Miracle-dz/UniFAR-FTUs huggingface dataset:
Handbook of practical camera calibration methods and models Optical Metrology Centre CHAPTER 4 CAMERA CALIBRATION METHODS

With a perfect lens system, light rays would pass from object space to image space and form a sharp image on the plane of focus according to the fundamental physical laws of optics. This model is often referred to as the pin-hole model where no distortion in the images is present and image quality is ignored. The reality of most lenses is that compromises necessary to minimise aberrations and imperfect construction means that elementary formulae are only good as a first approximation. Deviations from theoretically exact models, must be considered and mathematically modeled. Chapter 2 has provided a series of models for lens calibration and this chapter details various ways model parameters can be estimated.
Pianificazione Ottima di Reti di Stazioni Radiobase mediante Algoritmi Genetici a Codifica Binaria

The sudden growth of mobile communications, and more specifically the forthcoming new generations of mobile systems (such as UMTS) require the development of sophisticated tools for automatic and optimum planning and network design. Such systems must include accurate radiopropagation models, as well as efficient global optimizers. Due to the huge complexity of the task, the combined use of more than one radiopropagation model is needed, as well as their integrated use inside an optimization framework. An environment is proposed, based on a Geographical Information System (GIS) framework, inside which a wide variety of radiopropagation models can dynamically interact with a novel binary-coded genetic optimizer using multiple cost functions, so that the positioning, power sizing and tilting of radiobase antennas is optimized. Results on real cases, such as real GSM/DCS subnetworks, demonstrate the affordability and reliability of the system. The use of multiple cost functions, as well as the use of rigorous radiowave models, render the environment appropriate to achieve both radioprotection purposes (controlling the exposure of citizens to electromagnetic fields) and radiocommunication goals (for instance improving network coverage and quality-of-service).
A pathway-based data integration framework for prediction of disease progression

Motivation: Within medical research there is an increasing trend toward deriving multiple types of data from the same individual. The most effective prognostic prediction methods should use all available data, as this maximizes the amount of information used. In this article, we consider a variety of learning strategies to boost prediction performance based on the use of all available data. Implementation: We consider data integration via the use of multiple kernel learning supervised learning methods. We propose a scheme in which feature selection by statistical score is performed separately per data type and by pathway membership. We further consider the introduction of a confidence measure for the class assignment, both to remove some ambiguously labeled datapoints from the training data and to implement a cautious classifier that only makes predictions when the associated confidence is high. Results: We use the METABRIC dataset for breast cancer, with prediction of survival at 2000 days from diagnosis. Predictive accuracy is improved by using kernels that exclusively use those genes, as features, which are known members of particular pathways. We show that yet further improvements can be made by using a range of additional kernels based on clinical covariates such as Estrogen Receptor (ER) status. Using this range of measures to improve prediction performance, we show that the test accuracy on new instances is nearly 80%, though predictions are only made on 69.2% of the patient cohort. Availability: https://github.com/jseoane/FSMKL Contact: J.Seoane@bristol.ac. uk Supplementary information: Supplementary data are available at Bioinformatics online.
Precise set sharing and nullity analysis for java-style program

Finding useful sharing information between instances in object- oriented programs has been recently the focus of much research. The applications of such static analysis are multiple: by knowing which variables share in memory we can apply conventional compiler optimizations, find coarse-grained parallelism opportunities, or, more importantly,erify certain correctness aspects of programs even in the absence of annotations In this paper we introduce a framework for deriving precise sharing information based on abstract interpretation for a Java-like language. Our analysis achieves precision in various ways. The analysis is multivariant, which allows separating different contexts. We propose a combined Set Sharing + Nullity + Classes domain which captures which instances share and which ones do not or are definitively null, and which uses the classes to refine the static information when inheritance is present. Carrying the domains in a combined way facilitates the interaction among the domains in the presence of mutivariance in the analysis. We show that both the set sharing part of the domain as well as the combined domain provide more accurate information than previous work based on pair sharing domains, at reasonable cost.
A comparative performance evaluation of evolutionary algorithms for optimal design of three-phase induction motor

The attribute of an induction motor vary with the number of parameters and the performance relationship between the parameters also is implicit. In this paper a multi-objective problem is considered in which three phase squirrel cage induction motor (SCIM) has been designed in such a way that the efficiency is maximized while power density to be minimized simultaneously keeping various constraints in mind. Three well-known single objective methods such as tabu search (TS), simulated annealing (SA) and Genetic algorithm (GA) for comparing Pareto solutions has also been applied. Performance comparison carried out in this paper by performing different numerical experiments. The result shows that NSGA-II outperforms other three for the considered test cases.
A new constrained Independent Component Analysis method to analyze atrial arrhythmias

An arrhythmia occurs when the rhythm of the heartbeat is altered. Atrial arrhythmias are very common; they appear when electrical signals travel through the atria in a fast and disorganized way. The analysis of atrial arrhythmias include the estimation of the atrial component of the recorded electrocardiogram (ECG). This task can be done by Independent Component Analysis (ICA) since the atrial component is independent from the rest of signals superposed in the recording. We present a new algorithm based on ICA that adds to the independence ICA criterion a restriction about the waveform of the atrial signal. The constrained ICA algorithm allows to solve the inherent permutation ambiguity of ICA algorithms, since the first recover signal is the one close to the template incorporated to the separation process. The results confirm the goodness of this new algorithm since the ventricular component of the signal is canceled.
Design of a wide-band low-voltage grid impedance analyzer

In this paper the design and measurement results of a grid analysis and grid impedance measurement system are presented. The system is provided to measüre the freqüency dependent grid impedance in different PoCs to detect resonances and improve the power quality especially of grids with high amount of DERs. Moreover Active Filtering (AF) and reactive power feed-in are possible. It comprises also measurement of the negative and zero sequence as well as of subharmonics. The design of the converter is discussed in detail, the chosen method of impedance measurement is explained briefly, calculations for the selection of the converter topology and the selection of power semiconductor devices are made. A special hysteresis current control for 3-level Active Neutral Point Clamped (ANPC) converters is presented. Finally different measurement results are shown. These measurements of the grid impedance include subsynchronous frequencies in the range of 0.1 Hz to 30 Hz and frequencies in the range of 70 Hz to 10 kHz as well as measurements of the negative sequence and the zero sequence impedance of different low voltage grids.
Validation of a Simple Spherical Head Model as a Signal Capture Device for Head-Movement-Aware Prediction of Perceived Spatial Impression

In order to take head movement into account in objective evaluation of perceived spatial impression (including source direction), a suitable binaural capture device is required. A signal capture system was suggested that consisted of a head-sized sphere containing multiple pairs of microphones which, in comparison to a rotating head and torso simulator (HATS), has the potential for improved measurement speed and the capability to measure time varying systems, albeit at the expense of some accuracy. The error introduced by using a relatively simple sphere compared to a more physically accurate HATS was evaluated in terms of three binaural parameters related to perceived spatial impression – interaural time and level differences (ITD and ILD) and interaural cross-correlation coefficient (IACC). It was found that whilst the error in the IACC measurements was perceptually negligible when the sphere was mounted on a torso, the differences in measured ITD and ILD values between the sphere-with-torso and HATS were not perceptually negligible. However, it was found that the sphere-with-torso could give accurate predictions of source location based on ITD and ILD, through the use of a look-up table created from known ITD-ILD-direction mappings. Therefore the validity of the multi-microphone sphere-with-torso as a binaural signal capture device for perceptually relevant measurements of source direction (based on ITD and ILD) and spatial impression (based on IACC) was demonstrated.
Training sequence design for joint channel and frequency offset estimation with partial channel state information

We consider signal-carrier and single-user transmission over a frequency-selective channel. We focus on the data-aided joint estimation of the dispersive channel and the frequency offset. We propose a new training sequence selection strategy relevant for both parameters of interest in the context of a Ricean fading channel. Our strategy relies on the minimization of the mean-square error on data symbols at the output of a Wiener equalizer after frequency offset compensation. Simulations based on bit error rate confirm our claim.
Energy Efficient Data Centric Storage for Sensor Networks Employing Multilevel Grid Techniques

In this paper, we propose a new data centric storage using multilevel grid techniques for sensor network. The proposed method solves the hot-spot problems of existing data centric storages. By exploiting multilevel grid techniques, we lower or elevate the grid level of certain area according to the work load of sensor nodes. The level of a hot spot area is lowered so as that more sensor nodes cooperate to process data.
Reactive Balance Control after Stroke: Towards Enhanced Clinical Understanding and Assessment

Safe and independent mobility is a primary rehabilitation goal for those with stroke, of which balance control is a key determinant. The risk of falls post-stroke is high and fall rates rise dramatically soon after discharge from the hospital. Previous research has revealed the essential role that reactive balance control, specifically the capacity to initiate and execute a rapid step, has in preventing falls. Of concern, reactive balance control is not routinely assessed within physical therapy practice. Challenges to clinical assessment may include a lack of available methods that are safe, standardized and able to quantify and characterize balance responses. Therefore, this dissertation aimed to advance understanding of reactive stepping after stroke to inform and guide clinical assessment practices. The present findings affirmed that reactive stepping post-stroke is a significant problem not clearly revealed by commonlyused clinical measures that focus on voluntary control, thereby, supporting the need to develop targeted assessments of reactive balance control. Further, the findings revealed the potential for clinical uptake of alternate approaches, specifically the lean-and-release method, to assess reactive stepping among those in early stages of stroke rehabilitation. When paired with kinetic measurement technology, such approaches were able to quantify and reveal determinants of temporal dyscontrol of both the paretic and nonparetic lower-limbs, known to be associated
Effects of early unilateral blur on the macaque's visual system. I. Behavioral observations

We raised 8 macaque monkeys with chronic atropinization of one eye throughout the first 6–10 months after birth. This rearing procedure produces retinal image blur, with the most pronounced contrast attenuation occurring at high spatial frequencies. Measurements of contrast sensitivity were made using behavioral methods in 6 monkeys and evoked potential methods in 2 monkeys. The results showed that this rearing procedure produced long-term deficits in the contrast sensitivity and spatial resolution of the atropinized eye, which were not due to residual losses in accommodative capacity. There was considerable interanimal variation in the magnitude of the effects on visual performance. Similar losses in visual performance are seen in some forms of human amblyopia. Rearing monkeys with chronic instillation of atropine therefore provides a nonhuman primate model for studying the underlying neural mechanisms of anisometropic amblyopia.
Genomic Diversity and Evolution of Mycobacterium ulcerans Revealed by Next-Generation Sequencing

Mycobacterium ulcerans is the causative agent of Buruli ulcer, the third most common mycobacterial disease after tuberculosis and leprosy. It is an emerging infectious disease that afflicts mainly children and youths in West Africa. Little is known about the evolution and transmission mode of M. ulcerans, partially due to the lack of known genetic polymorphisms among isolates, limiting the application of genetic epidemiology. To systematically profile single nucleotide polymorphisms (SNPs), we sequenced the genomes of three M. ulcerans strains using 454 and Solexa technologies. Comparison with the reference genome of the Ghanaian classical lineage isolate Agy99 revealed 26,564 SNPs in a Japanese strain representing the ancestral lineage. Only 173 SNPs were found when comparing Agy99 with two other Ghanaian isolates, which belong to the two other types previously distinguished in Ghana by variable number tandem repeat typing. We further analyzed a collection of Ghanaian strains using the SNPs discovered. With 68 SNP loci, we were able to differentiate 54 strains into 13 distinct SNP haplotypes. The average SNP nucleotide diversity was low (average 0.06–0.09 across 68 SNP loci), and 96% of the SNP locus pairs were in complete linkage disequilibrium. We estimated that the divergence of the M. ulcerans Ghanaian clade from the Japanese strain occurred 394 to 529 thousand years ago. The Ghanaian subtypes diverged about 1000 to 3000 years ago, or even much more recently, because we found evidence that they evolved significantly faster than average. Our results offer significant insight into the evolution of M. ulcerans and provide a comprehensive report on genetic diversity within a highly clonal M. ulcerans population from a Buruli ulcer endemic region, which can facilitate further epidemiological studies of this pathogen through the development of high-resolution tools.
Text-Based Web Page Classification with Use of Visual Information

As the number of pages on the web is permanently increasing, there is a need to classify pages into categories to facilitate indexing or searching them. In the method proposed here, we use both textual and visual information to find a suitable representation of web page content. In this paper, several term weights, based on TF or TF-IDF weighting are proposed. Modification is based on visual areas, in which the text appears and their visual properties. Some results of experiments are included in the final part of the paper.
Dual-Transceiver Quantization Can Improve Error Performance in CDMA

A K-user direct-sequence spread-spectrum code- division multiple-access (CDMA) system with (q << log2 K) -bit baseband signal quantization at the demodulator is considered. It is shown that additionally quantizing the K + 1 level output signal of the CDMA modulator into q bits improves significantly the average bit-error performance in a non-negligible regime of noise variance, sigma2, and user load, beta, under various system settings, like additive white Gaussian noise (AWGN), Rayleigh fading, single-user detection, multi-user detection, random and orthogonal spreading codes. For the case of single-user detection in random spreading AWGN-CDMA, this regime is identified explicitly as sigma < gamma(q)yradicbeta, where gamma(q) is a certain pre-factor depending on q, and the associated BER improvement is derived analytically for q = 1, 2. For the other examined system settings, computer simulations are provided, corroborating this interesting behavior.
High-Resolution Mapping of Interstellar Clouds by Near-Infrared Scattering

We discuss the possibility of mapping interstellar clouds at unprecedentedly high spatial resolution by means of near-IR imaging of their scattered light. We calculate the scattering of the interstellar radiation field by a cloud model obtained from the simulation of a supersonic turbulent flow. Synthetic maps of scattered light are computed in the J, H, and K bands and allow us to make an accurate estimate of column density, in the range of visual extinction between 1 and 20 mag. We provide a formalism to convert the intensity of scattered light at these near-IR bands into a total gas column density. We also show that this new method of mapping interstellar clouds is within the capability of existing near-IR facilities, which can achieve a subarcsecond spatial resolution. This opens up new perspectives in the study of interstellar dust and gas structure on very small scales. The validity of the method has been recently demonstrated by the extraordinary images of the Perseus region that were obtained by Foster & Goodman and that motivated this investigation.
Hierarchical Recognition of Mixed Documents Consisting of the Korean/Alphanumeric Texts and Graphic Images

mCT In this paper, we propose an efficient algorithm which recognizes the mixed document consisting of the Korean/alphanumeric texts and graphic images. In the preprocessing step. we separate graphic image parts from the text parts by considering chain codes of cmected components. In the recognition step of the Korean/alphanumeric characters. we recognize the characters hierarchically using several features such as end points. branch points, cross points. partial projections. and distance features. Computer simulation shows that the proposed algorithm recognizes the mixed document effectively.
Bifurcation Analysis of a Semiconductor Laser with Filtered Optical Feedback

We study the dynamics and bifurcations of a semiconductor laser with delayed filtered optical feedback, where a part of the output of the laser reenters after spectral filtering. This type of coherent optical feedback is more challenging than the case of conventional optical feedback from a simple mirror, but it provides additional control over the output of the semiconductor laser by means of choosing the filter detuning and the filter width. This laser system can be modeled by a system of delay differential equations with a single fixed delay, which is due to the travel time of the light outside the laser. In this paper we present a bifurcation analysis of the filtered feedback laser. We first consider the basic continuous wave states, known as the external filtered modes (EFMs), and determine their stability regions in the parameter plane of feedback strength versus feedback phase. The EFMs are born in saddle‐node bifurcations and become unstable in Hopf bifurcations. We show that for small filter detu.
Profile-Based Adaptive DiffServ Policing with Learning Techniques

IETF's Differentiated Services (DiffServ) is a scalable, distributed architecture aimed to provide a fair distribution of network resources according to expected levels of service. However, variable traffic and performance expectations may require an adjustment of management policies so that congestion situations are avoided and service parameters are met. Existing solutions that improve the standard DiffServ architecture do not cope well with this dynamics and network resources are not efficiently managed, preventing user expectations from being properly fulfilled. In this paper we show how a reinforcement learning approach can optimize the choice of adaptation profiles for the optimal adjustment of ingress policies when a pre- congestion state is detected. Numerical results from simulations showed improvements for priority traffic (video) without impacting excessively the other traffic.
Relationship between the Development of Outer Hair Cell Electromotility and Efferent Innervation: A Study in Cultured Organ of Corti of Neonatal Gerbils

Outer hair cell (OHC) electromotility, which powers the cochlear amplifier, develops at a later stage of hearing ontogeny. There has been speculation whether efferents play a necessary role in directing or achieving OHC maturation in mammals. In this study, we examine whether the development of OHC motility depends on the establishment of efferent innervation of the cells’ synaptic pole by measuring electromotility of OHCs grown in cultures, deprived of efferent innervation. Tissue cultures of the organ of Corti were prepared from the cochleas of newborn gerbils. Solitary OHCs were obtained from 4- to 15-d-old cultures by enzymatic digestion and mechanical trituration. Length changes evoked by transcellular electrical stimulation were detected and measured with a photodiode sensor. Results show that OHCs develop electromotility between 6 and 13 d in culture without the presence of efferent innervation. The timetable for the onset of OHC electromotility is comparable with that in vivo. This demonstrates that the ontogeny of OHC electromotility is an intrinsic process that does not require the influence of efferent innervation.