There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Our understanding of the cellular implementation of systems-level neural processes like action, thought and emotion has been limited by the availability of tools to interrogate specific classes of neural cells within intact, living brain tissue. Here we identify and develop an archaeal light-driven chloride pump (NpHR) from Natronomonas pharaonis for temporally precise optical inhibition of neural activity. NpHR allows either knockout of single action potentials, or sustained blockade of spiking. NpHR is compatible with ChR2, the previous optical excitation technology we have described, in that the two opposing probes operate at similar light powers but with well-separated action spectra. NpHR, like ChR2, functions in mammals without exogenous cofactors, and the two probes can be integrated with calcium imaging in mammalian brain tissue for bidirectional optical modulation and readout of neural activity. Likewise, NpHR and ChR2 can be targeted together to Caenorhabditis elegans muscle and cholinergic motor neurons to control locomotion bidirectionally. NpHR and ChR2 form a complete system for multimodal, high-speed, genetically targeted, all-optical interrogation of living neural circuits.

Multimodal fast optical interrogation of neural circuitry

This chapter introduces the subject of statistical pattern recognition (SPR). It starts by considering how features are defined and emphasizes that the nearest neighbor algorithm achieves error rates comparable with those of an ideal Bayes’ classifier. The concepts of an optimal number of features, representativeness of the training data, and the need to avoid overfitting to the training data are stressed. The chapter shows that methods such as the support vector machine and artificial neural networks are subject to these same training limitations, although each has its advantages. For neural networks, the multilayer perceptron architecture and back-propagation algorithm are described. The chapter distinguishes between supervised and unsupervised learning, demonstrating the advantages of the latter and showing how methods such as clustering and principal components analysis fit into the SPR framework. The chapter also defines the receiver operating characteristic, which allows an optimum balance between false positives and false negatives to be achieved.

Statistical Pattern Recognition

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Introduction To Robust Estimation And Hypothesis Testing

Intra-Body communication (IBC) is a short-range body based communication using the human body as the transmission medium in biomedical application. Quasi-static electric field modeling of the galvanic coupling IBC channel is analyzed; Analytical solution of voltage distribution and signal attenuation in the forearm of human body from the model are investigated; Effects of human limb's properties in the model are studied. Finally, in vivo validation and calculation results are presented. Especially, the gain is greatly affected by the thickness of muscle both in calculation result and in vivo experiment.

In vivo validation of quasi-static field model in intra-body communication

In galvanic coupling conductive intracardiac communication(GCCIC) of the leadless pacemakers, the electrical signal transmitted directly through the myocardium and blood is inevitably affected by the cardiac cycle. Established studies focused more on the effect of the myocardium. However, our preliminary in-vitro experiments suggested that blood volume variations also significantly impacted signal transmission. In this article, we analyzed the blood volume variations during the cardiac cycle and designed an in-vitro experimental platform containing a simulated heart beating system and an automatic channel characteristic acquisition system, which controlled two peristaltic pumps to realize the periodic blood volume variations and the continuous acquisition of channel gain. Through the in-vitro porcine heart experiment, the effect of frequency and blood volume variations during the cardiac cycle on two channel gains was analyzed. Considering the impact of high-frequency signal leakage, the channel gain variations of the low frequency are the main concern. The results showed that the channel gain was positively correlated with frequency; it changed periodically with blood volume variations in the cardiac cycle, and the trends were different due to the different signal paths of the two channels. For the Right Ventricle-Right Atrium channel, the gain varied from $-67$ dB to $-53$ dB and is inversely correlated with blood volume. The gain fluctuation range was smaller for the Right Ventricle-Left Ventricle channel, about 2 dB. This study shows that the gain of intracardiac communication channels, especially the RV-RA channel, is influenced by blood volume variations during the cardiac cycle.

An Investigation on Conductive Intracardiac Communication Dynamic Channel Gain During the Cardiac Cycle for Leadless Pacemakers

In this article, we propose a novel method for temperature detection based on 1-D CNN and time-stretch method. Differing from traditional optical fiber temperature sensors that are demodulated by an optical spectrum analyzer (OSA) that needs long time to scan and a benchmark spectrum in advance, the demonstrated method can effectively solve the problem in demodulation and improve the detection speed. Besides, mapping the demodulation in the traditional spectral domain to the temporal domain through dispersion optical fiber can greatly reduce the system cost and the demodulation speed can be as high as 50 MHz. Furthermore, the designed peanut-shaped structured Mach–Zehnder interferometer (MZI) is simple to achieve, highly responsive to temperature, and easy to be mass produced at low cost. In the range of 10 °C–18 °C, the temperature sensitivity is up to 1.038 nm/°C, and the detection accuracy is up to 99.07% after using the 1-D CNN algorithm. The proposed sensor system is expected to play a potential role in important scenarios such as temperature monitoring of military weapons and space vehicle system management and control.

Temperature Fiber Sensor Based on 1-D CNN Incorporated Time-Stretch Method for Accurate Detection

The rapid development of the blooming city requires to expand the government healthcare services for the public because of increasing inhabitants. Additional temporary government healthcare service is set up within a university having an operating hospital in order to solve the urgent requests of the mass amount of the inhabitant. This has resulting resources (medical equipment and IT services) sharing by these healthcare entities but independent operations should be maintained. In order to keep the privacy and security of the digital data and patient data, this paper proposes a method of creating a new subnet as common network area for sharing the resources, while maintaining their independencies at the same time. We have added the network security appliances (firewalls) connecting to the healthcare entities. Through the features of network address translation (NAT), network policy and access control list, this common subnet with hybrid connection (university hospital network and the government hospital network) can accessed by these entities via the specified IP addresses. As a result, the existing IP addresses for each healthcare entity network can be retained, and providing the secured method to grant the access right to the common area to share the digitalized medical resources. In order to protect the security of the cooperated hospital's internal networks, unauthorized traffic into and out of the subnet is blocked or restricted by firewalls as per policies configured.

The Network Security Regime for the Hybrid Connection of Healthcare Entities

Capacitive Micromachined Ultrasonic Transducer (CMUT) is a type of ultrasonic transducer that can be applied in many fields like chemical and mechanical sensing, physical imaging, and bio-imaging. Sacrificial layer release is one of the fabrication methods and cavity releasing is the key part of this method. The stress of the sacrificial material is one of the causes making membranes break in this procedure. The previous studies had a phospho-silicide-glass (PSG) layer deposited between polysilicon sacrificial layer and silicon nitride membrane with LPCVD partially solved the problem. However, its processing temperature is relatively high, which makes it not compatible with CMOS integrated circuits (ICs). This work fabricated CMUTs in the sacrificial layer release process, with polysilicon as the main sacrificial layer. Utilizing chemical reaction of polysilicon in ashing process, a thin oxide was formed between the sacrificial layer and membrane while removing the remaining photoresist with ashing. The result showed that it could also help produce large membranes with a lower processing temperature, which can be more compatible with CMOS ICs. After fabrication, the impedance of an element with 100 μm diameter cells was measured to be several hundred ohms in air with 30 V bias voltage and the resonance frequency was 4.7 MHz.

Mang I Vai

Papers

In vivo validation of quasi-static field model in intra-body communication

An Investigation on Conductive Intracardiac Communication Dynamic Channel Gain During the Cardiac Cycle for Leadless Pacemakers

Temperature Fiber Sensor Based on 1-D CNN Incorporated Time-Stretch Method for Accurate Detection

The Network Security Regime for the Hybrid Connection of Healthcare Entities

Fabrication of CMUTs using sacrificial release process with ashing assisted polysilicon release