Abstract
This book presents, in an integrated form, both the analysis and synthesis of three different types of hidden Markov models. Unlike other books on the subject, it is generic and does not focus on a specific theme, e.g. speech processing. Moreover, it presents the translation of hidden Markov models’ concepts from the domain of formal mathematics into computer codes using MATLAB®. The unique feature of this book is that the theoretical concepts are first presented using an intuition-based approach followed by the description of the fundamental algorithms behind hidden Markov models using MATLAB®. This approach, by means of analysis followed by synthesis, is suitable for those who want to study the subject using a more empirical approach.

Abstract
The Gemini Infrared Multi-Object Spectrograph (GIRMOS) instrument proposes to carry out Multi-Object Adaptive Optics (MOAO) correction on the residual of the Gemini Mutlti-Conjugate AO System (GeMS)corrected wavefronts in either Ground Layer (GLAO) or Multi-Conjugate (MCAO) mode. This work has been undertaken to determine the extent to which the ensquared energy delivered to a GIRMOS IFU can be improved over typical GeMS operation by adding MOAO correction. One of the key advantages of using the MOAO-fed IFUs is the improvement in performance toward the edge of the field, making the full 2’ field of GeMS more available for simultaneous observing. Using the Object Oriented Matlab Adaptive Optics (OOMAO) library1 to simulate the full system under a wide range of configurations and error conditions, we have established the baseline error budget and used the simulation to enable ongoing investigation into the particular control schemes and system errors that arise from using GeMS LGS and NGS WFSs to divide atmospheric correction between up to 3 DMs at different altitude conjugations and optimization directions.

Abstract
The literature on gait analysis in Vascular Parkinsonism (VaP), addressing issues such as variability, foot clearance patterns, and the effect of levodopa, is scarce. This study investigates whether spatiotemporal, foot clearance and stride-to-stride variability analysis can discriminate VaP, and responsiveness to levodopa. Fifteen healthy subjects, 15 Idiopathic Parkinson's Disease (IPD) patients and 15 VaP patients, were assessed in two phases: before (Off-state), and one hour after (On-state) the acute administration of a suprathreshold (1.5 times the usual) levodopa dose. Participants were asked to walk a 30-meter continuous course at a self-selected walking speed while wearing foot-worn inertial sensors. For each gait variable, mean, coefficient of variation (CV), and standard deviations SDI and SD2 obtained by Poincare analysis were calculated. General linear models (GLMs) were used to identify group differences. Patients were subject to neuropsychological evaluation (MoCA test) and Brain MRI. VaP patients presented lower mean stride velocity, stride length, lift-off and strike angle, and height of maximum toe (later swing) (p < .05), and higher %gait cycle in double support, with only the latter unresponsive to levodopa. VaP patients also presented higher CV, significantly reduced after levodopa. Yet, all VaP versus IPD differences lost significance when accounting for mean stride length as a covariate. In conclusion, VaP patients presented a unique gait with reduced degrees of foot clearance, probably correlated to vascular lesioning in dopaminergic/non-dopaminergic cortical and subcortical non-dopaminergic networks, still amenable to benefit from levodopa. The dependency of gait and foot clearance and variability deficits from stride length deserves future clarification.

Abstract
In this study, an optical signal recording method for optogenetics stimulation of ChR2 channels expressed in human pulp dental (HPD) cells by using a fiber optic refractive index (RI) sensor based on all fiber Mach-Zehnder interferometer was proposed. All-fiber Mach-Zender interferometric biosensor is composed of a specially fabricated twin-core fiber spliced between two pieces of a single-mode fiber which one of the cores was doped with germanium and the other with phosphorous [1]. The interference pattern in the fiber Mach-Zehnder interferometer is occurred by coupling of the propagation lights of both fiber cores. For coupling the light into both cores, a short length of a coreless fiber optic was used. The length of twin-core fiber was 40 cm. Here, one core of the fiber acts as a reference arm and the other cores as sensing arm. For increasing evanescent wave around the sensing arm of the fiber optic biosensor, a short section of the cladding of the twin-core fiber about 2 cm was etched with HF solution. For this propose, after determining the direction of the cores so that the two cores were in the vertical direction, one side of the twin-core fiber was fixed on Plexiglas substrate by using UV glow and the upper side of the sensor was etched. The thickness of remained clad around the upper core was about 1 micrometer. In the experimental setup as is shown in Fig. 1(a), light from an SLD at 1550 nm after passing an isolator arrived at the sensor and output spectrum was monitored with an optical spectrum analyzer which has 10 pm wavelength resolution. The best RI sensitivity of the sensor in the range of 1.39 to 1.43 was obtained to be 675.74 nm/RIU. For detecting of cell signal by using optogenetic stimulation which ChR2 opsin was expressed on HPD cells, it needs that high concentrations of cells were immobilized to the etched fiber surface by PLL biopolymer. Optogenetic stimulation of ChR2 channel was done using a 470 nm laser diode [2] pulse with a frequency of 15 Hz, a number of pulses 120, duty cycle 50 in 60 seconds, and 300 second rest time. As a result of optogenetic stimulation and activation of light-sensitive ion channels, effective RI around the fiber optic biosensor changes [3]. Obtained results were shown in Fig. 1(b). Changes in the RI lead to a wavelength shift of the sensor spectrum. © 2019 IEEE.

Abstract
There is an increasing number of mobile robot applications. The demanding of the Industry 4.0 pushes the robotic areas in the direction of the decision. The autonomous robots should actually decide the path according to the dynamic environment. In some cases, time requirements must also be attended and require fast path planning methods. This paper addresses a comparison between well-known path planning methods using a realistic simulator that handles the dynamic properties of robot models including sensors. The methodology is implemented in SimTwo that allows to compare the A* and RRT* algorithms in different scenarios with dynamic and real time constraint scenarios. Copyright

Abstract
The emergence and popularization of online social networks suddenly made available a large amount of data from social organization, interaction and human behavior. All this information opens new perspectives and challenges to the study of social systems, being of interest to many fields. Although most online social networks are recent, a vast amount of scientific papers was already published on this topic, dealing with a broad range of analytical methods and applications. Therefore, the development of a tool capable of gather tailored information from social networks is something that can help a lot of researchers on their work, especially in the area of Natural Language Processing (NLP). Nowadays, the daily base medium where people use more often text language lays precisely on social networks. Therefore, the ubiquitous crawling of social networks is of the utmost importance for researchers. Such a tool will allow the researcher to get the relevant needed information, allowing a faster research in what really matters, without loosing time on the development of his own crawler. In this paper, we present an extensive analysis of the existing social networks and their APIs, and also describe the conception and design of a social network crawler which will help NLP researchers. © 2019 Association for Computing Machinery.