Length-speed ratio (lsr) as a characteristic for moving elements real-time classification

In this article, the length?speed ratio (LSR) is proposed as a basic characteristic for the real-time detection of moving objects. We define the LSR of a uniform moving zone as the relation between its length in the direction of motion and the speed of this motion. For a given zone of the image with uniform gray level (or patch), the greater its length in the direction of motion and the smaller its speed, the greater its LSR. A moving element is generally composed of various zones of uniform gray levels (or patches), which move with the same speed but which have different lengths in the direction of motion and which therefore have a characteristic set of LSR values. In this article, this ?LSR footprint? is proposed as the basic characteristic for the detection and subsequent classification of moving elements in image sequences. The problem of detecting a moving element in a sequence of images is transformed into the recognition of a pattern on a static image, namely the LSR footprint. We also specify how to obtain this characteristic in real time, we discuss its invariants and we consider the cases for which LSR detection of movement is applicable. We also present its use in some significant examples and we compare it with other methods applicable to similar computational problems

Quality of Service over Specific Link Layers: state of the art report

The Integrated Services concept is proposed as an enhancement to the current Internet architecture, to provide a better Quality of Service (QoS) than that provided by the traditional Best-Effort service. The features of the Integrated Services are explained in this report. To support Integrated Services, certain requirements are posed on the underlying link layer. These requirements are studied by the Integrated Services over Specific Link Layers (ISSLL) IETF working group. The status of this ongoing research is reported in this document. To be more specific, the solutions to provide Integrated Services over ATM, IEEE 802 LAN technologies and low-bitrate links are evaluated in detail. The ISSLL working group has not yet studied the requirements, that are posed on the underlying link layer, when this link layer is wireless. Therefore, this state of the art report is extended with an identification of the requirements that are posed on the underlying wireless link, to provide differentiated Quality of Service

Is time the real line?

This paper is devoted to discussing the topological structure of the arrow of time. In the literature, it is often accepted that its algebraic and topological structures are that of a one-dimensional Euclidean space $\mathbb{E}^1$, although a critical review on the subject is not easy to be found. Hence, leveraging on an operational approach, we collect evidences to identify it structurally as a normed vector space $(\mathbb{Q}, |\cdot|)$, and take a leap of abstraction to complete it, up to isometries, to the real line. During the development of the paper, the space-time is recognized as a fibration, with the fibers being the sets of simultaneous events. The corresponding topology is also exposed: open sets naturally arise within our construction, showing that the classical space-time is non-Hausdorff. The transition from relativistic to classical regimes is explored too.Comment: 26 pages, 9 figures. Misprints corrected and minor adjustments according to the review proces

Digital neuromorphic auditory systems

This dissertation presents several digital neuromorphic auditory systems. Neuromorphic systems are capable of running in real-time at a smaller computing cost and consume lower power than on widely available general computers. These auditory systems are considered neuromorphic as they are modelled after computational models of the mammalian auditory pathway and are capable of running on digital hardware, or more specifically on a field-programmable gate array (FPGA). The models introduced are categorised into three parts: a cochlear model, an auditory pitch model, and a functional primary auditory cortical (A1) model. The cochlear model is the primary interface of an input sound signal and transmits the 2D time-frequency representation of the sound to the pitch models as well as to the A1 model. In the pitch model, pitch information is extracted from the sound signal in the form of a fundamental frequency. From the A1 model, timbre information in the form of time-frequency envelope information of the sound signal is extracted. Since the computational auditory models mentioned above are required to be implemented on FPGAs that possess fewer computational resources than general-purpose computers, the algorithms in the models are optimised so that they fit on a single FPGA. The optimisation includes using simplified hardware-implementable signal processing algorithms. Computational resource information of each model on FPGA is extracted to understand the minimum computational resources required to run each model. This information includes the quantity of logic modules, register quantity utilised, and power consumption. Similarity comparisons are also made between the output responses of the computational auditory models on software and hardware using pure tones, chirp signals, frequency-modulated signal, moving ripple signals, and musical signals as input. The limitation of the responses of the models to musical signals at multiple intensity levels is also presented along with the use of an automatic gain control algorithm to alleviate such limitations. With real-world musical signals as their inputs, the responses of the models are also tested using classifiers – the response of the auditory pitch model is used for the classification of monophonic musical notes, and the response of the A1 model is used for the classification of musical instruments with their respective monophonic signals. Classification accuracy results are shown for model output responses on both software and hardware. With the hardware implementable auditory pitch model, the classification score stands at 100% accuracy for musical notes from the 4th and 5th octaves containing 24 classes of notes. With the hardware implementation auditory timbre model, the classification score is 92% accuracy for 12 classes musical instruments. Also presented is the difference in memory requirements of the model output responses on both software and hardware – pitch and timbre responses used for the classification exercises use 24 and 2 times less memory space for hardware than software

Virtual metrology for plasma etch processes.

Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point

Virtual metrology for plasma etch processes.

Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point

Experimental and model-based analysis of twin-screw wet granulation in pharmaceutical processes

A shift from batch to continuous processing is challenging but equally rewarding for the pharmaceutical sector. This opportunity for moving beyond traditional batch processing is possible due to a change of attitude in the regulatory environment by the publication of the process analytical technology (PAT) guidance. However, in order to utilise this opportunity, detailed process understanding about the key processes in pharmaceutical manufacturing is required to turn this transformation to the continuous mode into a success. Continuous wet granulation is a crucial part of future continuous manufacturing of solid dosage forms. Continuous high shear wet granulation is performed using a twin-screw granulator (TSG) which is characterised by a modular screw profile including a sequence of different screw elements with various shapes, orientations and functions. A TSG achieves mixing and granulation by a complex interplay between the screw configuration and process settings (e.g. feed rate, screw speed, etc.) to produce granules with certain specifications in a short time. Therefore, a fundamental understanding of these complex phenomena is required to optimise and control this new technology. Analysing the twin-screw wet granulation to a satisfactory degree is only possible when sufficient information on the rheo-kinetic characteristics of the granulation mixture is available. Thus an investigation of residence time distribution (RTD), the solid-liquid mixing, and the resulting granule size distribution (GSD) evolution governed by the field conditions in the TSG contain interesting information about mixing and different granulation rate processes such as aggregation and breakage. For this purpose, a combination of experimental and mathematical techniques/approaches was applied in this work. Additionally, a single placebo formulation based on α-lactose monohydrate was granulated in the experimental studies performed to verify the hypothesis proposed in this work. The characterisation of wetted material transport and mixing inside the confined spaces of the rotating screws was performed by the experimental determination of the residence time distribution at different process conditions and screw configurations using near infrared chemical imaging. The experimental data was later compared with a conceptual model based on classical chemical engineering methods to estimate the parameters of the model and to analyse the effects of changes in number of kneading discs and their stagger angle, screw speed, material throughput and liquid-to-solid ratio (L/S) on RTD. According to this study, increased screw speed resulted in a low mean residence time mean residence time and wider RTD, i.e. more axial mixing. Increasing powder feed rate increased mean residence time by higher throughput force while increasing L/S increased mean residence time by raising the sluggishness or inertia of the material in the barrel. The material transport in the mixing zone(s) of the TSG became more plug-flow like. Thus, an increase in the number of kneading discs reduced the axial mixing in the barrel. In addition, to understand the GSD dynamics as a function of individual screw modules along the TSG barrel, the change in GSD was investigated both experimentally and mathematically. Using a TSG which allows the opening of the barrel, samples from several locations inside the TSG barrel were collected after granulation at different process conditions and screw configurations. A detailed experimental investigation was hence performed to understand the granule size and shape dynamics in the granulator. The experimental data from this study together with the residence time measurements was then used for calibrating a population balance model for each kneading disc module in the twin-screw granulator in order to obtain an improved insight into the role of the kneading discs at certain locations inside the TSG. The study established that the kneading block in the screw configuration acts as a plug-flow zone inside the granulator. It was found that a balance between the throughput force and conveying rate is required to obtain a good axial mixing inside the twin-screw granulator. Also, a high throughput can be achieved by increasing the liquid-solid ratio and screw speed. Furthermore, the study indicated that the first kneading block after wetting caused an increased aggregation rate, which was reduced after the material processing by the second kneading block. In contrast, the breakage rate in the increased successively along the length of the granulator. Such a reversion in physical phenomena indicated potential separation between the granulation regimes, which can be promising for future design and advanced control of the continuous twin-screw granulation process. In another experimental study the transport and mixing (both axial and bulk mixing of solid-liquid) was linked to the GSD of the produced granules. This study demonstrated that insufficient solid-liquid mixing due to inability of the currently used kneading discs is the reason behind the inferior performance of the TSG in terms of yield. It was shown that other factors which support mixing such as higher axial mixing at a high screw speed and a low fill ratio support an increase in the yield. However, more effort is required to explore non-conventional screw elements with modified geometries to find screws which can effectively mix the solid-liquid material. Furthermore, in order to generalise the TSG knowledge, a regime map based approach was applied. Herewith, the scale independent parameters, L/S and specific mechanical energy (SME) were correlated. It was shown that an increasing L/S strongly drives the GSD towards a larger mean granule size. However, an increasing energy input to the system can effectively be used to lower the mean granule size and also narrow the width of the size distribution. Along with this, particle-scale simulations for the characterisation of liquid distribution in the mixing zone of the granulator were performed. It was found that the agglomeration is rather a delayed process which takes place by redistribution of liquid once the excess liquid on the particle surface is transferred to the liquid bridges. Moreover, the transfer of liquid from particle surface to liquid bridges, i.e. initialisation of agglomeration, is most dominant in the intermeshing region of the kneading discs. Besides the major outcomes of this work, i.e. building fundamental knowledge on pharmaceutical twin-screw wet granulation by combining experimental and theoretical approaches to diagnose the transport, mixing and constitutive mechanisms, several gaps and potential research needs were identified as well. As the regulators have opened up to increasingly rely on the science- and risk-based holistic development of pharmaceutical processes and products for commercialisation, the opportunity as well as responsibility lies with academic and industrial partners to develop a systematic framework and scientific approach to utilise this opportunity efficiently

Accumulative computation method for motion features extraction in active selective visual attention

A new method for active visual attention is briefly introduced in this paper. The method extracts motion and shape features from indefinite image sequences, and integrates these features to segment the input scene. The aim of this paper is to highlight the importance of the accumulative computation method for motion features extraction in the active selective visual attention model proposed. We calculate motion presence and velocity at each pixel of the input image by means of accumulative computation. The paper shows an example of how to use motion features to enhance scene segmentation in this active visual attention method

Motion features to enhance scene segmentation in active visual attention

A new computational model for active visual attention is introduced in this paper. The method extracts motion and shape features from video image sequences, and integrates these features to segment the input scene. The aim of this paper is to highlight the importance of the motion features present in our algorithms in the task of refining and/or enhancing scene segmentation in the method proposed. The estimation of these motion parameters is performed at each pixel of the input image by means of the accumulative computation method, using the so-called permanency memories. The paper shows some examples of how to use the ?motion presence?, ?module of the velocity? and ?angle of the velocity? motion features, all obtained from accumulative computation method, to adjust different scene segmentation outputs in this dynamic visual attention method