Dynamic S-Box Generation Using Novel Chaotic Map with Nonlinearity Tweaking

A substitution box (S-Box) is a crucial component of contemporary cryptosystems that provide data protection in block ciphers. At the moment, chaotic maps are being created and extensively used to generate these S-Boxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical attempts. In this paper, the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking approach. The projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their working makes both of these dynamic in nature. The tweak approach employs cubic polynomials while permuting the values of an initial S-Box to enhance its cryptographic fort. Values of the parameters are provided using the cipher key and a small variation in values of these parameters results in a completely different unique S-Box. Comparative analysis and exploration confirmed that the projected chaotic map exhibits a significant amount of chaotic complexity. The security assessment in terms of bijectivity, nonlinearity, bits independence, strict avalanche, linear approximation probability, and differential probability criteria are utilized to critically investigate the effectiveness of the proposed S-Box against several assaults. The proposed S-Box’s cryptographic performance is comparable to those of recently projected S-Boxes for its adaption in real-world security applications. The comparative scrutiny pacifies the genuine potential of the proposed S-Box in terms of its applicability for data security.     

Helicopter maintenance error analysis: Beyond the third order of the HFACS-ME

In this paper a statistical analysis of a sample of 58 helicopter maintenance-induced safety occurrences is conducted to study helicopter accidents and incidents’ survivability and the severity distribution of such occurrences. Analysis is also carried out to identify helicopter main and sub-systems mostly exposed to maintenance errors and to determine various types of such errors. Expected inherent relations between rotorcraft components affected and types of associated maintenance errors are investigated. Human factors-based triggers of these accidents and severe incidents are explored. The concept of Specific Failures (SFs) that immediately precede each of such occurrences is introduced for more detailed representation of the last breached individual and organizational safety barriers. Root causes of these safety occurrences were then sought utilizing the Human Factors Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy with a refined focus on its third order categories’ list. The rotorcraft characteristics influencing individuals and organizational behaviours within Maintenance, Repair and Overhaul organizations (MROs) are discussed in the light of the root cause investigation results.

Relevance to industry

The study of human reliability within helicopter maintenance industry is waited to emphasise the understanding of causes and propagation mechanisms of maintainers' errors and their consequences on the overall aviation safety. Previous works often investigated maintenance errors and their roles in promoting aviation accidents of fixed-wing aircraft; this research is investigating the case of rotorcraft.     

Neural network based controller for Cr–Fe batch reduction process

An automated pilot plant has been designed and commissioned to carry out online/real-time data acquisition and control for the Cr⁶⁺–Fe²⁺ reduction process. Simulated data from the Cr⁶⁺–Fe²⁺ model derived are validated with online data and laboratory analysis using ICP-AES analysis method. The distinctive trend or patterns exhibited in the ORP profiles for the non-equilibrium model derived have been utilized to train neural network-based controllers for the process. The implementation of this process control is to ensure sufficient Fe²⁺ solution is dosed into the wastewater sample in order to reduce all Cr⁶⁺–Cr³⁺. The neural network controller has been utilized to compare the capability of set-point tracking with a PID controller in this process. For this process neural network-based controller dosed in less Fe²⁺ solution compared to the PID controller which hence reduces wastage of chemicals. Industrial Cr⁶⁺ wastewater samples obtained from an electro-plating factory has also been tested on the pilot plant using the neural network-based controller to determine its effectiveness to control the reduction process for a real plant. The results indicate the proposed controller is capable of fully reducing the Cr⁶⁺–Cr³⁺ in the batch treatment process with minimal dosage of Fe²⁺.     

Selective determination of urea using urease immobilized on ZnO nanowires

Well-aligned zinc oxide (ZnO) nanowire arrays were fabricated on gold-coated plastic substrates using a low-temperature aqueous chemical growth (ACG) method. The ZnO nanowire arrays with 50–130 nm diameters and ∼1 μm in lengths were used in an enzyme-based urea sensor through immobilization of the enzyme urease that was found to be sensitive to urea concentrations from 0.1 mM to 100 mM. Two linear sensitivity regions were observed when the electrochemical responses (EMF) of the sensors were plotted vs. the logarithmic concentration range of urea from 0.1 mM to 100 mM. The proposed sensor showed a sensitivity of 52.8 mV/decade for 0.1–40 mM urea and a fast response time less than 4 s was achieved with good selectivity, reproducibility and negligible response to common interferents such as ascorbic acid and uric acid, glucose, K⁺ and Na⁺ ions.     

Power quality diagnosis using time frequency analysis and rule based techniques

Diagnosing a power quality disturbance means identifying the type and cause of the disturbance. Fast diagnosis of power quality disturbances is important so as to assist network operators in performing counter measures and implementing suitable power quality mitigation actions. In this study a novel method for performing power quality diagnosis is presented by using the S-transform and rule based classification techniques. The proposed power quality diagnosis method was evaluated for its functionality in detecting the type of short duration voltage disturbances and identifying the cause of the disturbances which may be due to permanent or non permanent faults. Based on the results, this new method has the potential to be used in the existing real time power quality monitoring system in Malaysia to expedite the diagnosis on the recorded voltage disturbances.     

Dynamic hybrid automatic repeat request (DHARQ) for WiMAX – Mobile multihop relay using adaptive power control

Wireless multihop network is currently attracting much attention as a new wireless broadband access technology due to numerous benefits. This work proposes a power control scheme for WiMAX multihop relay system. In contrast to existing power control and optimization approaches, our proposed method uses an adaptive Channel Quality Measurement for a relay station to reduce interferences to other mobile station (MS) or relay station (RS) within the same cell and hence increase the number of hops per link and consequently maximize the spatial reuse. The proposed power control is applied to a new dynamic HARQ algorithm for adaptive channel quality enhancement. Simulation results have indicated that the proposed approach achieves superior BER/PER performance enhancement in comparison to previous related works.     

Short-term and long-term memory analysis of learning using 2D and 3D educational contents

ABSTRACT

The effect of 2D and 3D educational content learning on memory has been studied using electroencephalography (EEG) brain signal. A hypothesis is set that the 3D materials are better than the 2D materials for learning and memory recall. To test the hypothesis, we proposed a classification system that will predict true or false recall for short-term memory (STM) and long-term memory (LTM) after learning by either 2D or 3D educational contents. For this purpose, EEG brain signals are recorded during learning and testing; the signals are then analysed in the time domain using different types of features in various frequency bands. The features are then fed into a support vector machine (SVM)-based classifier. The experimental results indicate that the learning and memory recall using 2D and 3D contents do not have significant differences for both the STM and the LTM.     

A survey on search results diversification techniques

The quantity of information placed on the web has been greater than before and is increasing rapidly day by day. Searching through the huge amount of data and finding the most relevant and useful result set involves searching, ranking, and presenting the results. Most of the users probe into the top few results and neglect the rest. In order to increase user’s satisfaction, the presented result set should not only be relevant to the search topic, but should also present a variety of perspectives, that is, the results should be different from one another. The effectiveness of web search and the satisfaction of users can be enhanced through providing various results of a search query in a certain order of relevance and concern. The technique used to avoid presenting similar, though relevant, results to the user is known as a diversification of search results. This article presents a survey of the approaches used for search result diversification. To this end, this article not only provides a technical survey of existing diversification techniques, but also presents a taxonomy of diversification algorithms with respect to the types of search queries.     

Crystal dislocation in SEM with image processing

Image processing algorithm is implemented to detect the grain boundary of the crystal using (SEM) Scanning Electron Microscopy. This paper presents a method for edge-detection in color image based on Sobel, Canny operator’s algorithm and discrete wavelet transform. The performance of these methods is effective and faster. Filtering is another approach to clear the noise of an image. Scanning Electron Microscopy (SEM) used to inspect semiconductor materials and devices for several decades, continues to increase in importance. Removal of noise is an important step in the image restoration process, but de-noising of the image has remained a challenging problem in recent research associated with image process. De-noising is used to remove the noise from corrupted images, while retaining the edges and other detailed features too are an essential part of de-noising.