Miracle-dz/UniFAR-FTUs huggingface dataset:
De-Noising of Underwater Acoustic Weak Signals Based on Compressed Sensing Technique

To remove the noise of weak signals detected in the underwater environment, the existing de-noising algorithms cannot perform satisfactorily. This paper aims to developing a new method to solve the problem, where the compressed sensing theory, wavelet transformation based filtering techniques and sparse signal reconstruction algorithm are employed. The simulation results show that the proposed algorithm performs favorably and has good potential to be used in some engineering applications.
Application of catastrophe theory to a slotted ALOHA communication system

Catastrophe theory is used to analyse the behaviour of a slotted ALOHA data communication system with the aim of demonstrating the power of catastrophe theory for the study of communication systems in general. A brief introduction to the required aspects of catastrophe theory is given, followed by detailed numerical and qualitative results of their application to slotted ALOHA.
A Long‐Range Touch Interface for Interaction with Smart TVs

A powerful interaction mechanism is one of the key elements for the success of smart TVs, which demand far more complex interactions than traditional TVs. This paper proposes a novel interface based on the famous touch interaction model but utilizes long‐range bare hand tracking to emulate touch actions. To satisfy the essential requirements of high accuracy and immediate response, the proposed hand tracking algorithm adopts a fast color‐based tracker but with modifications to avoid the problems inherent to those algorithms. By using online modeling and motion information, the sensitivity to the environment can be greatly decreased. Furthermore, several ideas to solve the problems often encountered by users interacting with smart TVs are proposed, resulting in a very robust hand tracking algorithm that works superbly, even for users with sleeveless clothing. In addition, the proposed algorithm runs at a very high speed of 82.73 Hz. The proposed interface is confirmed to comfortably support most touch operations, such as clicks, swipes, and drags, at a distance of three meters, which makes the proposed interface a good candidate for interaction with smart TVs.
Analysis of grid performance using an optical flow algorithm for medical image processing

The development of bigger and faster computers has not yet provided the computing power for medical image processing required nowadays. This is the result of several factors, including: i) the increasing number of qualified medical image users requiring sophisticated tools; ii) the demand for more performance and quality of results; iii) researchers are addressing problems that were previously considered extremely difficult to achieve; iv) medical images are produced with higher resolution and on a larger number. These factors lead to the need of exploring computing techniques that can boost the computational power of Healthcare Institutions while maintaining a relative low cost. Parallel computing is one of the approaches that can help solving this problem. Parallel computing can be achieved using multi-core processors, multiple processors, Graphical Processing Units (GPU), clusters or Grids. In order to gain the maximum benefit of parallel computing it is necessary to write specific programs for each environment or divide the data in smaller subsets. In this article we evaluate the performance of the two parallel computing tools when dealing with a medical image processing application. We compared the performance of the EELA-2 (E-science grid facility for Europe and Latin- America) grid infrastructure with a small Cluster (3 nodes x 8 cores = 24 cores) and a regular PC (Intel i3 – 2 cores). As expected the grid had a better performance for a large number of processes, the cluster for a small to medium number of processes and the PC for few processes.
Harrod's librarians' glossary and reference book. Comp. by Ray Prytherch. 9 ed.; Stella Keenan: Concise dictionary of library and information science. 2 ed.

beschreiben den Bandund Mittelbedarf der einzelnen bayerischen Universitäten. Andererseits werden diejenigen Leser, die sich lediglich über die aktuelle Version des bayerischen Etatmodells informieren möchten, in der Fülle der gebotenen statistischen Daten oft den roten Faden verlieren. Angesichts der Tatsache, dass die Kalkulationsbasis des neuen Modells, wie gezeigt wurde, auf einigen ziemlich handfesten Grundannahmen ruht, wäre eine knappere Darstellung, etwa in einem Zeitschriftenbeitrag, vollständig ausreichend gewesen. Dennoch ist das Werk zur Anschaffung und Lektüre zu empfehlen, da die Fülle des statistischen Materials im Kontext der praktischen wie politischen Probleme des universitären Erwerbungsgeschäfts wertvolle Argumentationshilfen bieten kann. Blickt man abschließend auf die praktische Wirkung des neuen Etatmodells, so hat es sich zumindest im bayerischen Kontext bisher als sehr erfolgreich erwiesen. Von Anfang an mitgetragen durch die bayerische Rektorenkonferenz, konnten die Landesuniversitäten auf der Grundlage des im Modell berechneten Sollbedarfs im Haushaltsjahr 2001 über 60 Millionen DM Literaturmittel verfügen. Dies entspricht immerhin 88 % des im Sollmodell errechneten Bedarfs. Hervorzuheben ist, dass diese Mittel den Hochschulen nicht im Rahmen des Globaletats für Forschung und Lehre, sondern separat als Infrastrukturmaßnahme zugewiesen werden und damit dem inneruniversitären Verteilungskampf von vornherein entzogen sind. Die Tatsache, dass auch in 2002 und 2003 die Mittelzuweisung für Literatur und Informationsversorgung in Bayern annähernd auf dem Niveau von 2001 gehalten werden konnte, zeigt deutlich, dass der praktische Erfolg des Modells nicht primär von der Ausgefeiltheit seiner Kalkulationsgrundlagen, sondern von seiner Akzeptanz bei den maßgeblichen politischen Akteuren abhängt. In diesem Sinne ist dem neuen „Bayerischen Modell“ ein breiter Erfolg auch über die Landesgrenzen hinaus zu wünschen.
The Relationship between Cognitive Load Measurements and Estimates of Computer Input Control Skills

This paper discusses several methods of estimating task difficulty of onscreen object movement tasks for three subject groups using five standard computer input devices (touchscreen, mouse, keyboard, trackball, and locking trackball). The subject groups are as follows: 19 computer-experienced adults, 39 normally developing children, and 15 children with mental retardation. Three separate measurements of cognitive load (mastery, speed, and user characteristics) are reported between user groups to compare conclusions about input device difficulty across different measurement techniques. Results indicate that speed measurements tend to emphasize similarity in device efficiency for skilled users, but that mastery measurements are essential to represent device effectiveness, particularly for unskilled users. Cognitive as well as physical user characteristics were associated with the successful acquisition of device control skills with training. Because each of the measurements used separately result in differe.
3D Modelling, Simulation and Prediction of Facial Wrinkles

Ageing is a natural phenomenon and it is part of our daily life process; the Facial Ageing (FA) process has been of a great interest to many researchers and some firms like airports and police departments; this is due to the fact that the face appearance changes as people age resulting in difficulties identifying certain individuals. In this paper, two-dimensional wrinkle maps will be used in the design of a three-dimensional system for the purpose of facial wrinkles simulation and prediction. Our findings will challenge many commercial softwares in the innovation of the techniques in setting solid grounds to generate real-time 3D wrinkles that can be used later for various reasons that may include security, 3D facial ageing simulation systems, facial animation, etc. The 2D binary wrinkles will be mapped on the corresponding 3D face models using the generated outlined images. NURBS curves will then be projected on those wrinkles to form a three-dimensional wrinkle map. The coloured wrinkle map, as well as some parameters, will be combined together in an algorithm to predict the appearance of the individual wrinkles in every age group that are divided into decades, starting from the age of 20. The novelty of the adopted procedure in comparison to the previous works, is the new elements that have been integrated and collaborated to boost accuracy and to generate a more realistic outcome.
Activity Theory: A Foundation for Designing Learning Technology?

Illuminating the codevelopment of practice and designed artifact is the central aim of Context and Consciousness: Activity Theory and Human-Computer Interaction. Nardi and her colleagues present activity theory (AT) as a method of organizing observations and a source of explanation. The book represents a successful East-West dialogue inspired by tenets of Soviet psychology, and seeks to interpret AT to the broader human-computer interaction (HCI) community. The concepts of this theory cluster around activity (conscious, practical, goal-directed human endeavors) and mediation (acts produce effects only through the help of culturally constructed tools). The concepts of activity and mediation provide insight into the codevelopment of practice and technology through researcher's narrative accounts of the connections between purposeful activity and computer interfaces. The authors of the introductory chapters of this book were ambitious. They predicted the ascension of AT, readily overcoming a current crisis in HCI. The crisis was portrayed as a malaise induced by the impotence of HCI in actual design. HCI has been on the sidelines for most user interface breakthroughs, often offering only a running commentary on why the winners won and losers lost. HCI has been "unable to penetrate the human side of the interface" (p. 19). HCI is afflicted by a
Gaussian Process Meta-Models for Efficient Probabilistic Design in Complex Engineering Design Spaces

Probabilistic design in complex design spaces is often a computationally expensive and difficult task because of the highly nonlinear and noisy nature of those spaces. Approximate probabilistic methods, such as, First-Order Second-Moments (FOSM) and Point Estimate Method (PEM) have been developed to alleviate the high computational cost issue. However, both methods have difficulty with non-monotonic spaces and FOSM may have convergence problems if noise on the space makes it difficult to calculate accurate numerical partial derivatives. Use of design and Analysis of Computer Experiments (DACE) methods to build polynomial meta-models is a common approach which both smoothes the design space and significantly improves the computational efficiency. However, this type of model is inherently limited by the properties of the polynomial function and its transformations. Therefore, polynomial meta-models may not accurately represent the portion of the design space that is of interest to the engineer. The objective of this paper is to utilize Gaussian Process (GP) techniques to build an alternative meta-model that retains the properties of smoothness and fast execution but has a much higher level of accuracy. If available, this high quality GP model can then be used for fast probabilistic analysis based on a function that much more closely represents the original design space. Achieving the GP goal of a highly accurate meta-model requires a level of mathematics that is much more complex than the mathematics required for regular linear and quadratic response surfaces. Many difficult mathematical issues encountered in the implementation of the Gaussian Process meta-model are addressed in this paper. Several selected examples demonstrate the accuracy of the GP models and efficiency improvements related to probabilistic design.Copyright ? 2005 by ASME
A voltage reduction technique for battery-operated systems

Two techniques for voltage reduction are presented, both of which can significantly reduce the power consumption of digital CMOS circuits. The fixed reduction of voltage is applicable to small systems with a low initial consumption, however, the optimum voltage is not reached and the correct operation of the circuit is not guaranteed. The self-adjusted reduction of voltage is adapted to bigger digital systems. The correct operation of the digital circuit is guaranteed, and the supply voltage is near the optimum for the speed requirements. This technique is more versatile, accurate, and reliable than the fixed one. >
Any Time Any Where- Remote Monitoring of Attendance System based on RFID using GSM Network

means Radio Frequency Identification is a wireless identification technique which becomes very popular these days and is used for the identification of physical objects like products, humans etc by the use of radio frequency. This technique is much more advantageous, safe, secure and easy with lower overhead in contrast with the other conventional technique used. It is much faster and it has two components i.e. RFID tag and RFID reader. In this paper, we have proposed a push based SMS sending approach by GSM cellular network to remote monitoring of attendance of student based on RFID.
An Unsupervised Sentiment Information Identification Approach

Existing research focuses on document-based sentiment analysis and documents are represented by the bag-of-words model. However, due to the loss of contextual information, this representation fails to capture the associative information between an opinion and its corresponding target. Additionally, several researchers focus on sentence-based approaches, which can effectively extract an aspect-sentiment word pair within one sentence. Nevertheless, their approaches can only deal with one aspect within one sentence and miss the identification of sentiment modifier. In order to solve these problems, this paper proposes a novel identification approach of aspect-modifier-sentiment word triple using shallow semantic information. Experimental results show that our approach is feasible and effective.
Parallel 2D Pre-Stack Imaging On PARAM Padma

Summary Obtaining high-resolution images of the underground geological structures using seismic reflection data in prestack or poststack domain is crucial for exploration of oil and gas deposits. In petroleum industry, seismic migration is one of the most compute intensive steps in seismic data processing sequence. It accurately images the reflected and diffracted energy and aids in delineating the structural features of the underground geological formations. Migration techniques are highly compute and input/output (I/O) intensive and therefore requires high performance computing. In the last decade the development of parallel distributed computing platforms, related system software and programming environments have made it possible to use parallel codes for high resolution imaging. Centre for Development of Advanced Computing (C-DAC), Pune has developed the OpenFrame architecture for scalable parallel computing applications. Various seismic migration algorithms have been developed and implemented for imaging purposes. In this presentation we will discuss the parallel implementation achieved on C-DAC’s PARAM Padma platform for two totally different 2D pre-stack migration algorithms. In both cases parallelisation has been done using MPI message passing environment and MPI I/O for parallel file reading and writing. The first algorithm is Finite difference based depth migration in frequency - space domain ( ω-x depth migration) and the second one is based on integral or summation approach migration in time (Kirchhoff time migration). The benchmarking results for both the algorithm clearly shows that large-scale problems can be solved by implementation of highly efficient and scalable codes. These codes can be easily ported across cluster of workstations.
Event Probability Based Priority Filter for Efficient Event Matching

Event matching plays a critical role in content-based publish/subscribe system. Most traditional methods focus on existing subscriptions separation and combination. However, an event usually comes with certain probability distribution in each dimension. Thus taking both existing subscriptions and probable coming event into consideration can improve event matching time efficiency. Based on that, we put forward PF (Priority Filter), a highly efficient event matching algorithm. By building up a unified model with historical subscriptions for continuous and discrete attributes, we derive formulas to calculate each attribute’s filtering rate. Besides, in order to guarantee time efficiency both in matching, inserting, and deleting, a red-black tree regarded as a priority filter is built up on all attributes according to filtering rate. Experiments demonstrate that PF has a 30% faster speed compared to existing methods with acceptable insertion and deletion time and memory consumption.
Design of multi-layer neural networks with powers-of-two weights

The feasibility of restricting the weight values to powers-of-two or sums of powers-of-two in multilayer neural networks is discussed. A learning procedure based on back-propagation to obtain a neural network with such weights is presented. This learning procedure requires full real arithmetic, and therefore must be performed offline. These neural networks do not require multipliers, and are well suited for high-speed and high-integration digital neural circuits. To show the effectiveness of the approach, tests on a pattern recognition problem are presented. <<ETX>>
The effect of image enhancement on biomedical pattern recognition

Image enhancement has been an area of active research for decades. Most studies were aimed at improving the quality of image display for better visualization. Yet few studies have been conducted to investigate the impact of image enhancement on biomedical pattern recognition. In this paper, we examine quantitatively the effect of image enhancement on the performance of biomedical pattern recognition. We apply the wavelet-based image enhancement technique developed in our earlier work [Y. Wang et al., Proc. ICASSP 2001, Salt Lake City, May, 2001], to a well-known biomedical pattern recognition problem: chromosome classification. Experiments were conducted on a test set of chromosome images before and after the enhancement, using the same feature measurement and classifier methods. The test results show that our image enhancement method substantially reduces the error rate of chromosome classification. We learn from this study that proper image enhancement leads to significantly improved recognition accuracy, and the quantification of performance improvement may be used as an objective measure of success for evaluating various image enhancement techniques.
Proposal for a 3‐D display with accommodative compensation: 3DDAC

This paper proposes a novel binocular-disparity three-dimensional (3-D) display with accommodative compensation (3DDAC) to achieve fatigue-free viewing. The display principle is based both on detecting gaze points and moving the display screen to the gaze depth in real time. Gaze detection is discussed with respect to whether eyeball rotation occurs or not, and screen motion is discussed with respect to whether the screen is real or a virtual image. In an experimental setup, a 3-D computer-graphics image was produced to evaluate the accommodation effect. The gaze position was fixed at the center of the field of view, and the display depth was controlled by a z-buffer value of the pixel focused on. The display screen was then moved, as a virtual image, by back-and-forth movements of a relay lens. It was determined that the perceived sharpness of the image increased for the proposed display mode.
Managing Complexity of HEVC Deployment

HEVC (H.265) promises to deliver the same video quality as H.264 but at half the bit rate. This is particularly important as the video industry moves beyond high definition to 4K and 8K. However, this achievement comes at the expense of complexity, at both the component and system levels. At the component level, there is greater latitude in making design decisions during both encode and decode. In systems, validating end-to-end interoperability has the potential to be a costly and time-consuming process as the number of variables increases exponentially. In this paper, we describe approaches to managing complexity when deploying HEVC. A key method centers on the integration of automated testing tools that layer on top of the standards. These hooks and functions provide increased visibility and test vector injection points. We describe how the combination of automated test tools, code with test tool hooks and certification against known good components and systems allows operators to reduce time-to-market and shrink their integration budgets.
An Error Correcting Method of BCH Code Applicable to Memory

An error correcting method of BCH code applicable to memory is proposed. The reliability and yield of memories can be efficiently improved by error correcting codes. Due to the limited length of data transfer bits in certain interfaces, check bits are not fully used by most BCH codes. The proposed method takes advantage of the nature of BCH codes to make full use of the check bits, so that more errors can be corrected than the original method. The algorithm can be achieved by pure logic circuits in a parallel way with only gate delay, suitable for special timing applications. The improvement of certain BCH code is evaluated by C++ and the hardware implementation is presented by FPGA.
Discovering large network motifs from a complex biological network

Graph structures representing relationships between entries have been studied in statistical analysis, and the results of these studies have been applied to biological networks, whose nodes and edges represent proteins and the relationships between them, respectively. Most of the studies have focused on only graph structures such as scale-free properties and cliques, but the relationships between nodes are also important features since most of the proteins perform their functions by connecting to other proteins. In order to determine such relationships, the problem of network motif discovery has been addressed; network motifs are frequently appearing graph structures in a given graph. However, the methods for network motif discovery are highly restrictive for the application to biological network because they can only be used to find small network motifs or they do not consider noise and uncertainty in observations. In this study, we introduce a new index to measure network motifs called AR index and develop a novel algorithm called ARIANA for finding large motifs even when the network has noise. Experiments using a synthetic network verify that our method can find better network motifs than an existing algorithm. By applying ARIANA to a real complex biological network, we find network motifs associated with regulations of start time of cell functions and generation of cell energies and discover that the cell cycle proteins can be categorized into two different groups.
A CMOS transceiver for DRAM bus system with a demultiplexed equalization scheme

An equalizing transceiver was implemented by using a 0.35-/spl mu/m CMOS technology for DRAM bus system. An equalization scheme was used in the receiver to reduce intersymbol interference (ISI). To maximize the data rate, a one-to-eight demultiplexing scheme was used in the equalizer of the receiver such that eight equalizers operate in parallel at the clock frequency, which is one-eighth the data rate. The maximum data rates were measured to be 840 Mb/s with twelve 5-pF capacitors connected in uniform spacing along a transmission line. The test criterion for successive transmission was set to the bit-error rate (BER) of 10/sup -12/ for the pseudorandom binary sequence (PRBS) data. The effectiveness of equalizers was demonstrated by measuring the BER with equalizers on and off, respectively. The chip size was 800/spl times/400 /spl mu/m/sup 2/ and the supply voltage was 3.3 V.