Object Identification by Signal Gain and Correlation

In this study, “ring rotation invariant transform” techniques are used to add more salient feature to the original images. The “ring rotation invariant transform” can solve image rotation problem, which transfers a ring signal to several signal vectors in the complex domain, whereby to generate invariant magnitude. Matrix correlation is employed to combine these magnitudes to generate the various discriminators, by which to identify objects. For managing image-shifting problem, one pixel in sample image is compared with surrounding pixels of unknown image. The comparison approaching in this study is by the basis of pixel-to-pixel-comparisons.

Theoretical bases of combined nonlinear optical demodulator-amplifer for broadband microwave photonics system

Our demodulator is based on the use of a strong light pump wave along with a signal modulated light wave. The demodulator is linear in terms of the modulation signal, which makes it possible to obtain a demodulated signal without harmonic distortion. The modulator conversion efciency and signal gain increase with increasing microwave baseband.

High data rates in optic fiber systems based on the gain optimization techniques

The signal gain is improved by nearly about 15 dB by using the hybrid optical amplifiers technique. The gain flattened filter technique has outlined a larger value of signal gain than the hybrid optical amplifiers technique by about 17 dB whereas the Glass Composition method in the hybrid modified model has a better increase in the optimum value of signal gain that reached to about 70 dB. Fiber Bragg Grating (FBG) technique has outlined optimum gain value that is reached to about 50 dB. The combination of these techniques are used for the best optimized value of signal gain.

Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework

Objective There are signals of clinicians’ expert and knowledge-driven behaviors within clinical information systems (CIS) that can be exploited to support clinical prediction. Describe development of the Healthcare Process Modeling Framework to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals). Materials and Methods We employed an iterative framework development approach that combined data-driven modeling and simulation testing to define and refine a process for phenotyping clinician behaviors. Our framework was developed and evaluated based on the Communicating Narrative Concerns Entered by Registered Nurses (CONCERN) predictive model to detect and leverage signals of clinician expertise for prediction of patient trajectories. Results Seven themes—identified during development and simulation testing of the CONCERN model—informed framework development. The HPM-ExpertSignals conceptual framework includes a 3-step modeling technique: (1) identify patterns of clinical behaviors from user interaction with CIS; (2) interpret patterns as proxies of an individual’s decisions, knowledge, and expertise; and (3) use patterns in predictive models for associations with outcomes. The CONCERN model differentiated at risk patients earlier than other early warning scores, lending confidence to the HPM-ExpertSignals framework. Discussion The HPM-ExpertSignals framework moves beyond transactional data analytics to model clinical knowledge, decision making, and CIS interactions, which can support predictive modeling with a focus on the rapid and frequent patient surveillance cycle. Conclusions We propose this framework as an approach to embed clinicians’ knowledge-driven behaviors in predictions and inferences to facilitate capture of healthcare processes that are activated independently, and sometimes well before, physiological changes are apparent.

High-speed fiber system capacity with bidirectional Er-Yb CDFs based on differential phase shift keying (DPSK) modulation technique

This paper simulates the bidirectional Er-Yb codoped fiber amplifiers (CDFs)-based DPSK modulation scheme for high speed fiber system capacity. The combination of Erbium-Ytterbium codoped fibers into a single fiber has been developed for the extension of the absorption bands for doped fibers. The signal gain variations versus pump wavelength variations have been demonstrated for various doped amplifiers with the proposed Er-Yb CDFs at amplifier length of 5 m. Also the signal gain variations versus pump wavelength variations have been illustrated for the proposed Er-Yb CDFs at 5 m amplifier length in different pumping configurations. The total optical power, max. Q factor, total electrical power, output optical signal/noise ratio, and signal gain variations versus fiber length variations have between simulated and clarified in the presence of bidirectional various lengths of Er-Yb CDFs.

Photoelectric Detection System and Machine Learning Recognition Method of Its Detection Images

In the photoelectric detection system, the photoelectric detector can convert the optical signal to be measured into a current signal, and the current amplifier transforms the current signal output by the detector into a voltage signal for amplification. In this study, the photo-multiplier tube (PMT) is selected as the photoelectric detector. Compared with other photoelectric detectors, it can obtain higher internal gain, higher sensitivity, and better response performance. The current amplifier is prepared by pre-amplifier and voltage amplifier. In order to capture photoelectric signals well, a large-format scanning system is set up to design each component module, control module, and host computer module of the system. Besides, a machine learning-based algorithm is proposed, namely semi-supervised manifold image recognition algorithm, which is used for identify photoelectric detection images. In the test process, the printed circuit board (PCB) and sapphire material are firstly used as the substrate of the current amplifier, and their influences in the circuit are compared. The peak value of the output noise of each substrate circuit is around 2.8 mV when the input of the current amplifier is short-circuited. Then, the signal gain and signal bandwidth of the photoelectric detection system remain stable when there is no optical signal input. During the process of changing the system signal gain ratio, the noise output of the system is the lowest when the voltage of PMT is 0.50 V and the current amplifier gain is set to 2.2 × 105 V/A. The proposed recognition algorithm can identify different types of targets well. After the image is projected into a two-dimensional space by the algorithm, the distance between classes increases, and the targets in the class promote aggregation, thereby enhancing the identify-ability between samples.

Simulation study of signal gain optimization based on hybrid composition techniques for high-speed optically dense multiplexed systems

This study created a 13 Gb/s transmission speed per 300 channel dense wavelength division multiplexing system based on hybrid optical fiber amplifiers and filter techniques to enhance signal gain. The filter techniques used here included a hybrid optical amplifier, a gain flattening filter (GFF), a Fabry–Perot filter, a fiber Bragg grating (FBG), and glass composition technique. The techniques were combined to optimize signal gain as follows: the study began with an erbium-doped fiber amplifier (EDFA), added a Raman amplifier, added GFF, added fiber Bragg grating, added glass composition, and finally achieved a hybrid-modified model after adding Fabry–Perot filter. The signal gain was optimized with the hybrid-modified model via the different operating parameters of the EDFA. The proposed model also showed a better performance (30–40 dB greater) than the previous model (Mahran O, Aly MH. Performance characteristics of dual-pumped hybrid EDFA/Raman optical amplifier. OSA – Applied Optics Jan 2016;55:22–6) after changing the values of the signal wavelength, the EDFA, and the length of the Raman amplifier.