function in q‐ball imaging, providing so‐called high angular resolution diffusion imaging. In between these two techniques, acquisitions on several spheres in q‐space offer an interesting trade‐off between the angular resolution and the radial information gathered in diffusion MRI. A careful design is central in the success of multishell acquisition and reconstruction techniques.