Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of artificial neural networks to the recognition of musical sounds

The aim of the presented work was to train a neural network in order to recognize a class of a chosen musical instrument. As problems related to analysis of sounds are related to human subjective perception abilities, then it seems that such tools of analyses as neural nets should be used for recognition processes. On the other hand, an artificial neural network should not be trained directly with subsequent samples of a sound, thus the feature extraction procedure is needed at first. As, there is no consensus regarding the selection of parameters for feature vector extraction, thus the experiment aimed to check whether calculated parameters are sufficient for creating a set of sound patterns used for neural network training. Some neural nets were investigated in the experiment, they were trained with so-called ELEVEN and FOURTEEN vector types. After the learning procedure was executed, other examples of the previously created database (but not seen by the neural network) were presented to neural nets. Results show that NNs (neural networks) are able to generalize information included in feature vectors. Therefore, when presenting data to NN inputs, there is no problem with variation of parameters within data, and consequently with data clustering, because a NN has the ability to generalize information during the learning phase. In the paper, an analysis of experimental results will be carried on, and conclusions derived from the performed tests will be presented.
Appareil, Image et Particule

This chapter (in French) compares the ways to access to events in science and in art. In particular, the Deotte's concept of "appareil" is discussed. To be published in Jean-Louis Deotte and Sylvestra Mariniello (ed.), Appareil et Intermedialite, L'Harmattan, 2007.
Finding Interesting Genes Using Reliability in Various Gene Expression Models

Most statistical methods for finding interesting genes are focusing on the summary values with large fold-changes or large variations. Very few methods consider the probe level data. We developed a new measure to detect reliability that incorporates the probe level data. This reliability measure is useful for exploring the microarray data without ignoring the probe level data. It is easy to calculate, and it can be used for all the other statistical methods as a good guideline to find real differentially expressed genes. Instead of filtering out genes before the analysis, we use whole genes in the analysis and make decisions with new reliability measures.
Model and application of a binaural 360/spl deg/ sound localization system

We introduce a biologically inspired sound localization system, based on an open two-microphone configuration. Its purpose is to perform a robust, 360-degree detection of objects, in particular humans, in the horizontal plane. In our approach, we consider neurophysiological findings to discuss the biological plausibility of the coding and extraction of spatial features, but also meet the demands and constraints of a practical application in the field of human-robot interaction. We process interaural time differences for the left/right detection and spectrum-based features to discriminate between, in front and behind. Tests in real environments are used to demonstrate the function and the application of the system. We briefly touch the point of handling different acoustic room characteristics and give reasons why the proposed model can show advantages over conventional correlation methods.
Objects, Abstraction, Data Structures And Design Using Java

This version of the book uses the latest Java technology, Java 2 Standard Edition Version 5.0 (J2SE V. 5.0), or otherwise known as "Version 5.0. " This revolutionary book intertwines problem solving and software engineering with the study of traditional data structures topics. The book emphasizes the use of objects and object-oriented design. Early chapters provide background coverage of software engineering. Then, in the chapters on data structures, these principles are applied. The authors encourage use of a five-step process for the solution of case studies: problem specification, analysis, design, implementation, and testing. As is done in industry, these steps are sometimes performed in an iterative fashion rather than in strict sequence. The Java Application Programming Interface (API) is used throughout the text. Wherever possible, the specification and interface for a data structure follow the Java Collections Framework. Emphasizes the use of objects and object-oriented design Provides a primer on the Java language and offers background coverage of software engineering Encourages an iterative five-step process for the solution of case studies: problem specification, analysis, design, implementation, and testing The Java Application Programming Interface (API) is used throughout
Efficient use of wireless bandwidth for multimedia applications

Two rapidly evolving and merging technologies are the Internet and wireless data communications. Another trend is the increased use of real-time multimedia applications for audio and video communication. The most popular transport protocol among these delay sensitive applications is UDP (user datagram protocol), which is a lightweight protocol that provides multiplexing among user processes and has low protocol processing overhead. UDP's checksum policy is to protect either an entire packet including UDP and IP headers or nothing in the packet at all. This conforms badly with applications that prefers errors in the payload to the loss of whole packets. Many real-time applications fall into this category. We present a new protocol, UDP Lite, that provides the kind of protection often needed by these real time applications especially when they are run over wireless networks. UDP Lite increases the flexibility of UDP by providing an optionally partial checksum. Each packet can be optionally divided into a sensitive and an insensitive part by the sender. Errors in the sensitive part will cause packets to be discarded by the UDP Lite receiver, while errors in the insensitive part are ignored by UDP Lite. We show how UDP Lite uses a wireless network more efficiently for two different scenarios. By combining UDP Lite with compressed RTP, the gain can be even higher. Simulations show that the error rate of the network can increase by almost an order of magnitude without increasing the packet loss ratio. This enables cheaper network solutions for applications such as IP telephony.
A COLOR FEATURES‐BASED METHOD FOR OBJECT TRACKING EMPLOYING A PARTICLE FILTER ALGORITHM

We proposed a method for object tracking employing a particle filter based on color feature method. A histogram‐based framework is used to describe the features. Histograms are useful because they have property that they allow changes in the object appearance while the histograms remain the same. Particle filtering is used because it is very robust for non‐linear and non‐Gaussian dynamic state estimation problems and performs well when clutter and occlusions are present on the image. Bhattacharyya distance is used to weight the samples in the particle filter by comparing each sample’s histogram with a specified target model and it makes the measurement matching and sample’s weight updating more reasonable. The method is capable to track successfully the moving object in different outdoor environment with and without initial positions information, and also, capable to track the moving object in the presence of occlusion using an appearance condition. In this paper, we propose a color features‐based method .
Recursive semi-blind equalizer for time-varying MIMO channels

This paper addresses the problem of semi-blind multi-input multi-output (MIMO) equalization of time-varying channels by employing recursive filtering methods. Based on a realistic channel model described in COST 207 project, we derive a state-space model that characterizes the behavior of the channel in time. The channel estimation and tracking are performed using a Kalman filter method, and a decision feedback equalizer derived using MMSE criterion is used to perform the equalization.
Double data rate SYNCHRONOUS DRAMs in high performance applications

Double Data Rate Synchronous DRAMs are recently introduced SDRAM type products that can offer an evolutionary change with performance advantages for all Memory Systems. These advantages are based on a synchronous I/O interface and dual edge clock based data bus with improved internal architecture that enables faster data throughput rates. Architectural differences are discussed between various memory solutions and future trends in Synchronous DRAMs. The device functionality and timing are explained as compared with single data rate SDRAMs. Performance estimations are shown for present and future DDR SDRAM products when compared with traditional commodity type DRAMs or single edge clock SDRAMs.
Agent routing algorithm in wireless sensor networks

Wireless sensor networks are a new technology of information acquisition and processing, so they are widely used in all kinds of fields. In the paper we introduce Agent technology into the wireless sensor network, conduct a in-depth research on the four routing schemes, and propose a new improved routing scheme, which considers the energy consumption of both nodes and path. Furthermore, The scheme we proposed has efficient routing function, can balance the energy consumption of nodes and extends the lifetime of the network in a more efficient way.
On Scaling Performance Operating Characteristics: Caveat Emptor

Problems associated with scaling and normalizing empirical performance operating characteristics (POCs) are examined. Normalization methods proposed by Wickens (1980) and by Mountford and North (1980) are critically evaluated. Computer simulations are used to generate raw-score and normalized POCs. The interpretation of transformed empirical POCs (Wickens, Mountford, and Schreiner, 1981) is shown 10 contain inconsistencies. The normalization techniques reviewed fail to resolve POC scaling problems. Caution must be exercised when interpreting transformed POCs.
A hierarchical combined feature and area-based stereo matching algorithm

This paper develops a novel computational framework for an accurate, robust, and efficient stereo analysis, which is a hierarchical scheme based on the combination of feature- and area-based matching, called hierarchical hybrid matching algorithm (HHM). The HHM can inherit the accuracy of the feature-based approaches, simplify the procedure of feature matching and produce robust and dense disparity fields. What is more, the HHM can reduce the dependency on the quantity and quality of the features extracted from the original images to a great degree. On the other hand, unlike existing area-based approaches the HHM can generate global disparity fields, produce more precise disparity estimates on the edge of the objects and avoid searching blindly in a wide range. Experimentations are carried out on a group of widely used stereo images.
Analysis of multiple reflection components

An algorithm is proposed for the detection and separation of specularity from Lambertian reflectance using multiple image frames from different viewpoints. The algorithm is based on the physical model of the multiple reflection mechanism in which the appearance of specularity varies depending on viewing direction while that of Lambertian reflection does not. The approach is to move camera sensors actively and to obtain as many image frames as possible. Experimental results are presented to show the efficiency of the algorithm. <<ETX>>
Application of temporal constrained predicate nets to production systems

This paper discusses the advantage of using a hybrid model to express the discrete aspects (events) as well as continuous aspects (time) of production systems. We propose an extension of the Petri Net model to take these two information types into account. Finally we use this new model to describe, to simulate and to check the properties of a production system in a simple example. The proposed model is close to the predicate transition one. However it is more general because it is not limited to finite domains. So, it allows continuous temporal properties to be explicitly defined. Moreover, we show how the constraints intervening in the behaviour modelling can be handled to demonstrate safety properties depending on time.
Understanding Scientific Reasoning

UNDERSTANDING SCIENTIFIC REASONING develops critical reasoning skills and works with students to improve their level of scientific and technological literacy. Giere teaches students how to understand and critically evaluate scientific information they encounter in popular and professional media. With its focus on science, Understanding Scientific Reasoning helps students learn how to examine scientific reports with a reasonable degree of sophistication. Giere explains how to reason through case studies using the same informal logic skills employed by scientists. Students sharpen their abilities to analyze a complex series of propositions and hypotheses in the same manner as scientists.
Rain Removal from Videos Using Curve Registration Techniques

Rain degrades the quality of outdoor videos. To recover the scene quality in images, rain steaks should be removed. A new rain removal method that can process richly textured images and recover moving objects occluded by rain without blur is proposed. This method is based on the fact that it is unlikely that two rain drops of the same size appear in the same position or neighboring positions in two consecutive frames, but the major part of scene in one frame will appear in the next frame even when there exist camera motion and object motion. Curve registration adopting dynamic time warping technique is used to distinguish the random part from the repeated part in video frames. Based on the registration result, rain pixels are detected and recovered. Experiments show the effectiveness of this rain removal method.
Ontogeny of long-term potentiation in the chronically implanted, freely-moving rat

The present study was undertaken to systematically examine the development of long-term potentiation (LTP), i.e., the ability to estabLish and maintain enhanced levels of celllar response following application of brief tetanic stimulation, of the hippocampal perforant path/dentate granule synapse in chronically implanted, behaving rats during the preweaning (15 days of age), early post-weaning (30 days of age) periods of development, and adulthood (90 days of age).
Brief Review of Software Security History with an Emphasis on Efforts Focused at Early Stages of the Software Lifecycle

The importance of software security has been profound recently. The main issue during the early efforts of the late 90s was how to counterattack the buffer overflows problem. However, emphasis has recently shifted on how to counterfeit software attacks at the design level starting with the introduction of security patterns. We have qualitatively analyzed the most important security patterns, and quantitatively evaluated software systems based on their design, using fuzzy risk analysis, based on the security patterns they contain and the STRIDE model of attacks. Additionally, we have analyzed the effectiveness of code obfuscation techniques, which we think is a starting point for future research.
Working with the ShortRead Package

> require(Genominator)> require(ShortRead)> require(yeastRNASeq)The data we will use are described in the vignette of the yeastRNASeq and was originally publishedin [1]. But to summarize, we have data from two di erent yeasts, a wild-type strain (\wt") and a mutantstrain (\mut"). Part of the RNA degradation pathway is knocked out in the mutant. For each strain wehave two lanes worth of data { it is the exact same sample and library preparation sequenced in both lanes.Only 500,000 raw reads from each lane is part of the yeastRNASeq package and they have been aligned withBowtie, keeping only unique hits with up to two mismatches. Since not all reads align, we will be workingwith a up to 500,000 reads per lane.The data is available as a list of AlignedRead class objects:> data(yeastAligned)> yeastAligned[[1]]class: AlignedReadlength: 423318 reads; width: 26 cycleschromosome: Scchr05 Scchr15 . Scchr08 Scchr13position: 541317 885627 . 488228 667296strand: - + . - +alignQuality: NumericQualityalignData varLabels: similar mismatch> sapply(yeastAligned, length)mut_1_f mut_2_f wt_1_f wt_2_f423318 420848 410349 430264In the package we also have the Bowtie output les, which we will use for illustration:> list.files(file.path(system.file(package = "yeastRNASeq"), "reads"),+ pattern = "bowtie")[1] "mut_1_f. bowtie.gz" "mut_2_f. bowtie.gz" "wt_1_f. bowtie.gz"[4] "wt_2_f. bowtie.gz"The Bowtie output les are compressed using gzip, ShortRead can handle this.Before importing a set of aligned reads using Genominator one usually has to make some decisionsregarding chromosome names as well as names of the columns in the resulting database.1
Logical unit and scene detection: a comparative survey

Logical units are semantic video segments above the shot level. Depending on the common semantics within the unit and data domain, different types of logical unit extraction algorithms have been presented in literature. Topic units are typically extracted for documentaries or news broadcasts while scenes are extracted for narrative-driven video such as feature films, sitcoms, or cartoons. Other types of logical units are extracted from home video and sports. Different algorithms in literature used for the extraction of logical units are reviewed in this paper based on the categories unit type, data domain, features used, segmentation method, and thresholds applied. A detailed comparative study is presented for the case of extracting scenes from narrative-driven video. While earlier comparative studies focused on scene segmentation methods only or on complete news-story segmentation algorithms, in this paper various visual features and segmentation methods with their thresholding mechanisms and their combination into complete scene detection algorithms are investigated. The performance of the resulting large set of algorithms is then evaluated on a set of video files including feature films, sitcoms, children's shows, a detective story, and cartoons.
Design and prototyping of a CMOS standard contactless current measurement macrocell for integrated microsystems in power control applications

The increasing complexity of integrated circuits has made microsystems integration feasible in the power control case, and system level considerations must now be taken into account. Considering this approach, this paper first presents an integrated microsystems design approach for power control systems. A top-down design methodology, detailed in previous published papers, demonstrates the large interest in developing intellectual properties or macrocells to reduce design cycles. Then, focus is applied to the design and prototyping of a contactless current measurement macrocell in standard CMOS technology. An improved sensitivity Hall plate is discussed and a final contactless current macrocell differential architecture, including two improved Hall plates and embedded electronics, is described. Experimental results on a 0.6 /spl mu/m CMOS standard technology prototype demonstrate the functionality of the silicon-proven high sensitivity current measurement Macrocell, without additional postprocessing cost.
Mathematical Theory of Neural Networks

Abstract : This report focuses on fundamental theoretical issues relevant to the capabilities, performance, and limitations of artificial neural networks. For static (feedforward) networks, subjects of investigation included the study of error surfaces for least squares fitting, VC and other learning dimensions, representability questions, and function approximation. For dynamic (recurrent) nets, covered are questions dealing with parameter identification and modeling, realizability and other systems-theoretic issues, theoretical computational capabilities, and learning-theoretic issues.
A new search algorithm based on probability in intrusion detection

Detection rate is vital to intrusion detection. We propose a new search algorithm base on probability to speed up the process rate for a novel compound intrusion detection system (CIDS). We employ an improved Bayesian decision theorem to build this compound model. The improved Bayesian decision theorem brings four profits to this model. The first is to eliminate the flaws of a narrow definition for normal patterns and intrusion patterns. The second is to extend the known intrusions patterns to novel intrusions patterns. The third is to reduce risks that detecting intrusion brings to system. The last is to offer a method to build a compound intrusion detection model that integrates misuse intrusion detection system (MIDS) and anomaly intrusion detection system (AIDS). During the experiment of this model, we find that different system calls sequences have different probabilities. So the sequences with high probabilities are compared prior to an observed sequence, which is the foundation of our new search algorithm. We evaluate the performance of the new algorithm using numerical results, and the results show this new algorithm increases the detection rate.
Term Graph Rewriting. Syntax and semantics

ion operator, 38 acyclic, 48 algebraic specification, 3 alpha conversion of cyclic terms, 44 annotated path, 47 ARS with finite information content, 105 with information content, 105 ARSI, 105 bisimilarity of terms, 92 context, 43 context restricted rewrite system, 39 continuity substitutive -, 134 syntactic -, 134 CRS rewrite rule, 38 cyclic term, 43 dag, 6 directed acyclic graph, 6 directed set, 31 disjoint union, 31 downward closed, 32 edge expansion, 58 equational logic, 73, 74 equivalent modulo garbage collection, 88 equivalent modulo scopes, 94 finite element of a CPO, 32 finite information content ARS with -, 105 first order terms, 3 flat cyclic term, 43 garbage free, 48, 88 generalized μ-calculus, 121 homeomorphic embedding, 57–59 horizontal sharing, 60 ideal, 32 completion, 32 indirection node, 49 infinitarily sound, 123 infinite normal form, 105 infinity, 31 information content ARS with -, 105 labeled translation, 48 lambda calculus with positions, 35 left-linear CRS rule, 39 letrec, 7 lower bound, 32 greatest -, 32 metaterms, 38 metavariables, 38 natural numbers, 31 plus infinity, 31 partial order, 31 complete -, 32 path
Identity-based directed proxy ring signature scheme

Abstract Proxy ring signature scheme allows a proxy signer to sign messages on behalf of the original signer while providing anonymity. In these schemes any verifier can verify the proxy signature and he can be sure that the message is indeed given out by the proxy signer group, on the other hand, nobody can figure out who the proxy signer is. If the signed message is sensitive to the signature receiver, the ordinary proxyring signature schemes seems to be not suitable. To meet this requirement, in this paper, we proposed an ID-based directed proxy ring signature scheme by combining the functionalities of directed signatures and proxy ring signature scheme. This scheme is very useful in some applications where the anonymously leaking information is sensitive to the signature receiver. We have discussed the security requirements of the proposed scheme.
An overview of logarithm-based image processing techniques for biomedical applications

Logarithm-based image processing methods are of interest since they have the capability to enhance low-contrast images. This paper presents an overview of the three logarithm-based image processing techniques: the multiplicative homomorphic system (MHS), the log-ratio (LR) and the logarithmic image processing model (LIP). They are compared from physical, computational, and application point of views.