Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-level PO MPPT control PV system considering shadow influence

This paper proposes the multi-level (ML) PO MPPT control of the photovoltaic (PV) system considering shadow influence. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation and shadow influence. Particularly, PV module integrated converter (MIC) system is very sensitive to the shadow influence because the capacity is very small. In order to increase an output and efficiency of the solar power generation, the maximum power point (MPP) control are necessary. Conventional constant voltage (CV) perturbation and observation (PO) and incremental conductance(IC) are the method finding MPP by the continued self-excitation vibration. The conventional MPPT control is unable to be performed when output is rapidly changing by shadow influence. To solve this problem, the new control algorithm of the MLPO in which the step value changes by output change is presented. The proposed algorithm compares the output error of the conventional control algorithm with the solar radiation, a temperature and shadow influence. In addition, the validity of this algorithm is proved through the response characteristics of the output error.
MODULES WITH SLIDING DEPTH

Several bounds for the depth of quotients of the symmetric algebra of a finitely generated module over a local C.M. ring are obtained, when its maximal irrelevant ideal is generated by a proper sequence of 1-forms and modulo conditions on the depth of the homology modules of the Koszul complex associated to this ideal (sliding depth conditions).
Simulation of rendezvous and docking between service spacecraft and non-cooperative target with MATLAB-Simulink and STK

A mathematical simulation method is presented to demonstrate proximity operation of rendezvous by utilizing MATLAB-Simulink and Satellite Tool Kit (STK). Relative position and attitude coupled dynamic model is established with kinematic and dynamic coupled effect of relative rotation on relative translation. It's used to illustrate relative motion between docking port on tumbling non-cooperative target spacecraft (T) subjected to external disturbances and another docking port on service spacecraft (S). It is common for spacecraft systems to be modeled with MATLAB-Simulink and STK for the sake of improving data precision and reliability of the numerical simulation. A versatile MATLAB-STK interface is adapted to propagate requisite parameters from MATLAB to STK and save calculation data from STK to MATLAB workspace. Moreover, an animation scenario is built for describing the whole proximity process vividly. Simulation results demonstrate high precision and authenticity of the proposed coupled relative motion model and high efficiency of MATLAB-STK interface is proved.
J un 2 00 6 Self-similar power transforms in extrapolation problems

A method is suggested allowing for the improvement of accuracy of self-similar factor and root approximants, constructed from asymptotic series. The method is based on performing a power transform of the given asymptotic series, with the power of this transformation being a control function. The latter is defined by a fixed-point condition, which improves the convergence of the sequence of the resulting approximants. The method makes it possible to extrapolate the behaviour of a function, given as an expansion over a small variable, to the region of the large values of this variable. Several examples illustrate the effectiveness of the method.
Self-Supervised Clustering for Codebook Construction: An Application to Object Localization

Approaches to object localization based on codebooks do not exploit the dependencies between appearance and geometric information present in training data. This work addresses the problem of computing a codebook tailored to the task of localization by applying regularization based on geometric information. We present a novel method, the Regularized Combined Partitional-Agglomerative clustering, which extends the standard CPA method by adding extra knowledge to the clustering process to preserve as much geometric information as needed. Due to the time complexity of the methodology, we also present an implementation on the GPU using nVIDIA CUDA technology, speeding up the process with a factor
A New Nonlinear Diffusion Method to Improve Image Quality

We propose a nonlinear diffusion method based on the gradient vector field construction to remove noises in image while preserving fine details. The blocky effect and over-smoothing, as usually seen in images processed by diffusion operators, are greatly reduced by our method. Results obtained from various images, including synthetic and magnetic resonance imaging (MRI), are used to demonstrate the performance of our new method. Comparing it with other diffusion methods, we find it obtains better performance in terms of removing noises without destroying detail features of images.
The Optimal Duration of Executive Compensation: Theory and Evidence

While much is made of the ills of “short-termism” in executive compensation, in reality very little is known empirically about the extent of short-termism in CEO compensation. This paper develops a new measure of CEO pay duration that reflects the vesting periods of different components of compensation, thereby quantifying the extent to which compensation is short-term and the extent to which it is long-term. It also develops a theoretical model that generates three predictions for which we find strong empirical support using our measure of pay duration. First, optimal pay duration is decreasing in the extent of mispricing of the firm’s stock. Second, optimal pay duration is longer in firms with poorer corporate governance. Third, CEOs with shorter pay durations are more likely to engage in myopic investment behavior, and this relationship is stronger when the extent of stock mispricing is larger.
Cross-Layer Optimization of Voice over IP in Wireless Mesh Networks

In non-static multi-radio/multi-channel wireless mesh networks architectures such as Net-X, mesh nodes need to switch channels in order to communicate with different neighbors. Present channel schedulers do not consider the requirements of real time traffic such as voice over IP. Thus the resulting quality is low. We propose a novel channel scheduler for the Net-X platform that takes into account packet priorities. We evaluate the algorithm on the KAUMesh testbed. Our algorithm outperforms the standard round-robin scheduler both in terms of average delay and jitter.
Heat tolerance level in dairy herds: a review on coping strategies to heat stress and ways of measuring heat tolerance

Tolerance to heat stress is worth noting considering the constant increase in the ambient temperature and high productivity that elevates the likelihood of heat stress in the dairy herd. Besides exposure to hot temperatures, increase in performance of dairy cows is positively related to heat load which results in heat stress. This necessitates the need to incorporate heat tolerance in the breeding objectives. Measuring heat tolerance is still a challenge and might be complex to assess in the dairy herd. Through regressing phenotypic performance of temperature–humidity index (THI), heat tolerance can be assessed. However, the use of the same THI across region might not be effective due to the differences within and among breeds in either same or different herds. The reason being the differing cow’s (Bos taurus) adaptive and productive response to increasing THI value across different areas. There is vast information about the THI values from the tropics and the temperate regions, however, there is still a gap for THI values for semi and arid places under the pasture-based system. Understanding the coping strategies by the dairy cow to heat stress is important. Various studies have outlined much on the coping strategies but there is still a need to relate the homeostatic and acclimation responses to tolerance to heat stress. This review focusses on discussing the heat stress coping strategies in relation to heat stress tolerance and the ways of assessment in a dairy herd.
Designing a Fast and Reliable Main Memory with Memristor Technology

Several memory vendors are pursuing different kinds of memory cells that can offer high density, non-volatility, high performance, and high endurance. In this work, we focus on Memristor technology and identify some of the significant problems in state-of-the-art implementations. These problems include sneak currents during reads and non-uniformity in cell behavior within an array. These problems manifest as long read latencies, long write latencies, and high cache line error rates. To address these problems, we introduce multiple innovations to a memristor memory system: (i) We employ a background sneak current read that can be amortized across several other data reads from the same column, thus introducing “open-column” semantics for memristor array access. (ii) We also introduce a novel data mapping policy that reduces multi-bit error rates in cache lines. However, this policy also increases the average write latency for a cache line. (iii) We overcome this drawback by introducing data compression and avoiding poorly behaving cells during writes. The result is a memristor memory system that performs 12% better and has 30X lower probability of suffering a two-bit error compared to the baseline.
A new approach for LSB based image steganography using secret key

This paper introduces a best approach for Least Significant Bit (LSB) based on image steganography that enhances the existing LSB substitution techniques to improve the security level of hidden information. It is a new approach to substitute LSB of RGB true color image. The new security conception hides secret information within the LSB of image where a secret key encrypts the hidden information to protect it from unauthorized users. In general, in LSB methods, hidden information is stored into a specific position of LSB of image. For this reason, knowing the retrieval methods, anyone can extract the hidden information. In our paper, hidden information is stored into different position of LSB of image depending on the secret key. As a result, it is difficult to extract the hidden information knowing the retrieval methods. We have used the Peak Signal-to-Noise Ratio (PSNR) to measure the quality of the stego images. The value of PSNR gives better result because our proposed method changes very small number of bits of the image. The obtained results show that the proposed method results in LSB based image steganography using secret key which provides good security issue and PSNR value than general LSB based image steganography methods.
New Results on Deterministic Cramér–Rao Bounds for Real and Complex Parameters

The Cramér-Rao bounds (CRB) is a lower bound of great interest for system analysis and design in the asymptotic region [high signal-to-noise ratio (SNR) and/or large number of snapshots], as it is simple to calculate and it is usually possible to obtain closed form expressions. The first part of the paper is a generalization to complex parameters of the Barankin rationale for deriving MSE lower bounds, that is the minimization of a norm under a set of linear constraints. With the norm minimization approach the study of Fisher information matrix (FIM) singularity, constrained CRB and regularity conditions become straightforward corollaries of the derivation. The second part provides new results useful for system analysis and design: a general reparameterization inequality, the equivalence between reparameterization and equality constraints, and an explicit relationship between parameters unidentifiability and FIM singularity.
Impedance Analysis of Bunch Length Measurements at the ATF Damping Ring

We present energy spread and bunch length measurements at the Accelerator Test Facility (ATF) at KEK, as functions of current, for different ring rf voltages, and with the beam both on and off the coupling resonance. We fit the on-coupling bunch shapes to those of an impedance model consisting of a resistor and an inductor connected in series. We find that the fits are reasonably good, but that the resulting impedance is unexpectedly large.
High accuracy visual servoing for aerial manipulation using a 7 degrees of freedom industrial manipulator

This paper is devoted to the performance optimization of an aerial manipulation system composed of a Flettner-helicopter and 7 DoF manipulator. With experiments we demonstrate that the time delays in signal propagation between perception and actuation modules play an important role for the overall performance of an aerial manipulator system using visual servoing. We present an approach for estimation of the perception-action time delay and its active compensation based on the predicted motion of the manipulator end-effector.
Low-leakage power-rail ESD clamp circuit with gated current mirror in a 65-nm CMOS technology

A new power-rail ESD clamp circuit is proposed and verified with consideration of the gate leakage issue in 65-nm CMOS technology. The proposed circuit can reduce the total leakage current of the traditional power-rail ESD clamp circuit in two orders of magnitude. Moreover, the proposed circuit reduces the required silicon area by boosting the capacitor with a current mirror. The measured leakage current of the proposed power-rail ESD clamp circuit is 220nA (VDD = 1V, T=25°C), much lower than the 20. 55μA of the traditional design. In addition, the required area for the proposed design is 50μm × 30μm, which is a 40% reduction in silicon area to the traditional one, that can sustain the HBM (MM) ESD stress of 3.5kV (250V).
Ieee Computer Graphics and Applications 55 Visualizing the Surface of a Living Human Brain

C adaver dissection is widely accepted as the gold standard for anatomy education. It provides students with knowledge of or-gans' shape and size, gives them an appreciation of spatial relationships between organs, and introduces them to death in a controlled manner. However , financial and ethical pressures have reduced this approach's availability and use. 1 So, anatomy education today employs a variety of approaches, including physical models, pro-sections (dissections of a cadaver), problem-based learning scenarios, and interactive computer-graphics-based systems. These approaches offer potential benefits to students but have drawbacks. For example, physical models are useful for teaching spatial relationships. However, their lack of close resemblance to the human body requires that instructors adequately explain the correspondence between the models and the associated body parts. 2 Computer-generated anatomy models can be more flexible but are rendered in grayscale or in pseudo-color that's at best a gross approximation of healthy living organs' true appearance. Even cadaveric specimens differ considerably in appearance from when they were live tissue. Photographs are static, 2D, and typically show only a section of the organ. We believe that more realistic 3D models of internal human anatomy will improve anatomy education, preparing novice surgeons or nurses to more easily recognize anatomy the first time they're exposed to an operation on a real patient. We also wanted to create high-fidelity anatomical models for use in interactive surgical simulators. We selected the human brain as the target organ for our initial experiments. The brain is difficult to access in situ and is challenging to model owing to its complex surface structure. We've already produced a training simulator for ventricular catheterization 3 and wanted to improve the visual fidelity of the brain model it uses. This procedure exposes an area of the patient's brain (similar to that in Figure 1), letting surgeons insert a catheter through the brain tissue until it punctures the lateral ventricle. They can then drain cerebrospi-nal fluid from the ventricles. As the catheter initially penetrates brain tissue, some deformation of the nearby brain surface occurs ; our simulator will need to implement this effect in real time. We obtained access to both a cadaveric dissection room and an operating theater during a neu-rosurgical procedure to obtain color data from calibrated photography of exposed brain tissue. We obtained the parameters required for a bidirectional reflectance distribution function (BRDF) and used them in the rendering pipeline. The cadaveric-brain data …
Hand-dorsa vein recognition based on partition Local Binary Pattern

A new hand-dorsa vein recognition method based on Partition Local Binary Pattern (PLBP) is presented in this paper. The proposed method employs hand-dorsa vein images acquired from a low-cost, near infrared device. After preprocessing, the image is divided into sub-images. LBP uniform pattern features are extracted from all the sub-images, which are combined to form the feature vector for token vein texture features. The method is assessed using a similarity measure obtained by calculating the distance between the feature vectors of the tested sample and the target sample. The algorithm is tested on a database of 2040 images from 102 individuals built up by a custom-made acquisition device. The experimental results show that PLBP performs better than other features.
Sensorimotor adaptation of speech I: Compensation and adaptation.

When motor actions (e.g., reaching with your hand) adapt to altered sensory feedback (e.g., viewing a shifted image of your hand through a prism), the phenomenon is called sensorimotor adaptation (SA). In the study reported here, SA was observed in speech. In two 2-hour experiments (adaptation and control), participants whispered a variety of CVC words. For those words containing the vowel /E/, participants heard auditory feedback of their whispering. A DSP-based vocoder processed the participants' auditory feedback in real time, allowing the formant frequencies of participants' auditory speech feedback to be shifted. In the adaptation experiment, formants were shifted along one edge of the vowel triangle. For half the participants, formants were shifted so participants heard /a/ when they produced /E/; for the other half, the shift made participants hear /i/ when they produced /E/. During the adaptation experiment, participants altered their production of /E/ to compensate for the altered feedback, and these production changes were retained when participants whispered with auditory feedback blocked by masking noise. In a control experiment, in which the formants were not shifted, participants' production changes were small and inconsistent. Participants exhibited a range of adaptations in response to the altered feedback, with some participants adapting almost completely, and other participants showing very little or no adaptation.
The technique of MIEELDLD as a measure of the shock-capturing property of numerical methods for hyperbolic conservation laws

In this paper, we use some numerical methods namely Lax-Wendroff (LW), two-step Lax-Friedrichs (LF), two variants of composite methods made up of Lax-Wendroff and the two-step Lax-Friedrichs and Fromm's scheme to solve a 1D linear advection and 1D diffusionless Burger's equation, at some values of the Courant number. We then use two optimisation techniques based on both dispersion and dissipation and two optimisation techniques based on only dispersion and obtain the variation of the integrated errors vs. the CFL number. It is seen that out of the five techniques, only one is a good measure of the shock-capturing of property of numerical methods.
Facilitated Cross-Bridge Interactions with Thin Filaments by Familial Hypertrophic Cardiomyopathy Mutations in α-Tropomyosin

Familial hypertrophic cardiomyopathy (FHC) is a disease of cardiac sarcomeres. To identify molecular mechanisms underlying FHC pathology, functional and structural differences in three FHC-related mutations in recombinant α-Tm (V95A, D175N, and E180G) were characterized using both conventional and modified in vitro motility assays and circular dichroism spectroscopy. Mutant Tm's exhibited reduced α-helical structure and increased unordered structure. When thin filaments were fully occupied by regulatory proteins, little or no motion was detected at pCa 9, and maximum speed (pCa 5) was similar for all tropomyosins. Ca2+-responsiveness of filament sliding speed was increased either by increased pCa50 (V95A), reduced cooperativity n (D175N), or both (E180G). When temperature was increased, thin filaments with E180G exhibited dysregulation at temperatures ~10°C lower, and much closer to body temperature, than WT. When HMM density was reduced, thin filaments with D175N required fewer motors to initiate sliding or achieve maximum sliding speed.
Transfer Significant Subgraphs across Graph Databases

A key step of graph classification is to identify informative subgraphs that encode label information. For instance, in drug efficacy prediction, the drugs (chemical compounds) effective against the same disease usually contain similar chemical-subgraphs effective to control the disease. Then, one can use such chemical subgraphs to identify effective drugs. We call these subgraphs significant subgraphs. In this paper, the aim is to utilize the significant subgraphs from related graph datasets to help label graphs of the target dataset. For example, we utilize the breast cancer drug data, and transfer the anti-cancer subgraphs to help label another set of drug data against lung cancer. To do so, we propose a Bayesian-based transfer learning model. The key idea is to first evaluate the similarity between the target and source datasets by estimating the degree they share on their significant subgraphs. This dataset similarity is then used to judiciously select significant subgraphs from similar (related) datasets to the target dataset. An optimization problem is devised to maximize the likelihood that the selected subgraphs are significant in the target dataset. The objective function is further proven to have the antimonotone property which can help prune the search space significantly. Sixteen sets of experiments show that the proposed algorithm can effectively reduce the error rates by as much as 40%. More importantly, it is 10 times faster than the comparison models, which include unsupervised and supervised significant subgraph mining algorithms.
Extending web content management systems navigation capabilities with semantic navigation maps

This paper presents an automatic approach built on information retrieval and clustering techniques to enhance the navigation capabilities of modern Web Content Management Systems (WCMSs). The approach uses Latent Semantic Indexing to discover correlations between the contents published through these systems, and a fuzzy clustering algorithm to form groups of related contents. For each page of the developed website, a set of navigation links towards pages showing similar or related content and a measure of such similarity is proposed. An implementation of the approach for the Joomla! Open Source WCMS and the results from a case study on a real world website are also presented.
Parameter estimation for agenda-based user simulation

This paper presents an agenda-based user simulator which has been extended to be trainable on real data with the aim of more closely modelling the complex rational behaviour exhibited by real users. The trainable part is formed by a set of random decision points that may be encountered during the process of receiving a system act and responding with a user act. A sample-based method is presented for using real user data to estimate the parameters that control these decisions. Evaluation results are given both in terms of statistics of generated user behaviour and the quality of policies trained with different simulators. Compared to a handcrafted simulator, the trained system provides a much better fit to corpus data and evaluations suggest that this better fit should result in improved dialogue performance.