Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Time motion analysis of football (soccer) referees during official matches in relation to the type of fluid consumed

The aim of the present study was to determine the effect of volume and composition of fluid replacement on the physical performance of male football referees. Ten referees were evaluated during three official matches. In one match the participants were asked to consume mineral water ad libitum, and in the others they consumed a pre-determined volume of mineral water or a carbohydrate electrolyte solution (6.4% carbohydrate and 22 mM Na+) equivalent to 1% of their baseline body mass (half before the match and half during the interval). Total water loss, sweat rate and match physiological performance were measured. When rehydrated ad libitum (pre-match and at half time) participants lost 1.97 ± 0.18% of their pre-match body mass (2.14 ± 0.19 L). This parameter was significantly reduced when they consumed a pre-determined volume of fluid. Sweat rate was significantly reduced when the referees ingested a pre-determined volume of a carbohydrate electrolyte solution, 0.72 ± 0.12 vs 1.16 ± 0.11 L/h ad libitum. The high percentage (74.1%) of movements at low speed (walking, jogging) observed when they ingested fluid ad libitum was significantly reduced to 71% with mineral water and to 69.9% with carbohydrate solution. An increase in percent movement expended in backward running was observed when they consumed a pre-determined volume of carbohydrate solution, 7.7 ± 0.5 vs 5.5 ± 0.5% ad libitum. The improved hydration status achieved with the carbohydrate electrolyte solution reduced the length of time spent in activities at low-speed movements and increased the time spent in activities demanding high-energy expenditure.

Three-dimensional kinematic analysis of upper and lower limb motion during gait of post-stroke patients

The aim of this study was to analyze the alterations of arm and leg movements of patients during stroke gait. Joint angles of upper and lower limbs and spatiotemporal variables were evaluated in two groups: hemiparetic group (HG, 14 hemiparetic men, 53 ± 10 years) and control group (CG, 7 able-bodied men, 50 ± 4 years). The statistical analysis was based on the following comparisons (P ≤ 0.05): 1) right versus left sides of CG; 2) affected (AF) versus unaffected (UF) sides of HG; 3) CG versus both the affected and unaffected sides of HG, and 4) an intracycle comparison of the kinematic continuous angular variables between HG and CG. This study showed that the affected upper limb motion in stroke gait was characterized by a decreased range of motion of the glenohumeral (HG: 6.3 ± 4.5, CG: 20.1 ± 8.2) and elbow joints (AF: 8.4 ± 4.4, UF: 15.6 ± 7.6) on the sagittal plane and elbow joint flexion throughout the cycle (AF: 68.2 ± 0.4, CG: 46.8 ± 2.7). The glenohumeral joint presented a higher abduction angle (AF: 14.2 ± 1.6, CG: 11.5 ± 4.0) and a lower external rotation throughout the cycle (AF: 4.6 ± 1.2, CG: 22.0 ± 3.0). The lower limbs showed typical alterations of the stroke gait patterns. Thus, the changes in upper and lower limb motion of stroke gait were identified. The description of upper limb motion in stroke gait is new and complements gait analysis.

Real-time monitoring of laser scribing process utilizing high-speed camera

Currently, laser scribing is growing material processing method in the industry. Benefits of laser scribing technology are studied for example for improving an efficiency of solar cells. Due high-quality requirement of the fast scribing process, it is important to monitor the process in real time for detecting possible defects during the process. However, there is a lack of studies of laser scribing real time monitoring. Commonly used monitoring methods developed for other laser processes such a laser welding, are sufficient slow and existed applications cannot be implemented in fast laser scribing monitoring. The aim of this thesis is to find a method for laser scribing monitoring with a high-speed camera and evaluate reliability and performance of the developed monitoring system with experiments. The laser used in experiments is an IPG ytterbium pulsed fiber laser with 20 W maximum average power and Scan head optics used in the laser is Scanlab’s Hurryscan 14 II with an f100 tele-centric lens. The camera was connected to laser scanner using camera adapter to follow the laser process. A powerful fully programmable industrial computer was chosen for executing image processing and analysis. Algorithms for defect analysis, which are based on particle analysis, were developed using LabVIEW system design software. The performance of the algorithms was analyzed by analyzing a non-moving image from the scribing line with resolution 960x20 pixel. As a result, the maximum analysis speed was 560 frames per second. Reliability of the algorithm was evaluated by imaging scribing path with a variable number of defects 2000 mm/s when the laser was turned off and image analysis speed was 430 frames per second. The experiment was successful and as a result, the algorithms detected all defects from the scribing path. The final monitoring experiment was performed during a laser process. However, it was challenging to get active laser illumination work with the laser scanner due physical dimensions of the laser lens and the scanner. For reliable error detection, the illumination system is needed to be replaced.

Design and Material Selection of High-Speed Rotating Electrical Machines

The increasing emphasis on energy efficiency is starting to yield results in the reduction in greenhouse gas emissions; however, the effort is still far from sufficient. Therefore, new technical solutions that will enhance the efficiency of power generation systems are required to maintain the sustainable growth rate, without spoiling the environment. A reduction in greenhouse gas emissions is only possible with new low-carbon technologies, which enable high efficiencies. The role of the rotating electrical machine development is significant in the reduction of global emissions. A high proportion of the produced and consumed electrical energy is related to electrical machines. One of the technical solutions that enables high system efficiency on both the energy production and consumption sides is high-speed electrical machines. This type of electrical machines has a high system overall efficiency, a small footprint, and a high power density compared with conventional machines. Therefore, high-speed electrical machines are favoured by the manufacturers producing, for example, microturbines, compressors, gas compression applications, and air blowers. High-speed machine technology is challenging from the design point of view, and a lot of research is in progress both in academia and industry regarding the solution development. The solid technical basis is of importance in order to make an impact in the industry considering the climate change. This work describes the multidisciplinary design principles and material development in high-speed electrical machines. First, high-speed permanent magnet synchronous machines with six slots, two poles, and tooth-coil windings are discussed in this doctoral dissertation. These machines have unique features, which help in solving rotordynamic problems and reducing the manufacturing costs. Second, the materials for the high-speed machines are discussed in this work. The materials are among the key limiting factors in electrical machines, and to overcome this limit, an in-depth analysis of the material properties and behavior is required. Moreover, high-speed machines are sometimes operating in a harsh environment because they need to be as close as possible to the rotating tool and fully exploit their advantages. This sets extra requirements for the materials applied.

Structural analysis of the Paint Lake Deformation Zone, Northern Ontario /

The Paint Lake Deformation Zone (PLDZ), located within the Superior Province of Canada, demarcates a major structural and lithological break between the Onaman-Tashota Terrane to the north and the Beardmore-Geraldton Belt to the south. The PLDZ is an east-west trending lineament, approximately 50 km in length and up to 1 km in width, comprised of an early ductile component termed the Paint Lake Shear Zone and a late brittle component known as the Paint Lake Fault. Structures associated with PLDZ development including S-, C- and C'-fabrics, stretching lineations, slickensides, C-C' intersection lineations, Z-folds and kinkbands indicate that simple shear deformation dominated during a NW-SE compressional event. Movement along the PLDZ was in a dextral sense consisting of an early differential motion with southside- down and a later strike-slip motion. Although the locus of the PLDZ may in part be lithologically controlled, mylonitization which accompanied shear zone development is not dependent on the lithological type. Conglomerate, intermediate and mafic volcanic units exhibit similar mesoscopic and microscopic structures where transected by the PLDZ. Field mapping, supported by thin section analysis, defines five strain domains increasing in intensity of deformation from shear zone boundary to centre. A change in the dominant microstructural deformation mechanism from dislocation creep to diffusion creep is observed with increasing strain during mylonitization. C'-fabric development is temporally associated with this change. A decrease in the angular relationship between C- and C'-fabrics is observed upon attaining maximum strain intensity. Strain profiling of the PLDZ demonstrates the presence of an outer primary strain gradient which exhibits a simple profile and an inner secondary strain gradient which exhibits a more complex profile. Regionally metamorphosed lithologies of lower greenschist facies outside the PLDZ were subjected to retrograde metamorphism during deformation within the PLDZ.

Differences in Standing and Sitting Postures of Youth with Idiopathic Scoliosis from Quantitative Analysis of Digital Photographs

The objective of this study was to explore whether differences in standing and sitting postures of youth with idiopathic scoliosis could be detected from quantitative analysis of digital photographs. Standing and sitting postures of 50 participants aged 10–20-years-old with idiopathic scoliosis (Cobb angle: 15° to 60°) were assessed from digital photographs using a posture evaluation software program. Based on the XY coordinates of markers, 13 angular and linear posture indices were calculated in both positions. Paired t-tests were used to compare values of standing and sitting posture indices. Significant differences between standing and sitting positions (p < 0.05) were found for head protraction, shoulder elevation, scapula asymmetry, trunk list, scoliosis angle, waist angles, and frontal and sagittal plane pelvic tilt. Quantitative analysis of digital photographs is a clinically feasible method to measure standing and sitting postures among youth with scoliosis and to assist in decisions on therapeutic interventions.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Recurrence Quantification Analysis of System Signals for Detecting Tool and Chatter in Turning

In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Design and synthesis of efficient mac architectures for high speed decimal processor

Most of the commercial and financial data are stored in decimal fonn. Recently, support for decimal arithmetic has received increased attention due to the growing importance in financial analysis, banking, tax calculation, currency conversion, insurance, telephone billing and accounting. Performing decimal arithmetic with systems that do not support decimal computations may give a result with representation error, conversion error, and/or rounding error. In this world of precision, such errors are no more tolerable. The errors can be eliminated and better accuracy can be achieved if decimal computations are done using Decimal Floating Point (DFP) units. But the floating-point arithmetic units in today's general-purpose microprocessors are based on the binary number system, and the decimal computations are done using binary arithmetic. Only few common decimal numbers can be exactly represented in Binary Floating Point (BF P). ln many; cases, the law requires that results generated from financial calculations performed on a computer should exactly match with manual calculations. Currently many applications involving fractional decimal data perform decimal computations either in software or with a combination of software and hardware. The performance can be dramatically improved by complete hardware DFP units and this leads to the design of processors that include DF P hardware.VLSI implementations using same modular building blocks can decrease system design and manufacturing cost. A multiplexer realization is a natural choice from the viewpoint of cost and speed.This thesis focuses on the design and synthesis of efficient decimal MAC (Multiply ACeumulate) architecture for high speed decimal processors based on IEEE Standard for Floating-point Arithmetic (IEEE 754-2008). The research goal is to design and synthesize deeimal'MAC architectures to achieve higher performance.Efficient design methods and architectures are developed for a high performance DFP MAC unit as part of this research.

Performance analysis of FIR digital filter design: RNS versus traditional

Residue Number System (RNS) based Finite Impulse Response (FIR) digital filters and traditional FIR filters. This research is motivated by the importance of an efficient filter implementation for digital signal processing. The comparison is done in terms of speed and area requirement for various filter specifications. RNS based FIR filters operate more than three times faster and consumes only about 60% of the area than traditional filter when number of filter taps is more than 32. The area for RNS filter is increasing at a lesser rate than that for traditional resulting in lower power consumption. RNS is a nonweighted number system without carry propogation between different residue digits.This enables simultaneous parallel processing on all the digits resulting in high speed addition and multiplication in the RNS domain

Performance Analysis of Reversible Fast Decimal Adders

This paper presents a performance analysis of reversible, fault tolerant VLSI implementations of carry select and hybrid decimal adders suitable for multi-digit BCD addition. The designs enable partial parallel processing of all digits that perform high-speed addition in decimal domain. When the number of digits is more than 25 the hybrid decimal adder can operate 5 times faster than conventional decimal adder using classical logic gates. The speed up factor of hybrid adder increases above 10 when the number of decimal digits is more than 25 for reversible logic implementation. Such highspeed decimal adders find applications in real time processors and internet-based applications. The implementations use only reversible conservative Fredkin gates, which make it suitable for VLSI circuits.

An efficient scheme for the evaluation of coding performance of high speed links incorporating joint error behaviour based on Monte Carlo Method

While channel coding is a standard method of improving a system’s energy efficiency in digital communications, its practice does not extend to high-speed links. Increasing demands in network speeds are placing a large burden on the energy efficiency of high-speed links and render the benefit of channel coding for these systems a timely subject. The low error rates of interest and the presence of residual intersymbol interference (ISI) caused by hardware constraints impede the analysis and simulation of coded high-speed links. Focusing on the residual ISI and combined noise as the dominant error mechanisms, this paper analyses error correlation through concepts of error region, channel signature, and correlation distance. This framework provides a deeper insight into joint error behaviours in high-speed links, extends the range of statistical simulation for coded high-speed links, and provides a case against the use of biased Monte Carlo methods in this setting

Annealing inducedlowcoercivity,nanocrystallineCo–Fe–Si thin films exhibitinginversecosine angular variation

Co–Fe–Si based films exhibit high magnetic moments and are highly sought after for applications like soft under layer sinper pendicular recording mediatomagneto-electro-mechanical sensor applications.In this workt he effect of annealing on s tructural,morphologicaland magnetic propertiesofco–Fe–Si thin films wasinvestigated.compositional analysis using x-rayphotoelectron spectroscopy and secondary ion massspectroscopyrevealedanativeoxidesurfacelayerconsistingofoxidesofco,feandsionthe surface. The morphology of theas deposited films shows mound like structures conformingtothe Volmer–Webergrowthmodel.Nanocrystallisationofamorphous films upon annealing was observed by glancing anglex-raydiffraction and transmission electron microscopy.Theevolutionofmagnetic properties with annealing is explained using the Herzermodel.Vibrating sample magnetometry measurements carried out at various angles from01 to 901 to the applied magnetic field were employed to study the angula rvariation of coercivity.The angular variation fits the modified Kondorsky model. Interestingly,the coercivity evolution with annealing deduced frommagneto-opticalKerreffectstudies indicates areversetrendcomparedtomagetisationobservedinthebulk.Thiscanbeattributedtoa domain wallpinningatnativeoxidelayeronthesurfaceofthin films. Theevolutionofsurfacemagnetic properties iscorrelatedwithmorphologyevolutionprobedusingatomicforcemicroscopy.The morphology aswellasthepresenceofthenativeoxidelayerdictatesthesurfacemagneticproperties and this is corroborated by the apparent difference in the bulk and surface magnetic properties