Miracle-dz/UniFAR-FTUs huggingface dataset:
ELECTRE Methods in Solving Group Decision Supports System Bioinformatics on Gene Mutation Detection simulation

Analysis of genes expression can be done with the investigation of a particular microarray data for the description of a gen. This is done to identify whatgenes that were active in the human body. Detection of gene mutation is an activity that can provide contribution in the medical field. Detection of mutated gene is needed to avoid the diseases caused by themsuch as cancer. The detection of gene mutations can be performed by utilizing computer-based system. Group Decision Support System (GDSS) is a computer-based system that can be utilized in detecting human gene mutations that cause disease. The ELECTRE method, which is a Multi-Attribute DecisionMaking, is a method in modeling multi-criteria GDSS. In this paper we propose implementation of model for multi-criteria GDSS in which the simulation data is the mutated genes that can causecancer
Problem-Independent Approach to Multiprocessor Dependent Task Scheduling

This paper concerns Directed Acyclic Graph task scheduling on parallel executors. The problem is solved using two new implementations of Tabu Search and genetic algorithm presented in the paper. A new approach to solution coding is also introduced and implemented in both metaheuristics algorithms. Results given by the algorithms are compared to those generated by greedy LPT and SS-FF algorithms; and HAR algorithm. The analysis of the obtained results of multistage simulation experiments confirms the conclusion that the proposed and implemented algorithms are characterized by very good performance and characteristics. Keywords—Tasks scheduling, DAG, genetic algorithm, Tabu
Gravity compensation algorithms for parallel haptic interface

This paper presents an experimental comparison of different algorithms for the gravity compensation of parallel mechanisms, with special reference to a 5DOF haptic interface that has been realized at PERCRO. Two methods for the static balancing of this mechanism have been investigated: a classical method, based on Lagrange's approach and an algorithm that adopts the screw theory. This last method allows solving the problem in a more intuitive way. Some experimental results are reported in order to confirm this approach.
ROI-based tissue type extraction and volume estimation in 3D brain anatomy

In recent times, ROI-based extraction and volume estimation of various brain tissue types has gained immense attention from medical and computational research community. In diagnosing certain diseases, the volume of a specific brain region (e.g. Hippocampus) needs to be estimated to the best possible accuracy. Compared to the whole brain approaches, Region of Interest (ROI)-based approaches require an additional task of locating the ROI on subjects MRI. Given that no two brains are of the same size and shape, automatic extraction of ROI requires a certain degree of sophistication. The goal is to extract a particular region from brain imaging data and estimate the volumes of different tissue types (i.e., grey matter, white matter, and cerebro-spinal fluid) automatically. The experiments are conducted with ROI extraction using two softwares, namely, SPM and itk-SnAP. In the first one, whole brain segmentation is performed on normalized images and then a predefined mask is used to extract region of interest. itk-SnAP uses a region growing approach for segmentation. Results of these methods are compared and the analysis shows that both methods give comparable results. However, it is observed that itk-SnAP is more robust for calculating volumes of small regions. In this paper we proposed a pipelining process which contains different stages like normalization, ROI masks generation, segmentation and volume estimation by using VBM5 and itk-SnAP tools.
Pairwise representations of shape

Representation of arbitrary shape for the purposes of visual object recognition is an unsolved problem. This paper outlines some theoretical properties of shape representations based on stored geometric constraints that make them suitable for input to a 3D object recognition system. The construction of such representations is detailed together with an evaluation of their efficacy based on experimental findings. <<ETX>>
ALMA software scalability experience with growing number of antennas

The ALMA Observatory is a challenging project in many ways. The hardware and software pieces were often designed specifically for ALMA, based on overall scientific requirements. The observatory is still in its construction phase, but already started Early Science observations with 16 antennas in September 2011, and has currently (June 2012) 39 accepted antennas, with 1 or 2 new antennas delivered every month. The finished array will integrate up to 66 antennas in 2014. The on-line software is a critical part of the operations: it controls everything from the low level real-time hardware and data processing up to the observations scheduler and data storage. Many pieces of the software are eventually affected by a growing number of antennas, as more processes are integrated into the distributed system, and more data flows to the Correlator and Database. Although some early scalability tests were performed in a simulated environment, the system proved to be very dependent on real deployment conditions and several unforeseen scalability issues have been found in the last year, starting with a critical number of about 15 antennas. Processes that grow with the number of antennas tend to quickly demand more powerful machines, unless alternatives are implemented. This paper describes the practical experience of dealing with (and hopefully preventing) blocking scalability issues during the construction phase, while the expectant users push the system to its limits. This may also be a very useful example for other upcoming radio-telescopes with a large number of receivers.
A fuzzy learning algorithm for redundant manipulators using nonlinear programming

The fuzzy learning algorithm is a control algorithm which has been developed for the kinematic control of redundant robotic manipulators without any modelling of the manipulator itself. It is based on conventional kinematic control methods for manipulators combined with the techniques of fuzzy regression and fuzzy inferencing to learn the appropriate kinematic models based on actual trajectory data. In this paper, we modify the fuzzy regression formulation itself, which is a linear programming problem, to learn a fuzzy generalized inverse of the manipulator Jacobian, which is normally a non-unique matrix. However, we impose additional constraints in the fuzzy regression formulation, and modify the cost function to maximize the effect of the additional constraints, such that the matrix that is learned is one which optimizes the subtask as well as executing the main task of trajectory tracking. The modification of the cost function results in the fuzzy regression formulation being transformed into a nonlinear programming problem. <<ETX>>
Development of an Application Program for the Design and Analysis of Choice Experiments with R

This paper aims to develop an application program for the design and statistical analysis of choice experiments with R. Microsoft Excel is used as the user interface, and RExcel, which is included in the R-(D)COM Server, connects MS Excel and R. The AlgDesign and the survival package in R are used for designing the choice sets and analyzing a data set respectively. In the Japanese environment, this program has several advantages in comparison with MS Excel-based application programs or using R via the command prompt mode. First, it can design the choice sets via the GUI mode. Second, it automatically generates the data set for a conditional logit model. Finally, the accuracy of the estimation result is improved. However, since this program is designed for novice users of the choice experiments, the upper bound of the number of attributes, levels, alternatives per choice set, and choice sets is imposed, and an analytical model is limited to the conditional logit model.
A statistical framework to enlarge the potential of digital TV broadcasting

The use of formal probabilistic modelling together with advanced statistical inference in communications engineering, has the potential of providing a powerful workbench for deriving conclusions about the behaviour of systems and sources of data and therefore developing innovative and efficient control and management strategies of communication systems. Targeting the efficient dimensioning of systems and resources in order to make possible the provision of high-quality and larger-choice services to the end-users, this paper proposes the use of a Bayesian framework in video broadband communications. In the context of the combined transmission of several good-quality video sources, such as a digital television broadcast service, using VBR video encoding algorithms and based on prior beliefs and statistical models, an intelligent multiplexer is capable of predicting the probable amount of free space and fill it with extra services or increase the quality of the transmitted channels.
Plucked-string models: From the Karplus-Strong algorithm to digital waveguides and beyond

The emergence of what is called physical modeling and model-based sound synthesis is closely related to the development of computational simulations of plucked string instruments. Historically, the first physical approaches (Hiller and Ruiz 1971a, 1971b; McIntyre and Woodhouse 1979; McIntyre, Schumacher, and Woodhouse 1983) were followed by the Karplus-Strong (KS) algorithm (Karplus and Strong 1983). The KS algorithm was discovered as a simple computational technique that seemingly had nothing to do with physics. Soon thereafter, Julius Smith and David Jaffe showed a deeper understanding of its relation to the physics of the plucked string (Smith 1983; Jaffe and Smith 1983). Later, Julius Smith generalized the underlying ideas of the KS algorithm by introducing the theory of digital waveguides (Smith 1987). Digital waveguides are physically relevant abstractions yet computationally efficient models, not only for plucked strings, but for a variety of one-, two-, and three-dimensional acoustic systems (Van Duyne and Smith 1993; Savioja, Rinne, and Takala 1994; Van Duyne, Pierce, and Smith 1994). Further investigations embodied these ideas in more detailed synthesis principles and implementations, resulting in high-quality and realistic syntheses of plucked string instruments (Sullivan 1990; Karjalainen and Laine 1991; Smith 1993; Karjalainen, Valimaki, and Janosy 1993; Vilimaki, Huopaniemi, Karjalainen, and Jainosy 1996). A recent overview of research in this field is given by Smith (1996). The equivalence of Karplus-Strong and digital waveguide formulations in sound synthesis was already known when the waveguide theory appeared (Smith 1987, 1992, 1997); however, the relation has never been explicated in full detail. The first aim of this article is to show how the more "physical" waveguide model of a plucked string can be reduced to an extended form of the Karplus-Strong type that we call the single delay-loop (SDL) mod l. For a linear and time-invariant (LTI) case, this reduction is relatively straightforward, and results in a computationally more efficient digital filter structure. (Note that the historical order of the KS algorithm and digital waveguides is the reverse of their logical order, since the generalization was not developed until after the KS algorithm was designed. This article's title reflects the historical evolution: the "beyond" refers to recent generalizations and extensions of both concepts.) The second aim of this article is to discuss further extensions to the basic SDL models that make them capable of simulating plucking styles, beats in string vibration, sympathetic vibrations, and resonant strings. Such techniques have already been proposed and studied (Jaffe and Smith 1983; Smith 1993; Karjalainen, Vilimiki, and Janosy 1993). Here we discuss them in the context of our recent implementations of plucked-string models.
Comparison of Display Requirements Generated Via Hierarchical Task and Abstraction-Decomposition Space Analysis Techniques

Cognitive work analysis (CWA) techniques are the primary methods available for designers to obtain the knowledge required to create interfaces to complex systems involving cognitive work. There are a wide and growing variety of analysis methods available with a variety of claims for their relative strengths and weaknesses, but it is extremely rare for anyone actually to apply different analytic techniques to the same analysis problem. The work reported here begins to address this gap by directly comparing the information requirements produced by what are probably the 2 most commonly used analysis techniques-Rasmussen's (1985) Abstraction-Decomposition Space (ADS) or "Abstraction Hierarchy" and Shepherd's (1989) Hierarchical Task Analysis (HTA) technique. These 2 approaches were selected because each is well known in the literature, yet they rarely have been directly compared on a common problem. Our comparison shows that the techniques produce different yet complementary information about the interaction .
A secure image delivery scheme with regional protection capability using image inpainting and editing

Abstract In this paper, a secure image delivery scheme that can protect the privacy of secret region in the transmitted image is proposed. The secret region that requires protection is firstly analogised as the repairing and cloning region in the problems of image inpainting and editing. By inpainting and modified Poisson editing, the original protection region can effectively be concealed or disguised with other meaningful content. In the modified Poisson editing process, the twice Laplacian operator is used to improve the seamless transition on the boundary of protection region. The bits generated by the original content of the region are then reversibly embedded into the inpainted or disguised image to form the final protected image. The protected image can be delivered in channels securely, and the attacker cannot obtain the real content of the image without the keys. Experiments were conducted to show the effectiveness and security of the scheme.
Bayesian Data Analysis

Inference is the process of going from observed effects to underlying causes, and is the inverse process to deduction. Whereas deduction is exact, inference is imprecise, and necessarily probabilistic. Inference is the basis of science: we are always faced with observations we would like to explain in terms of underlying physical causes. Bayesian inference is an approach to the problem based on an identity in conditional probability (Bayes’s theorem). Notable Bayesians have included Pierre-Simon Laplace (who inferred the mass of Saturn from contemporary observations using Bayesian methods, and obtained a value consistent with modern estimates), the economist John Maynard Keynes, and the applied mathematician and geophysicist Harold Jeffreys. Bayesian inference has at times been controversial, because of its incorporation of subjective prior information into the process of inference. Historically the Bayesian approach was referred to as “subjective probability. ” In recent decades there has
How to Build a Low-Cost Eye-Tracking System

Eye tracking, previously the purview of well-funded laboratories, is now available to any individual who wishes to study gaze patterns. Advances in eye-tracking technology have made it possible for those with meager budgets but an abundance of motivation to engage in studies that examine participants’ eye movements and fixations. This article presents a how-to guide for creating low-cost eye-tracking solutions and includes discussion of optical hardware, tracking software, and data analysis programs. The wider availability of eye-tracking technology ensures that the broader scientific community has access to techniques that can inform design and enhance research.
Development of a computer aided product-form design tool based on numerical definition scheme and neural network

The evolution of a product form during the design process is typically governed by the designer’s individual preferences and creative instincts. As a consequence, there is a risk that the product form may fail to satisfy the consumers’ expectations or may induce an unanticipated consumer response. This study commences developing a computer aided product-form design (CAPD) tool based on numerical definition scheme (NDS) and back-propagation neural network (BPNN). A NDS approach is employed to depict an explicit product form, and a series of evaluation trials are then performed to establish the correlation between the product form features and the consumers’ perceptions of the product image. The results of the evaluation trials are used to construct a BPNN model to predict the likely consumer response to any arbitrary product form. The feasibility of developing a CAPD tool is demonstrated using a 3D knife form in this study. : Product form, Consumers’ perception, CAPD, NDS, BPNN
Effects of Thermal Annealing on the Optical Properties of Titanium Oxide Thin Films Prepared by Chemical Bath Deposition Technique

A titanium oxide thin film was prepared by chemical bath deposition technique, deposited on glass substrates using TiO2 and NaOH solution with triethanolamine (TEA) as the complexing agent. The films were subjected to post deposition annealing under various temperatures, 100, 150, 200, 300 and 399oC. The thermal treatment streamlined the properties of the oxide films. The films are transparent in the entire regions of the electromagnetic spectrum, firmly adhered to the substrate and resistant to chemicals. The transmittance is between 20 and 95% while the reflectance is between 0.95 and 1%. The band gaps obtained under various thermal treatments are between 2.50 and 3.0 ev. The refractive index is between 1.52 and 2.55. The thickness achieved is in the range of 0.12-0.14 μm. These properties of the oxide film make it suitable for application in solar cells: Liquid and solid dye-sensitized photoelectrochemical solar cells, photo induced water splitting, dye synthesized solar cells, environmental purifications, gas sensors, display devices, batteries, as well as, solar cells with an organic or inorganic extremely thin absorber. These thin films are also of interest for the photooxidation of water, photocatalysis, electro chromic devices and other uses.
An LMI approach to decentralized stabilization of interconnected time-delay systems

This paper deals with the problems of stability and decentralized stabilization of interconnected continuous-time linear systems with constant time-delays in the state of each subsystems as well as in the interconnections. Delay-dependent LMI based methodologies of stability analysis and decentralized stabilization via linear memoryless state-feedback are developed. Extensions of the stabilization result to more complex control problems, such as decentralized static output feedback, decentralized H/sub /spl infin// control, and decentralized robust stabilization are also discussed.
Multi-Robot Formation Control Based on the Artificial Potential Field Method

The artificial potential field method is one of multi-robot formation control methods. In this paper we make a study on multi-robot formation control based on the artificial potential field method and the leader-follower method. The robots are set leader robot and follower robots respectively. According to the known ideal distance between the leader and follower, we adjust the repulsiveness or attractiveness to maintain multi-robot formation. Multi-robots obstacle avoidance is adopted the artificial potential field method. In this paper the triangle formation is taken as an example. At last the simulation result proves the validity of this algorithm.
Literature Survey of SAR Algorithm in Photovoltaic System

Every solar energy harvester systems have got two sources of energy loss: the MPPT circuit and the dc–dc converter. To increase the efficiency of the PV energy harvester, the energy losses from the MPPT circuit and the dc–dc converter need to be minimized. Here a new MPPT algorithm called successive approximation register is introduced. This MPPT algorithm has got a power down mode and a fast tracking time, to achieve low power consumption and energy savings. With this MPPT algorithm energy losses from the MPPT circuit can be minimized and this technique can be greatly applicable to low power application systems mainly as well as for high power application. DOI: http://dx.doi. org/10.11591/ijece.v4i2. 4557
Using LAMS Version 2 for a game-based Learning Design

This article describes the use of LAMS for modelling and running a game-based Learning Design. In particular, it focuses on the new features in LAMS Version 2 (including branching in LAMS V2.1) to implement the proposed game design. The article also considers implementation issues such as monitoring of student progress, teacher intervention in student activities, and "traces" (records of student activities). The article concludes with options for rapid re-use and adaptation of the proposed game design using LAMS authoring. Editors: Laurence Vignollet (Universit e de Savoie, France). Interactive elements: Demonstration accounts for LAMS are available at http://demo.lamscommunity. org/ - by signing-up for an account here and importing the relevant LAMS design files (via Import under the File menu under Authoring in LAMS), educators can explore, run and modify the examples given here. The LAMS design for this article can be downloaded at http://www.lamscommunity. org/lamscentral/sequence? seq%5fid=627869
A real-time detection for traffic surveillance video shaking

Shaking happens to the traffic surveillance video inevitably, which can lead to the degradation of monitor system performance. A hierarchical gray project the correlation algorithm (HGPC) is proposed to solve the problem of the shaking in the traffic surveillance video. First, global hierarchical gray project correlation algorithm (GHGPC) is used to detect the video roughly. Then, in order to further improve the detection accuracy, we used the local hierarchical gray project correlation algorithm (LHGPC) to deal with the results from the rough matching. The experiment results on the video library HGTVL database show that the accuracy of the proposed algorithm is 91.4%, which is superior to the previous methods. In addition, the detection time is only 47ms, which meets the real-time requirement. Therefore, it is proved to be effective and feasible to dispose the video shaking. Keywords-video shaking; hierarchical; gray projection; correlation coefficient; real-time
Quick Start to Data Analysis with SAS

1. Introduction 2. SAS Programming Concepts 3. Preparing the Data for Analysis 4. Introduction to Data Step Programming 5. Combining Datasets 6. Introduction to Procedures 7. A Statistical Roadmap for the SAS System 8. Statistics for Single Variables 9. Statistics for Relationships with Continuous Dependent Variables 10. Statistics for Relationships with Categorical Dependent Variables 11. More About SAS Programming 12. PROCs That Create Datasets 13. Recoding and Labeling with PROC FORMAT 14. Working with Character Data 15. Putting It All Together APPENDIXES: A. Using the Display Manager / B. Resources / C. Common Problems (and Solutions) / Index
49.1: Invited Paper: Low Power, High Color Gamut, PenTile RGBCW Hybrid FSC LCD

Hybrid operation of a locally desaturated field sequential color (FSC) multiprimary backlight with a subpixel rendered multiprimary color filtered liquid crystal display offers the potential for lower power consumption and higher color gamut than conventional local dimming RGB filtered LCD TV panels, while further reducing color break‐up compared to locally desaturated FSC LCD w/o color filters.