CS‐EWMA Chart for Monitoring Process Dispersion

Control charts are the most extensively used technique to detect the presence of special cause variations in processes. They can be classified into memory and memoryless control charts. Cumulative sum and exponentially weighted moving average control charts are memory‐type control charts as their control structures are developed in such a way that the past information is not ignored as it is done in the case of memoryless control charts, like the Shewhart‐type control charts. The present study is based on the proposal of a new memory‐type control chart for process dispersion. This chart is named as CS‐EWMA chart as its plotting statistic is based on a cumulative sum of the exponentially weighted moving averages. Comparisons with other memory charts used to monitor the process dispersion are done by means of the average run length. An illustration of the proposed technique is done by applying the CS‐EWMA chart on a simulated dataset. Copyright © 2012 John Wiley & Sons, Ltd.     

Controlled-release naproxen using micronized ethyl cellulose by wet-granulation and solid-dispersion method

This study has been undertaken to develop a controlled-release tablet dosage form of naproxen using ethocel (ethyl cellulose) as the rate-controlling polymer. The formulations were made by employing the conventional wet-granulation method and the solid-dispersion method. Tablets made by both methods were compared for their controlled-release dissolution profiles. Both methods were useful in developing the controlled-release formulations of naproxen with desirable properties. However, the amount of polymer required to make a formulation with the desired release profile was 33% less via solid dispersion than via wet granulation. A cumulative 88% of naproxen was released from the solid-dispersion formulation, compared with 84% from the wet-granulation formulation.     

Effects of Modified Atmosphere Packaging with Various Carbon Dioxide Composition on Biogenic Amines Formation in Indian Mackerel (Rastrelliger kanagurta) stored at 5 ± 1°C

The profile of major biogenic amines was investigated in Indian mackerel packed in modified atmosphere for up to 12 days at 5 ± 1°C. Beheaded and gutted Indian mackerel was packed under different carbon dioxide compositions to study the effects on biogenic amines formation. The treatments were control air (C), vacuum packaging (VP), 30% CO₂/65% N₂/5% O₂ (M30C), 60% CO₂/35% N₂/5% O₂ (M60C), 80% CO₂/15% N₂/5% O₂ (M80C) and 100% CO₂ (M100C). Each amine responded differently to different CO₂ levels. After 12 days of storage, concentrations of histamine were reduced by 6.4%, 8.5%, 70.3%, 78.8% and 90.2% in fish packed under VP, M30C, M60C, M80C and M100C, respectively as compared with control air. Changes in putrescine and cadaverine showed a similar pattern. Gas mix of M30C and VP stimulated the formation of tyramine reaching 203 and 172 ppm, respectively. Higher composition of CO₂ had a significant inhibitory effect on tyramine concentration (p < 0.05). There were parallel increases of putrescine and spermidine in C, VP and M30C. No significant effect of CO₂ was observed on spermine (p > 0.05). After 9 days of storage, more than 300 ppm of histamine was detected in mackerel packed in VP and M30C; therefore, these atmospheres pose a histamine intoxication risk. Copyright © 2013 John Wiley & Sons, Ltd.     

Enhancement of electrical properties by including nano-aluminum nitride to micro-silicon carbide/silicone elastomer composites for potential power module packaging applications

This paper reports an enhancement of the electrical properties of micro-silicon carbide/silicone elastomer (m-SiC/SE) composites by adding nano-aluminum nitride (n-AlN) for the next-generation power module encapsulation applications. The electrical properties, such as nonlinear conductivity, DC breakdown strength, dielectric spectroscopy, and thermally stimulated discharge current, of the pure SE, m-SiC/SE microcomposite, and m-SiC/n-AlN/SE hybrid composites added with 1 wt%, 3 wt%, and 5 wt% n-AlN fillers are investigated. The m-SiC/n-AlN/SE hybrid composites exhibit better nonlinear conductivity characteristics and enhanced DC breakdown strength than the m-SiC/SE microcomposite. Amongst all materials, the 3 wt% n-AlN addition in the hybrid composite has the best enhancement effect on the nonlinear conductivity characteristics and DC breakdown strength. However, it has the lowest low-frequency real and imaginary permittivities among the SE micro and hybrid composites. Furthermore, a m-SiC/n-AlN heterogenous interface model is proposed to explain the mechanism of enhanced electrical properties of the m-SiC/n-AlN/SE composites. It is found that higher m-SiC/n-AlN heterogenous interface barriers are constructed after adding n-AlN fillers, thereby inhibiting the charge carrier transport at low electric fields. In contrast, more conductive paths are activated at high electric fields by the contacted m-SiC fillers via n-AlN fillers, promoting the charge carrier transport at high electric fields.

     

Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

In recent years, the number of Gun-related incidents has crossed over 250,000 per year and over 85% of the existing 1 billion firearms are in civilian hands, manual monitoring has not proven effective in detecting firearms. which is why an automated weapon detection system is needed. Various automated convolutional neural networks (CNN) weapon detection systems have been proposed in the past to generate good results. However, These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection system. These models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance videos. This research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key parameter. The proposed framework is based on You Only Look Once (YOLO) and Area of Interest (AOI). Initially, the models take pre-processed frames where the background is removed by the use of the Gaussian blur algorithm. The proposed architecture will be assessed through various performance parameters such as False Negative, False Positive, precision, recall rate, and F1 score. The results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are achieved. Speed reached 0.010 s per frame compared to the 0.17 s of the Faster R-CNN. It is promising to be used in the field of security and weapon detection.     

Profiling Casualty Severity Levels of Road Accident Using Weighted Majority Voting

To determine the individual circumstances that account for a road traffic accident, it is crucial to consider the unplanned connections amongst various factors related to a crash that results in high casualty levels. Analysis of the road accident data concentrated mainly on categorizing accidents into different types using individually built classification methods which limit the prediction accuracy and fitness of the model. In this article, we proposed a multi-model hybrid framework of the weighted majority voting (WMV) scheme with parallel structure, which is designed by integrating individually implemented multinomial logistic regression (MLR) and multilayer perceptron (MLP) classifiers using three different accident datasets i.e., IRTAD, NCDB, and FARS. The proposed WMV hybrid scheme overtook individual classifiers in terms of modern evaluation measures like ROC, RMSE, Kappa rate, classification accuracy, and performs better than state-of-the-art approaches for the prediction of casualty severity level. Moreover, the proposed WMV hybrid scheme adds up to accident severity analysis through knowledge representation by revealing the role of different accident-related factors which expand the risk of casualty in a road crash. Critical aspects related to casualty severity recognized by the proposed WMV hybrid approach can surely support the traffic enforcement agencies to develop better road safety plans and ultimately save lives.     

A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos

The use of multimedia data sharing has drastically increased in the past few decades due to the revolutionary improvements in communication technologies such as the 4th generation (4G) and 5th generation (5G) etc. Researchers have proposed many image encryption algorithms based on the classical random walk and chaos theory for sharing an image in a secure way. Instead of the classical random walk, this paper proposes the quantum walk to achieve high image security. Classical random walk exhibits randomness due to the stochastic transitions between states, on the other hand, the quantum walk is more random and achieve randomness due to the superposition, and the interference of the wave functions. The proposed image encryption scheme is evaluated using extensive security metrics such as correlation coefficient, entropy, histogram, time complexity, number of pixels change rate and unified average intensity etc. All experimental results validate the proposed scheme, and it is concluded that the proposed scheme is highly secured, lightweight and computationally efficient. In the proposed scheme, the values of the correlation coefficient, entropy, mean square error (MSE), number of pixels change rate (NPCR), unified average change intensity (UACI) and contrast are 0.0069, 7.9970, 40.39, 99.60%, 33.47 and 10.4542 respectively.     

Investigation of charge transport mechanism in semiconducting La<Subscript>0.5</Subscript>Ca<Subscript>0.5</Subscript>Mn<Subscript>0.5</Subscript>Fe<Subscript>0.5</Subscript>O<Subscript>3</Subscript> manganite prepared by sol–gel method

Here in, we report the charge transport mechanism in semiconducting La_0.5Ca_0.5Mn_0.5Fe_0.5O₃ (LCMFO) polycrystalline material synthesized via sol–gel auto combustion route. X-ray diffraction (XRD) analysis confirmed the orthorhombic phase of the prepared material. Temperature dependent resistivity and impedance spectroscopy measurements have been carried out to probe the dielectric and electrical conduction mechanism which revealed a change of Mott variable range to the small polaronic hopping conduction mechanism around 303 K. The complex impedance and modulus spectra undoubtedly showed the contribution of both grain and grain boundary effect on the conduction properties of LCMFO. An equivalent circuit [(R_gbQ_gb) (R_gQ_g)] model has been used to address the electrical parameters associated with the different phases (grains and grain boundaries) having different relaxation times. The values of resistances of two phases obtained after fitting the equivalent circuit in the nyquist plot have been analyzed which confirmed the change of conduction mechanism around 303 K. The resultant change in conduction mechanism is also supported by the conductivity plots.     

Vertically grown multiwalled carbon nanotube anode and nickel silicide integrated high performance microsized (1.25 μL) microbial fuel cell

Microbial fuel cells (MFCs) are an environmentally friendly method for water purification and self-sustained electricity generation using microorganisms. Microsized MFCs can also be a useful power source for lab-on-a-chip and similar integrated devices. We fabricated a 1.25 μL microsized MFC containing an anode of vertically aligned, forest type multiwalled carbon nanotubes (MWCNTs) with a nickel silicide (NiSi) contact area that produced 197 mA/m(2) of current density and 392 mW/m(3) of power density. The MWCNTs increased the anode surface-to-volume ratio, which improved the ability of the microorganisms to couple and transfer electrons to the anode. The use of nickel silicide also helped to boost the output current by providing a low resistance contact area to more efficiently shuttle electrons from the anode out of the device.