Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Preservation of Theses and Dissertations Through Collaboration

Abstract While university libraries have a long tradition of preserving scholarship, they are less experienced in the technology-dependent and computer networked environment. By taking advantage of current activities and expertise that exist in various parts of the institution, policies and practices can be linked that will engender long-term accessibility. Under ideal circumstances preservation is not an isolated process; rather, it is built into the information life cycle beginning with a work's creation and continuing through to storage and access. Electronic theses and dissertations (ETDs) provide a good starting point to determine the processes and policies that will lead to confidence in digital preservation.
Interaction Analysis: Foundations and Practice

Interaction Analysis as we describe it here is an interdisciplinary method for the empirical investigation of the interaction of human beings with each other and with objects in their environment. It investigates human activities, such as talk, nonverbal interaction, and the use of artifacts and technologies, identifying routine practices and problems and the resources for their solution. Its roots lie in ethnography (especially participant observation), sociolinguistics, ethnomethodology, conversation analysis, kinesics, proxemics, and ethology. Video technology has been vital in establishing Interaction Analysis, which depends on the technology of audiovisual recording for its primary records and on playback capability for their analysis.2 Only electronic recording produces the kind of data corpus that allows the close interrogation required for Interaction Analysis. In particular, it provides the crucial ability to replay a sequence of interaction repeatedly for multiple viewers-and on multiple occasions.
Forward and backward tone mapping of high dynamic range images based on subband architecture

This paper presents a novel High Dynamic Range (HDR) tone mapping (TM) system based on sub-band architecture. Standard wavelet filters of Daubechies, Symlets, Coiflets and Biorthogonal were used to estimate the proposed system performance in terms of Low Dynamic Range (LDR) image quality and reconstructed HDR image fidelity. During TM stage, the HDR image is firstly decomposed in sub-bands using symmetrical analysis-synthesis filter bank. The transform coefficients are then rescaled using a predefined gain map. The inverse Tone Mapping (iTM) stage is straightforward. Indeed, the LDR image passes through the same sub-band architecture. But, instead of reducing the dynamic range, the LDR content is boosted to an HDR representation. Moreover, in our TM sheme, we included an optimization module to select the gain map components that minimize the reconstruction error, and consequently resulting in high fidelity HDR content. Comparisons with recent state-of-the-art methods have shown that our method provides better results in terms of visual quality and HDR reconstruction fidelity using objective and subjective evaluations.
A Simplified Approach to Magnetic Equivalent Circuit Modelling of Induction Machines

The fundamentals of megnetic equivalent circuit representation of electromechanical systems and the application of these principles to the computation of induction machine dynamics have been presented in earlier papers. The purpose of this paper is to introduce some simplifications which clarify the principles of the method and speed up the computation. The ability of the method to evaluate both time and space variations simultaneously is illustrated with graphs which represent the travelling waves in induction machines on a tooth by tooth basis.
Performance And Reliability Analysis Of Computer Systems (an Example-based Approach Using The Sharpe Software

Performance and Reliability Analysis of Computer Systems: An Example-Based Approach Using the SHARPE Software Package provides a variety of probabilistic, discrete-state models used to assess the reliability and performance of computer and communication systems. The models included are combinatorial reliability models (reliability block diagrams, fault trees and reliability graphs), directed, acyclic task precedence graphs, Markov and semi-Markov models (including Markov reward models), product-form queueing networks and generalized stochastic Petri nets. A practical approach to system modeling is followed; all of the examples described are solved and analyzed using the SHARPE tool. In structuring the book, the authors have been careful to provide the reader with a methodological approach to analytical modeling techniques. These techniques are not seen as alternatives but rather as an integral part of a single process of assessment which, by hierarchically combining results from different kinds of models, makes it possible to use state-space methods for those parts of a system that require them and non-state-space methods for the more well-behaved parts of the system. The SHARPE (Symbolic Hierarchical Automated Reliability and Performance Evaluator) package is the `toolchest' that allows the authors to specify stochastic models easily and solve them quickly, adopting model hierarchies and very efficient solution techniques. All the models described in the book are specified and solved using the SHARPE language; its syntax is described and the source code of almost all the examples discussed is provided. Audience: Suitable for use in advanced level courses covering reliability and performance of computer and communications systems and by researchers and practicing engineers whose work involves modeling of system performance and reliability.
Research on Application of Extended Mean-Shift Algorithm in Image Smoothing

This paper studied a method which can extend Mean-Shift algorithm based on Kernel. We describe its basic idea, given the specific steps of the algorithm. And given the application of extended Mean-Shift algorithm in the area of image smoothing. The research also show that extended Mean-Shift algorithm has displayed strong vitality in image segmentation and real-time object tracking.
A Method Of Noise Reduction On Image Processing

Describes a new control method for a noise reduction system developed to eliminate blur and picture trail in moving pictures using image processing. The method uses temporal information as well as other parameters such as frequency, amplitude, and picture pattern. The technique has been applied to the noise reduction circuit of the MUSE decoding system (Japanese HDTV). >
Modeling and query the uncertainty of network constrained moving objects based on RFID data

The management of network constrained moving objects is more and more practical, especially in intelligent transportation system. In the past, the location information of moving objects on network is collected by GPS, which cost high and has the problem of frequent update and privacy. The RFID (Radio Frequency IDentification) devices are used more and more widely to collect the location information. They are cheaper and have less update. And they interfere in the privacy less. They detect the id of the object and the time when moving object passed by the node of the network. They don't detect the objects' exact movement in side the edge, which lead to a problem of uncertainty. How to modeling and query the uncertainty of the network constrained moving objects based on RFID data becomes a research issue. In this paper, a model is proposed to describe the uncertainty of network constrained moving objects. A two level index is presented to provide efficient access to the network and the data of movement. The processing of imprecise time-slice query and spatio-temporal range query are studied in this paper. The processing includes four steps: spatial filter, spatial refinement, temporal filter and probability calculation. Finally, some experiments are done based on the simulated data. In the experiments the performance of the index is studied. The precision and recall of the result set are defined. And how the query arguments affect the precision and recall of the result set is also discussed.
Market-Based Distributed Task Assignment for Rendezvous Mission over Networks with Limited Connectivity

Abstract This paper extends the market-based task assignment algorithm to handle the networks with limited connectivity. The original algorithm was proposed to allocate tasks which cannot be executed by a single agent, but fully connected network is assumed. After analyzing the existing approaches for task allocation in limited networks, a new communications protocol is proposed which preserve key features of the original algorithm. The data required for task allocation algorithm is relayed via bridge agents. By adopting relaying operation, the proposed strategy allocates tasks regardless of the network topology. Convergence property is also preserved. Numerical simulation is performed to verify the feasibility of the proposed strategy considering the communication load.
Modularity Structure and Traffic Dynamics of ISP Router-level Topologies

Internet behavior becomes more complex due to ever-changing networking technologies and applications. Thus, understanding and controlling the complex behavior of the Internet are important for designing future networks. Previous studies revealed that flow control in the transport layer affects the traffic dynamics of the Internet. However, it is not clear how the topological structure impacts traffic dynamics. In this paper, we show the traffic fluctuation of the BA topologies generated by the Barab ́ siAlbert (BA) model and the ISP router-level topologies. The number of links with highly fluctuating queue length increases dramatically compared to that in the stop-and-wait model. Even in this case, the high-modularity structures of the ISP topologies reduce the number of highly fluctuating links compared with the BA topologies.
Synthesis of some pyrazolo[1,5‐c][1,3]benzoxazines and a new 5H‐pyrazolo[1,5‐c][1,3,2]benzoxazaphosphorine ring system

Condensations of 5-(2-hydroxyphenyl)pyrazoline 3a with 4-carboxybenzaldehyde, glyoxylic acid and N,N-carbonyldiimidazole leading to pyrazolobenzoxazine derivatives were studied. The observed diastere-oselectivity is discussed. Reaction of 3a with Lawesson reagent gave rise to a new 5H-pyrazolo[1,5-c]-[1,3,2]benzoxazaphosphorine heterocyclic system.
A Short Range Synthetic Aperture Imaging Radar with Rotating Antenna

The design of a short range synthetic aperture imaging radar is introduced in this paper. A radar hologram is acquired using a small omnidirectional antenna that is mounted on a rotating platform. After each turn of the platform a high resolution 360 ◦ 2D image is reconstructed; a rotating window function optimizes the reconstructed image function to get the best image focus for detecting both weak and strong scatterers. The rotating window function depends on the target direction and is executed for each image point and each target direction. The size of the synthetic aperture - and thus the lateral resolution of the imaging system - is determined by the diameter of the circular antenna trajectory. In contrast to common radar scanner concepts that utilize highly directional and thus bulky antennas, the proposed scanner concept has the advantage of using a small, lightweight omni-directional antenna. The developed radar system is much more compact and the scanning mechanics are significantly simplified. Furthermore, an omni-directional antenna offers very straightforward options for powering the radar on the rotation platform. Measurement results obtained with a 24 GHz FMCW short range radar sensor illustrate the performance of the proposed SAR imaging method.
Object Localization by Cooperation between Human Position Sensing and Active RFID System in Home Environment

: We propose methods for object localization by cooperation between human position sensing and active Radio Frequency Identiﬁcation (RFID) system in a home environment. The traditional object localization methods based on received signal strength indicator from active RFID system su ﬀ er from the distortion of RF signal caused by human existence. Two proposed methods improve this problem using a human position sensing system and pattern recognition technique. One method selects the classiﬁers based on human position in object localization. The other method narrows location candidates using position data and detection data of human handling motion with the sensor embedded in the active RFID tag. The experiment in the human natural handling scenario demonstrated that the methods improved the performance of object localization in human existence.
Autosophy image compression and vision for aerospace sensing

Autosophy is an emerging science dealing with self-assembling structures, such as crystals or living trees. It provides a new mathematical theory of 'learning', a new post Shannon 'Information Theory' and algorithms for growing self-assembling 'Information Networks' in a memory. Autosophy methods can extract the 'True Information' from images, resulting in orders of magnitude 'lossless' images compression for transmitting aerospace sensor data and for storing these images in data bases. Robot vision is simplified by the peculiar Omni Dimensional storage method in which each image pattern or fragment is stored only once. Autosophy methods may succeed, where conventional image processing has failed, in providing electronic vision comparable to our own.
LWT based encrypted payload steganography

Steganography is used in covert communication for transportation of secrete information. In this paper we propose LWT based Encrypted Payload Steganography (LEPS). The payload is segmented into two parts say block 1 and block 2. The LWT is applied on block 2 to generate four sub bands. Payload block 1 is retained in the spatial domain itself. The values of approximation band coefficients of block 2 and spatial domain intensity values of block 1 are compressed. The LWT is applied on cover image to generate wavelet sub bands and considered only diagonal sub bands (XD). The XD band is decomposed into three parts. The key values are embedded into first part of XD band. The compressed payload is embedded in second and third blocks of XD adaptively. The payload can be retrieved at the destination by adapting reverse process of embedding. It is observed that the values of PSNR and capacity are better in the case of proposed algorithm compared to existing algorithm.
Product Name Recognition for Informal Text: Exploring Features

Product name recognition refers to locate the name of product in text automatically. We built a conditional random field to recognize product name from forum posts and explored various features to compare their impact on the performance. These features include not only traditional features used for NER but also distributed word representations which are novel features obtained from new area of machine learning.
Multiresolution blind source separation method using sparsity for harmonic retrieval

The goal of this paper is to give a multiresolution blind source separation(BSS) algorithm using sparsity for harmonic retrieval. After the perspective of BSS is briefly presented, the general and detailed definition of the multiresolution BSS model is given. The multiresolution BSS algorithm for harmonic retrieval by sparsity property using multiscale independent component analysis(ICA) method is constructed in detail. Some simulations of the proposed algorithm are also exhibited. The paper concludes by discussing the impact of multiresolution BSS research and outlining potential future research directions and applications.
A competitive learning neural network for auditory information processing using the pulsed neuron model

The purpose of this study is to construct an auditory information processing system using the pulsed neuron model, which is suited to hardware implementation. The realization of a competitive learning network composed only of pulsed neuron models is investigated. A new winner neuron decision process is proposed in which the threshold of each neuron is controlled by a state-detection neuron, which monitors the firing situation of the competitive learning neurons. A competitive learning network is constructed on the basis of the proposed method. An operation simulation demonstrates that the winner neuron can be determined by the proposed method, following the change of the input signal, by using only pulsed neuron models, thus realizing vector quantization suited to auditory information processing. © 2005 Wiley Periodicals, Inc. Syst Comp Jpn, 36(13): 13–22, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ scj.20346
Search by Fuzzy Inference in a Children's Dictionary

This research aims at promoting the usage of an online children's dictionary within a context of reading comprehension and vocabulary acquisition. Inspired by document retrieval approaches developed in the area of information retrieval (IR) research, we adapt a particular IR strategy, based on fuzzy logic, to a search in the electronic dictionary. From an unknown word, searched for by a learner, our proposed fuzzy inference process makes it possible to retrieve relevant lexical information from any entry of the dictionary. Furthermore, it organises this information in the form of semantic maps of an adaptable size surrounding the query word. Manual construction of such semantic maps are seen as being effective for helping learners in vocabulary acquisition and reading comprehension tasks. Our research leads to a capability for building them automatically. Using concrete examples, we provide details of the calculation for the construction of semantic maps as well as for the retrieval of information. We introduce a software component which could be integrated in a computer assisted language learning (CALL) environment to promote vocabulary acquisition in L1.
A brain–computer interface for motor assist by the prefrontal cortex

Considerable research has been conducted on the development of brain–computer interfaces (BCIs). Although there have been several reports on BCIs that assist motor functions by measurement of brain activity in the motor cortex, only a few studies have discussed BCIs that assist motor functions by measurement of activity in areas other than the motor cortex. In this study, we experimentally develop a BCI that assists motor functions on the basis of brain activity in the prefrontal cortex. In this BCI system, subjects are presented with the labyrinth problem. Concretely, brain activity is measured using fNIRS and the data are acquired in real time. The signal processing module implements low-pass filtering of these signals. Further, the pattern classification module used in this system currently is a support vector machine. Twenty-two subjects, both male and female, volunteered to participate in this experiment. Eight of these twenty-two subjects were able to solve the labyrinth problem. In this experiment, we could not obtain a high distinction. However, these results show that it is possible to develop BCI systems that assist motor functions using information from the prefrontal cortex. © 2012 Wiley Periodicals, Inc. Electron Comm Jpn, 95(10): 1–8, 2012; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ecj.11426
Application of particle swarm optimization in model updating for wire-driven parallel manipulators

In the wire-driven parallel suspension system, because manufacturing and assembling deviations exist, the expected control accuracy can not be reached. A mathematical model of wire-driven parallel manipulators is established. Effects of the deviations eliminated can improve the accuracy of the mathematical model. Particle swarm optimization (PSO) is a robust stochastic evolutionary computation technique, which is very easy to understand and implement. Particle swarm optimization is used to calculate model deviations and find values of the deviations. The results obtained by the particle swarm optimization algorithm can update the mathematical model of the wire-driven parallel manipulators and improve the control accuracy of the wire-driven suspension system.
Personality Traits of Adolescents Measured on Levenson Tridimensional Scales of Personality Measure

Personality traits of male and female adolescents of age group 16-18 years have been measured and compared for the internal, external, and luck/chance loci of controls LOC on the Levenson Tridimensional Scales TDS of personality measure. Based on the findings of present investigations, it has been reported that boys and girls emerged to be more or less equal on the internal and external scales. However, boys have indicated greater tendencies to believe than the girls on luck/chance scales of LOC have.
Optimization of semi-global stereo matching for hardware module implementation

Stereo vision is one of the most intensively studied areas in the field of computer vision. It allows the creation of a 3D model of a scene given two images of the scene taken with optical cameras. Although the number of stereo algorithms keeps increasing, not many are suitable candidates for hardware implementations that could guarantee real-time processing in embedded systems. One of such algorithms is semi-global matching, which seems to balance well the quality of the disparity map and computational complexity. However, it still has quite high memory requirements, which can be a problem if the low-cost FPGAs are to be used. This is because they often suffer from a low external DRAM memory throughput. In this article, a few methods to reduce both the semi-global matching algorithm complexity and memory usage, and thus required bandwidth, are proposed. First of all, it is shown that a simple pyramid matching scheme can be used to efficiently reduce the number of disparities checked per pixel. Secondly, a method of dividing the image into independent blocks is proposed, which allows the reduction of the amount of memories required by the algorithm. Finally the exact requirements for the bandwidth and the size of the on-chip memories are given.
Comparison of various subjective video quality assessment methods

In this paper, we present comparison of three subjective testing methods: the double stimulus continuous quality scale (DSCQS) method, the single stimulus continuous quality evaluation (SSCQE) method and the absolute category rating (ACR) method. The DSCQS method was used for validate objective models in the VQEG Phase II FRTV test. The SSCQE method is chosen to be used in the VQEG RRTV test. The ACR method is chosen to be used in the VQEG Multimedia test. Since a different subjective test method is used in each test, analyses of the three methods will provide helpful information in understanding human perception of video quality.
Different decision tree induction strategies for a medical decision problem

The paper presents a comparative study of selected recognition methods for the medical decision problem -acute abdominal pain diagnosis. We consider if it is worth using expert knowledge and learning set at the same time. The article shows two groups of decision tree approaches to the problem under consideration. The first does not use expert knowledge and generates classifier only on the basis of learning set. The second approach utilizes expert knowledge for specifying the decision tree structure and learning set for determining mode of decision making in each node based on Bayes decision theory. All classifiers are evaluated on the basis of computer experiments.
A Promotion SAR Raw Data Compressing Algorithm Based on BAQ

BAQ algorithm is widely used in SAR raw data compressing, but SAR raw data does not perfectly submit to normal distribution in some cases. One of situation is fractional saturation of raw data. This paper proposes a promoted BAQ algorithm to compress SAR raw data by changing the quantization algorithm. The promoted algorithm increase the SNR of rebuild data with little bandwidth burden. Keywords-SAR;BAQ;raw data