MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

Engineering and Technology

Transportation services for safe travel are critical to a country's growth. The dangerous pavement surface is caused by a variety of asphalt pavement distresses. Potholes are the primary cause of pavement distress. Many methods for detecting and correcting potholes in asphalt pavement have been presented in this paper. Potholes are essential indicators of structural difficulties in the asphalt road, and recognition of the potholes is a significant issue for smooth and safe driving. On the other hand, manually discovering and evaluating strategies is expensive and time-consuming. Consequently, several efforts have been made to develop technology for the detection and recognition of potholes automatically, which may reduce vehicle damage, driver stress with a smaller number of accidents. In this review paper, we explored and reviewed the existing pothole detection systems based on sensor, vision, machine learning, and deep learning algorithms. The systems based on equipment and methods are presented in this paper. © Grenze Scientific Society, 2022.

World University root node

School of Electronics & Communication Engineering

13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022

Survey on Pothole Detection Methods

Biomass gasification is a thermochemical conversion process in which diversified solid organic wastes produce majorly gaseous products (syngas) and tarry residue. The availability of sufficient quantities of biomass and effective utilization of municipal solid wastes make biogasification a very important technique. Major focus of gasification technology is to maximize syngas production as it can directly be used for power generation or be utilized as potential feedstock for other chemicals and biofuel production. In this chapter insights into process chemistry of gasification and its key operating conditions are majorly discussed along with various types of available bio-gasifiers. Present-day challenges for the gasification technology are highlighted along with a thoughtful insight to its sustainable growth potential. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

School of Chemical Engineering

Handbook of Waste Biorefinery: Circular Economy of Renewable Energy

Chemistry to Technology of Gasification Process: A Close Look into Reactions and Kinetic Models

The thermal performance of any structure depends on the thermal characteristics of the structural material. Thus, it is crucial to study the behavior of that material for thermal resistance and thermal insulation. The performance of that material is governed by its thermal conductivity, which describes the ability of the material to allow the flow of heat across it in the presence of differential temperature. Thermal variations are highly hazardous from the point of view of durability of the structure and needs more attention to improve the structural properties. It has been proved that thermocol (Polystyrene foam) has good insulating properties and also has a low thermal conductivity and therefore a good thermal insulating material. In this study, experimental tests are conducted on concrete slab with and without using thermocol for flexure and as an insulating material in R.C. slab for studying the behavior of slab for thermal insulation. Concluding from the results of thermal conductivity it is proved that the thermocol is a good insulating material and the slab is good in thermal insulation compared to RCC slab. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

School of Civil Engineering

Structural Integrity

Structural Assessment of Composite Concrete Members for Waterproofing and Thermal Insulation

Video transmitting over wired or wireless channels such as internet is the area of research because of its fast growth. There are more chances of loss of packets in wireless medium. In existing video recovering methods, either there is a delay as packets are sending it again or redundancy of data, Video Error Concealment (VEC) is the method used for minimizing the errors in the video due to any transmission errors or addition of noise. There are different domains that are used for error concealment such as temporal, spatial, and spatio-temporal. To achieve error concealment techniques, there are different algorithms such as Boundary Matching Algorithm, Frequency Selective Extrapolation, and Patch Matching. The proposed method is a novel method in the spatio-temporal domain. It can significantly improve the subjective and objective video quality. Hence, spatio-temporal algorithm is adopted over other domains. There are many algorithms for VEC. The optimized algorithms should be used for obtaining better quality of videos. Particle Swarm Optimization (PSO) is one of the best optimized bio-inspired algorithms. This PSO technique can be used to conceal the errors in different formats of videos. Correlation is used for detection of errors in the videos, and each error frame is concealed using PSO algorithm in MATLAB. This was tested for different standard videos and different types and variety of errors for single, multiple, and sequential errors. In comparison to error videos, parameters including PSNR, SSIM, and Entropy improved for concealed videos, while MSE decreased. The results clearly indicate improvement in quality of videos. The errors in the video should be recovered as it is used in many applications such as in internet video streaming, mobile phone, TV, and video conference and in medical areas such as MRI and satellite transmissions. © 2022 Scrivener Publishing LLC.

Object Detection by Stereo Vision Images

Video error concealment using Particle Swarm Optimization

Robust estimation of noise strength in Magnetic Resonance Images (MRIs) is a task of great importance due to its extensive applications in image post-processing techniques. Many noise estimation algorithms have been proposed in the past to retrieve noise characteristics of the magnitude image. These algorithms rely on either the spatial or transform domain information of the image. In this research article, we propose a noise estimation algorithm that utilizes a hybrid Discrete Wavelet Transform (DWT) and edge information suppression based algorithm to estimate the strength of noise in magnitude MR images. The wavelet coefficients corresponding to spatial domain edges are eliminated using a down-sampled complement of the Sobel edge map. The distribution of average noise energy in spatial and transform domain which follows Parseval's theorem is utilized for calculating the initial noise estimate. Further, the robustness of the proposed algorithm is enhanced using Feedforward Neural Network. The proposed algorithm is observed to be computationally fast and accurate. Results on synthetic and clinical T1- and T2-w brain MRIs following Gaussian or Rician distribution show better performance than the existing benchmark algorithms over a wide range of input noise. © 2021 Elsevier Ltd

Biomedical Signal Processing and Control

Noise estimation in 2D MRI using DWT coefficients and optimized neural network

Magnetic resonance images are often influenced by noise. Reliable estimation of noise characteristics is important for image post-processing. The benchmark algorithms often assume a uniform noise model across the image; that is, the noise features are spatially invariant. A few noise estimators are found to cope with nonhomogeneous noise; however, they either require multiple acquisitions or other additional information. In this research work, we develop a method that can accurately estimate the nonhomogeneous parameters of noise from just a single magnitude image. The proposed algorithm is a two-step approach. In the first step, we evaluate the standard deviation of noise assuming that it follows Gaussian distribution. This step utilizes a hybrid of spatial domain edge information suppression and transforms domain coefficient statistics to estimate a single value of standard deviation of noise in magnitude MR images. In the second step, the evaluated noise is corrected using the analytical expression that establishes the relationship between Gaussian noise and Rician noise. Results on synthetic and clinical data evidence the better performance of the proposed algorithm when compared to the benchmark methods. © 2021 Wiley Periodicals LLC.

International Journal of Imaging Systems and Technology

Estimation of Nonhomogeneous Noise in 2D Magnetic Resonance Imaging

The number of cores in the multiprocessor system on the chip is growing exponentially because of the computational requirements of the applications. Efficient communication between processors on a chip intensely impacts the performance of the on-chip multiprocessor system in terms of power, speed, and space requirements. To tackle such complex integrated interconnect technology systems, three-dimensional (3D) Optical Network-on-Chip (ONoC) is a promising solution. As the optical router is a core of 3D ONoC, it needs the optimized router design in terms of the number of components used, insertion loss, power consumption, and other parameters. This paper proposes a novel design of a 6 × 6 intra-layer non-blocking optical router and an inter-layer (vertical) optical router using a micro-ring resonator (MRR). The performance analysis is carried out using the Phoenix simulator. The proposed 6 × 6 optical router has the lowest number of waveguide crossings and waveguide bendings than existing non-blocking optical routers of 3D ONoC. Furthermore proposed inter-layer optical router has reduced the number of waveguide crossings. The ONoC with X-Mesh topology using our design outperforms in terms of insertion loss and signal to noise ratio over benchmarks. © 2022 Elsevier GmbH

Optik

Efficient non-blocking optical router for 3D optical network-on-chip

The Internet of Things (IoT) allows the connections of a large number of sensors, actuators, and smart devices for persisting connectivity. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

SpringerBriefs in Applied Sciences and Technology

Localization Approaches for Internet of Things

With the rapid growth in the deployments of Internet of things (IoT)-based smart devices and innovative real-life applications, there has been unceasing demand to offer the requisite data rates and quality of service. The 5G deployments are expected to fulfill such requirements at the access level. It would also serve the necessities of a wide and specialized range of applications that may need very high data rates or extremely low energy consumption. Furthermore, there would be potentials for the bottlenecks at the core and backhaul networks. Such constraints could be addressed by designing better transport networks at core and backhauls, and photonic networks are the best candidate. This paper presents the study on the integration of 5G and photonics networks, the proposed architectures, challenges, open issues, and silicon photonics’ role in the near future to further enhance the end-to-end performance of the communication networks. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes on Data Engineering and Communications Technologies book series

Photonic-Based Front-Mid-Backhaul Access for 5G

Globally, SLM is changing the way organizations design and manufacture products. It is an emerging manufacturing technique. This technique is classified as additive layered manufacturing, as the component is built by adding material in layers. Components/parts manufactured by Selective Laser Melting (SLM) find a lot of applications in many industries like aerospace, biomedical and automobile. Proposed research work investigates the effect of various process parameters on the mechanical properties manufactured by the SLM process of Stainless Steel 316L [SS316L]. The literature indicates that process parameters having maximum impact on mechanical properties includes Laser Power (P), Exposure Time (T), Border Power (BP) and Hatch Spacing (HS). The effect of these process parameters on Ultimate Tensile Strength (UTS) and Surface Roughness (SR) was investigated. This research work aims to enhance the performance measures, by optimizing the process parameters used in SLM with Grasshopper Optimization Algorithm (GOA) technique. GOA was used to achieve maximum ultimate tensile strength and minimum surface roughness in a single set of experimentation through a multiobjective approach.