Miracle-dz/UniFAR-FTUs huggingface dataset:
Possibilities for Computer Animated Films in Cartography

AbstractThis paper describes pioneer work in animated mapping with computers, using the cathode ray tube fixed intensity beam as the drawing 'tool' on the 'raster' or working area. The controlled light image is recorded by a shutterless cine camera. Replacement of the draughtsman by a computer makes possible the automatic drawing of images by slight successive changes, resulting in an animated map. Examples are given from several scientific fields.
Image quality assessment based on distortion identification

A New Global Full-Reference Image Quality System based on classification and fusion scheme is proposed. It consists of many steps. The first step is devoted to the identification of the type of degradation contained in a given image based a Linear Discriminant Analysis (LDA) classifier using some common Image Quality Metric (IQM) as feature inputs. An IQM per degradation (IQM-D) is then used to estimate the quality of the image. For a given degradation type, the appropriate IQM-D is derived by combining the top three best IQMs using an Artificial Neural Network model. The performance of the proposed scheme is evaluated first in terms of good degradation identification. Then, for each distortion type the image quality estimation is evaluated in terms of good correlation with the subjective judgments using the TID 2008 image database.
SLO blind data set inversion and classification using physically complete models

Discrimination studies carried out on TEMTADS and Metal Mapper blind data sets collected at the San Luis Obispo UXO site are presented. The data sets included four types of targets of interest: 2.36" rockets, 60-mm mortar shells, 81-mm projectiles, and 4.2" mortar items. The total parameterized normalized magnetic source (NSMS) amplitudes were used to discriminate TOI from metallic clutter and among the different hazardous UXO. First, in object's frame coordinate, the total NSMS were determined for each TOI along three orthogonal axes from the training data provided by the Strategic Environmental Research and Development Program (SERDP) along with the referred blind data sets. Then the inverted total NSMS were used to extract the time-decay classification features. Once our inversion and classification algorithms were tested on the calibration data sets then we applied the same procedure to all blind data sets. The combined NSMS and differential evolution algorithm is utilized for determine the NSMS strengths for each cell. The obtained total NSMS time-decay curves were used to extract the discrimination features and perform classification using the training data as reference. In addition, for cross validation, the inverted locations and orientations from NSMS-DE algorithm were compared against the inverted data that obtained via the magnetic field, vector and scalar potentials (HAP) method and the combined dipole and Gauss-Newton approach technique. We examined the entire time decay history of the total NSMS case-by-case for classification purposes. Also, we use different multi-class statistical classification algorithms for separating the dangerous objects from non hazardous items. The inverted targets were ranked by target ID and submitted to SERDP for independent scoring. The independent scoring results are presented.
CPAR-language extensions to C for irregular and adaptive parallel computations

The CPAR language consists of a set of extensions to the C language, designed to support parallel programming on distributed-memory multiprocessors, in particular, irregular and adaptive computations which are hard to do well in languages such as Fortran-90 or High Performance Fortran (HPF). CPAR provides data accesses over a global name space using concepts of communication functions and object streams. These constructs allow programmers to specify interprocessor data transfer between arrays or pointer-based data structures without getting involved with the split phases of "send" and "receive" of a communication. Our experience of using CPAR to program an N-body simulation problem is briefly described. <<ETX>>
A Study of Meter Placement Method for Distribution Systems

In this paper a novel method of meter placement for distribution systems is proposed. By analyzing the characters of the sensitive matrix of estimated errors of measurements, the sensitive genes are defined which are produced by measurements in the total variance of estimated errors of measurements. The scheme of meter placement is decided according to their orders in the sensitive gene table. The new approach can use lesser real-time meter placements and more pseudo measurements to satisfy the evaluated criterions on the base of branch-current-based state estimation. An analysis is done for the IEEE 33-bus systems and tested results present the advantage of new idea.
Medical Image Registration Combined with SURF and Improved RANSAC Algorithm

Aiming at the requirements of medical image registration for good robustness, high-accuracy and speed, this paper proposes a Medical Image Registration algorithm Combined SURF with improved RANSAC algorithm. This algorithm first of all extracts SURF featured points from images and matches similar featured points, then the improved RANSAC algorithm is used to eliminate wrong matches, and finally the image registration process is accomplished by estimating space geometric varied parameters according to least square method. The algorithm combines robustness and high efficiency of SURF and high-accuracy of improved RANSAC algorithm. Experimental results show that in the condition of images with noise, non-uniform intensity and large scope of the initial misalignment, the proposed algorithm achieves better robustness and higher speed while maintaining good registration accuracy compared with the conventional ional area-based and feature-based registration methods.
PNAVSIM: A Numerical Simulation Package for Pulsar Navigation

PNAVSIM is a package for numerical investigation of pulsar navigation. It contains a number of methods and algorithms for the simulation purpose in navigation. The photon-level integrated simulation model can be built easily based on the PNAVSIM library. The toolkit API can also be conveniently used by the developer in his own program. Functions are packed into modules at different levels. The top-level modules dealing with the spacecraft orbit dynamics, the pulse signal time delay, and the navigation algorithms are introduced. The structure of the PNAVSIM package makes it possible for developers to build simulation models flexibly and quickly, which enables more efficient applications of pulsar navigation.
Blind MPEG-2 video watermarking in DCT domain robust against scaling

Watermarking techniques that need no original information during watermark detection, known as blind watermarking, are more desirable than informed ones for practical usage and convenience in watermark extraction. A blind MPEG-2 watermarking technique operating in the DCT (discrete cosine transform) domain is presented, which is generally robust against arbitrary ratio scaling, provided that turbo codes are used for error correction. The method can be directly applied to other block-DCT-based video compression techniques. The main advantage of the scheme is its simplicity, blindness and the ability to tailor the watermark payload in a trade-off with other watermark requirements. As synchronisation is automatically obtained from the frames in the scaled video itself, a connection between the source and the target video is not necessary for watermarking detection.
Design of Virtual Machine Monitor for Embedded Systems

Recently virtualization has been one of the most popular research topics in system software area. While there are many commercial virtualization products for general-purpose computer system, little efforts are made to virtualize embedded system. In this paper, we design and implement a virtual machine monitor which divides each physical hardware resource of an embedded system into logical ones and reorganizes them into many virtual machines so that several real-time operating systems run concurrently on a single embedded system. We measure various performance metrics of the virtual machine monitor developed on a real embedded system. The results of the measurement study show that our virtual machine monitor has enough potentiality of its application to real-world embedded systems.
Neuromorphic self-tuning PID controller

Using the nonlinear mapping capability of neural networks (NNs) a tuning method of a proportional integral derivative (PID) controller based on a backpropagation (BP) method of multilayered NNs is derived. Simulated and experimental results show that the proposed method can identify the appropriate parameters of the PID controller when it is implemented to both linear and nonlinear plants. <<ETX>>
Mining Frequent Itemset Using ParallelComputing Apriori Algorithm

Frequent itemset mining from a large transactional database is a very time consuming process. A famous frequent pattern mining algorithm is Apriori. Apriori algorithm generates a frequent itemsets in loop manner, one frequent item adds in itemsets per loop. Apriori algorithm required multiple times dataset scans for itemset generation therefore it is time consuming process. Sometime Apriori become a holdup for large transactional dataset because of the long running time of the algorithm. This paper presents an efficient scalable Multi-core processor parallel computing Apriori that reduce the execution time and increase performance. Java concurrency libraries package used for the multi-core utilization that is easy and simple implementation technique. Furthermore, we compare the performance of Apriori sequential and parallel computing on the basis of time and varying support count for various transactional datasets.
Verification of Sleep/Wake Detection Algorithms for Kindergarten Support System Based on Activity Recognition

: Practical application of a human monitoring system draws increasing attention with the high developments of information & communication technology and robot technology. Utilizing these technologies, a kindergarten support system for children, parents, and childminders using the activity recognition (AR) has been studied in author’s previous studies. In this paper, several wake / sleep identiﬁcation algorithms for infants as an additional AR were veriﬁed by using orthodox algorithms that were used for adults. Investigating combinations of sensor position to infant’s body (arm or leg), sampling frequency (5Hz to 50Hz), threshold for acceleration detection (0.1m / s 2 to 0.9m / s 2 ), and types of wake / sleep detection algorithms (count-scaled, Cole, Sadeh, and zero-threshold algorithms), it was conﬁrmed that the count-scaled algorithm could obtain highest identiﬁcation accuracy as high as 89.0% under adequate measurement condition.
A Guide to GOMS Model Usability Evaluation using GOMSL and GLEAN4

The standard accepted technique for developing a usable system, empirical user testing, is based on iterative testing and design revision using actual users to test the system and help identify usability problems. It is widely agreed that this approach, inherited from Human Factors, does indeed work when carefully applied (Landauer, 1995). However, Card, Moran, & Newell (1983) have argued, and many HCI researchers have agreed (e.g., see Butler, Bennett, Polson, & Karat, 1989), that empirical user testing is too slow and expensive for modern software development practice, especially when difficult-to-get domain experts are the target user group. One response has been the development of "discount" or "inspection" methods for assessing the usability of an interface design quickly and at low cost (Nielsen & Mack, 1994). However, another response, which has been evolving since the seminal Card, Moran, and Newell work, is the concept of engineering models for usability. Analogously to the models used in other engineering disciplines, engineering models for usability produce quantitative predictions of how well humans will be able to perform tasks with a proposed design. Such predictions can be used as a surrogate for actual empirical user data, making it possible to iterate through design revisions and evaluations much more rapidly. Furthermore, unlike purely empirical assessments, an engineering model for an interface design can capture the essence of the design in an inspectable representation, making it easier to reuse successful design insights in the future.
Modeling and analysis of the dynamic location registration and paging in microcellular systems

A 0-1 integer programming model is considered to determine the most appropriate dynamic location registration (LR) area of each subscriber in microcellular systems. The minimization model of the LR area updating and paging signal costs is examined. The model is based on the subscriber characteristics, such as the call arrival rate and the velocity, as well as the regional information. The control channel blocking probabilities are considered as constraints to meet the service level of subscribers. A dynamic scheme which adaptively updates the size and shape of the LR area is developed by solving the minimization problem. Paging and location updating procedures are presented based on the dynamic procedure. The superiority of the proposed scheme is demonstrated with various computational results.
Subband coding of museal images

Data compression is quite relevant for storage and transmission of museal data. This work reports on the performance of subband coding applied to paintings pictures obtained by an HDTV camera. The performance of different analysis/synthesis filter banks and coding schemes is compared. The best results are obtained via Johnston's filters and a uniform threshold quantizer. The effectiveness of a scalable use of subband coding in this application is also reported.
The Natural History of Cigarette Smoking: Predicting Young-Adult Smoking Outcomes From Adolescent Smoking Patterns

Assessed the magnitude of risk that adolescent cigarette smoking carries for adult smoking. Using a longitudinal, prospective design, results indicate that even infrequent experimentation in adolescence significantly raises the risk for adult smoking and that regular (at least monthly) adolescent smoking raises the risk for adult smoking by a factor of 16 compared to nonsmoking adolescents. Relative risk was also increased by an early onset of smoking and by a stable, uninterrupted course from experimentation to regular smoking. Relative risk did not significantly vary by age or sex. The continuity of smoking behavior between adolescence and adulthood supports the importance of primary prevention programs directed at adolescent populations.
Digital sampling process for audio class D, pulse width modulated power amplifiers

Digital audio class D amplifiers require a digital process to convert the sampled audio signal into a pulse width modulated (PWM) signal. The present methods of generating PWM are either analogue (natural sampling) and are unsuitable for digital systems or use a digital process (uniform sampling) which introduces excessive distortion. An alternative sampling process is described which is suitable for digital implementation yet introduces the low levels of distortion usually associated with natural sampling.
Maneuvering target tracking using passive TDOA measurements

This paper proposes a novel interacting multiple model (IMM) algorithm to track a maneuvering target, with the aim of improving the tracking performance of a time difference of arrival (TDOA) passive tracking system. Under the architecture of the proposed algorithm, the multiple model deals with the model switching, while the iterated extended Kalman filter (EKF) accounts for non-linearity in the dynamic system models. The tracking performances of the proposed algorithm, EKF, IMM are compared via Monte Carlo simulations. Simulation results indicate that the proposed algorithm is an effective nonlinear filtering algorithm for TDOA passive tracking system, and has higher tracking precision than the IMM and EKF. The proposed algorithm can reduce nearly 6.75% and 61.23% of the positioning error than IMM and EKF algorithms.
An Alternative Artificial Intelligence Technique for Detecting Outliers

Data are rarely perfect. Whether the problem is data entry errors or rare events. Outliers have two opposing properties. They can be noises that disturb regression and classification task. On the other hand, they can provide valuable information about rare phenomena, which can lead to knowledge discovery. This paper proposes a hybrid algorithm including K Nearest Neighbor and Support Vector Machine (KSVM) that detects outliers by taking the advantages of the two intelligent techniques, Support Vector Machine (SVM) and K Nearest Neighbour (KNN). Also a global efficiency measure introduced to compare different methods. Finally, a comparison between KNN, SVM, and KSVM is conducted using detection rate, accuracy rate, false alarm rate, true negative rate and the proposed global efficiency measure based on benchmark data called Milk data.
From little things big things grow: scaling‐up assessment of experiential learning

Purpose – The new economies of the twenty‐first century require new approaches to learning and teaching from higher education (HE). Accordingly many universities have gradually scaled‐up learner‐centred approaches, including flexible delivery and technology‐enhanced learning, from the domains of enthusiasts towards the institutional level. This paper seeks to argue that these new economies and styles of learning and teaching bring similar requirements for scaling of assessment practices in HE, in particular, that it is now time for many universities to consider change initiatives to scale‐up the assessment of experiential learning to the institutional level.Design/methodology/approach – The need to scale‐up assessment of experiential learning in the Australian and international higher HE contexts is discussed and a variety of change initiatives to scale‐up assessment of experiential learning at the University of South Australia is described. These initiatives are explored in the wider context of change ma.
Challenging valve replacement in posterior mitral annular calcification.

The ‘How-to-do’ paper by Nezic et al. [1] was truly interesting. These authors resolve, by a simple technique, a really challenging surgical problem: the method of implanting a valve prosthesis when the posterior mitral annulus is heavily calcified, sometimes involving the posterior left ventricular myocardium. The only drawback of the above-mentioned technique appears to be the calcification of the anterior mitral leaflet (AML). I successfully adopted this technique to perform a mitral valve replacement on a 74-year old man with aortic bioprosthesis failure and calcified mitral valve stenosis. I performed the operation with a minor modification that I think further simplifies the proposed technique. Briefly, the AML was removed from its insertion and brought posteriorly. It was first sewed by two 4/0 polypropylene sutures starting bilaterally where the AML crossed the mitral annulus out of its calcification area. The two running sutures were also brought up to the left atrial posterior wall, avoiding the placement of any sutures on the ventricular posterior wall (personal modification). At the time of bioprosthesis insertion, a 2/0 pledgetted subannular mattress stitch was passed bilaterally through the posterior annulus, overriding the AML where it crossed, then to the prosthetic sewing ring. The remaining ‘posterior’ stitches were passed only through the transposed AML in a kind of ‘subannular’ fashion, without securing them to the calcified area of the posterior left ventricular wall (personal modification), avoiding the need for partial decalcification. Finally, the bioprosthesis was secured to the anterior annulus in the usual manner. Both the postoperative and 3-month follow-up echocardiography revealed the regular function of the bioprosthesis. Neither perivalvular leakages nor rocking mobility of the bioprosthesis ring, which appeared well fixed in the proper position, was detected. The patient is still in good clinical condition 6 months after the operation. In conclusion, I had a satisfactory surgical experience with the suggested technique, and therefore I recommend its use whenever indicated.
The U.S. e-File Initiative: An Investigation of the Antecedents to Adoption from the Individual Taxpayers’ Perspective

Electronic tax filing (e-file) in the United States is one of the most rapidly emerging areas of e-government. This study proposes a model of e-file diffusion that integrates acceptance factors and personal factors to assess the impact of adoption, trust and optimism on e-file utilization. To test the model, a survey was administered to 260 participants. The data analysis was conducted using multiple linear regression. The findings indicate that performance expectancy, social influence, computer anxiety, optimism bias and trust of the government all have a significant impact on intention to use an electronic tax filing system. Implications for practice, suggestions for future research, and limitations of the study are discussed.
Broadband microstrip antenna excited by coplanar waveguide

The configuration and radiation characteristics of an antenna system exciting a rectangular microstrip antenna with coplanar waveguide are studied. In addition, a method for broadbanding is discussed. (1) The radiation characteristics of this antenna are characterized by simulation and experiment, and basic design data are obtained. (2) A method of construction for an antenna system with a parasitic element stacked on the microstrip antenna is investigated. It is confirmed that a broadband characteristic of about 23% in terms of return loss (VSWR ≤ 2.0) can be obtained. (3) In addition, the radiation pattern and gain of the present antenna system are studied. It is shown that these characteristics are broadband in nature. Further, the mutual coupling between the elements is studied, since this is important for the consideration of array antenna. Basic design data are obtained. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 85(10): 1–7, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.10010
Intelligent Sensor System UPnP Networks Interface and Device Selection Realization

The network interface is the key position in an intelligent sensor system to realize plug and play. Based on UPnP (Universal Plug and Play) and IEEE 1451serie standards, an IEEE 1451/UPnP bridge is designed to solve the differences of message formats, self-identification description, and device discovery between these two standards. Using UPnP device selection method based on information axiom, the calculation of parameters information is distributed to each NCAP (Network Capable Application Processor) that meeting the service request. The test results indicate that this method simplifies the service discovery process, reduces network interface data traffic overhead, and increases UPnP device service efficiency.
Metrics and Models in Software Quality Engineering

From the Publisher: Author Biography: Dr. Stephen H. Kan, an ASQC Certified Quality Engineer, is responsible for IBM Rochester's software quality strategy and plans, quality assessment, software measurements, and statistical analysis. He has been the software quality focal point for the software system of the AS/400 computer since its initial release in 1988.