Feedback approach to quality monitoring of a manufacturing process

This research represents a unique approach to quality monitoring of a process when data are autocorrelated. The effect of autocorrelated data is evaluated by modelling the manufacturing process as either as an autoregressive model of order one or two. Statistical process control is utilized and evaluated as a technique to detect known process disturbance. Due to the observed weaknesses of the statistical process control techniques, the Kalman filter is proposed as a technique to eliminate the autocorrelation from the process data.     

Modeling a Markovian decision process by neural network

One of the difficulties in generating an optimal policy for systems planning and control by the Markov decision process is that the state transition probabilities must be known a priori. A usual approach to estimate the state transition probabilities is by using historical data. However, if the process is not completely stationary, it may be more convenient to obtain estimates of the transition probabilities by using another approach, namely, parameter adaptation by neural networks.

A significant advantage of neural network modeling of the Markovian decision problem is that the temporal nonstationary state transition probabilities can be revised by a parameter learning paradigm. The objective of this paper is to present this approach and demonstrate its applicability by modeling a finite-stage decision problem.     

Implications of Routh stability criteria

According to the Routh criteria, a polynomial is stable if and only if all the coefficients in the first column of the stability table are of the same sign. Does this imply that elements in other columns would be of the same sign? This is investigated here in detail. The investigation reveals that if any element in any row of the table is of different sign, the system is unstable.     

A novel heuristic simulation‐optimization method for critical infrastructure in smart transportation systems

A simulation‐based optimization is a decision‐making tool that helps in identifying an optimal solution or a design for a system. An optimal solution and design are more meaningful if they enhance a smart system with sensing, computing, and monitoring capabilities with improved efficiency. In situations where testing the physical prototype is difficult, a computer‐based simulation and its optimization processes are helpful in providing low‐cost, speedy and lesser time‐ and resource‐consuming solutions. In this work, a comparative analysis of the proposed heuristic simulation‐optimization method for improving quality‐of‐service (QoS) is performed with generalized integrated optimization (a simulation approach based on genetic algorithms with evolutionary simulated annealing strategies having simplex search). In the proposed approach, feature‐based local (group) and global (network) formation processes are integrated with Internet of Things (IoT) based solutions for finding the optimum performance. Further, the simulated annealing method is applied for finding local and global optimum values supporting minimum traffic conditions. A small‐scale network of 50 to 100 nodes shows that genetic simulation optimization with multicriteria and multidimensional features performs better as compared to other simulation‐optimization approaches. Further, a minimum of 3.4% and a maximum of 16.2% improvement is observed in faster route identification for small‐scale IoT networks with simulation‐optimization constraints integrated model as compared to the traditional method. The proposed approach improves the critical infrastructure monitoring performance as compared to the generalized simulation‐optimization process in complex transportation scenarios with heavy traffic conditions. The communicational and computational‐cost complexities are least for the proposed approach.     

High Gain Solution-Processed Carbon-Free BiSI Chalcohalide Thin Film Photodetectors

Chalcohalide semiconductors are an emergent class of materials for optoelectronics. Here, the first work on BiSI chalcohalide thin film photodetectors (PDs) is presented. An entirely new method for the fabrication of bismuth chalcohalide thin films (BiOI and BiSI) is developed. This method circumvents the use of any ligands or counter ions during fabrication and provides highly pure thin films free of carbon residues and other contaminants. When integrated into lithographically patterned lateral PDs these BiSI thin films show outstanding performances and high stability. The direct ≈1.55 eV bandgap of BiSI perfectly accommodates optical sensing over the full visible spectrum. The responsivity (R) of the BiSI PDs reaches 62.1 A W⁻¹, which is the best value reported to date across chalcohalide materials of any type. The BiSI PDs display remarkable sensitivity to low light levels, supporting a broad operational detectivity ≈10¹² Jones over four decades in light intensity, with a peak specific detectivity (D*) of 2.01 × 10¹³ Jones. The dynamics of photocurrent generation are demonstrated to be dominated by photoconductive gain. These results cement BiSI as an exciting candidate for high performance photodetector applications and encourage ongoing work in BiSX (X = Cl, Br, I) materials for optoelectronics.     

Evidence of Spin Frustration in a Vanadium Diselenide Monolayer Magnet

Monolayer VSe₂, featuring both charge density wave and magnetism phenomena, represents a unique van der Waals magnet in the family of metallic 2D transition‐metal dichalcogenides (2D‐TMDs). Herein, by means of in situ microscopy and spectroscopic techniques, including scanning tunneling microscopy/spectroscopy, synchrotron X‐ray and angle‐resolved photoemission, and X‐ray absorption, direct spectroscopic signatures are established, that identify the metallic 1T‐phase and vanadium 3d¹ electronic configuration in monolayer VSe₂ grown on graphite by molecular‐beam epitaxy. Element‐specific X‐ray magnetic circular dichroism, complemented with magnetic susceptibility measurements, further reveals monolayer VSe₂ as a frustrated magnet, with its spins exhibiting subtle correlations, albeit in the absence of a long‐range magnetic order down to 2 K and up to a 7 T magnetic field. This observation is attributed to the relative stability of the ferromagnetic and antiferromagnetic ground states, arising from its atomic‐scale structural features, such as rotational disorders and edges. The results of this study extend the current understanding of metallic 2D‐TMDs in the search for exotic low‐dimensional quantum phenomena, and stimulate further theoretical and experimental studies on van der Waals monolayer magnets.     

Design and Analysis of HEMT by 5 nm Technology

Silicon - This paper presents the design and simulations of 5 nm HEMT. The analysis of analog parameters, electrical parameters and the RF performance of the 5 nm HEMT has been...     

A novel self adaptive-electric fish optimization-based multi-lane changing and merging control strategy on connected and autonomous vehicle

Wireless Networks - Merging areas on freeways are key locations due to vehicles’ fixed lateral differences. Though, such challenges are considerably unnecessary with connected and autonomous...