Miller Equivalents and Their Applications

Miller’s theorems are utilized for approximate as well as exact analysis of both passive and active networks in conjunction with other theorems on a single element or different elements in succession. In this paper, all the four possible Miller equivalents are fully exploited for the exact analysis by applying on different elements simultaneously. This has never been attempted before and may be viewed as an alternate approach for analyzing the networks. The four Miller equivalents are derived using the substitution theorem followed by typical illustrative examples.     

Integrating systems analysis and control for implementing process analytical technology in bioprocess development

This paper provides a perspective on the increasingly critical role that systems analysis and process control play in bioprocess development today. This is of particular importance to the manufacturers of biotech therapeutics since the product quality is critical and depends on the process and its control. Because a large number of process variables and raw materials can influence the overall outcome of a bioprocess, the correct determination of the process trajectory is often an intensive exercise. A follow‐up involving design of a suitable process control strategy for implementation of process conditions would be logical. However, such an exercise can no longer consider each unit operation one at a time but rather requires holistic inclusion of all upstream and downstream unit operations for successfully meeting the global standards laid down by various regulatory agencies by exploring the potential of process analytical technology (PAT) to achieve bigger objectives. In this perspective, the focus is on the core issues associated with process integration and how these may influence future process development. © 2014 Society of Chemical Industry     

LiBH4 as solid electrolyte for Li-ion batteries with Bi2Te3 nanostructured anode

The present study highlights the first-ever application of fastest lithium (Li) ion conducting complex hydride containing cluster anions, namely lithium borohydride (LiBH₄) into an all-solid-state Li-ion battery having Bi₂Te₃ as anode material. Bi₂Te₃ nanostructures were prepared by the simple wet chemical method and characterized by their crystal structure, morphology and electronic structure using X-ray diffraction (XRD), scanning electron microscopy (SEM), Transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). SEM and TEM experiments revealed the dimensions as 20–60 nm for nanoparticles and 30–90 nm for nanosheets. The formation of Bi₂Te₃ nanostructures along with Bi₂O₃ as the residual phase is confirmed by XRD analysis. The crystallite size of nanoparticles and nanosheets are calculated as 19 nm and 39 nm respectively from XRD profile. The XPS study also confirms the formation of nanostructured Bi₂Te₃ along with Bi₂O₃. Finally, the electrochemical performance of these nanostructures is observed using the galvanostatic charge-discharge curve at 0.1C and 0.5C.     

A New Type of Analog Multiplier

A new type of four-quadrant analog multiplier is proposed. Compared to the triangle-averaging and time-division type of multipliers it does not require a triangular-wave generator and thus it is quite simple. Unlike time-division multipliers based on the charge-equalization principle, it immediately acquires the steady state when one particular signal changes from one value to the other. Experimental results closely agree with the theoretical predictions. Improvements towards better accuracy and faster response are suggested.     

Concept convergence process: A framework for improving product concepts

Concept selection is one of the most important decisions in product development, since success of the final product depends on the selected concept. The exploration and evaluation of alternatives early in the product development (PD) process reduces the amount and magnitude of changes in later stages and increases the likelihood of success of new product development (NPD) projects. Though, currently available methods attempt to select the best concept from the available set of initial concepts, they do not help create an improved concept based on the learning and knowledge generated through the evaluation of initial concepts. The paper proposes a framework for selecting and/or evolving improved concepts through a rigorous concept evaluation and convergence process. The concept convergence process allows bringing together the best (desirable) traits from the initial set of concepts and creates a new set of hybrid concepts. The framework uses a fuzzy inference process for evaluating each initial concept against identified decision criteria, thus generating hybrid concepts to select the best feasible concept under given cost and technological constraints. The approach is demonstrated using a steering wheel concept generation example.     

Distributed denial of service attacks and its defenses in IoT: a survey

The Journal of Supercomputing - A distributed denial of service (DDoS) attack is an attempt to partially or completely shut down the targeted server with a flood of internet traffic. The primary...     

An attention-based deep learning model for credibility assessment of online health information

With the surge of searching and reading online health-based articles, maintaining the quality and credibility of online health-based articles has become crucial. The circulation of deceptive health information on numerous social media sites can mislead people and can potentially cause adverse effects on people's health. To address these problems, this work uses deep learning approaches to automate the assessment and scoring of online health-related articles' credibility. The paper proposed an Attention-based Recurrent Multichannel Convolutional Neural Network (ARMCNN) model. The proposed model incorporates a BiLSTM layer, a multichannel CNN layer, and an attention layer and predicts the credibility of online health information. To perform a reliable evaluation of the presented model, we utilize the health articles reviewed by the experts, compiled in a labeled dataset termed “Pubhealth,” which consists of thousands of health articles. The results are evaluated using five performance measures, accuracy, precision, recall, f1-score, and area under the ROC curve (AUC). Furthermore, we extensively compared the proposed model with different deep learning and machine learning models such as Long short-term memory (LSTM), Bidirectional LSTM, CNN (Convolutional neural network), and RNN-CNN. The experimental results showed that the proposed model produced state-of-the-art performance on the used dataset by achieving an accuracy of 0.88, precision of 0.92, recall of 0.87, f1-score of 0.90, and AUC of 0.94. Further, the proposed model yielded better performance than other benchmarked techniques for the credibility assessment of online health articles.     

A Hybrid Approach for Extracting EMG signals by Filtering EEG Data for IoT Applications for Immobile Persons

Wireless Personal Communications - Brain Computer interface (BCI) is an emerging technology which empowers human to regulate the computer or other electronic gadgets with brain signals. This paper...     

Water‐induced degradations in MWCNT embedded glass fiber/epoxy composites: An emphasis on aging temperature

This article is focused to elucidate the critical influence of diffusion temperature on the water uptake and subsequent degradation behavior of multi‐walled carbon nanotube embedded glass fiber/epoxy (MWCNT‐GE) composite. Presence of MWCNT in the glass fiber/epoxy (GE) composite significantly suppressed its water absorption propensity at lower aging temperature (25 °C). However, MWCNT reinforcement in GE composite adversely affected its high temperature water resistance due to generation of unfavorable thermal and hygroscopic stresses at the MWCNT/polymer interfaces. Effect of MWCNT and water diffusion temperature on the glass transition temperature and chemical bonding characteristics of GE composite have been verified by differential scanning calorimetry and Fourier transformed infrared spectroscopy. Flexural testing of the water saturated samples revealed that diffused water exerts more detrimental effect on mechanical performance of MWCNT‐GE composite than that of control GE composite. The extent of recovery in mechanical performance of the composites has also been evaluated after complete desorption of the water saturated samples. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45987.