Chaos based Zero-steganography algorithm

Multimedia Tools and Applications - Conventional steganography focuses on invisibility and undetectability, as the main concern is to make the algorithms immune to steganalysis. Zero-steg-anography...     

Influence of metal‐oxide‐supported bentonites on the pyrolysis behavior of polypropylene and high‐density polyethylene

In this article, we report on the pyrolysis of polypropylene (PP) and high‐density polyethylene (HDPE) in the absence and presence of plain and metal‐oxide‐impregnated bentonite clays [BCs; acid‐washed bentonite clay (AWBC), Zn/AWBC, Ni/AWBC, Co/AWBC, Fe/AWBC, and Mn/AWBC] into useful products. Thermal and catalytic runs were performed at 300°C in the case of PP and at 350°C in the case of HDPE for a contact time of 30 min. The effects of different catalysts and their concentrations on the overall yields and the yields of liquid, gas, and residue were studied. The efficacy of each catalyst is reported on the basis of the highest liquid yields (in weight percentage). The derived liquid products were analyzed by Fourier transform infrared spectroscopy and gas chromatography–mass spectroscopy; this confirmed the presence of paraffins, olefins, and naphthenes. The results indicate the catalytic role of impregnated BCs compared to plain BC with the optimum efficiency shown by Co/AWBC in the case of PP and Zn/AWBC in the case of HDPE toward the formation of liquid products in a desirable C range with the enrichment of olefins and naphthenes in the case of PP and paraffins and olefins in the case of HDPE compared to the thermal run. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41221.     

Predicting the colour properties of viscose knitted fabrics using soft computing approaches

The aim of this paper was to predict the colour strength of viscose knitted fabrics by using fuzzy logic (FL) model based on dye concentration, salt concentration and alkali concentration as input variables. Moreover, the performance of fuzzy logic (FL) model is compared with that of artificial neural network (ANN) model. In addition, same parameters and data have been used in ANN model. From the experimental study, it was found that dye concentration has the main and greatest effects on the colour strength of viscose knitted fabrics. The coefficient of determination (R²), root mean square (RMS) and mean absolute errors (MAE) between the experimental colour strength and that predicted by FL model are found to be 0.977, 1.025 and 4.61%, respectively. Further, the coefficient of determination (R²), root mean square (RMS) and mean absolute errors (MAE) between the experimental colour strength and that predicted by ANN model are found to be 0.992, 0.726 and 3.28%, respectively. It was found that both ANN and FL models have ability and accuracy to predict the fabric colour strength effectively in non-linear domain. However, ANN prediction model shows higher prediction accuracy than that of Fuzzy model.     

Synthesis of finite state machines for improved state verification

Finite State Machines (FSMs) are used in diverse areas to model hardware and software systems. Verification of FSMs is essential to ensure reliability of systems. To verify that a machine is in an expected state in testing, Unique Input/Output (UIO) sequences are used. The aforementioned testing methodology requires that each state in the FSM has an UIO. However, it is possible for a given machine that few or even none of its states have an UIO sequence. This paper presents a guided heuristic algorithm for synthesizing FSMs such that each state has an UIO sequence. The states of an FSM with identical I/O labels on transitions are grouped in order to identify the states which do not possess UIO sequence. The transitions are then augmented by adding extra output terminals incrementally so that new UIO sequences are created for the states. A greedy approach is used to optimize the number of added outputs. Initially, the transitions which lead to state convergence (i.e., transitions with identical input/output labels taking a set of states to the same next state) and constrained self-loop (i.e., transitions taking a set of states either to itself or leads to state convergence) are identified since a state with only these transitions will never have a UIO sequence. Extra output terminals are added to the FSM which are used only while testing and the augmented output labels make sure that the states are neither convergent nor has constrained self-loop, thereby ensuring UIO sequence. The proposed algorithm, referred to as AUGP, was tested with a large number of FSMs including the Microelectronics Center of North Carolina (MCNC) FSM benchmarks. The augmented state transition table was used as input to a UIO computation algorithm (developed by the same authors [Ahmad I, et al. IEE Proc Comput Digital Tech 2004;151(2):131]) to check the performance of the augmentation algorithm and the tested FSMs were found to possess UIO sequence for all states.     

Bioreactor temperature profile controller using inverse neural network (INN) for production of ethanol

This paper presents the use of inverse neural networks (INN) for temperature control of a biochemical reactor and its effect on ethanol production. The process model is derived indicating the relationship between temperature, pH and dissolved oxygen. Using fundamental model obtained data sets; an inverse neural network has been trained using the back-propagation learning algorithm. Two types of temperature profile are used to compare the performance of the INN and conventional PID controllers. These controllers have been simulated in MATLAB for a quantitative comparison. The results obtained by the neural network based INN controller and by the PID controller are presented and compared. There is an improvement in the performance of INN controller in settling time and dead time and steady state error over the PID controller.     

Clearance and friction-induced dynamics of chain CVT drives

A continuously variable transmission (CVT) is an emerging automotive transmission technology that offers a continuum of gear ratios between desired limits. A chain CVT is a friction-limited drive as its performance and torque capacity rely significantly on the friction characteristic of the contact patch between the chain and the pulley. Moreover, such a CVT is susceptible to clearance formation due to assembly defects or extensive continual operation of the system, which further degrades its performance and leads to early wear and failure of the system. The present research focuses on developing models to understand the influence of clearance and different friction characteristics on the dynamic performance of a chain CVT drive. A detailed planar multibody model of a chain CVT is developed in order to accurately capture the dynamics characterized by the discrete structure of the chain, which causes polygonal excitations in the system. A suitable model for clearance between the chain links is embedded into this multibody model of the chain CVT. Friction between the chain link and the pulley sheaves is modeled using different mathematical models which account for different loading scenarios. The mathematical models, the computational scheme, and the results corresponding to different loading scenarios are discussed. The results discuss the influence of friction characteristics and clearance parameters on the dynamic performance, the axial force requirements, and the torque transmitting capacity of a chain CVT drive.     

Investigation of Tool Wear and Surface Finish by Analyzing Vibration Signals in Turning Assab-705 Steel

Various occurrences in machining influence the machining dynamics and thus produce vibration in the cutting tool-workpiece arrangement. In this investigation, with tri-axial accelerometer mounted on the tool-holder in turning ASSAB-705 steel, vibration signals have been captured with and without cutting. The nature of vibrations arising in the cutting tool at different cutting conditions has been investigated. It has been observed that the RMS amplitude of vibration along all three axes for the increasing cutting speed was mixed in nature; however, an increasing trend was noticed in the vibrations along the feed, V_x and radial, V_y directions. The vibration along the main cutting direction, V_z was mixed, initiated by large vibration and then decreased until a particular cutting speed was reached and finally increased steadily. The feed vibration component, V_x has a similar response to the change of the workpiece surface roughness, while the other two components, V_y and V_z have the more coherent response to the rate of flank wear progression throughout the tool life. The natural frequency of different machine parts vibration has been found to be within the band of 0 Hz – 4.2 kHz, whereas the frequencies of different occurrences in turning varied between 98 Hz and 42 kHz.