A secure cookie scheme

Cookies are the primary means for web applications to authenticate HTTP requests and to maintain client states. Many web applications (such as those for electronic commerce) demand a secure cookie scheme. Such a scheme needs to provide the following four services: authentication, confidentiality, integrity, and anti-replay. Several secure cookie schemes have been proposed in previous literature; however, none of them are completely satisfactory. In this paper, we propose a secure cookie scheme that is effective, efficient, and easy to deploy. In terms of effectiveness, our scheme provides all of the above four security services. In terms of efficiency, our scheme does not involve any database lookup or public key cryptography. In terms of deployability, our scheme can be easily deployed on existing web services, and it does not require any change to the Internet cookie specification. We implemented our secure cookie scheme using PHP and conducted experiments. The experimental results show that our scheme is very efficient on both the client side and the server side.A notable adoption of our scheme in industry is that our cookie scheme has been used by Wordpress since version 2.4. Wordpress is a widely used open source content management system.     

Analysis and tuning of adaptive generalized predictive control

The adaptive Generalized Predictive Controller (Clarke et al., 1987a, b) is capable of controlling plants with variable dead-time, unknown model orders and unstable poles and zeros. This paper shows how the GPC control law can be written in an equivalent general linear transfer function form which simplifies closed-loop (eg. root locus) analysis. Three recommended strategies for selecting the design parameters during the commissioning stage allow the user to adjust the closed-loop speed of response on-line using only a single active tuning parameter. Experimental runs confirm the ability of adaptive GPC to provide a consistent closed-loop response in spite of large process changes.     

Stiction – definition, modelling, detection and quantification

Stiction or high static friction is a common problem in spring-diaphragm type control valves, which are widely used in the process industry. Recently, there have been many attempts to understand, define, model and detect stiction in control valves. There are several methods for detecting stiction, but quantification of the actual amount of stiction still remains a challenge. This paper discusses briefly the definition and modelling of stiction. Then it demonstrates a new method to detect and quantify the actual amount of valve stiction using routine operating data. The proposed method is completely data-driven. No additional excitation or experimentation of the plant is required.     

Home Automation Using Augmented Reality (HAAR)

Wireless Personal Communications - The development of Smart Home Controllers has seen rapid growth in recent years, especially for smart devices, that can utilize the Internet of Things (IoT)....     

Detection and quantification of valve stiction by the method of unknown input estimation

Valve stiction is one of the most common causes of oscillations in industrial process control loops. Such oscillations can degrade the overall performance of the loop and eventually the final product quality. The detection and quantification of valve stiction in industrial process control loops is thus important. From previous studies in the literature, a sticky valve has been shown to have a distinct signature of the stiction phenomena in its valve positioner data. However, the position of the modulating control valves is seldom available. We consider the problem of estimating the valve position as an unknown input estimation problem. In this work, we propose a novel application of the unknown input estimator in order to estimate the valve position given the process model and the data of the process variable and controller output. Using the estimated valve position, we can detect and also quantify the amount of stiction. We demonstrate the efficacy of the method through simulation examples where a sticky valve is deliberately introduced in the closed loop using a two-parameter stiction model available in the literature. Application of the proposed methodology to a laboratory scale flow control loop is presented. An industrial case study is also presented in which the algorithm accurately detects and quantifies stiction in the level control loop of a power plant.     

Hop chains: Secure routing and the establishment of distinct identities

We present a secure routing protocol that is immune to Sybil attacks and that can tolerate collusion of Byzantine routers. It can tolerate either initial collusion of Byzantine routers or runtime collusion of non-adjacent Byzantine routers, both in the absence of runtime collusion between adjacent routers. For these settings, the calculated distance from a destination to a node is not smaller than the actual shortest distance from the destination to the node. The protocol can also simultaneously tolerate initial collusion of Byzantine routers and runtime collusion of adjacent Byzantine routers but in the absence of runtime collusion between non-adjacent routers. For this setting, it guarantees a bound on the difference between the calculated distance and the actual shortest distance. The bound depends on the number of Byzantine routers on a path. The protocol makes very weak timing assumptions and requires synchronization only between neighbors or second neighbors. We propose to use this protocol for secure localization of routers using hop-count distances, which can be then used as a proof of identity of nodes.     

Closed loop identification and control loop reconfiguration: an industrial case study

The results of a joint university–industry collaborative project for control loop reconfiguration using closed loop experimental data from a fuel gas pressure control system are described in this paper. The fuel gas pressure was being regulated using a butane stream. For economic reasons, it was necessary to switch control to the ethane stream. Previous attempts at effecting this changeover had proved unsuccessful. In this study, a powerful system identification technique namely Canonical Variate Analysis (CVA) was employed to obtain the empirical plant models. A PI controller was then designed using the direct synthesis method. Acceptable closed loop behavior was obtained with little online tuning.     

Utility of solid phase spectrophotometry for the modified determination of trace amounts of cadmium in food samples

A modified selective, highly sensitive and accurate procedure for the determination of trace amounts of cadmium which reacts with 1-(2-benzothiazolylazo)-2-hydroxy-3-naphthoic acid (BTAHNA) to give a deep violet complex with high molar absorptivity (7.05 × 10⁶ L mol⁻¹ cm⁻¹, 3.92 × 10⁷ L mol⁻¹ cm⁻¹, 1.78 × 10⁸ L mol⁻¹ cm⁻¹, and 4.10 × 10⁸ L mol⁻¹ cm⁻¹), fixed on a Dowex 1-X8 type anion-exchange resin for 10 mL, 100 mL, 500 mL, and 1000 mL, respectively. Calibration is linear over the range 0.2-3.5 μg L⁻¹ with RSD of ?1.14% (n = 10). The detection and quantification limits were calculated. Increasing the sample volume can enhance the sensitivity. The method has been successfully applied for the determination of Cd(II) in food samples, water samples and some salts samples without interfering effect of various cations and anions.     

An image differencing method for interface level detection in separation cells

Bitumen extraction from oil sands is carried out in large separation cells using a water-based extraction process. Controlling the Bitumen-froth and Middlings interface in these cells at an optimum level provides significant economical and environmental benefits. Traditional sensors are not reliable in estimating this interface level and novel vision-based sensors have been developed previously to overcome this problem. These sensors estimate the interface level and its confidence for separation cells with a single sight glass. The confidence value only represents the turbidity of the interface and hence cannot be used for control decision making in all process conditions. The current work describes an image differencing algorithm for interface level detection which also facilitates the computation of a confidence estimate that is accurate in most process situations. The confidence value is computed based on noise statistics, an appropriately chosen edge detection method and a change detection algorithm. Another significant advantage of the algorithm is that both the interface level and the confidence estimation procedures can be extended in a straight-forward manner to handle the presence of multiple sight glasses. Off-line results show that the algorithm accurately detects the interface level in normal process conditions (with high confidence values) and outputs correct confidence values in other situations with very low false-positive and false-negative error rates. On-line industrial implementation results show that the vision sensor tracks the interface level very closely and results in significant automation of plant.     

From data to diagnosis and control using generalized orthonormal basis filters. Part I: Development of state observers

This work is aimed at the development of a state observer (steady state Kalman filter) for a multivariable system with unknown time delays, which is subjected to unmeasured disturbances. To design such a filter, we explore the feasibility of capturing system dynamics using generalized orthonormal basis filters (GOBF). A two step identification procedure is proposed by exploiting the fact that the GOBF based models have output error structure. The deterministic component of the model is identified in the first step and used to compute a residual signal. In the second step, a filter that whitens the residuals is estimated using GOBF and combined with the deterministic component. A minimal order state realization of the innovation form of the state model is then generated from this high order model using realization based sub-space based state space (4SID) identification algorithm. When time delays are not known a-priori, the similarity between GOBF and Pade approximation is used to estimates time delay matrix directly from multivariate data. The efficacy of the proposed modeling technique is demonstrated by carrying out simulation studies on the benchmark Shell control problem and experimental evaluation on a stirred tank heater (STH) system. From the analysis of simulation and experimental results, it can be inferred that the proposed approach produces fairly accurate estimates of the time delay matrix and the deterministic and stochastic components of the dynamic model.