Miracle-dz/UniFAR-FTUs huggingface dataset:
Theoretical and Empirical Properties of the Genetic Algorithm as a Numerical Optimizer

Abstract We investigate the basic form of the genetic algorithm as an optimization technique. Its failure to maximize a simple function of a string of 50 binary variables prompts a closer study of Holland's “schema theorem” and we find the implications of this result to be much weaker than are often claimed. Further theoretical results and exact calculations for simple problems provide an understanding of how the genetic algorithm works and why it failed in our original application. We show that the algorithm can be fine tuned to succeed in that problem but only by introducing features that could cause serious difficulties in harder problems.
How asymmetry helps load balancing

This paper deals with balls and bins processes related to randomized load balancing, dynamic resource allocation and hashing. Suppose n balls have to be assigned to n bins, where each ball has to be placed without knowledge about the distribution of previously placed balls. The goal is to achieve an allocation that is as even as possible so that no bin gets much more balls than the average. A well known and good solution for this problem is to choose d possible locations for each ball at random, to look into each of these bins, and to place the ball into the least full among these bins. This class of algorithms has been investigated intensively in the past but almost all previous analyses assume that the d locations for each ball are chosen uniform and independently at random from the set of all bins. We investigate whether a non-uniform and possibly dependent choice of the d locations for a ball can improve the load balancing. Three types of selections are distinguished: 1) uniform and independent 2) non-uniform and independent 3) non-uniform and dependent. Our first result shows that choosing the locations in a non-uniform way (type 2) results in a better load balancing than choosing the locations uniformly (type 1). Surprising, this smooth load balancing is obtained by an algorithm called "Always-Go-Left" which creates an asymmetric assignment of the balls to the bins. Our second result is a lower bound on the smallest-possible maximum load that can be achieved by any allocation algorithm of type 1, 2, or 3.
Cluster and calendar based visualization of time series data

A new method is presented to get an insight into univariate time series data. The problem addressed is how to identify patterns and trends on multiple time scales (days, weeks, seasons) simultaneously. The solution presented is to cluster similar daily data patterns, and to visualize the average patterns as graphs and the corresponding days on a calendar. This presentation provides a quick insight into both standard and exceptional patterns. Furthermore, it is well suited to interactive exploration. Two applications, numbers of employees present and energy consumption, are presented.
Moving visual representations of video objects for content-based search and browsing

This paper proposes object-based moving visual representations for quick browsing of video content. These representations are hierarchical, such that at the coarse level a sequence of alpha planes provides a moving representation of object shape and motion information for object contours. Alternatively, a 2D mesh representation provides a complete visual representation of object motion and shape. The finest level visual representation can be obtained by texture mapping onto the moving meshes. The paper also discusses trade-offs between each representation in terms of the amount of indexing information that needs to be stored, the robustness of the representation, and the accuracy of the representation.
An Architecture To Adapt Scalable Virtual Characters

Virtual humans and avatars are enhancing a lot of current computer applications. This leads to the usage of complex characters for presentations, e-learning tasks and virtual reality applications. Often it might be suitable to have the possibilty of scaling the character to avoid performace problems or to fit the personal needs of the user. An universal architecture to control the scaling of the character is presented. It is based on an Adaptation Engine and different scalability modules which can be configured to the preferences of the user and the graphical system.
Crop physiology calibration in CLM

Farming is using more terrestrial ground, as population increases and agriculture is increasingly used for nonnutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such pro5 cesses, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under 10 a given atmospheric forcing and available resources. CLMCrop development used measurements of gross primary productivity and net ecosystem exchange from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper we calibrate these parameters for one 15 crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). 20 Preprint ANL/MCS-P5150-0614
Cache-Oblivious Searching and Sorting

Algorithms that use multi-layered memory hierarchies efficiently have traditionally relied on detailed knowledge of the characteristics of memory systems. The cache-oblivious approach changed this in 1999 by making it possible to design memory-efficient algorithms for hierarchical memory systems without such detailed knowledge. As a consequence, one single implementation of a cache-oblivious algorithm is efficient on any memory hierarchy. The purpose of the thesis is to investigate the behavior of cacheoblivious searching and sorting algorithms through constant-factors analysis and benchmarking. Cache-oblivious algorithms are analyzed in the ideal-cache model, which is an abstraction of real memory systems. We investigate the assumptions of the model in order to determine the accuracy of cache-complexity bounds derived by use of the model. We derive the constant factors of the cache complexities of cache-oblivious, cache-aware, and traditional searching and sorting algorithms in the idealcache model. The constant factors of the work complexities of the algorithms are derived in the pure-C cost model. The analyses are verified through benchmarking of implementations of all algorithms. For the searching algorithms, our constant-factors analysis predicts the benchmark results quite precisely — considering both memory performance and work complexity. For the more complex sorting algorithms our results show the same pattern, though the similarities between predicted and measured performance are not as significant. Furthermore, we develop a new algorithm that lays out a cache-oblivious static search tree in memory in linear time, which is an improvement of the algorithms known so far. We conclude that by combining the ideal-cache model and the pure-C model, the relative performance of programs can be predicted quite precisely, provided that the analysis is carefully done.
Analysis of software Metrics Tools (A Survey Approach)

Measure the software and the software development process are very important for organization.This paper presents result of study in which we describe about the suit of object oriented design metrics based on java language and also i will explain which approach is better and easy when we are going to build the tool in java. As we know when we are calculate software metrics by different different tools the result will differ due to metrics tools use different methodology. For this purpose i will compare two methodology of sofwtare metrics tools with practical approach.
Stability-constrained model predictive control with state estimation

This article presents an extension to stability-constrained model predictive control (SCMPC) incorporating state estimation. It is proved that asymptotic stability of the closed loop system is guaranteed for SCMPC when a stable state estimator is used rather than direct measurement of the full state variables. The results are illustrated with experimental results from a real-time implementation of SCMPC with state estimation for control of a plasma enhanced chemical vapor deposition (PECVD) system.
Improved hydrogeophysical characterization and monitoring through parallel modeling and inversion of time-domain resistivity andinduced-polarization data

Electrical geophysical methods have found wide use in the growing discipline of hydrogeophysics for characterizing the electrical properties of the subsurface and for monitoring subsurface processes in terms of the spatiotemporal changes in subsurface conductivity, chargeability, and source currents they govern. Presently, multichannel and multielectrode data collections systems can collect large data sets in relatively short periods of time. Practitioners, however, often are unable to fully utilize these large data sets and the information they contain because of standard desktop-computer processing limitations. These limitations can be addressed by utilizing the storage and processing capabilities of parallel computing environments. We have developed a parallel distributed-memory forward and inverse modeling algorithm for analyzing resistivity and time-domain induced polar-ization (IP) data. The primary components of the parallel computations include distributed computation of the pole solutions in forw.
Reinforcement Learning for the Adaptive Control of Nonlinear Systems

The adaptive control of nonlinear systems is a nontrivial problem. Examples of this class of problems are found widely in many areas of control applications. While techniques for the adaptive control of linear systems have been well-established in the literature, there are few corresponding techniques for nonlinear systems. In this work an attempt is made to present a method for the adaptive control of nonlinear systems based on a feedfoward neural network. The proposed approach incorporates a neuro-controller used within a reinforcement learning framework, which reduces the problem to one of learning a stochastic approximation of an unknown average error surface. Emphasis is placed on the fact that the neuro-controller dose not need any input/output information about the controlled system. The proposed method promises to be an efficient tool for adaptive control for both static and dynamic nonlinear systems. Several examples are included to illustrate the proposed scheme. >
Advanced lithium ion battery charger

A lithium-ion battery charger has been developed for four and eight cell batteries or multiples thereof. This charger has the advantage over those using commercial lithium-ion charging chips in that the individual cells are allowed to be taper charged at their upper charging voltage rather than be cut-off when all cells of the string have reached the upper charging voltage limit. Since 30-60% of the capacity of lithium-ion cells maybe restored during the taper charge, this charger has the distinct benefit of fully charging lithium ion-batteries by restoring all of the available capacity to all of its cells.
Subspace based estimation of the signal to interference ratio for CDMA cellular systems

The signal to interference ratio (SIR) has been highlighted in the literature to be an efficient criterion for several radio resource management algorithms such as power control and handoff. We address the problem on how to obtain fast and accurate measurements of this quantity in a practical context. We develop a general SIR estimation technique for CDMA cellular systems, that is based on a signal subspace approach using the sample covariance matrix of the received signal. Analysis and simulation results for an IS-95 like system show that the SIR can be estimated to within 80 percent of the actual SIR after only 20 ms, or within 90 percent of the actual SIR after only 40 ms.
Effect of transition element substitution on thermoelectric properties of semiconductor clathrate compounds

Semiconductor clathrate compounds are energetically being studied as a new class of thermoelectric material based on the concept of Phonon Glass and Electron Crystal, since the materials combine glasslike low thermal conductivity and relatively good carrier mobility. These fascinating properties of clathrate compounds depend strongly on the details of their crystal structures. We will review our attempts to improve the thermoelectric properties of clathrate compounds by the modification of the electronic properties through the elemental substitution as well as by the optimization of doping level. We have revealed that the substitution of transition metal platinum, which causes the local ordering at the particular site of the framework, brings about a significant effect on the thermoelectric properties. The result indicates a new way for developing novel clathrate compounds with high thermoelectric performance.
Current-conveyor based field programmable analog array

An approach for designing field programmable analog array is described. The analog array is based on current-conveyors. It consists of a regular pattern of current conveyor based analog cells. This design benefits from the current conveyor characteristics (large bandwidth, low number of discrete elements needed), which provides designers with elementary current-mode blocks. An elementary cell based on a two current conveyors architecture has been developed. It is both used as an analog cell and an interconnection element. Each elementary cell is associated with tunable resistors and capacitors. The analog function is implemented by using the elementary cells programmed as current-mode amplifiers or continuous-time filters. The first step of this approach is to be able to develop basic analog functions such as low frequency filtering and amplifying. A new topology based on the developed analog elementary cell is proposed and should be shortly validate. The major difference compared with the previous proposed approaches is the use of the same element both as active element and switching element, with no use of transistor based switches in the signal path.
External stores grouping for aero database update

For any high performance fighter aircraft, validation and update of wind tunnel aero database from flight testing is a mandatory requirement for developing high fidelity simulators and for upgrading the control laws. System identification techniques are routinely applied by the aircraft industry for this purpose. The flight test effort increases manifold if all the store combinations are to be flight tested. The importance of grouping store combinations to reduce the flight test efforts towards aircraft system identification cannot, therefore, be undermined. This paper demonstrates the concept of store grouping using wind tunnel aero database of a high performance aircraft. Classification is performed using both longitudinal and lateral-directional aerodynamic characteristics. The store grouping tolerances are obtained heuristically by utilizing the standard deviation among the members of a particular store group. The success of the classification approach is demonstrated by presenting typical results of identified updates to the aerodynamic coefficients from flight test data and through time response validation plots. This concept of store grouping can be extended to provide clearance for any new store as the flight envelope is expanded.
Longitudinal Comparison of Desktop and fMRI Scanner Versions of the Computerized Test of Information Processing in Multiple Sclerosis: A Pilot Study

Deficits in information processing speed are common in individuals with MS, but adequate detection of such is fraught with methodological difficulties. The Computerized Test of Information Processing (CTIP) is a relatively new measure that addresses some of these methodological concerns. The equivalency of a desktop and fMRI scanner version of the CTIP at detecting cognitive impairment and monitoring cognition over time was examined in a sample of individuals with multiple sclerosis (MS). Six individuals with a confirmed diagnosis of MS completed both the desktop and a modified scanner version of the CTIP at baseline and 3 year follow-up. Both forms of the task remained equally as sensitive at detecting cognitive impairment across the two time points. Similarly, reaction time performance was generally equivalent across both forms although participants made more errors on the scanner task. No participant demonstrated reliably significant change in performance over time. A modified version of the CTIP adapted for use in an fMRI environment holds promise for the detection of information processing speed deficits in MS.
Intravascular microcatheters steered by conducting polymer actuators

Conducting polymer/solid polyelectrolyte actuating structures designed for realising steerable microcatheters are presented. They exploit the electromechanochemical phenomena of /spl pi/-electron conjugated conducting polymer occurring when ionic species are exchanged with the surrounding solid polyelectrolyte. Experimental determination of the governing material constants, modelling of the composite material and finite element computer simulations of the mechanical properties of cylindrical structures provide favourable indication about the feasibility of effective steerable, miniaturised catheters. Simulations about 2-3 Fr endoscope tips show that a degree of bending of about 30 and a developed distal force of about 4 gr can be obtained, The device would possess high potentialities for intravascular explorations and robotic-like diagnostic or surgical minimally invasive operations.
Multi-rate fusion of visual and inertial data

We present a method for fusing data from a vision system and an inertial measurement unit. The problem considered is that of pose estimation for a rapidly moving camera, and we show that given delayed low bandwidth visual observations of line correspondences and high bandwidth rate gyro measurements we are able to estimate the camera orientation with respect to an inertial frame. This can be done without knowing or estimating the camera position. The estimates are of high bandwidth and this is consistent with real-time constraints due to the complementary characteristics of the two sensors which are fused in a multi-rate way. The algorithm has interesting mathematical properties as it does not use any local parameterization of the orientation such as Euler angles. Instead, the state estimates evolve on the group of rotation matrices.
A scaled testbed for vehicle control: the IRS

Presents a testbed for vehicle control experiments: The Illinois Roadway Simulator (IRS). This is a scaled roadway suitable for easily visualizing preliminary vehicle control studies. The concept of the IRS is given along with the details of its design and construction. A review of vehicle dynamics gives the standard bicycle model for linear operating conditions. The parameters of the model are then obtained for representative IRS vehicles. The resulting vehicle dynamics are then compared with dynamics of full-scale vehicles for dynamic similitude. The dynamic similitude comparison is the key to gaining confidence in the scaled testbed as an accurate representation of actual vehicles. A series of experimental verifications are used to match the identified vehicle dynamics to the responses predicted by the standard vehicle model with some additional augmentations.
FaceID–Bones Narrate: A Semi Automated Approach for Forensic Facial Reconstruction

Forensic facial reconstruction is still at its infancy in Sri Lanka and is yet to utilize the advanced technologies of other countries. Hence introducing a more efficient multimedia based technique to the local forensic officials in order to improve the efficiency and the accuracy of the reconstructions is the aim of this study. In contrast to the other mechanisms used for facial reconstruction by others, this paper adopts a novel approach of muscle based facial reconstruction which goes hand in hand with the manual reconstruction process. The adopted process involved, acquiring a 3D model of the skull and digitally sculpting muscles in a 3D environment, followed by adding different facial features to improve identification. The research also encompassed a tissue thickness analysis that is conducted for the first time on Sri Lankans as well as a facial component analysis, both of which were needed to improve the accuracy of the final output. This procedure was attempted on cases of the age category 20-30 and of medium weight. The outputs and the process were evaluated with different parties such as general public, forensic officials, lawyers and CID all of which are to be benefited from this application. The ultimate goal of conducting the study was to understand and overcome the challenges faced in developing this novel application for the Sri Lankan Forensic officials and to establish the first unit for facial reconstruction in Sri Lanka. DOI: http://dx.doi. org/10.4038/icter.v6i1. 6097 International Journal on Advances in ICT for Emerging Regions 2013 6(1)
A robust singing melody tracker using adaptive round semitones (ARS)

In this paper, an approach for melody tracking is proposed and applied to applications of automatic singing transcription. The melody tracker is based on adaptive round semitones (ARS) algorithm, which converts a pitch contour of singing voice to a sequence of music notes. The pitch of singing voice is usually much more unstable than that of musical instruments. A poor-skilled singer may generate voice with even worse pitch correctness. ARS deals with these issues by using a statistic model, which predicts singers' tune scale of the current note dynamically. Compared with the other approaches, ARS achieves the lowest error rate for poor singers and seems much more insensitive to the diversity of singers' singing skills. Furthermore, by adding on the transcription process a heuristic music grammar constraints based on music theory, the error rate can be reduced 20.5%, which beats all the other approaches mentioned in the other literatures.
Adaptive algorithm for automatic analysis of electronystagmographic signals

The vestibular system is important for the maintenance of static and dynamic equilibrium of the human body. Dysfunctions within this system may lead to abnormal reflex eye movements known as nystagmus. It is possible to diagnose several pathologies of the human vestibular system through the analysis of this signal. In a previous work a computational algorithm that automatically evaluates the nystagmus' slow component velocity was developed. This algorithm gave good results when compared to the clinical analysis, but it did not foresee the possibility of expressive changes in the signal to noise ratio. Here, the author presents a new algorithm that monitors the level of noise associated to the signal and modifies its parameters in such a way as to improve the results. Comparisons between these two algorithms were done and the results indicate a clear superiority of this new technique over the previous one.