Miracle-dz/UniFAR-FTUs huggingface dataset:
Particle Size Distributions in Heterogeneous Catalysts: What Do They Tell Us About the Sintering Mechanism?

Supported metal catalysts were treated at temperatures up to 900 °C, and sintering times up to 4000 h and the particle size distributions were determined via transmission electron microscopy (TEM), SEM and scanning transmission electron microscope (STEM). Sintering conditions were chosen so that the mechanism of sintering would range from Ostwald ripening to particle migration and coalescence. Previous theoretical models have suggested that a size distribution skewed towards small particles can arise from Ostwald ripening, while a size distribution with a long tail towards large particles can only come from particle migration and coalescence. Some of our experimental measurements were performed under conditions that favor Ostwald ripening, while others were performed under conditions that favor particle migration and coalescence. In every instance, the experimental particle size distributions could be fitted to a log normal distribution, and were always skewed to the right, with a tail towards larger particle diameters. Hence, we conclude that no inference about sintering mechanism can be derived from the particle size distribution.
Modeling HIV Dynamics Using Unified Mixed-Effects Models

SYNOPTIC ABSTRACT Studies of HIV dynamics play a crucial role in understanding the pathogenesis of HIV infection and in evaluating antiviral therapies. To accelerate AIDS clinical trials, viral load (HIV-1 RNA copies) is now used as a surrogate marker. The time range of collecting the viral load data may be divided into three successive stages. There are several existing models for the first and second stage viral load data. Recently a semiparametric nonlinear mixed-effects (NLME) model has been proposed for the complete viral load data which include the third stage viral load data, i.e., the data of those patients who fail the therapies. An important and challenging problem is if the existing models that are good only for the first one or two-stage viral load data can be generalized so that they are applicable for the complete viral load data. Another question is which model is the most preferred. In this paper, we propose a unified mixed-effects model, which models population characteristics and individual variations semiparametrically, so that all existing and recently proposed models are its special cases. We employ a basis-based approach to solve this model. We also discuss and generalize the existing and recently proposed models, including uniexponential, biexponential, multiexponential and biexponential semiparametric models. We employed AIC and BIC to compare these models and found that for the complete viral load data, the recently proposed biexponential semiparametric NLME model is the best.
Comparison between Waveform and Bug Path Planning Algorithm for Mobile Robot

Mobile robots frequently find themselves in a circumstance where they need to find a trajectory to another position in their environment, subject to constraints postured by obstacles and the capabilities of the robot itself. This study compared path planning algorithms for mobile robots to move efficiently in a collision free grid based static environment. Two algorithms have been selected to do the comparison namely wavefront algorithm and bug algorithm. The wavefront algorithm involves a breadth-first search of the graph beginning at the goal position until it reaches the start position. The bug algorithm uses obstacles borders as guidance toward a goal with restricted details about the environment. The algorithms are compared in terms of parameters such as execution time of the algorithm and planned path length by using Player/Stage simulation software. Results shown that wavefront algorithm is a better path planning algorithm compared to bug algorithm in static environment.
Polymorphism and Subtyping in Interfaces

RAPIDE is a programming language framework designed for the development of large, concurrent, real-time systems by prototyping. The framework consists of a type language and default executable, specification and architecture languages, along with associated programming tools. Interfaces are the central construct of the type system. This document describes RAPIDE interfaces, their expressiveness and their use as a typing construct.
CONTROL OF LARGE GRAPHICS DATA SET VISUALIZATION USING SCRIPT LANGUAGE

This paper describes certain area of scripting languages application in visualization process. The focus is on 3D geometric transformations. Algorithm of 3D object rotation is present in more detail and resulting real time implementation in Ruby is demonstrated. Integration into existing VR system for immersive visualization of complex datasets is explained. The object movement from start to destination position is implemented as sequence of sub-movements with particular increments of path. Visualization engine combines script and object to final result and the output is a scene with rotating object in real-time.
Reading Texts in Translation Classes: Discourse Analysis Perspectives

This paper aims at finding out what opportunities discourse analysis can offer in teaching translation. Specifically, it attempts to determine what areas of discourse analysis are relevant to teaching Arabic-English translation at college level as well as to identify what translation instructors and students can borrow from other related disciplines and make use of them in the classroom. A critical review of published theories and models was done to examine the main concepts in this regards. The paper concludes with emphasizing the role of discourse analysis in the shift from target text being purely equivalency-oriented text to a dynamic-oriented text.
Unsharp masking and its inverse processing integrated in a compression/decompression scheme: application to cardiac angiograms

Image data compression can be useful for storage or transmission of cardiac angiograms. In clinical systems, images are recorded in a `raw' format, and are usually processed with an edge enhancement filter to improve the visibility of medical information. The raw images are needed for other processing including quantitative measurements, and their enhanced version is used for display. We report on a compression scheme based on full-frame DCT which allows the integration of enhancement in the codec. We investigated whether the raw or the enhanced image should be compressed. We studied an inverse filter and integrated it in the decompression process, so that a non-enhanced image can be derived after enhancement and compression. The de-enhancement filter acts as a low pass filter for the quantization noise. We proposed to improve the inverse filter using a regularized signal restoration technique.
Measures that discriminate among online searchers with different training and experience

The major research objectives were to identify the differences among the searchers of users of online bibliographic systems who have different backgrounds of training and experience, and the differences among the searches of persons with and without experience of the Eric database. A quasi‐experimental research design used forty‐two searchers separated into five experience levels who conducted two pre‐selected searches using the Dialog system and the Eric database. The results were measured with variables which related to the search outcome, i.e., cost effectiveness, precision, and recall and to the search process and errors.
Chains of Reference in Computer Simulations

This paper proposes an extensionalist analysis of computer simulations (CSs). It puts the emphasis not on languages nor on models, but more precisely on symbols, on their extensions, and on their various ways of referring. It shows that chains of reference of symbols in CSs are multiple and of different kinds. As they are distinct and diverse, these chains enable different kinds of remoteness of reference and different kinds of validation for CSs. Although some methodological papers have already but implicitly taken into account the heterogeneity and variety of the relationships of reference in CSs, hence of cross-validations, this diversity is still overlooked in the epistemological literature on CSs. As a consequence, a particular outcome of this analytical and explicitly extensional view is an ability to classify existing epistemological theses on the epistemic status of CSs according to what their authors choose to select and put at the forefront: either the extensions of symbols, or the symbol-types, or the symbol-tokens, or the internal denotational hierarchies of the CS seen as a whole or the references of these hierarchies to external denotational hierarchies seen as wholes. Through the adoption of this extensionalist view together with its precise conceptual differentiations, it also becomes possible to explain more precisely the reasons why some complete reduction of the epistemic role of CSs to classical epistemic paradigms such as "experience", "experiment", or "theoretical argument" remains doubtful. On this last point, in particular, this paper is in agreement with what many epistemologists already have acknowledged. But it proposes new conceptual means - new in this context - to explain the situation further.
A Hybrid Approach For Spoken Language Machine Translation

In this paper, we propose a hybrid approach, which is a statistical machine translation (SMT), while using an example-based decoder. In this way, it will solve efficiently the re-ordering problem in SMT and the problems for spoken language MT, such as lots of omissions, idioms etc. We present a novel re-ordering model for SMT firstly and then an example-based decoder. Through experiments, we show that this approach obtains significant improvements over the baseline on a Chinese-English spoken language translation task.
Image-based logistic regression parameters of deforestation in Rondonia, Brazil

Achieves an improved understanding of those factors associated with deforestation in the tropics. We developed a logistic regression model of deforestation based on features detectable on Landsat imagery. The model was developed for a study area in Central Rondo/spl circ/nia, Brazil using images covering a 20-year time period. The model incorporates five main parameters in predicting the amount of deforestation on individual settlement lots. These include (1) proximity of a lot to nearest paved road (PPR); (2) proximity of a lot to nearest secondary road; (3) distance to nearest forest/cleared edge (PFC); (4) distance to a market center; (5) distance to a major urban center. PPR and PFC were the strongest indicators of deforestation. In Rondo/spl circ/nia, deforestation strongly follows the pattern of roads creating a fishbone network. Deforestation increases at the edges of forest clearings as agriculture becomes unproductive over time. Several other parameters including agriculture and pasture suitability indices and soil ranking, using ancillary GIS data were tested using logistic regression but accounted for little variability in the model. The model is compared to actual Landsat classifications and field verification of deforestation in cross validation scheme over the 20-year time period.
A digital phase‐locked loop with and filter

In general, it is known that if the stationary characteristics of a PPL, phase-locked loop, are improved, its transient response characteristics are deteriorated, while if the transient response characteristics are improved, its stationary characteristics are deteriorated. The DPLL, digital PLL, is not an exception in regards to the features. Here, we will realize a loop which is superior both in the effective phase error and the average transient response time compared with conventional DPLL with less deterioration of the average transient response time caused by improved effective phase error, due to inserting AND filter to the conventional binary quantized DPLL. The characteristics of the proposed loop are analyzed theoretically by use of the Markov chain and confirmed to be identical by computer simulation. These results prove that the proposed loop has better characteristics than the conventional ones.
A modified RBF neural network for efficient current-mode VLSI implementation

A modified RBF neural network model is proposed allowing efficient VLSI implementation in both analog or digital technology. This model is based essentially on replacing the standard Gaussian basis function with a piece-wise linear one and on using a fast allocation unit learning algorithm for determination of unit centers. The modified RBF approximates optimally Gaussians for the whole range of parameters (radius and distance). The learning algorithm is fully on-line and easy to be implemented in VLSI using the proposed neural structures for on-line signal processing tasks. Applying the standard test problem of the chaotic time series prediction, the functional performances of different RBF networks were compared. Experimental results show that the proposed architecture outperforms the standard RBF networks, the main advantages being related with low hardware requirements and fast learning while the learning algorithm can be also efficient embedded in silicon. A suggestion for current-mode implementation is presented together with considerations regarding the computational requirements of the proposed model for digital implementations.
Dynamic Frame Length ALOHA

Adding frame structure to slotted ALOHA makes it very convenient to control the ALOHA channel and eliminate instability. The frame length is adjusted dynamically according to the number of garbled, successful, and empty timeslots in the past. Each terminal that has a packet to transmit selects at random one of the n timeslots of a frame. Dynamic frame length ALOHA achieves a throughput (expected number of successful packets per timeslot) of 0.426 which compares favorably with the 1/e (\approx0.368) upper bound of ordinary slotted ALOHA.
Semantic Knowledge Representations for Soft Data Fusion

ion is the process of highlighting some of the aspects of a thing in order to grasp its characteristics. It is somehow a process of generalization. Abstracting an observable thing leads to a general representation of this reality, which is often called a concept. Data items are unprocessed and uninterpreted symbols. They are elementary descriptions of measurable properties. Information is what data items become once they have been interpreted and contextualized so to become useful within a specific objective and for a specific user. Having information is “knowing what is happening”. The information answers to questions such as “who? ”, “what? ”, “where? ” and “when? ” Knowledge is a combination of information with experience and judgment. It allows reasoning among information and interpreting data in order to create new data and information items. The knowledge answers to the question “How? ”. In the specific case of fusion, the notions of data, information and knowledge are also linked one to another within the process of abstraction (see Figure 1). The aim of information and data fusion is to have a representation of an external situation. This representation can be built thanks to observations of the external situation that are acquired through sensors and reported to fusion systems. Sensors are either low-level physical sensors, that report about physical measurements such as temperature or speed, or human observers that report about (some parts of) complex situations. In the first case, the physical sensors give a set of data that must be interpreted. The human sensors, on the contrary, provide interpreted information. Combining all the information items in order to deduce new information and pieces of knowledge is the role of the information fusion systems. Both data and information fusion systems use domain knowledge in order to interpret and combine the data and information items, according to a specific aim and within a specific context. Domain knowledge is also used in order to solve inconsistencies and discrepancies among the data and information items. 2.2 Soft data: a new challenge for decision support systems “Soft data” items are observations that are generated by humans. They may be expressed as unconstrained natural language (see Sambhoos et al. (2008)), through textual data or speech signal, but can also be made of semi constrained data items such as xml files or data bases, which are keyed in by humans through forms for instance. As soft data is provided by 4 Efficient Decision Support Systems – Practice and Challenges From Current o Future
ON THE BOOTSTRAP METHOD OF ESTIMATION OF RESPONSE SURFACE FUNCTION

Nowadays, in many fields of science it is necessary to carry out miscellaneous analyses using classical statistical methods, which usually have correct assumptions. These assumptions in the research realities cannot always be met, which makes it impossible to carry out analyses and leads to incorrect conclusions and recommendations. The study of the production process largely consists in the use of tools of statistical quality control which are based on classical statistical methods. These methods result in some improvements in technological and economic results of the manufacturing process. One of the tools of statistical quality control is the design of experiments, whose important element is the estimation of response surface function. The aim of this paper is to present the bootstrap method of estimation of response surface function and its use for empirical data.
Comparison of numerical and neural network methods for the kinematic modeling of a hybrid structure robot

A combination of parallel and serial mechanisms allows for stiff and dexterous motion of the robotic end-effector but increases the complexity of the kinematic problem. Many of the geometric parameters for such robots are difficult to obtain. This paper presents the numerical and neural network methods to solve the kinematics for such a hybrid robot named Exechon®. Both methods avoid the geometric measurement in the real robot. The geometric parameters used in the numerical model are identified by a particle swarm optimization algorithm. At the same time, a radial basis function-based neural network is trained to approximate the kinematics of the Exechon robot. The resultant models are then compared in terms of modeling accuracy and real-time ability. The presented methods are generic and can be applied to other robots with similar structures.
Asymmetry in Some Common Assignment Algorithms: The Dispersion Factor Solution

Many common assignment algorithms are based on Dial's original design to determine the paths that trip makers will follow from a given origin to destination centroids. The purpose of this paper is to show that the rules that have to be applied result in two unwanted properties. The first is that trips assigned from an origin centroid i to a destination j can be dramatically different to those resulting from centroid j to centroid i, even if the number of trips is the same and the network is perfectly symmetric. The second is that the number of paths that are ‘accepted’ by the algorithm can be surprisingly small. Asymmetry can cause numerous problems in transport model applications. It will not only produce unrealistic results, but also, as is demonstrated here, makes convergence toward supply — demand equilibrium impossible. The paper describes the principles on which Dial-type algorithms are based, the way in which they affect the transport model structure, and how the unwanted characteristics arise. An alternative algorithm, based on a dispersion factor and multipath search is presented, pointing out the advantages, both theoretical and operational, and some difficulties. A simple network is used as an example throughout the paper, and references to real applications are made.
Automated annotation of significant scenes based on structure of broadcast sports video

For broadcast sports video, the authors attempted automatic generation of semantic annotations for parts that seem important from the viewpoint of story, in accordance with the composition of the video and the game. First, the parts of a sports video which seem significant in the progress of the game are extracted from the closed caption text stream by keyword sequence search. The information concerning the play and the player in each part is extracted and the annotation is generated. Then, in order to determine the position in the video to which the annotation should be attached, the video is partitioned by similarly extracting the game-progress part by matching to the image stream. Finally, by establishing the time synchronization of the two streams, the generated annotation is attached to the video. An experiment was performed in which the method was applied to videos of American football games, as an example of sports videos. Automatic annotation was achieved accurately for the game-progress part with a reproduction rate of 75% and a match rate of 90%. © 2003 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 86(12): 69–78, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.10206
Binocular Stereo Matching Method Based on Parallax Waveform Analysis and Conjoint Measurement of Saliency Map

In this paper, we propose a coarse-fine matching algorithm based on parallax waveform analysis and conjoint measurement, which aims at performing the binocular stereo matching in natural scene. For the reason that human only notices the most saliency parts in image, we first extract the saliency areas of the two images, which suppresses the interference of background and reduces the computation cost. According to the saliency map, a global algorithm based on parallax waveform analysis is proposed to achieve the best coarse matching. On this basis, the fine matching is completed by analyzing the local features with the conjoint measurement of SAD and SSIM, which further improves the accuracy in binocular stereo matching. The performance of our algorithm is well demonstrated by experiments.
An efficient ARQ system for mobile communications

Two modifications of an ARQ (automatic repeat request) scheme proposed by E.J. Weldon (IEEE Trans. on Comm., vol.COM-30, p.480-486, March 1982) for use in systems with limited receiver buffer is studied. Unlike Weldon's scheme in which all erroneous data packets are discarded, the present schemes make use of copies of the data packet which may contain errors. A number of channel models are considered, namely a binary symmetric channel and a nonfading and a Rayleigh fading channel with additive white Gaussian noise. In all cases, it is found that the throughput can be substantially increased. Under poor channel conditions, the use of forward error correction can lead to further improvement. <<ETX>>