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

C-60:Li@C-60 hybrid n-type semiconducting films were first fabricated. The Fermi level of 1\% Li@C-60-added C-60 films was determined to be -4.52 eV, which was 0.12 eV higher than that of pristine C-60 films. A fraction of Li@C-60 is distributed uniformly within the C-60 film. Its application in PSCs was demonstrated, in which the addition of Li@C-60 into a C-60 film improved the device performance.

World University root node

School of Mechanical Engineering

CHEMICAL COMMUNICATIONS

Li@C60 endohedral fullerene as a supraatomic dopant for C60 electron-transporting layers promoting the efficiency of perovskite solar cells

2D perovskite-stabilized FACsPbI(3) (FA = formamidinium) perovskite solar cells were fabricated in both normal-type and inverted-type architectures. While the normal-type devices exhibited a high power conversion efficiency of 20.2\%, their reproducibility was limited. On the other hand, the inverted-type devices exhibited an efficiency of 18.2\% with a greater stability and higher reproducibility than those of the normal-type devices. The reduced reproducibility of the normal-type devices was associated with the crack formation on the perovskite films during a spin-coating process. The hardness of both the perovskite and the sublayer was directly linked to the crack formation. Inverted-type 2D/3D FACsPbI(3) with ozone-treated poly(triarylamine) as sublayer exhibited the highest phase stability owing to the hydrophobic nature of poly(triarylamine) and improved energy level alignment upon an ozone treatment. In addition, strong interaction between phenethylamine cations of the 2D perovskite and of the 3D FACsPbI(3) crystal at grain boundaries contributed to the high phase stability.

ACS APPLIED ENERGY MATERIALS

Stable and Reproducible 2D/3D Formamidinium-Lead-lodide Perovskite Solar Cells

Transfer learning has gained more attention recently by utilizing knowledge acquired from one domain to advance a learning performance in another domain. Existing homogeneous transfer learning methods have progressed to a point where feature spaces are common in training and testing domains. However, heterogeneous transfer learning is still in its nascent stage where features of training and testing domains are different. Taking this into account, Bregman Divergence Regularization is used to minimize the probability distribution difference between training and testing domains and to take them together to a shared subspace. To discriminate data within individual domains, a projection matrix is obtained using Fisher Linear Discriminant Analysis subspace learning algorithm. Experimentation is performed on two efficiently used biometrics: the face and fingerprint. Two types of cross-domain settings are used: (1) Face + Finger2Finger where training samples come from face (labeled samples) and fingerprint (unlabeled samples) data sets, while testing is performed on a fingerprint dataset. (2) Finger + Face2Face where training samples come from fingerprint (labeled samples) and face (unlabeled samples) data sets while testing is performed on a face dataset. This paper proposes a cross domain association between face and fingerprint that finds utility in forensic applications.

School of Electronics & Communication Engineering

Evolutionary Intelligence

Cross domain association using transfer subspace learning

In numerous scenarios of forensic applications, only a partial face image is available for recognition purposes. Hence, the systems working on components of the face and partial face images have gained great importance. This paper proposes a novel approach for component-based face recognition and association under transfer learning and demonstrates that the knowledge gained from complete face images is transferred to classify components of the face. Three important components of a face, viz. ears, lips, and nose, are used for association and recognition. These components are unique, stable, and unaltered by the change in poses and expressions. Association is found between the face and nose, face and lips, as well as face and ears. Although, these face components and the face itself are from different domains, they share common information which is utilized to transfer the knowledge gained from one domain to another. Similarly, different types of half-faces are considered: left, right, upper, and lower half and left, right, upper, and lower diagonal for the association between complete and partial face images. Because of the association between a face and its different components, the proposed method can be applied to holistic face recognition, component-based face recognition and partial face recognition.

Information Sciences

Component-based face recognition under transfer learning for forensic applications

A mobile grid (MG) consists of interconnected mobile devices which are used for high performance computing. Fault tolerance is an important property of mobile computational grid systems for achieving superior arrangement reliability and faster recovery from failures. Since the failure of the resources affects task execution fatally, fault tolerance service is essential to achieve QoS requirement in MG. The faults which occur in MG are link failure, node failure, task failure, limited bandwidth etc. Detecting these failures can help in better utilisation of the resources and timely notification to the user in a MG environment. These failures result in loss of computational results and data. Many algorithms or techniques were proposed for failure handling in traditional grids. The authors propose a checkpointing based failure handling technique which will improve arrangement reliability and failure recovery time for the MG network. Experimentation was conducted by creating a grid of ubiquitously available Android-based mobile phones.

School of Computer Engineering & Technology

International Journal of Grid and High Performance Computing

Application Checkpointing Technique for Self-healing from Failures in Mobile Grid Computing

Routing in the Internet of Things (IoT) renders the protection against various network attacks as any attacker intrudes the routing mechanism for establishing the destructive mechanisms against the network, which insists the essentiality of the security protocols in IoT. Thus, the paper proposes a secure protocol based on an optimization algorithm, Monarch-Earthworm Algorithm (Monarch-EWA), which is the modification of the Monarch Butterfly algorithm using the Earthworm Optimization Algorithm (EWA) in order to render effective security to the network. Initially, the effective nodes are selected using the Deep Convolutional Neural Network (deep CNN) classifier based on the factors, trust and energy of the node, and stochastic gradient descent algorithm trains the deep CNN classifier. The secure nodes are involved in routing for which the secure multipath is chosen optimally using the proposed Monarch-EWA, which chooses the secure multipath based on the factors, energy and trust. The analysis of the proposed method in the presence of attacks, such as black hole, message replicate and distributed denial of service, reveals that the proposed method outperformed the existing methods. The proposed Monarch-EWA protocol acquired the maximal energy, throughput and detection rate of 0.2268 J, 48.2759% and 82.6231%, respectively, with the minimal delay of 0.0959 ms.

The Computer Journal, Oxford University Press UK

Monarch-EWA: Monarch-Earthworm-Based Secure Routing Protocol in IoT

Forming process in sheet metal working refers to the manufacturing of products by deforming the material in the required die cavity without being broken or local necking. Defects such as wrinkling, local necking, and cracking may occur during the process. These are the results of either reduction or increase in sheet thickness while the material is being stretched inside die cavity. Prevention of defects is important during forming and is challenging if the thicknesses of forming sheets is less than 100 microns. These sheets are applied in the manufacturing of components having two dimensions of less than millimeter size, an operation known as micro-forming. Miniaturization has attracted many fields such as medical instrumentation, mobile manufacturing, automotive, and aerospace. Appropriate strain distribution in forming ensures products with better quality. Forming limit diagram (FLD) has been invented to plot major and minor strains along with forming limit curves. In other words, FLD shows wrinkling, localized necking as well as safe zones with various strain paths, and it proves to be a basic tool for understanding rupture characteristics of the material. There are three approaches for plotting FLD such as empirical (analytical), numerical, and experimental. The research work presents experimental micro-forming investigations on an ultra-thin brass sheet of 90 microns, to plot FLD, using the limit dome height test according to ASTM E2218-02 standard. The experimental setup was designed and developed to micro-form standard specimens applying 15 mm hemispherical punch. FLD plotted with experimental and empirical approaches shows agreement on failure limit curve.

Materials and Manufacturing Processes

Micro Forming Analysis of Ultra-Thin Brass Foil

The increased number of terrorist attacks mostly in the last few years has shown that the effect of blast loads on buildings is a serious matter which we should be considered during design process of buildings. Although these kinds of terrorist attacks are exceptional cases, man-made disasters; dynamic loads i.e. blast loads are really need to be carefully calculated just like earthquake and wind loads. The investigation of behavior of Ferrocement composites and Steel Fibre Reinforced Concrete composites under blast loading is presented in this paper. Individual ferrocement panels and Steel Fibre Reinforced Concrete panels are tested analytically under blast load, and the behavior against blast loading is then studied.

School of Civil Engineering

International Journal of Scientific & Technology Research

Comparative study of steel fiber reinforced concrete panels and ferrocement panels under blast loading by FEM analysis

In recent years, the research on the anomaly detection has been rapidly increasing. The researchers were worked on different anomalies in videos. This work focuses on fall as an anomaly as it is an emerging research topic with application in elderly safety areas including home environment. The older population staying alone at home is prone to various accidental events including falls which may lead to multiple harmful consequences even death. Thus, it is imperative to develop a robust solution to avoid this problem. This can be done with the help of video surveillance along with computer vision. In this paper, a simple yet efficient technique to detect fall with the help of inexpensive depth camera was presented. Frame differencing method was applied for background subtraction. Various features including orientation angle, aspect ratio, silhouette features, and motion history image (MHI) were extracted for fall characterization. The training and testing were successfully implemented using SVM and SGD classifiers. It was observed that SGD classifier gives better fall detection accuracy than the SVM classifier in both training and testing phase for SDU fall dataset. © Springer Nature Singapore Pte Ltd. 2019.

Advances in Intelligent Systems and Computing

An intelligent video surveillance system for anomaly detection in home environment using a depth camera

Maintaining human healthcare is one of the biggest challenges that most of theincreasing population in Asian countries are facing today. There is an unrelentingneed in our medical community to develop applications that are low on cost, withhigh compression, as huge number of patient’s data and images need to be transmittedover the network to be reviewed by the physicians for diagnostic purpose. Thisimplemented work represents discrete wavelet-based threshold approach. Using thisapproach by applying N-level decomposition on 2D wavelet types like Biorthogonal,Haar, Daubechies, Coiflets, Symlets, Reverse Biorthogonal, and Discrete Meyer, var-ious levels of wavelet coefficients are obtained. The lossless hybrid encoding algo-rithm, which combines run-length encoder and Huffman encoder, has been used forcompression and decompression purpose. This work is proposed to examine theefficiency of different wavelet types and to determine the best. The objective of thisresearch work is to improve compression ratio and compression gain.