- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Regulation of Optimal Entropy Squeezing Sudden Generation for a Moving Atomic Qubit Interacting with the Coherent Fields via Two-Photon Process
摘要： From the quantum information point of view, we investigate the regulation of optimal entropy squeezing sudden generation (OESSG) and disappearance (OESSD) for a moving atomic qubit interacting with the coherent field via two-photon process. It is shown that physical substance of atomic OESSG is entanglement sudden death of the atomic qubit and field, and atomic OESSD corresponds to the transient entanglement resurrection of atomic qubit and field. The duration, number component and stable cycle of the atomic OESSG can be controlled by choosing the initial atomic distribution angle ? and structure parameter p of the field mode, respectively. We realize the periodic exchange of atomic OESSG of components Sx and Sy, and also propose the exchange preparation scheme of atomic optimal entropy squeezing state. Our proposal may be useful for instantaneous control of quantum noise and retention of maximum coherent states of single atomic qubit in the noisy environment.
关键词： Optimal entropy squeezing sudden generation,Optimal entropy squeezing state,Field mode structure parameter,Moving atomic qubit
更新于2025-09-19 17:15:36
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Secure medical image steganography through optimal pixel selection by EH-MB pipelined optimization technique
摘要： In today’s world, transmission of information over the channel is not secure for example patient records and other sensitive information. In order to protect this sensitive information, it is coded within the image, audio or text files which is decodable only with the help of a particular key. To enable security to the covert communication and safeguarding the information for securing medical data to avoid medical related cybercrimes, we have proposed a method for medical image steganography using Elephant Herding-Monarch Butterfly (EH-MB) Optimization algorithm for effective selection of pixels for embedding the secret message (i.e. image/text medical report data) in the cover image. Initially, the cover is converted to frequency domain using multilevel DWT, where, the pixel selection is done optimally in the high frequency components using EH-MB algorithm. EH-MB based pixel selection procedure uses a fitness function that depends on the cost function, which calculates the edge, entropy, and intensity of the pixel for evaluating fitness. Simulation was done in the working platform of MATLAB and comparison of the proposed steganography approach was done with the other existing methods in terms of Peak-Signal-to Noise-Ratio and Mean Square Error to prove the effectiveness of the proposed approach.
关键词： Intensity,Elephant herding,Steganography,Object,MSE,PSNR,Entropy,Covert,Segmentation,Edge,Monarch butterfly
更新于2025-09-19 17:15:36
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Estimating physical properties from liquid crystal textures via machine learning and complexity-entropy methods
摘要： Imaging techniques are essential tools for inquiring a number of properties from different materials. Liquid crystals are often investigated via optical and image processing methods. In spite of that, considerably less attention has been paid to the problem of extracting physical properties of liquid crystals directly from textures images of these materials. Here we present an approach that combines two physics-inspired image quantifiers (permutation entropy and statistical complexity) with machine learning techniques for extracting physical properties of nematic and cholesteric liquid crystals directly from their textures images. We demonstrate the usefulness and accuracy of our approach in a series of applications involving simulated and experimental textures, in which physical properties of these materials (namely: average order parameter, sample temperature, and cholesteric pitch length) are predicted with significant precision. Finally, we believe our approach can be useful in more complex liquid crystal experiments as well as for probing physical properties of other materials that are investigated via imaging techniques.
关键词： machine learning,physical properties,image analysis,complexity-entropy methods,liquid crystals
更新于2025-09-19 17:15:36
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - A Fast Palette Reordering Technique Based on GPU-Optimized Genetic Algorithms
摘要： Color re-indexing is one of main approaches for improving the loss-less compression of color indexed images. Zero-order entropy reduction of indexes matrix is the key to obtain high compression ratio. However, obtaining the optimal re-indexed palette is a challenging problem that cannot be solved by brute-force approaches. In this paper we propose a novel re-indexing approach where the Travelling Salesman Problem is solved through Ant Colony Optimization. Our method is proved to achieve high quality results by outperforming state-of-art ones in terms of compression gain. Additionally, we exploit clustering and GPU computing to make our solution extremely fast.
关键词： Ant Colony Optimization,Data compression,Color,Entropy,Image coding
更新于2025-09-19 17:15:36
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A multilevel color image thresholding scheme based on minimum cross entropy and alternating direction method of multipliers
摘要： In this paper, we focus on the problem of fast color image segmentation and propose a two-stage image segmentation method using multi-level thresholding algorithm and statistical region merging(SRM) technique. With the help of the alternating direction method of multipliers(ADMM), the optimal threshold values can be determined by the centroid of sub-modes of the image histogram that follow minimum cross entropy(MEC). In the second stage, a modified SRM is used to remove over-segmented regions of thresholded image to bring the final result. Experimental results depicts that the proposed approach selects threshold values more efficiently as compared to other MCE-based thresholding techniques and produces high quality of the segmented color images than the other methods like mean-shift, normalized cuts(Ncuts) and differential evolution (Q=7).
关键词： Multi-Level image segmentation,Minimum cross entropy,Color image,Alternating direction method of multipliers.
更新于2025-09-19 17:15:36
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Laser processing as a high-throughput method to investigate microstructure-processing-property relationships in multiprincipal element alloys
摘要： A direct laser deposition processing method was applied to construct compositional and microstructural libraries of AlxCoCrFeNi in an efficient and high-throughput manner. Among the compositions (x ? 0.51 e1.25) and quench rates (26e6400 K/s) studied, most of the laser deposited alloys exhibit a cellular microstructure, similar to the cast materials. The microstructural feature sizes were found to follow a power law relationship with the quench rate. The dependence of the microhardness on microstructural length scale was also investigated and observed to follow a Hall-Petch relationship. This study indicates that laser processing is an effective method for rapidly and efficiently evaluating multiprincipal element alloys and their microstructures.
关键词： Direct laser deposition,High-entropy alloys,Mechanical property,Microstructure
更新于2025-09-19 17:13:59
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[IEEE 2019 Device Research Conference (DRC) - Ann Arbor, MI, USA (2019.6.23-2019.6.26)] 2019 Device Research Conference (DRC) - Tunnel junctions for vertically integrated multiple nitrides laser diodes
摘要： Biometric veri?cation systems are designed to accept multiple similar biometric measurements per user due to inherent intrauser variations in the biometric data. This is important to preserve reasonable acceptance rate of genuine queries and the overall feasibility of the recognition system. However, such acceptance of multiple similar measurements decreases the imposter’s dif?culty of obtaining a system-acceptable measurement, thus resulting in a degraded security level. This deteriorated security needs to be measurable to provide truthful security assurance to the users. Entropy is a standard measure of security. However, the entropy formula is applicable only when there is a single acceptable possibility. In this paper, we develop an entropy-measuring model for biometric systems that accepts multiple similar measurements per user. Based on the idea of guessing entropy, the proposed model quanti?es biometric system security in terms of adversarial guessing effort for two practical attacks. Excellent agreement between analytic and experimental simulation-based measurement results on a synthetic and a benchmark face dataset justify the correctness of our model and thus the feasibility of the proposed entropy-measuring approach.
关键词： Biometric system,security,guessing,entropy measurement
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Evaluation of Graphene Oxide as the Passivation Layer for Si Solar Cells
摘要： Biometric veri?cation systems are designed to accept multiple similar biometric measurements per user due to inherent intrauser variations in the biometric data. This is important to preserve reasonable acceptance rate of genuine queries and the overall feasibility of the recognition system. However, such acceptance of multiple similar measurements decreases the imposter’s dif?culty of obtaining a system-acceptable measurement, thus resulting in a degraded security level. This deteriorated security needs to be measurable to provide truthful security assurance to the users. Entropy is a standard measure of security. However, the entropy formula is applicable only when there is a single acceptable possibility. In this paper, we develop an entropy-measuring model for biometric systems that accepts multiple similar measurements per user. Based on the idea of guessing entropy, the proposed model quanti?es biometric system security in terms of adversarial guessing effort for two practical attacks. Excellent agreement between analytic and experimental simulation-based measurement results on a synthetic and a benchmark face dataset justify the correctness of our model and thus the feasibility of the proposed entropy-measuring approach.
关键词： guessing,entropy measurement,security,Biometric system
更新于2025-09-19 17:13:59
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[IEEE 2019 19th International Conference on Advanced Robotics (ICAR) - Belo Horizonte, Brazil (2019.12.2-2019.12.6)] 2019 19th International Conference on Advanced Robotics (ICAR) - Closed-Loop Control of a Magnetically Actuated Fiber-Coupled Laser for Computer-Assisted Laser Microsurgery
摘要： In binary classi?cation, two-way confusion matrices, with corresponding measures, such as sensitivity and speci?city, have become so ubiquitous that those who review results may not realize there are other and more realistic ways to visualize data. This is, particularly, true when risk and reward considerations are important. The approach suggested here proposes that classi?cation need not offer a conclusion on every instance within a data set. If an algorithm ?nds instances (e.g., patient cases in a medical data set) in which attributes pertaining to a patient’s disease offer zero to nil information, there should be no classi?cation offered. From the physician’s perspective, disclosure of nil information should be welcome because it might prevent potentially harmful treatment. It follows from this that the developer of a classi?er can provide summary results amendable for helping the consumer decide whether or not it is prudent to pass or act (commission versus omission). It is not always about balancing sensitivity and speci?city in all cases, but optimizing action on some cases. The explanation is centered on John Kelly’s link of gambling with Shannon information theory. In addition, Graham’s margin of safety, Bernoulli’s utiles, and Hippocratic Oath are important. An example problem is provided using a Netherlands Cancer Institute breast cancer data set. Recurrence score, a popular molecular-based assay for breast cancer prognosis, was found to have an uninformative zone. The uninformative subset had been grouped with positive results to garner higher sensitivity. Yet, because of a positive result, patients might be advised to undergo potentially harmful treatment in the absence of useful information.
关键词： data compression,cancer,clinical diagnosis,sensitivity and speci?city,Data analysis,genetic expression,entropy
更新于2025-09-19 17:13:59
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Thermodynamics assessment on cooling photovoltaic modules by phase change materials (PCMs) in critical operating temperature
摘要： Increasing the temperature of photovoltaic (PV) cells decreases their electricity generation. The use of phase change materials (PCMs) is one of the most common methods for controlling the rate of increasing the temperature of PV cells. This research focuses on thermodynamic analysis of PV/PCM systems with and without fins in maximum operating temperature of PV modules (85 °C). Polyethylene glycol 600 (PEG-600) and paraffin, with different melting points, have been studied experimentally as PCM in an indoor condition. Moreover, the effect of using fins was investigated. For this critical temperature, the results showed that using paraffin could be better for controlling the temperature of PV cells, due to its closer melting point with the module temperature. In the case of fins included, the temperature differences of 28.0 °C and 8.8 °C between the case of paraffin + fin and the case of PEG 600 + fin in comparison with the conventional PV module were measured, respectively. At this critical temperature condition, the output power of a PV module cannot exceed the half of its nominal power. The exergy efficiency of the paraffin + fin case was measured to 4.2% more than the conventional one. Also, entropy generation was calculated and reduction up to 5% was shown for paraffin + fin in comparison with the conventional one. Moreover, variations of the Rayleigh number for proposed cases are calculated too.
关键词： Energy,Critical operating temperature,Entropy,Photovoltaic,PCM,Exergy
更新于2025-09-19 17:13:59