Miracle-dz/UniFAR-FTUs huggingface dataset:
Delay generation methods with reduced memory requirements

Modern diagnostic ultrasound beamformers require delay information for each sample along the image lines. In order to avoid storing large amounts of focusing data, delay generation techniques have to be used. In connection with developing a compact beamformer architecture, recursive algorithms were investigated. These included an original design and a technique developed by another research group. A piecewise-linear approximation approach was also investigated. Two imaging setups were targeted -- conventional beamforming with a sampling frequency of 40 MHz and subsample precision of 2 bits, and an oversampled beamformer that performs a sparse sample processing by reconstructing the in-phase and quadrature components of the echo signal for 512 focal points. The algorithms were synthesized for a FPGA device XCV2000E-7, for a phased array image with a depth of 15 cm. Their performance was as follows: (1) For the best parametric approach, the gate count was 2095, the maximum operation speed was 131.9 MHz, the power consumption at 40 MHz was 10.6 mW, and it requires 4 12-bit words for each image line and channel. (2) For the piecewise-linear approximation, the corresponding numbers are 1125 gates, 184.9 MHz, 7.8 mW, and 15 16-bit words.
Retrieval and organizational strategies in conceptual memory: a computer model

Abstract : People effortlessly recall past events and episodes in their lives many times in the course of a normal day. A reasonable goal in the design of computer programs is to construct a memory with that same capability. To facilitate human-like retrieval of events from a computer memory, we must first specify a reasonable memory organization. We must then design updating and retrieval processes to build up and access that information. This thesis will present such a theory, and will describe a computer program called CYRUS which implements that theory. CYRUS (Computerized Yale Retrieval and Updating System) stores and retrieves episodes in the lives of Secretaries of State Cyrus Vance and Edmund Muskie. When new events are added to its memory, CYRUS integrates them into memory along with the events it already knows about. CYRUS can then answer questions posed to it in English about the events it stores. The algorithms and memory organization used in CYRUS have been developed by examining the way people answer questions requiring extensive memory search. Its reconstructive processes include instantiation strategies, which construct and elaborate on contexts for search, and search strategies, which direct construction.
Turbo product codes and their application in the fourth-generation mobile communication system

In this paper, we firstly present turbo product codes (TPCs) for forward error correction (FEC) coding, including TPCs encoding process and decoding principle, and then compare TPCs with turbo convolutional codes (TCCs) error coding solution. The performance of TPCs is shown to be closer to the Shannon limit than TCCs. Secondly, we introduce TPCs’ application in the 4th generation (4G) mobile communication system which is being developed in our country at present. The concept of TPC-OFDM system which promises higher code rate than conventional OFDM is first modified. Finally, simulation results show that the simplified 4G uplink systems offer Bit Error Rate of nearly 0 over IMT-2000 channel at Eb/N0 > 15dB.
A Novel Web Classification Algorithm Using Fuzzy Weighted Association Rules

In associative classification method, the rules generated from association rule mining are converted into classification rules. The concept of association rule mining can be extended in web mining environment to find associations between web pages visited together by the internet users in their browsing sessions. The weighted fuzzy association rule mining techniques are capable of finding natural associations between items by considering the significance of their presence in a transaction. The significance of an item in a transaction is usually referred as the weight of an item in the transaction and finding associations between such weighted items is called fuzzy weighted association rule mining. In this paper, we are presenting a novel web classification algorithm using the principles of fuzzy association rule mining to classify the web pages into different web categories, depending on the manner in which they appear in user sessions. The results are finally represented in the form of classification rules and these rules are compared with the result generated using famous Boolean Apriori association rule mining algorithm.
A Dual Effect of Pictorial Enrichment in Learning from Television News: Gunter's data revisited

Abstract An impairing effect of TV visuals reported by Gunter in this journal in 1980 appears to be inconsistent with other recent findings, which have suggested beneficial effects of still and film visualisations on news learning. Re‐examination of Gunter's data reveals that visual enrichment of news stories influenced learning in two distinct ways. Pictures reduced the recall of concurrently presented spoken information, but at the same time enhanced the recall of information presented in ‘talking head’ lead‐ins which preceded them.
Neuro-fuzzy recognition of K-complexes in sleep EEG signals

A new pattern recognition procedure is introduced for the automatic detection of K-complexes in EEG sleep polygraphies employing fuzzy logic and neural networks. The developed detection system was implemented in C, supplying a hardware-independent solution with a very rapid recognition of the K-complexes. With the aid of the determined K-complexes and detected sleep spindles, the respective stage 2 in the sleep polygraphy can be evaluated directly from the EEG signal and visualized. This represents a significant criterion for the objective assessment of a patient's sleep quality.
NTIMIT: a phonetically balanced, continuous speech, telephone bandwidth speech database

The creation of the network TIMIT (NTIMIT) database, which is the result of transmitting the TIMIT database over the telephone network, is described. A brief description of the TIMIT database is given, including characteristics useful for speech analysis and recognition. The hardware and software required for the transmission of the database is described. The geographic distribution of the TIMIT utterances is described, followed by information regarding calibration signals used to readily determine the effect of the transmission setup and the distortions introduced by the telephone network. <<ETX>>
Parallel fine spatial resolution satellite sensor image segmentation based on an improved Pulse‐Coupled Neural Network

An improved Pulse‐Coupled Neural Network (PCNN), which has two modules with different inner processing mechanisms, was introduced and applied to segment an IKONOS image with different parameters. Results show that the improved PCNN can segment the image in a parallel and multiscale way, and the output image is easier to analyse than with the basic PCNN.
Method of lines solution of partial differential equations. [MOL1D package]

An analysis is given of effective strategies for the so-called method of lines solution of the initial boundary-value problem for partial differential equations of the form u/sub t/ = g(x,t,u,u/sub x/,u/sub xx/,f/sub x/), where f = f*x,t,u,u/sub x/,u/sub xx/). Also described is a user-oriented FORTRAN subroutine package called MOL1D for the numerical solution of equations of this type using the method of lines. 5 figures, 10 tables.
LISA: A Linguistic Information System

The prototype-part of this paper describes a system enabling computing machinery to understand a problem stated in everyday English and to solve it. A complex problem is stated purely in natural language, as if it was intended to be read by a human. The system uses linguistic knowledge of English words and the English grammar as well as semantic knowledge of the problem domain it operates in to understand it. By “understanding the problem”, we mean any kind of processing that can be applied to the natural-language problem-representation, which equips the system with the knowledge needed to actually solve it. Such an “understander” must not use any problem-specific knowledge explicitly stated by the programmer in a machine-readable form, knowledge about the problem is supposed to be inferred solely from its natural-language representation. This requires analyzing each word that appears in the input, a task known as “morphological analysis” in Natural Language Processing, which is related to that of “lexical analysis” or “lexing” in compiler-construction. It is carried out in our prototype by machine-code which is generated by a special compiler. After words are morphologically analyzed, they are translated into a structured representation that deals with the English language’s grammar. Building up such a representation is a parser’s job. Our parser is a highly performanceoptimized implementation of the algorithm suggested by Earley (1970). It uses dynamic programming to parse its input in polynomial time, regardless of ambi-
Fast Intermode Decision for Scalable Video Coding using Statistical Hypothesis Testing

In this paper, a fast intermode decision scheme is introduced by efficiently performing the mode decision using statistical hypothesis testing for hierarchical B-picture coding of SVC, in which much computational power is expensed for combined variable block sizes and hierarchical B-pictures. The hypothesis testing in the proposed method is performed on blocks to have early termination for RD computation of all possible modes. The early termination in intermode decision is performed by comparing the pixel values of current blocks and corresponding motion-compensated blocks. The proposed scheme exhibits effective early termination behavior in intermode decision and leads to a significant reduction up to 69% in computational complexity with slight increment in bit amounts. The degradation of visual quality turns out to be negligible in terms of PSNR values.
High-brightness AlGaInP light emitting diodes

First commercially introduced in 1990, AlGaInP light emitting diodes (LEDs) currently are the highest (luminous) efficiency visible solid-state emitters produced to date in the red through yellow spectral regime. The attainment of this high-efficiency performance is a result of the development of advanced metalorganic chemical vapor deposition crystal growth techniques, which have facilitated the high-quality growth of this quaternary alloy as well as the implementation of complex device designs. Furthermore, the highest efficiency family of AlGaInP devices (based upon a transparent-substrate platform and commercially introduced in 1994) have been realized as result of the development and implementation of direct compound semiconductor wafer bonding technology. As a result, the luminous efficiency of AlGaInP LEDs exceeds or rivals that of unfiltered incandescent lamps and other conventional lighting sources. Further improvements in these techniques (and the realization of efficient, high-power LEDs) are expected to make AlGaInP LEDs even more competitive with conventional lamp technology, thus enhancing the position of LED's in many applications as a preferred lighting source.
Heterogeneous distributed genetic algorithms based on the crossover operator

Making distinctions between the subpopulations of a distributed genetic by applying genetic algorithms with different configurations, we obtain the so-called heterogeneous distributed genetic algorithms. These algorithms represent a promising way for introducing a correct exploration/exploitation balance in order to avoid the premature convergence problem and improve the behavior of the search process. In this paper we present a type of heterogeneous distributed real-coded genetic algorithms that apply a different crossover operator to each subpopulation. The importance of this operator on the genetic algorithm's performance made us to differentiate between the subpopulations in this fashion. Experiments carried out with two instances of this approach show that they consistently outperform equivalent sequential genetic algorithms and homogeneous distributed genetic algorithms.
A Dynamic Programming Approach to Identifying the Shortest Path in Virtual Learning Environments

E-learning has been widely adopted as a promising solution by many organizations to offer learning-on-demand opportunities to individual employees (learners) in order to reduce training time and cost. While successful information systems models have received much attention among researchers, little research has been conducted to assess the success and/or effectiveness of e-learning systems in an organizational context. The development of information technologies has contributed to the growth in online training as an important educational method. The online training environment enables learners to undertake customized training at any time and in any place. Moreover, information technology allows both the trainers and learners to be decoupled in terms of time, place, and space. In this article, dynamic programming is applied to find the shortest path in the learning environment for users and an analytical hierarchy process approach is used to turn the qualitative parameters into quantitative ones.
Robotics-Driven Activities: Can They Improve Middle School Science Learning?

This study used case studies from three science teachers to compare three groups of students studying Grade 8 physics using Robolab instead of traditional lab materials. The three teachers represented an English as a second language class, a regular class with many English language learner students, and a Mathematics, Engineering, Science Achievement class of afterschool volunteer students. The teachers responded to nine questions regarding issues such as how robotics addresses the middle school physics standards, promotes inquiry learning and science literacy in students, increases applications and connection of science to everyday life, and provides the scaffolding for more discussion of everyday English and science academic language through the use of robotics materials and lab groups. The results indicated that robotics can promote inquiry, make physics more interesting, and help students learn and practice new words in English, among others.
Interactive Music Systems: Machine Listening and Composing

From the Publisher: This supplement to Interactive Music Systems contains audio and program examples that document a variety of systems and the music they produce. An extensive library of Macintosh software allows the user to experiment with or adapt existing interactive systems. Some parts of the library require the presence of underlying software environments, such as SrnallTalk, LISP, or Opcode's Max Language. The program discussed most extensively on interactive music systems, Robert Rowe's Cypher, will run on any Macintosh computer.
THREE TYPES OF PASSIVES FOR PSYCH-VERBS

This paper analyzes passives of psych-verbs within the framework of Conceptual Semantics in the sense of Jackendoff (1983, 1987, 1990). It is shown that there are three types of passives derived from psych-verbs: both verbal and adjectival passives followed by a by-phrase, contrary to Grimshaw's (1990) claim, and an adjectival passive with an idiosyncratic preposition like at or with. These three types of passives have different conceptual structures, with the prepositions being introduced through different adjunct rules. *
Crop type identification by integration of high-spatial resolution multispectral data with features extracted from coarse-resolution time-series vegetation index data

Crop type identification is the basis of crop acreage estimation and plays a key role in crop production prediction and food security analysis. However, the accuracy of crop type identification using remote-sensing data needs to be improved to support operational agriculture-monitoring tasks. In this paper, a new method integrating high-spatial resolution multispectral data with features extracted from coarse-resolution time-series vegetation index data is proposed to improve crop type identification accuracy in Hungary. Four crop growth features, including peak value, date of peak occurrence, average rate of green-up, and average rate for the senescence period were extracted from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) profiles and spatially enhanced to 30 m resolution using resolution merge tools based on a multiplicative method to match the spatial resolution of Landsat Thematic Mapper (TM) data. A maximum likelihood classifier (MLC) was used to classify the TM and merged images. Independent validation results indicated that the average overall classification accuracy was improved from 92.38% using TM to 94.67% using the merged images. Based on the classification results using the proposed method, acreages of two major summer crops were estimated and compared to statistical data provided by the United States Department of Agriculture (USDA). The proposed method was able to achieve highly satisfactory crop type identification results.
A /spl Sigma/-/spl Delta/ fractional-N frequency synthesizer using a wide-band integrated VCO and a fast AFC technique for GSM/GPRS/WCDMA applications

A fractional-N frequency synthesizer (FNFS) in a 0.5-/spl mu/m SiGe BiCMOS technology is implemented. In order to operate in a wide-band frequency range, a switched-capacitors bank LC tank voltage-controlled oscillator (VCO) and an adaptive frequency calibration (AFC) technique are used. The measured VCO tuning range is as wide as 600 MHz (40%) from 1.15 to 1.75 GHz with a tuning sensitivity from 5.2 to 17.5 MHz/V. A 3-bit fourth-order /spl Sigma/-/spl Delta/ modulator is used to reduce out-of-band phase noise and to meet a frequency resolution of less than 3 Hz as well as agile switching time. The experimental results show -80 dBc/Hz in-band phase noise within the loop bandwidth of 25 kHz and -129 dBc/Hz out-of-band phase noise at 400-kHz offset frequency. The fractional spurious is less than -70 dBc/Hz at 300-kHz offset frequency and the reference spur is -75 dBc/Hz. The lock time is less than 150 /spl mu/s. The proposed synthesizer consumes 19.5 mA from a single 2.8-V supply voltage and meets the requirements of GSM/GPRS/WCDMA applications.
The two-dimensional LMS algorithm and its application to sub-band filtering

Image filtering is a branch of digital image processing, where the aim is to reduce noise while maintaining the quality of the signal data. Adaptive filters offering advantages over `fixed' filters have been used but suffer some reduction of image quality. Subband adaptive filtering has previously been investigated for speech processing and has been shown to have advantages over fullband filtering. Benefits in applying subband techniques to two-dimensional (2D) filtering problems are anticipated when filtering two images of the same scene where the noise corruption in each image is correlated at different levels across the frequency range. The present paper presents initial findings from subband filtering of images using a 2D noise cancellation algorithm. Test results are presented to illustrate the effect of scanning pattern, and to compare with other algorithms due to Hadhoud and Thomas [1988] and Ohki and Hashiguchi [1991].
Extending the KLANGPILOT Score Language for Real-Time Notation

The original version of the KLANGPILOT notation environment was developed in LISP in 1992, with the purpose of generating Csound scores while allowing more sophisticated control of sound synthesis. It was a text-based, human-readable score language that described musical ideas in a way better suited to the creative process of composition. This language was then translated by the computer into detailed parameters for various sound-synthesis methods. As faster computers became available, a new real-time version of KLANGPILOT was developed that aimed to provide a highly intuitive and interactive user interface for entering, editing and displaying sound including timbral parameters. This article focuses on KLANGPILOT's engine for musical representation in real-time and shows basic concepts of a real-time graphical paradigm of sound representation within the Max/MSP programming environment.
Pel-adaptive lossless predictive coding based on image segmentation

Lossless image coding that can recover original image from its compressed signal is required in the fields of medical imaging, fine arts, printing, and any applications demanding high image fidelity. MAR (Multiplicative Autoregressive) predictive coding is an efficient lossless compression scheme. In this method, prediction coefficients are fixed within the subdivided block-by-block image and cannot to be adopted to local statistics efficiently. Furthermore, side-information such as prediction coefficients must be transmitted to the decoder at each block. In this paper, we propose an improved MAR coding method based on image segmentation. The proposed MAR predictor can be adapted to local statistics of image efficiently. This coding method does not need transmit side- information to the decoder at each pixel. The effectiveness of the proposed model is shown through experiments using SHD images.
Tailbiting and decoding recursive systematic codes

Convolutional codes require either termination bits or tailbiting in order to maintain constant error correcting ability across the entire data frame. Termination reduces throughput but the more efficient tailbiting technique has applied only to feedforward encoders. A tailbiting system is proposed for recursive systematic codes, which combines the advantages of these codes and tailbiting.
BOND-GRAPHS FOR INFORMATION SYSTEMS

Abstract In this paper, an approach dealing with the dynamical aspect of information systems modelling is described. The main idea that governs this article is that the bond-graphs language can be applied to information systems theory. An extension of bond-graphs words is presented to cope with information exchanges. The aim of this task is to show that bond-graphs concepts can be used to model all the aspects of the information system model (static, dynamical,.). After a brief introduction, the bond-graph language for information systems is dealt with. Particular cases and a short comparison with the Jackson software development method constitute the subject of the sections that follow, then the tools required to model the running of the information system modelled by Bond-graphs are presented. The problem is clearly presented as follows: can the energetic point of view be applied to information systems? If so, is it possible to apply the bond-graph language to those systems?
Non-Probabilistic Reliability Computation and Efficiency Assessment Based on Interval Model

A new interval non-probabilistic reliability method is proposed in this paper. The sampling control factor is introduced, which can regulate the distribution of the sampling domain structure. The efficiency of the reliability calculation is effectively improved. The numerical results prove that this method can effectively and feasibly improve the computational efficiency of structural reliability by changing the value in practical engineering calculations when is located at a suitable interval.