Classification of DoS Attacks in Smart Underwater Wireless Sensor Network

As per the most recent literature, Orthogonal Frequency Division Multiplexing (OFDM), a multi access technique, is considered most suitable for the 3G, 4G and 5G techniques in high speed wireless communication. What made OFDM most popular is its ability to deliver high bandwidth efficiency and superior data rate. Besides it, high value of peak to average power ratio (PAPR) and Inter Carrier Interference (ICI) are the challenges to tackle down via appropriate mitigation scheme. As a research contribution in the present work, an improved self-cancellation (SC) technique is designed and simulated through Simulink to mitigate the effect of ICI. This novel proposed technique (Improved SC) is designed over discrete wavelet transform (DWT) based OFDM and compared with conventional SC scheme over different channel conditions i.e. AWGN and Rayleigh fading environments. It is found that proposed DWT-OFDM with Improved SC scheme outperforms conventional SC technique significantly, under both AWGN and Rayleigh channel conditions. Further, in order to justify the novelty in the research contribution, a Split-DWT based Simulink model for Improved SC scheme is investigated to analyse the BER performance. This Split-DWT based Simulink model presented here foretells the future research potential in wavelet hybridization of OFDM to side-line ICI effects more efficiently.

     

Miscibility behavior of blend of polyesteramides of linseed oil and dehydrated castor oil with poly(methacrylic acid)

Blending of two polymers in solution is a simple and cost‐effective technique to improve upon the physical and mechanical properties of the component polymers through synergism. To obtain maximum synergy in their properties, the component polymers should be miscible with each other on molecular scale. Polymer blends of complex physicomechanical properties are being actively investigated. Poly(methacrylic acid) (PMAA), a commercial polymer, yields transparent, hard, brittle, and water‐sensitive films. It has been blended with natural polymers like dextran, collagen, and gelatin to obtain films with improved physical and mechanical characteristics. Polyesteramides, which are easily synthesized from vegetable seeds oil, a sustainable resource, have found application in surface coatings. These oligomeric products do not make free standing films in the ambient condition. The polyesteramides from vegetable seeds oil can be used to obtain blend with PMMA of improved mechanical and water absorption properties. In this study, linseed oil polyesteramide (LOPEA) and dehydrated castor oil polyesteramide (DCPEA), the source oils with different unsaturation in their fatty acid chains, were blended with PMAA through mixing in solution in the ratio DCPEA/LOPEA: PMAA as 80/20, 70/30, 60/40, 50/50, 40/60, 30/70, and 20/80. In the first instance, the miscibility of the two components was investigated in solution by viscosity and ultrasonic measurements and in solid phase through differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). Moisture absorption by the blend was also studied. DCPEA and LOPEA show immiscibility with PMAA in solution phase while LOPEA with more unsaturation in the fatty acid chain of the oil was found more immiscible than DCPEA. DCPEA shows a narrow miscibility window in the solid phase while LOPEA was found immiscible with PMAA in the solid phase too. Uptake of moisture was found to be markedly reduced in the blends of DCPEA/LOPEA with PMAA. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 1367–1374, 2007:     

A branch-and-bound algorithm to minimize total weighted completion time on identical parallel machines with job release dates

In this paper, we consider an identical parallel machine scheduling problem with release dates. The objective is to minimize the total weighted completion time. This problem is known to be strongly NP-hard. We propose some dominance properties and two lower bounds. We also present an efficient heuristic. A branch-and-bound algorithm, in which the heuristic, the lower bounds and the dominance properties are incorporated, is proposed and tested on a large set of randomly generated instances.     

An industrial portrait background removal solution based on knowledge infusion

Background removal of an identity (ID) picture consists in separating the foreground (face, body, hair and clothes) from the background of the image. It is a necessary groundwork for all modern identity documents that also has many benefits for improving ID security. State of the art image processing techniques encountered several segmentation issues and offer only partial solutions. It is due to the presence of erratic components like hairs, poor contrast, luminosity variation, shadow, color overlap between clothes and background. In this paper, a knowledge infused approach is proposed that hybridizes smart image processing tasks and prior knowledge. The research is based on a divide and conquer strategy aiming at simulating the sequential attention of human when performing a manual segmentation. Knowledge is infused by considering the spatial relation between anatomic elements of the ID image (face feature, forehead, body and hair) as well as their “signal properties”. The process consists in first determining a convex hull around the person’s body including all the foreground while keeping very close to the contour between the background and the foreground. Then, a body map generated from biometric analysis associated to an automatic grab cut process is applied to reach a finer segmentation. Finally, a heuristic-based post-processing step consisting in correcting potential hair and fine boundary issues leads to the final segmentation. Experimental results show that the newly proposed architecture achieves better performances than tested current state-of-the-art methodologies including active contours, generalist popular deep learning techniques, and also two other ones considered as the smartest for portrait segmentation. This new technology has been adopted by an international company as its industrial ID foreground solution.

     

Abiotic stress of ZnO‐PEG,ZnO‐PVP,CuO‐PEG and CuO‐PVP nanoparticles enhance growth,sweetener compounds and antioxidant activities in shoots of Stevia rebaudiana Bertoni

Nanoparticles are known to play remarkable role as abiotic stress elicitors in plants. This study reports the comparative analysis of effects produced by capped [zinc oxide (ZnO)‐polyethylene glycol (PEG), ZnO‐polyvinyl pyrrolidone (PVP), copper oxide (CuO)‐PEG, CuO‐PVP] and uncapped (ZnO and CuO) nanoparticles on the medicinal plant, Stevia rebaudiana raised in vitro for the production of commercially important sweetener compounds. In context of shoot organogenesis, ZnO‐PEG, ZnO‐PVP, CuO‐PEG, CuO‐PVP were employed to the growth medium that resulted in increased growth parameters, and larger content of steviol glycosides as compared to the shoots raised in medium containing ZnO and CuO, revealed by high‐performance liquid chromatography. In the meanwhile, non‐enzymatic antioxidant activities including total phenolic content, total flavonoid content, total antioxidant capacity, total reducing power and 2,2‐diphenyl‐1‐picryl hydrazyl‐free radical scavenging activity were calculated and showed comparatively greater amounts in shoots grown in medium containing capped ZnO or CuO nanoparticles. Furthermore, the ZnO and its derivatives revealed to be more reactive at 1 mg/l of concentration. Whereas, the CuO and its derivatives produced greater response on Stevia at 10 mg/l concentration of nanoparticles. This study paves the way for more such studies encompassing capped and uncapped nanoparticles and their ultimate effect on in‐vitro grown plant tissues for the production of active metabolites on industrial scale.Inspec keywords: nanoparticles, chromatography, resins, polymers, zinc compounds, copper compounds, food technology, agricultureOther keywords: nanoparticles, sweetener compounds, antioxidant activities, Stevia rebaudiana Bertoni, abiotic stress elicitors, zinc oxide‐polyethylene glycol, zinc oxide‐polyvinyl pyrrolidone, copper oxide‐polyethylene glycol, medicinal plant, shoot organogenesis, steviol glycosides, high‐performance liquid chromatography, nonenzymatic antioxidant activities, total phenolic content, total flavonoid content, total antioxidant capacity, total reducing power, 2,2‐diphenyl‐1‐picryl hydrazylfree radical scavenging activity, derivatives, active metabolite production, copper oxide‐polyvinyl pyrrolidone     

On the performance of different capability indices under normal and non-normal distributions

In this article, we have examined the performance of some useful capability indices using normal and non-normal distributions. The confidence intervals are calculated and mean coverage rates are observed for different capability indices. The effects of symmetry and kurtosis of parent distributions are examined on the mean coverage rates of different capability indices. Moreover, we have investigated the robustness (of confidence interval) using the median and percentile-based indices. We have considered the well-known distributions including normal, gamma, t, Weibull, and chi-squared. For these process scenarios, we have observed that some indices resist disturbance only in symmetry of the parent distribution, some resist the disturbance in symmetry and kurtosis of the distribution, and some indices don’t resist against either type of disturbance.     

On the Efficiency of Runs Rules Schemes for Process Monitoring

There are two main types of variations, namely, common and special causes leading to in‐control and out‐of‐control states, respectively. Control charts are popular tools used to differentiate between these two states of a process. Implementation of runs rules schemes with control charts is an attractive approach for process monitoring. This study is designed to describe the methodology of runs rules schemes and discuss their implementation for different types of control charts. We have considered memory‐less charts, namely, , S, and R charts for our study purposes. It is examined that the efficiency gain depends on the number of decision points utilized to implement a given rule. Moreover, superiority of runs rules schemes may vary for different types of location and dispersion charts. An application example using a dataset is also included in the study for practical considerations. Copyright © 2015 John Wiley & Sons, Ltd.     

A New Combined Shewhart–Cumulative Sum S Chart for Monitoring Process Standard Deviation

The combined application of a Shewhart chart and cumulative sum (CUSUM) control chart is an effective tool for the detection of all sizes of process shifts as the scheme combines the advantages of a CUSUM at detecting small to moderate shifts and Shewhart for the quick detection of very large shifts. This article proposes new combined Shewhart–CUSUM S charts based on the extreme variations of ranked set sampling technique, for efficient monitoring of changes in the process dispersion. Using Monte Carlo simulations, the combined scheme is designed to minimize the average extra quadratic loss over the entire process shift domain. The results show that the combined Shewhart–CUSUM S charts uniformly outperform several other procedures for detecting increases and decreases in the process variability. Moreover, the proposed scheme can detect changes that are small enough to escape the Shewhart S chart or fairly large to escape detection by the CUSUM S chart. Numerical example is given to illustrate the practical application of the proposed scheme using real industrial data. Copyright © 2015 John Wiley & Sons, Ltd.     

Intensity-based statistical features for classification of lungs CT scan nodules using artificial intelligence techniques

A computer-aided diagnostic (CAD) system for effective and accurate pulmonary nodule detection is required to detect the nodules at early stage. This paper proposed a novel technique to detect and classify pulmonary nodules based on statistical features for intensity values using support vector machine (SVM). The significance of the proposed technique is, it uses the nodules features in 2D & 3D and also SVM for the classification that is good to classify the nodules extracted from the image. The lung volume is extracted from Lung CT using thresholding, background removal, hole-filling and contour correction of lung lobe. The candidate nodules are extracted and pruned using the rules based on ground truth of nodules. The statistical features for intensity values are extracted from candidate nodules. The nodule data are up-samples to reduce the biasness. The classifier SVM is trained using data samples. The efficiency of proposed CAD system is tested and evaluated using Lung Image Consortium Database (LIDC) that is standard data-set used in CAD Systems for Lungs Nodule classification. The results obtained from proposed CAD system are good as compare to previous CAD systems. The sensitivity of 96.31% is achieved in the proposed CAD system.