- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Cuff-less continuous measurement of blood pressure using wrist and fingertip photo-plethysmograms: Evaluation and feature analysis
摘要： Continuous monitoring of blood pressure improves prevention and control of cardiovascular diseases. Currently, cuff-based oscillometric sphygmomanometers are commonly used to monitor the systolic and diastolic blood pressure. However, this technique is discontinuous in nature and inconvenient for repeated measurements. Here we have proposed indirect measurement of blood pressure from photo-plethysmograms (PPG) simultaneously recorded from wrist and fingertip. The signals were recorded from 111 participants and different morphological features were obtained from PPG and its second derivative, acceleration plethysmograms (APG). Moreover, different measures of pulse transit time (PTT) and pulse wave velocity (PWV) were obtained from the recorded PPGs. Multi-layer Neural Networks were used to estimate the non-linear relationship between these features and systolic and diastolic blood pressures (SBP and DBP). Mean absolute errors of 6.77 and 4.82 mmHg were achieved in comparison with measurements from a validated commercial oscillometric sphygmomanometer. Feature analysis provided insight about the importance of features for estimating BP, and demonstrated that these features are not the same for SBP and DBP. Using the highest-ranked 15 and 13 features obtained from moving-backward algorithm the mean absolute errors were reduced to 5.31 and 4.62 mmHg for SBP and DBP. However, the optimum optimal feature sets provided by a genetic algorithm for estimating SBP/DBP led to the lowest mean absolute errors of 4.94/4.03. These results compared to previous studies and the available standards suggest that the method is a promising substitute for oscillometric sphygmomanometers which can be used conveniently for continuous monitoring of blood pressure.
关键词： Genetic algorithms,Non-obstructive blood pressure measurement,Multi-layer neural networks,Photo-plethysmography
更新于2025-09-23 15:23:52
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Total polyphenol quantitation using integrated NIR and MIR spectroscopy: A case study of Chinese dates ( <i>Ziziphus jujuba</i> )
摘要： Polyphenols are the foremost measure of phytochemicals in Chinese dates due to their many potential health benefits such as averting cancers, reducing the risk of coronary artery disease, diuretic activity, myocardial stimulant, coronary dilator and muscle relaxant. To quantitate the polyphenols in Chinese dates using a data fusion approach with near‐infrared (NIR) and mid‐infrared (MIR) spectroscopy. A total of 80 Chinese dates samples were used for data acquisition from both NIR and MIR spectroscopy. The efficient spectral intervals were extracted by the synergy interval partial least square (Si‐PLS) algorithm as input variables for NIR‐MIR fusion model. A genetic algorithm (GA) was used to construct the model based on NIR‐MIR fusion. The performance of the developed models was evaluated using correlation coefficients of calibration (R2) and prediction (r2), root mean square error of prediction (RMSEP), bias and residual prediction deviation (RPD). The data fusion model based on the GA was superior compared to NIR and MIR build model. The optimal GA‐fusion model yielded R2 = 0.9621, r2 = 0.9451, RPD = 2.44, calibration set bias = 0.004 and prediction set bias = 0.061, computing only 15 variables. These findings reveal that integration of NIR and MIR is possible for the prediction of total polyphenol content in Chinese dates.
关键词： spectroscopy techniques,polyphenols,genetic algorithms,principal component analysis,spectral interval selection
更新于2025-09-23 15:23:52
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[IEEE 2019 IEEE 16th India Council International Conference (INDICON) - Rajkot, India (2019.12.13-2019.12.15)] 2019 IEEE 16th India Council International Conference (INDICON) - Performance Comparison Between Bipolar and Unipolar Switching Scheme for a Single-Phase Inverter Based Stand-alone Photovoltaic System
摘要： Self-organizing network (SON) mechanisms reduce operational expenditure in cellular networks while enhancing the offered quality of service. Within a SON, self-healing aims to autonomously solve problems in the radio access network and to minimize their impact on the user. Self-healing comprises automatic fault detection, root cause analysis, fault compensation, and recovery. This paper presents a root cause analysis system based on fuzzy logic. A genetic algorithm is proposed for learning the rule base. The proposed method is adapted to the way of reasoning of troubleshooting experts, which ease knowledge acquisition and system output interpretation. Results show that the obtained results are comparable or even better than those obtained when the troubleshooting experts define the rules, with the clear benefit of not requiring the experts to define the system. In addition, the system is robust, since fine tuning of its parameters is not mandatory.
关键词： genetic algorithms,self-organizing networks (SONs),Fuzzy systems,troubleshooting,root cause analysis,self-healing,supervised learning
更新于2025-09-23 15:21:01
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MedGA: A novel evolutionary method for image enhancement in medical imaging systems
摘要： Medical imaging systems often require the application of image enhancement techniques to help physicians in anomaly/abnormality detection and diagnosis, as well as to improve the quality of images that undergo automated image processing. In this work we introduce MedGA, a novel image enhancement method based on Genetic Algorithms that is able to improve the appearance and the visual quality of images characterized by a bimodal gray level intensity histogram, by strengthening their two underlying sub-distributions. MedGA can be exploited as a pre-processing step for the enhancement of images with a nearly bimodal histogram distribution, to improve the results achieved by downstream image processing techniques. As a case study, we use MedGA as a clinical expert system for contrast-enhanced Magnetic Resonance image analysis, considering Magnetic Resonance guided Focused Ultrasound Surgery for uterine fibroids. The performances of MedGA are quantitatively evaluated by means of various image enhancement metrics, and compared against the conventional state-of-the-art image enhancement techniques, namely, histogram equalization, bi-histogram equalization, encoding and decoding Gamma transformations, and sigmoid transformations. We show that MedGA considerably outperforms the other approaches in terms of signal and perceived image quality, while preserving the input mean brightness. MedGA may have a significant impact in real healthcare environments, representing an intelligent solution for Clinical Decision Support Systems in radiology practice for image enhancement, to visually assist physicians during their interactive decision-making tasks, as well as for the improvement of downstream automated processing pipelines in clinically useful measurements.
关键词： Medical imaging systems,Genetic Algorithms,Uterine fibroids,Magnetic resonance imaging,Bimodal image histogram,Image enhancement
更新于2025-09-23 15:21:01
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Extraction of the minority carrier transport properties of solar cells using the Hovel model and genetic algorithms
摘要： In this paper, a quick and accurate method for extraction of the minority carrier transport properties of p-n or n-p junction solar cells, such as diffusion lengths and surface recombination velocities, is presented. The knowledge of these parameters is essential to investigate factors that limit the performance of photovoltaic devices. The proposed method, based on genetic algorithms and the analytical Hovel model, is used to fit the external quantum efficiency (EQE) curves of solar cells with different emitter thicknesses. As a demonstrative example of application of the procedure carried out in this work, theoretical and experimental EQE curves of n-p GaAs solar cells under the standard AM1.5G spectrum have been used in order to extract the desired parameters. Errors less than 2.4% have been obtained, which shows the ability of the developed tool. An analysis of the total number of iterations is presented. Results obtained can be used to improve the design, optimization and manufacturing process of high efficiency photovoltaic devices.
关键词： diffusion length,surface recombination velocity,Hovel model and genetic algorithms,solar cells
更新于2025-09-23 15:19:57
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An Efficient Non-Invasive Method to Fabricate In-Fiber Microcavities Using a Continuous-Wave Laser
摘要： Natural ecosystems exhibit complex dynamics of interacting species. Man-made ecosystems exhibit similar dynamics and, in the case of mobile app stores, can be said to perform optimization as developers seek to maximize app downloads. This work aims to understand stability and instability within app store dynamics and how it affects ?tness. The investigation is carried out with AppEco, a model of the iOS App Store, which was extended for this paper and updated to model the store from 2008 to 2014. AppEco models apps containing features, developers who build the apps, users who download apps according to their preferences, and an app store that presents apps to the users. It also models developers who use commonly observed strategies to build their apps: innovator, milker, optimizer, copycat, and ?exible (the ability to choose any strategy). Results show that despite the success of the copycat strategy, there is a clear stable state for low proportion of copycats in developer populations, mirroring results in theoretical biology for producer–scrounger systems. The results also show that the best ?tness is achieved when the evolutionary optimizer (as producer) and copycat (as scrounger) strategies coexist together in stable proportions.
关键词： mobile app developers,Agent-based simulation,evolutionary ecosystem model,genetic algorithms,app stores,producer–scrounger systems,computational modeling
更新于2025-09-23 15:19:57
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[IEEE 2018 26th Telecommunications Forum (TELFOR) - Belgrade, Serbia (2018.11.20-2018.11.21)] 2018 26th Telecommunications Forum (TELFOR) - Routing, Modulation and Spectrum Allocation in Elastic Optical Networks
摘要： Elastic optical networks are seen as an efficient solution for future optical networks. In these networks, the routing, modulation and spectrum allocation problem consists of finding an optimal network utilization by jointly addressing all three aspects. We examine two different approaches for solving this problem dynamically in a network with a variable traffic. The first approach uses several candidate shortest paths and allows dynamic spectral (re)allocation, while the second approach employs a genetic algorithm for finding the most appropriate path. Our results showed that the second approach could often provide lower average blocking probability and a more efficient spectrum utilization than the first one, particularly for networks with shorter links, indicating that it is a potential solution for future high capacity transport network.
关键词： Genetic algorithms,Routing modulation and spectrum allocation,Elastic optical networks
更新于2025-09-19 17:15:36
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A Joint Routing and Channel Assignment Scheme for Hybrid Wireless-Optical Broadband-Access Networks
摘要： In this paper, we investigate mechanisms for improving the quality of communications in wireless-optical broadband access networks (WOBAN), which present a promising solution to meet the growing needs for capacity of access networks. This is achieved by using multiple gateways and multi-channel operation along with a routing protocol that effectively reduces the effect of radio interference. We present a joint route and channel assignment scheme with the objective of maximizing the end-to-end probability of success and minimizing the end-to-end delay for all active upstream traffic in the WOBAN. Performance evaluations of the proposed scheme are presented using ns-2 simulations, which show that the proposed scheme improves the network throughput up to three times and reduces the traffic delay by six times in presence of 12 channels and four network interface cards (NICs), compared to a single channel scenario.
关键词： genetic algorithms,channel assignment,wireless mesh networks,access networks,optical networks,quality-aware routing
更新于2025-09-19 17:15:36
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Spatiotemporal Mode-Locking in Multimode Fiber Lasers
摘要： Over the last few decades, there has been considerable concern over the multifactory manufacturing environments owing to globalization. Numerous studies have indicated that ?exible job-shop scheduling problems (FJSPs) and the distributed and FJSPs (DFJSPs) belong to NP-hard puzzle. The allocation of jobs to appropriate factories or ?exible manufacturing units is an essential task in multifactory optimization scheduling, which involves the consideration of equipment performance, technology, capacity, and utilization level for each factory or manufacturing unit. Several variables and constraints should be considered in the encoding problem of DFJSPs when using genetic algorithms (GAs). In particular, it has been reported in the literature that the traditional GA encoding method may generate infeasible solutions or illegal solutions; thus, a specially designed evolution process is required. However, in such a process, the diversity of chromosomes is lost. To overcome this drawback, this paper proposes a re?ned encoding operator that integrates probability concepts into a real-parameter encoding method. In addition, the length of chromosomes can be substantially reduced using the proposed algorithm, thereby, saving computation space. The proposed re?ned GA algorithm was evaluated with satisfactory results through two-stage validation; in the ?rst stage, a classical DFJSP was adopted to show the effectiveness of the algorithm, and in the second stage, the algorithm was used to solve a real-world case. The real-world case involved the use of historical data with 100 and 200 sets of work orders of a fastener manufacturer in Taiwan. The results were satisfactory and indicated that the proposed re?ned GA algorithm could effectively overcome the con?icts caused by GA encoding algorithms.
关键词： distributed and ?exible job-shop,scheduling problems,probability-based encoding operator,?exible job-shop,Genetic algorithms
更新于2025-09-19 17:13:59
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[IEEE 2019 Far East NDT New Technology & Application Forum (FENDT) - Qingdao, Shandong province, China (2019.6.24-2019.6.27)] 2019 Far East NDT New Technology & Application Forum (FENDT) - Laser line generation for optimized interaction with hidden defects in active thermography
摘要： Self-organizing network (SON) mechanisms reduce operational expenditure in cellular networks while enhancing the offered quality of service. Within a SON, self-healing aims to autonomously solve problems in the radio access network and to minimize their impact on the user. Self-healing comprises automatic fault detection, root cause analysis, fault compensation, and recovery. This paper presents a root cause analysis system based on fuzzy logic. A genetic algorithm is proposed for learning the rule base. The proposed method is adapted to the way of reasoning of troubleshooting experts, which ease knowledge acquisition and system output interpretation. Results show that the obtained results are comparable or even better than those obtained when the troubleshooting experts define the rules, with the clear benefit of not requiring the experts to define the system. In addition, the system is robust, since fine tuning of its parameters is not mandatory.
关键词： troubleshooting,self-healing,genetic algorithms,self-organizing networks (SONs),root cause analysis,Fuzzy systems,supervised learning
更新于2025-09-19 17:13:59