Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulation and coding for land mobile satellite channels

A summary is presented of the various modulation and coding techniques that have been investigated for 2.4/4.8-kb/s 5-kHz-spaced, land mobile satellite (LMS) channels. Two detection schemes are described which have many inherent advantages due to their common feed-forward processing structure. These are differentially coherent and pilot-aided detection. Based on the channel throughput and bit error rate (BER) performance requirements, i.e. 4.8 kb/s and 10/sup -3/ BER at 11 dB E/sub b//N/sub 0/, it is shown that rate-2/3, eight-phase-shift-keying (8PSK), trellis-coded modulation (TCM) with data symbol interleaving is the preferred modulation type. The receiver is implemented using differential detection augmented with feed-forward Doppler estimation. <<ETX>>
What's in a Name? The Importance of Naming grid Grobs When Drawing Plots in R

Any shape that is drawn using the grid graphics package can have a name associ- ated with it. If a name is provided, it is possi- ble to access, query, and modify the shape after it has been drawn. These facilities allow for very detailed customisations of plots and also for very general transformations of plots that are drawn by packages based on grid.
Simulating whole-body PET scanning with rapid analytical methods

Presents a 3D whole-body PET simulator that generates multiple, yet statistically accurate, realizations of projection data within a computation time that is short enough to enable the measurement of the task performance of image reconstruction algorithms. The whole-body simulator takes into account the following effects: the separate amounts of statistical noise contributed by true, scattered, and random coincidences, activity outside the field of view, activity decay between bed positions, detector efficiencies and resolution, and noise arising from the transmission scan. The principle of the simulation is to analytically calculate projections based on the geometrical specification of the emission and attenuation objects that comprise the MCAT phantom. A pre-determined level of statistical noise is then added to the projection data, which is then inputted to the same data correction and image reconstruction procedures used in practice. The authors compare the results of multiple realizations of simulated and measured phantom studies at statistical noise levels similar to those encountered in 3D whole-body PET scanning. They obtain comparable statistical noise properties for the fully corrected emission sinograms, and also show that a simple model accurately predicts the statistical noise added by random and scattered coincidences generated by activity outside the field of view.
Pulse amplitude-modulated time-based interface for off-chip interconnect

ABSTRACT An increased number of bits pulse amplitude-modulated differential-time signalling interface for off-chip interconnect is introduced in this article by combining the differential time signalling (DTS) technique with the pulse amplitude-modulation (PAM) approach. Applying the PAM to the DTS-transmitted signal increases the total number of the transmitted bits per symbol while maintaining the transmitted signal bandwidth. 4-bit 6 Gb/s DTS serial link has been designed and simulated using 65 nm CMOS mixed signal technology. 5-bit 7.5 Gb/s and 6-bit 9 Gb/s amplitude-modulated DTS serial links have been designed, simulated and compared to the 6 Gb/s DTS serial link. The three serial links use 1.5 Gb/s as input clock signal. In the amplitude-modulated DTS-transmitted signal, the rising and falling edges of the input clock signal are modulated in time as well as the transmitted signal amplitude is modulated. A reference clock pulse is generated from the input clock signal and embedded on the transmitted signal to be used as reference timing at the receiver circuit. The design details of the designed links are presented in the article. The 9 Gb/s link uses a 60 cm 4003C Rogers substrate as a transmission channel. The transmitted signal spectrum is presented and compared for the three designed links. The total power consumption of the 9 Gb/s amplitude-modulated DTS interface is less than 25 mW.
3D characterization of the arterial wall using intravascular ultrasound

The authors consider an application of tissue characterization techniques to images obtained from intravascular ultrasound. Three methods are considered, frequency tracking based on advanced spectral estimators, tissue characterization by edge detection, and characterization by textural analysis. A computer-based imaging system was developed that uses a multi-element catheter-mounted ultrasound probe. The system is capable of reconstructing three-dimensional models of arterial structures, which may be manipulated by computer software. The 3-D imaging capability allows a much more detailed analysis of complex stenoses and arterial lesions. An example of the results of this procedure is illustrated. <<ETX>>
HIERARCHIC AND NON-HIERARCHIC GROUPING METHODS: AN EMPIRICAL COMPARISON OF TWO TECHNIQUES

Hierarchic and non-hierarchic grouping methods are compared and the reallocation property of the latter is identified as an important advantage as it overcomes the problem of chaining, which is inherent in hierarchic methods. The two methods are used to produce regionalizations of crop composition data for the counties of Ohio in 1940. The grouping strategies are applied to the orthogonal crop dimen- sions from a Principal Components Analysis. Various data treatments are explored and their crucial method- ological role is noted in determining the group struc- ture of the final classifications. Different regionalizations were produced by each method and each data treatment. The non-hierarchic method gave simpler classifications. Stepwise discrim- inant analysis was used as a test of the efficiency of each method. Non-hierarchic classifications were more similar to the 'optimal' classifications produced by the discriminant analysis than those of the hierarchic method. The effect of subjective decisions in grouping strategies are often underestimated and the role of alternative methodologies in classification problems needs more careful evaluation.
Evolution based approaches to the preservation of endangered natural languages

Cultural algorithms, a form of evolutionary programming, employ a dual inheritance mechanism at population and knowledge levels to support problem solving, reasoning and knowledge extraction. Domain knowledge is extracted and separated from individuals within a population and is placed in a belief space. Hierarchical structures employed in the belief space help to accelerate and guide population evolution. The structure of the cultural algorithm lends itself well to a data rich, but knowledge poor distributed environment. In this paper we investigate the use of cultural algorithms to collect and mediate information collected from Web searches and Web services related to the task of acquiring and preserving knowledge about endangered languages where this knowledge about endangered languages where this knowledge is stored in a number of disparate sites.
Matimo: metaheuristic approach towards implementation of membership models in opportunistic network

Today there is a great demand to provide ubiquitous connectivity, even in those regions and geographical terrains which were previously considered inaccessible. Delay tolerant network has emerged as a strong potential candidate to achieve this ardent task as they are usually characterized by long delays and intermittent connectivity. In this paper we try to determine the optimized routing in delay tolerant network (DTN), by taking the concept of anycast routing that can be used for many applications in DTNs, as they prove useful when nodes wish to send messages to at least one, and preferably only one, of the members in destination group. In this paper we analyse anycast routing algorithm for DTNs by deploying metaheuristic technique of genetic algorithms (GAs) with the help of five membership models. These membership models yields a specified rate of delivery of message to the desired destination node. The GA is applied to use the concept of subpopulation to produce the next generation of the population of nodes based on out-degree and in-degree property of nodes. We propose a new Genetic algorithm driven routing algorithm to meet the routing needs of the nodes in the group and then exhibit the results after carrying out extensive simulation in MATLAB using five membership models.
Motion analysis of human ambulatory patterns

Studying the visual motion of human ambulatory patterns is of great importance for both vision research and applications. The authors first present three new algorithms for the recovery of three-dimensional structures from the motion of certain types of joints of articulated objects assuming perspective projection. Then based on the assumption that a human body can be considered as an articulated object and each part of the articulated object is rigid, they apply these algorithms to motion analysis of human ambulatory patterns in a combined way. The proposed algorithms have been tested in terms of the uniqueness of real solution and the speed of convergence using the synthesized data. <<ETX>>
World Wide Web Virtual Computer: reaching the active, global student

This paper addresses research using the World Wide Web (WWW) as a platform for the delivery of an interactive hypermedia tutorial and simulation package. Developed for active, global learners, the WWW Virtual Computer allows students to learn about and build a virtual computer. As a tutorial, the WWW Virtual Computer provides hypertext and digital movies on each of the components of a computer system. As a simulation, students can configure seventeen different components of the computer. After configuration, the student can run three benchmarks against the system to measure its performance. Each of the benchmarks provides an animation of which components of the computer are being heavily utilized as well as a description of which component of the computer system is the bottleneck. The student can then redesign the system to address performance bottlenecks and improve performance within student-selected constraints.
A simple modulation scheme for error performance improvement of low-deviation digital FM

The paper proposes a simple digital modulation scheme named LF (lowpass filtered)-/spl pi//2 TFSK. Since it is essentially a constant envelope modulation scheme, it can be applied to severely band-limited channels such as land mobile and satellite mobile radio channels. Its error performance is superior to that of MSK modulation in band-limited channels at the cost of a slightly wider bandwidth (approximately 1.06 times) than GMSK. The required E/sub b//N/sub 0/ with 2-bit differential detection at the error rate of 10/sup -5/ is 2.3 dB smaller than that of GMSK in an additive Gaussian channel and 3 dB smaller at the average error rate of 10/sup -4/ in a fast Rayleigh fading channel. The above result, obtained by an exact error rate analysis, was confirmed by laboratory experiments at a frequency of 880 MHz. The spectral characteristics were analyzed through computer simulations and the results were found to agree with those obtained from a hardware implementation. >
TEXT-INDEPENDENT SPEAKER RECOGNITION USING COMBINED LPC AND MFC COEFFICIENTS

There are so many techniques for textindependent speaker recognition. However this text-independent speaker recognition is very difficult because the recognition is performed irrespective of what one he is saying. This paper presents a very simple approach to text independent recognition where the recognition is performed by using both LPC and MFC coefficients in parallel and the results of both methods are combined for best matching of the speaker. Here the ANN is used for classification.
Reading text in images with EAST and Kaldi

Thinking of the motivation for using smart artificial systems to help or even substitute people when dealing with a specific task, one of the first aspects that comes on my mind is the speed computers are capable of working at. These systems are often solemnly called ”artificial intelligence”, which is wrong in my point of view, as they cannot perform the complex cognitive behavior as humans can do. However, when a specific (not complex) behavior is required to deal with a certain task, machines can be effectively used by taking advantage of their working pace and moreover of the fact they never get bored or tired. One of such applications is image processing in general. No living human is capable of browsing and processing thousands of images per second, but a well-designed artificial system possibly could be. This work is focused on reading text in images, especially in scanned documents, and motivated by a call for digitization of huge amount of archival scans and searching in them. The desired functionality of the developed system is what the commonly known shortcut CTRL+F does, however, applied on a scanned document instead of a digital text.
Modeling and Observations of Massive Star ClusterFormation

In the Universe’s panoply of star forming environments, super star clusters stand out as the most impressive. Their high densities, masses, and gas pressures are the extremes. But because so few examples exist in the Milky Way, and most are observed in distant blue compact dwarf galaxies, merger overlap regions, and similarly turbulent environments, details about their formation and early evolution remain obscure unknowns. In this dissertation, I outline my modeling efforts that provide useful observables to studies of both embedded and optically visible high mass star forming environments. New dust radiative transfer models provide a set of infrared colors that will help determine some basic envelope properties; their use will only be fully realized with the advent of the James Webb Space Telescope. Likewise, models of the molecular emission from the envelope sheds new light on our understanding of the geometry in these regions, and highlights the ways in which future Atacama Large Millimeter/submillimeter Array observations will shed light on super star cluster formation. Observations of a superassociation in the SMC provide some intriguing new insights into the dust and molecular properties of giant Hii regions at low metallicity and in hard radiation fields. And finally, Hi recombination line models offer compelling evidence that line pumping by the stellar continuum in Hii regions, and the subsequent line fluorescence, while important for the interpretation of Hydrogen line fluxes, can easily be overestimated with low-resolution input spectra. By modeling aspects of massive star cluster evolution from when they are deeply embedded in their natal molecular cloud until they are surrounded by an Hii region, I have touched upon some of the most important aspects relating their physical properties with their observable properties. Future observations and models are planned to continue these investigations and provide concrete answers to many of the questions that remain about massive cluster formation.
Simple computation of the coupling coefficient due to a rectangular current loop for loaded circular cavities

A simple method is described to compute the coupling coefficient due to a rectangular loop in a circular cavity that may be loaded with a dielectric resonator. The resonant frequency and the unloaded Q-factor are computed from the modal solution without the presence of the loop. An equivalent circuit is obtained for the unloaded cavity and the loop coupling is represented by a series inductance. As an example the resonant frequency (f/sub 0/), unloaded Q-factor (Q/sub 0/) and the coupling coefficient (K) for a dielectric resonator (DR) placed in a parallel plate cavity are computed. The measured input impedance of the parallel plate resonator is in good agreement with computed values.
MLOGITROC: Stata module to calculate multiclass ROC Curves and AUC from Multinomial Logistic Regression

mlogitroc generates multiclass ROC curves for classification accuracy based on multinomial logistic regression using mlogit. The algorithm begins by running mlogit B=100 times using bootstrapped records for each run while the original class labels are intact. Class prediction is then performed for records not sampled during bootstrapping, and accuracy for the left out records is determined as the fraction of correct class membership predictions. This results in B=100 realizations of the accuracy for the alternative distribution. Next, B=100 mlogit runs are made again, but this time after shuffling class labels of all records prior to modeling, which results in B=100 realizations of null accuracy. Smoothed probability distributions are obtained for the B=100 alternative and null accuracy values using kernel density estimation (KDE, Gaussian kernel) to obtain 100 smoothed realizations for alternative and null accuracy. The false positive rate (FPR), true positive rate (TPR), and area under the curve (AUC) are determined from the smooth pdfs derived from KDE. Twoway scatter plots of the smoothed pdfs are constructed, followed by plotting the ROC curve.
New Mathematic Method of Calculating Instantaneous Un-deformed Chip Thickness with Tool Run-out in Micro-end-milling

A new mathematic method of calculating instantaneous un-deformed chip thickness is established through analysis of true cutting tool tip trajectories. Two specific formulas are given in condition of two-flute and four-flute micro end milling. Then cutting process of each tooth with tool run out is analyzed by applying the new method in two-flute and four-flute micro slot milling. This new method considered comprehensive radial cutter run-out which include the spindle run-out and assemble errors and can be used to calculate the un-deformed chip thickness of cutting tools with any number of teeth. The accuracy and practicability are verified and some differences between micro milling and traditional milling process are pointed out by comparing the new method with other methods such as Bao’s and Newton-Raphson method. Cutting force is predicted based on the new method in micro slot milling experiment. The simulation result shows a very good agreement with experiment data.
Information Processing Effects of Accounting Consistency: Evidence from Egypt

Using path analysis, this study investigates the direct and indirect effect of accounting consistency and accounting-based earnings quality proxy on market synchronicity of the Egyptian listed firms. We firstly examine how time-series accounting consistency achieves earnings quality. We find a significant association between time series accounting consistency and lower variation of accruals residuals. We also examine the direct impact of accruals quality on stock returns synchronicity. We find a significant association between lower variation of accruals residuals and higher stock returns synchronicity. Finally we examine the direct and indirect impact of accounting consistency on market synchronicity. We find that the consistent use of accounting policies can achieve market synchronicity only after achieving earnings quality. Our findings indicate that earnings quality increases the effect of time series accounting consistency on achieving stock returns synchronicity.
HybridConcatenated Coding Scheme for MIMO Systems

Abstract: Inthis paper, two hybrid concatenated super-orthogonal space-time trellis codes(SOSTTC) applying iterative decoding are proposed for flat fading channels. Theencoding operation is based on the concatenation of convolutional codes,interleaving and super-orthogonal space-time trellis codes. The firstconcatenated scheme consists of a serial concatenation of a parallelconcatenated convolutional code with a SOSTTC while the second consists ofparallel concatenation of two serially concatenated convolutional and SOSTTCcodes. The decoding of these two schemes is described, their pairwise errorprobabilities are derived and the frame error rate (FER) performances areevaluated by computer simulation in Rayleigh fading channels. The proposedtopologies are shown to perform better than existing concatenated schemes with aconstituent code of convolutional andspace-time codes in literature.
Medical Diagnois using Simplified Multi-dimensional Fuzzy Reasoning

This paper proposes a method for computer-assisted medical diagnosis using simplified multi-dimensional fuzzy reasoning. The reasoning is based on the iterative use of fuzzy modus ponens and fuzzy modus tollens. Seven types of easy-to-gather production rules for fuzzy medical diagnosis are proposed. The fuzzy inference mechanism accepts patient's symptoms with attached degree of compatibility and infers diagnoses with a degree of certainty that expresses the degree to which it can be certain that the diagnosis is correct. Truthfulness of relationships between symptoms and diseases are fuzzily expressed in terms of linguistic truth values such as "Very True" and "Possibly True". Practical methods for the examination of unconfirmed symptoms and for the reexamination of given symptoms are also considered.
User Agents in the Interface to Digital Libraries

Digital libraries are promising to make an immense information universe available to users. Large volumes of multimedia data will flow through high speed communication networks to satisfy the requests placed by patrons in this virtual space where research will take place. However, availability does not automatically imply effortless access for every individual user or group of users. The volume, complexity and dynamism of the information managed by digital libraries pose significant problems in bridging the accessibility gap between users’ needs and available resources.
SEMANTIC SEGMENTATION OF INDOOR 3D POINT CLOUD WITH SLENET

Abstract. With the rapid development of new indoor sensors and acquisition techniques, the amount of indoor three dimensional (3D) point cloud models was significantly increased. However, these massive “blind” point clouds are difficult to satisfy the demand of many location-based indoor applications and GIS analysis. The robust semantic segmentation of 3D point clouds remains a challenge. In this paper, a segmentation with layout estimation network (SLENet)-based 2D–3D semantic transfer method is proposed for robust segmentation of image-based indoor 3D point clouds. Firstly, a SLENet is devised to simultaneously achieve the semantic labels and indoor spatial layout estimation from 2D images. A pixel labeling pool is then constructed to incorporate the visual graphical model to realize the efficient 2D–3D semantic transfer for 3D point clouds, which avoids the time-consuming pixel-wise label transfer and the reprojection error. Finally, a 3D-contextual refinement, which explores the extra-image consistency with 3D constraints is developed to suppress the labeling contradiction caused by multi-superpixel aggregation. The experiments were conducted on an open dataset (NYUDv2 indoor dataset) and a local dataset. In comparison with the state-of-the-art methods in terms of 2D semantic segmentation, SLENet can both learn discriminative enough features for inter-class segmentation while preserving clear boundaries for intra-class segmentation. Based on the excellence of SLENet, the final 3D semantic segmentation tested on the point cloud created from the local image dataset can reach a total accuracy of 89.97%, with the object semantics and indoor structural information both expressed.