Miracle-dz/UniFAR-FTUs huggingface dataset:
A universal and robust human skin color model using neural networks

We propose a new image classification technique that utilizes neural networks to classify skin and non-skin pixels in color images. The aim is to develop a universal and robust model of the human skin color that caters for all human races. The ability to detecting solid skin regions in color images by the model is extremely useful in applications such as face detection and recognition, and human gesture analysis. Experimental results show that the neural network classifiers can consistently achieve up to 90% accuracy in skin color detection.
Estimation methods comparison of SVAR model with the mixture of two normal distributions - Monte Carlo analysis

This paper addresses the issue of obtaining maximum likelihood estimates of parameters for structural VAR models with a mixture of distributions. Hence the problem does not have a closed form solution, numerical optimization procedures need to be used. A Monte Carlo experiment is design to compare the performance of four maximization algorithms and two estimation strategies. It is shown that the EM algorithm outperforms the general maximization algorithms such as BFGS, NEWTON and BHHH. Moreover simplification of the probelm introduced in the two steps quasi ML method does not worsen small sample properties of the estimators and therefore may be recommended in the empirical analysis.
REAL-TIME GESTURE BASED HUMAN COMPUTER INTERACTION FOR OFFICE APPLICATIONS

The project proposes a method to control the movement of a mouse pointer using simple hand gestures and a webcam is proposed. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. Using the history of motion, the trajectory of the movement of the hand is drawn and then used to identify a gesture. A region of interest algorithm is proposed, in order to scale the motion when the user is located far away from the point of capture. The motion of the mouse pointer is scaled accordingly. Demonstrations using our prototype clearly illustrate the benefits of our system. We first created an Image Database consisting of four different hand gesture images. Before populating the database for an images of various gesture categories in Hand Gesture Recognition system, each image was first processed i.e., the images were converted to 8-bit grayscale images and filtering was performed to minimize any noise present in the images. The method mentioned above were applied on the input test images captured form the sensor device of the system to find the suitable match form the data base. The methods used were successful to retrieve the correct matches. The results based on speed and accuracy was analyzed.
Automatic traffic monitoring by intelligent sound detection

A traffic sensing technique is described which utilizes a microphone array to detect the sound waves generated by the road vehicles. The detected sounds are then digitized and processed by an on-site computer using a correlation based algorithm, which extracts key data reflecting the road traffic conditions, e.g. the speed and density of vehicles on the road, automatically on-site. In comparison with existing traffic sensors, the proposed system offers lower installation and maintenance costs and is less intrusive to the surrounding environment. The results of theoretical analysis, computer simulation and some preliminary experiments are presented.
Recognition of visual object classes

Humans can look at a scene or a photograph and easily recognize objects. Outside my window I can see cars, people walking a dog on a brick pathway, trees, buildings, etc. This perception is so effortless that it belies the difficulty of the task. Visual perception begins with light that is reflected from the scene into the eye. The light impinges upon the retina and is transduced by a two-dimensional array of photoreceptors into noisy electrical signals. The brain must then accomplish the difficult task of transforming from this low-level representation to a higher-level understanding of the scene in terms of regions, surfaces, textures, and objects. For computer vision the problem is the same, but the hardware is different. A camera approximates the function of the eye and retina; that is, the camera produces a two-dimensional array of numbers (pixel values) representing the intensity of light reflected from the scene. The fundamental question addressed in this thesis is the following: what mathematical processing should be applied to the pixel values in order for a computer to recognize objects? The methods we propose are not intended as a model of human brain function, although they may provide some insight. We are simply trying to solve the same visual recognition problems as the brain without concern for whether (or how) our algorithms could be realized in neuronal "hardware. " We have developed a new framework for recognizing visual object classes in which the class members consist of characteristic parts in a deformable spatial configuration. Human faces are an object class of this type, since faces consist of eyes, nose, and mouth arranged in a configuration that varies depending on expression and pose and also from one person to another. A second object class is cursive handwriting, which consists of loops, cusps, crossings, etc. arranged in a deformable pattern. In our approach, the allowed object deformations are represented through shape statistics, which are learned from examples. Instances of an object in an image are detected by finding the appropriate features in the correct spatial configuration. Our algorithm is robust with respect to partial occlusion, detector false alarms, and missed features. Potential applications include intelligent tools for finding objects in image data-bases, human-machine interfaces, user authentication, intelligent data gathering and compression, signature verification, and keyword spotting. Experimental results will be presented for two problems: (1) locating quasi-frontal views of human faces in cluttered scenes and with occlusions and (2) spotting keywords in on-line cursive handwriting data.
Compilations of communicating processes into delay-insensitive circuits

The authors address the compilation of VLSI programs described in CP-0 into VLSI circuits. So-called abstract circuits play a central role in the compilation method. Abstract circuits are obtained by a syntax-directed decomposition of CP-0 programs and may subsequently be implemented as delay-insensitive ('purely self-timed') circuits. The compilation method is presented together with an assessment of the performance of compiled delay-insensitive circuits based on first-time-right silicon. It is concluded that, with the compilation method presented, CP-0 programs of any complexity can be implemented as efficient VLSI circuits. <<ETX>>
How to use data swapping to create useful dummy data for panel datasets

"Many research data centres (RDCs) provide access to micro data by means of onsite use and remote execution of programs. An efficient usage of these modes of data access requires the researchers to have dummy data, which allows them to familiarize with the real data. These dummy data must be anonymous and look the same as the original data, but they do not have to render valid results. For complex datasets such as panel data or linked data, the creation of useful dummy data is not trivial. In this paper we suggest to use data swapping with constraints in order to keep some consistency and correlation between variables within crosssections and over time. It is easy to be implemented even for datasets with many variables and many survey waves. " (Author's abstract, IAB-Doku) ((en))
Thermal contact algorithms in SIERRA mechanics : mathematical background, numerical verification, and evaluation of performance.

We examine algorithms for the finite element approximation of thermal contact models. We focus on the implementation of thermal contact algorithms in SIERRA Mechanics. Following the mathematical formulation of models for tied contact and resistance contact, we present three numerical algorithms: (1) the multi-point constraint (MPC) algorithm, (2) a resistance algorithm, and (3) a new generalized algorithm. We compare and contrast both the correctness and performance of the algorithms in three test problems. We tabulate the convergence rates of global norms of the temperature solution on sequentially refined meshes. We present the results of a parameter study of the effect of contact search tolerances. We outline best practices in using the software for predictive simulations, and suggest future improvements to the implementation.
A Bargaining approach to optimizing load shedding in islanded microgrid operation

Abstract A microgrid is an emerging frontier in meeting the challenges in providing reliable power supply to a small community. Microgrid operation is one of the important topics on microgrid. The goal of microgrid operation is to maintain power balance. In an islanded operation mode of a microgrid, when power imbalance occurs by supply shortage, load shedding is generally used. For an efficient and fair load shedding, some game theoretic approaches have been proposed. The load-shedding schemes consider that a power consumer uses a continuous range of values to present its power demand. However, in reality, some consumers use integer and discrete values and it limits power utilization. In this paper, we define a load-shedding problem with consideration of the discrete characteristic of power demands. To solve the load-shedding problem, we employ a game theoretic approach. In order to show the functionality and performance of our load-shedding scheme, we implement a microgrid operation system by using our scheme.
A robust planning and control system handling fuzziness

A robust real-time planning and control system against the fuzziness, mainly caused by the behavior of the users, is proposed in this paper. The planner of the system constructs a tree-structured plan by a best-first algorithm giving priority to the reliable paths, and memorizes it. Based on the sensory information about the users, the controller executes the plan, selecting the most reliable and useful path of the tree. If no suitable path is available, the planner makes other plans within a limited amount of time. Therefore, the system realizes an interactive robot planning according to the user's reactions. To confirm the robustness of the planning system, we consider the simulation of an autonomous robot controlled by the planner, whose role is to assist a human worker. The robot transforms its plan according to the behavior of the worker. <<ETX>>
AFL-1: A Programming Language for Massively Concurrent Computers

Abstract : Computational models are arising in which programs are constructed by specifying large networks of very simple computational devices. Although such models can potentially make us of a massive amount of concurrency, their usefulness as a programming model for the design of complex systems will ultimately be decided by the design of complex systems will ultimately be decided by the ease in which such networks can be programmed (constructed). This thesis outlines a language for specifying computational networks. The language (AFL-1) consists of a set of primitives, and a mechanism to group these elements into higher levels structures. An implementation of this language runs on the Thinking Machines Corporation, Connection Machine. Two significant examples were programmed in the language, an expert system (CIS), and a planning system (AFPLAN). These systems are explained and analyzed in terms of how they compare with similar systems written in conventional languages.
Elektronik Kütüphane Hizmetlerinin Öğretim Elemanları Tarafından Benimsenmesinde Etkili Olan Faktörler: Anadolu Üniversitesi Öğretim Elemanları Üzerinde Bir Araştırma

The change occured in information and communication technologies has created a significant impact on libraries and information-documentation centers like any organizations. Transitions are taking place in paper-based systems toward electronic systems in the information services that libraries offered. In the presence of large investments made, the adoption and use of these systems by faculty members are becoming increasingly important. In this study, it is intended to define the factors that affect instructors’ adoption/use of electronic library services. To achieve this goal, Technology Acceptance Model (TAM) is used as a theoretical framework and some features in the extenden versions of the model are also considered. In the study individual differences such as innovativeness, self-efficacy and computer anxiety are examined within the context of TAM. The study was conducted with a sample of 426 academic staff working in Anadolu University. The structural equation modeling (SEM) technique was employed to explain the adoption process. The results proved that TAM to be a good theoretical tool to understand instructors’ acceptance/ use of electronic library services and also demonstrate the effects of individual differences (innovativeness, self-efficacy and computer anxiety) on usage intention through perceived ease of use and perceived usefulness. All of the individual differences have significant effects on perceived ease of use of electronic library services. In addition, innovativeness is a much broader concept, that has direct effects on attitude and usage intention. The research model explains 47% of the variance in the acceptance/use of electronic libraries by instructors.
Geographic Disparities in Accessibility to Food Stores in Southwest Mississippi

Disparities in accessibility to healthy food are a critical public-health concern. Poor access to reasonably priced, nutritious, and good-quality food may lead to poor diet and increase the risks of health problems such as obesity, diabetes, and cardiovascular diseases. This research advances the popular two-step floating catchment area (2SFCA) method by incorporating a kernel density (KD) function to form the ‘KD2SFCA method’. The study applies the method to measure the spatial access to food stores in southwest Mississippi, and examines the interaction between the spatial access and nonspatial factors. The research shows that neighborhoods with higher scores of urban socioeconomic disadvantage actually have better spatial accessibility to food stores; but higher percentages of carless households and lower income in some neighborhoods may compromise overall accessibility. Neighborhoods with stronger cultural barriers tend to be associated with poorer spatial accessibility. The study clearly differentiates spatial and nonspatial factors in access inequalities, and thus helps policy makers to design corresponding remedial strategies.
Image cancellation approach to depth-from-focus

ABSTRACT Depth calculation of an object allows computer reconstruction of the surface ofthe object in three dimensions. Such information provides human operators 3D meas-urements for visualization, diagnostic and manipulation. It can also provide the neces-sary coordinates for semi or fully automated operations. This paper describes a micros-copic imaging system with computer vision algorithms that can obtain the depth infor-mation by making use of the shallow depth of field of microscopic lenses. Background There are many ways of obtaining range (or depth) information. These methods can roughly beclassified into two categories: passive and active. [1,2] Active range methods usually require an activesource such as a laser and operate in a scanning motion. The typical passive range imaging method uses the principle of stereoscope. Two CD) cameras are mounted in close baseline. The two images obtained from the cameras are registered to generate the image disparities, and range information is cal-culated by triangulation.At high magnification (sub-micron resolution), confocal imaging systems use the shallow depth offield of a microscopic lens and scanning laser (or visible light) and detector in coherent motion to gen-erate sharp three dimensional images. [31 In recent years, confocal microscopy has become a powerfultool for biomedical research, as well as semiconductor metrology and inspection. [4] Confocal systemsrequire accurate scanning of mirrors and synchronization of detectors, and complex lens and light beamassembly. It does not lend itself for applications that require miniaturization of the imaging system.The depth-from-focus approach uses image processing techniques to deduce object depth informa-tion from blurring. The advantage is, it does not require stereo imaging heads, nor does it require scan-ning motion. A number of methods have been developed to solve the depth-from-focus problem. includ-ing theoretical derivations of 3D image formation and 3D OTF (optical transfer function)[5], deblurringof individual image sections using serial sectioning[6], range calculation from a single image based onblurring[7J, and range calculation from serial sections[8,91. The 3D OTF shows a missing frequencyresponse which can cause numerical problems. Depth detection based on image blurring is usually verysparse.In this paper, we will describe the microscopic imaging hardware that is used to obtain opticalsections. Optical sections are a series of images obtained from focusing on an object at different depths.We will present an iterative image cancellation algorithm to enhance object surface features at eachfocal plane. Based on the sharpness of these features, one can determine the focal plane they laid in.The image processing results are illustrated.
A MCDM MODEL FOR PERFORMANCE APPRAISAL

En This paper proposes a linguistic performance appraisal from a competency management perspective, where there are di®erent sets of reviewers taking part in the evaluation process that have a di®erent knowledge about the evaluated employees. Reviewers can express their assessments in di®erent linguistic domains according to their knowledge. The proposed method will conduct each linguistic label provided by reviewers as a fuzzy set in the common domain to compute collective assessments that will allow to the management team to make their decisions about employees.
Systems of correlations in rule and category learning: Use of structured input in learning syntactic categories

Abstract Three studies with artificial grammars investigated one property of natural language and one learning procedure which capitalises on this property to aid learning. Learning syntax is difficult because the rules and categories of syntax form a mutually defining system. Structural analogies to other systems (e.g. semantics, interaction) are limited and unreliable. On the other hand, treating syntax as a formal system and applying distributional analysis poses an extremely difficult learning problem. The property investigated is systematicity, coherence among multiple interpredictive features marking syntactic categories. The learning procedure is a method for directing attention to predictive features. This procedure predicts that an individual correlational rule or pattern will be learned more easily when it is part of a system of rules among intercorrelated features than when the identical rule occurs in isolation—complexity facilitates learning. The artificial grammar experiments varied the stru.
The great principles of the CRONE control

The paper deals with the great principles of the CRONE control. If the first generation CRONE strategy confers robustness on stability degree by reducing the phase margin variations by means of a constant phase CRONE regulator, the second generation CRONE strategy cancels these variations directly by means of a variable phase CRONE regulator. The third generation CRONE strategy is characterized by an open loop Black-Nichols Locus which forms an indifferent direction straight line segment around the unit gain frequency. This segment, called template, is used to construct damping contours in the Black-Nichols plane. <<ETX>>
Notice of Violation of IEEE Publication Principles Minimal cost attack aware routing and wavelength assignment in optical network security

Transparent optical networks based on wavelength division multiplexing (WDM) can exploit the huge capacity of optical fibers by dividing it among different wavelengths. Physical-layer attacks, such as high-powered jamming, can seriously degrade network performance and must be dealt with efficiently. Hence route lightpaths in such a way as to minimize the potential damage caused by various physical-layer attacks. A new objective criterion for the routing and wavelength assignment (RWA) problem, which we call the maximum Lightpath Attack Radius (maxLAR) is used to formulate the routing subproblem as an integer linear program (ILP). Lightpaths, are established between pairs of nodes. Given a physical topology and a set of lightpath demands, the RWA problem consists of finding a physical route for each lightpath demand and assigning to each route a wavelength, subject to the constraints. The maxLAR is the maximum number of lightpaths any one lightpath is link-sharing with, where link-sharing is defined as a property indicating whether two lightpaths traverse at least one common physical link. Results indicate that the formulation achieves significantly better results for the maxLAR. For larger networks, a tabu search algorithm for attack-aware lightpath routing, in combination with an existing graph-coloring algorithm for wavelength assignment is used. Testing and comparing with existing approaches from literature indicate its superiority with respect to the maxLAR and thus the congestion is reduced effectively.
Adaptive smoothing techniques for 3-D unstructured meshes

To correctly capture the behavior of deforming material volumes in 3-D, the Los Alamos unstructured grid code X3D has access to a variety of moving mesh algorithms. The authors present two such algorithms which markedly differ in their computational complexity. The first algorithm, Moving finite Elements for Surfaces, has only 2-D computational complexity, in that they only solve for interface motions and obtain volume point motions through interpolation. The second algorithm, Minimum Error Gradient Adaption, has 3-D complexity, since the volume tetrahedral deformations must be computed. Naturally, the 3-D complexity algorithm can model realistically a larger class of physical problems than the lower complexity approach. They present examples in metallic grain growth and semiconductor process modeling.