arXiv subjects

Ayan Chatterjee

Publications and source records attributed to Ayan Chatterjee.

At least 37 records · Page 2Linked to original sources

arXiv2022

MultiViz: A Gephi Plugin for Scalable Visualization of Multi-Layer Networks

The process of visually presenting networks is an effective way to understand entity relationships within the networks since it reveals the overall structure and topology of the network. Real networks are extremely difficult to visualize due to their immense complexity, which includes vast amounts of data, several types of interactions, various subsystems and several levels of connectivity as well as changes over time. This paper introduces the "MultiViz Plugin," a plugin for gephi, an open-source software tool for graph visualization and modification, in order to to visualize complex networks in a multi-layer manner. A collection of settings are availabe through the plugin to transform an existing network into a multi-layered network. The plugin supports several layout algorithms and lets user to choose which property of the network to be used as the layer. The goal of the study is to give the user complete control over how the network is visualized in a multi-layer fashion. We demonstrate the ability of the plugin to visualize multi-layer data using a real-life complex multi-layer datasets.

cs.SI↗

arXiv2022

Testing of Machine Learning Models with Limited Samples: An Industrial Vacuum Pumping Application

There is often a scarcity of training data for machine learning (ML) classification and regression models in industrial production, especially for time-consuming or sparsely run manufacturing processes. A majority of the limited ground-truth data is used for training, while a handful of samples are left for testing. Here, the number of test samples is inadequate to properly evaluate the robustness of the ML models under test for classification and regression. Furthermore, the output of these ML models may be inaccurate or even fail if the input data differ from the expected. This is the case for ML models used in the Electroslag Remelting (ESR) process in the refined steel industry to predict the pressure in a vacuum chamber. A vacuum pumping event that occurs once a workday generates a few hundred samples in a year of pumping for training and testing. In the absence of adequate training and test samples, this paper first presents a method to generate a fresh set of augmented samples based on vacuum pumping principles. Based on the generated augmented samples, three test scenarios and one test oracle are presented to assess the robustness of an ML model used for production on an industrial scale. Experiments are conducted with real industrial production data obtained from Uddeholms AB steel company. The evaluations indicate that Ensemble and Neural Network are the most robust when trained on augmented data using the proposed testing strategy. The evaluation also demonstrates the proposed method's effectiveness in checking and improving ML algorithms' robustness in such situations. The work improves software testing's state-of-the-art robustness testing in similar settings. Finally, the paper presents an MLOps implementation of the proposed approach for real-time ML model prediction and action on the edge node and automated continuous delivery of ML software from the cloud.

cs.SE↗

arXiv2022

IoT Anomaly Detection Methods and Applications: A Survey

Ongoing research on anomaly detection for the Internet of Things (IoT) is a rapidly expanding field. This growth necessitates an examination of application trends and current gaps. The vast majority of those publications are in areas such as network and infrastructure security, sensor monitoring, smart home, and smart city applications and are extending into even more sectors. Recent advancements in the field have increased the necessity to study the many IoT anomaly detection applications. This paper begins with a summary of the detection methods and applications, accompanied by a discussion of the categorization of IoT anomaly detection algorithms. We then discuss the current publications to identify distinct application domains, examining papers chosen based on our search criteria. The survey considers 64 papers among recent publications published between January 2019 and July 2021. In recent publications, we observed a shortage of IoT anomaly detection methodologies, for example, when dealing with the integration of systems with various sensors, data and concept drifts, and data augmentation where there is a shortage of Ground Truth data. Finally, we discuss the present such challenges and offer new perspectives where further research is required.

cs.SE↗

arXiv2021

Automated Human Activity Recognition by Colliding Bodies Optimization-based Optimal Feature Selection with Recurrent Neural Network

In smart healthcare, Human Activity Recognition (HAR) is considered to be an efficient model in pervasive computation from sensor readings. The Ambient Assisted Living (AAL) in the home or community helps the people in providing independent care and enhanced living quality. However, many AAL models were restricted using many factors that include computational cost and system complexity. Moreover, the HAR concept has more relevance because of its applications. Hence, this paper tempts to implement the HAR system using deep learning with the data collected from smart sensors that are publicly available in the UC Irvine Machine Learning Repository (UCI). The proposed model involves three processes: (1) Data collection, (b) Optimal feature selection, (c) Recognition. The data gathered from the benchmark repository is initially subjected to optimal feature selection that helps to select the most significant features. The proposed optimal feature selection is based on a new meta-heuristic algorithm called Colliding Bodies Optimization (CBO). An objective function derived by the recognition accuracy is used for accomplishing the optimal feature selection. Here, the deep learning model called Recurrent Neural Network (RNN) is used for activity recognition. The proposed model on the concerned benchmark dataset outperforms existing learning methods, providing high performance compared to the conventional models.

cs.LG↗

arXiv2021

Gravitational Collapse in the EGB Gravity

The Einstein- Gauss- Bonnet (EGB) gravity is an important modification of the Einstein theory of gravity and, for many gravitational phenomena, the Gauss- Bonnet (GB) correction term leads to drastic differences. In this paper, we study gravitational collapse in the $5$-dimensional EGB theory. We construct the spherical marginally trapped surfaces and determine the evolution of marginally trapped surfaces when the infalling matter admits a wide variety of initial density distribution. We show that the location of black hole horizon depends crucially on the initial density and velocity profile of the inflating matter as well as on the GB coupling constant. A detailed comparison is made with the results of Einstein's theory.

gr-qc↗

arXiv2021

Algorithm To Calculate Pulse from PPG Signal After Eliminating Touch Errors from the Fingertip Video Captured by Smartphone Camera

With the ongoing heart problems of the population worldwide, the medical requirements of the people are expected to increase. Electrocardiogram (ECG) is one of the proven to capture the heart response signal to assess the electrical and muscular functions of the heart. The ECG setup is expensive and needs proper training, and of course, it is not instant. For fast, accurate heart parameter monitoring, scientists pay attention to the photoplethysmogram signal (PPG), based on the light intensity of a particular wavelength. Android smartphone with a good quality camera has come to ordinary people's reach and has become one of the most necessary and rugged devices for today and future generations. We can use its powerful features to solve or assess heart state monitoring by capturing the image's necessary data. The mobile camera has a photo emitting diode and a photodetector. The light source illuminates the tissue. The photodetector calculates the small variation in light intensity associated with blood volume change in the vessels (mainly fingertips, toes, and ears). We have captured unfocused contact video to capture PPG using an Android Smartphone. Then, we removed a certain percent of camera touch errors based on average pixel intensity count in the red plane, and it is a new approach that has been introduced in this research. We used a 2nd order Butterworth (IIR) band pass filter for noise removal, FFT Hann Window for frequency analysis and leakage reduction. We have developed an algorithm using MATLAB as a development platform, for accurate pulse (BPM) measurement. Moreover, we have done a comparative analysis of developed algorithm with other available algorithms for PPG-based pulse calculation. In this study, the fingertip video was captured when the body was at rest

eess.SP↗

arXiv2021

Gravitationally collapsing stars in $f(R)$ gravity

The gravitational dynamics of a collapsing matter configuration which is simultaneously radiating heat flux is studied in $f(R)$ gravity. Three particular functional forms in $f(R)$ gravity are considered to show that it is possible to envisage boundary conditions such that the end state of the collapse has a weak singularity and that the matter configuration radiates away all of its mass before collapsing to reach the central singularity.

gr-qc↗

arXiv2020

Leveraging Technology for Healthcare and Retaining Access to Personal Health Data to Enhance Personal Health and Well-being

Health data is a sensitive category of personal data. It might result in a high risk to individual and health information handling rights and opportunities unless there is a palatable defense. Reasonable security standards are needed to protect electronic health records (EHR). All personal data handling needs adequate explanation. Maintaining access to medical data even in the developing world would favor health and well-being across the world. Unfortunately, there are still countries that hinder the portability of medical records. Numerous occurrences have shown that it still takes weeks for the medical data to be ported from one general physician (GP) to another. Cross border portability is nearly impossible due to the lack of technical infrastructure and standardization. We demonstrate the difficulty of the portability of medical records with some example case studies as a collaborative engagement exercise through a data mapping process to describe how different people and datapoints interact and evaluate EHR portability techniques. We then propose a blockchain-based EHR system that allows secure, and cross border sharing of medical data. The ethical and technical challenges around having such a system have also been discussed in this study.

cs.CR↗

arXiv2020

Dynamical horizons and Super-Translation transitions of the horizon

A condition is defined which determines if a supertranslation is induced in the course of a general evolution from one isolated horizon phase to another via a dynamical horizon. This condition fixes preferred slices on an isolated horizon and is preserved along an Isolated Horizon. If it is not preserved, in the course of a general evolution, then a supertranslation will be said to have been induced. A simple example of spherically symmetric dynamical horizons is studied to illustrate the conditions for inducing supertranslations.

gr-qc↗

arXiv2020

Exponential corrections to black hole entropy

Using the quasilocal properties alone we show that the area spectrum of a black hole horizon must be discrete, independent of any specific quantum theory of gravity. The area spectrum is found to be half-integer spaced with values $8πγ\ell_{p}^{2}j$ where $j\in \mathbb{N}/2$. We argue that if microstate counting is carried out for quantum states residing on the horizon only, correction of $\exp(-\mathcal{A}/4\ell_{p}^{2})$ over the Bekenstein-Hawking area law must arise in black hole entropy.

gr-qc↗

arXiv2020

A Proposed Access Control-Based Privacy Preservation Model to Share Healthcare Data in Cloud

Healthcare data in cloud computing facilitates the treatment of patients efficiently by sharing information about personal health data between the healthcare providers for medical consultation. Furthermore, retaining the confidentiality of data and patients' identity is a another challenging task. This paper presents the concept of an access control-based (AC) privacy preservation model for the mutual authentication of users and data owners in the proposed digital system. The proposed model offers a high-security guarantee and high efficiency. The proposed digital system consists of four different entities, user, data owner, cloud server, and key generation center (KGC). This approach makes the system more robust and highly secure, which has been verified with multiple scenarios. Besides, the proposed model consisted of the setup phase, key generation phase, encryption phase, validation phase, access control phase, and data sharing phase. The setup phases are run by the data owner, which takes input as a security parameter and generates the system master key and security parameter. Then, in the key generation phase, the private key is generated by KGC and is stored in the cloud server. After that, the generated private key is encrypted. Then, the session key is generated by KGC and granted to the user and cloud server for storing, and then, the results are verified in the validation phase using validation messages. Finally, the data is shared with the user and decrypted at the user-end. The proposed model outperforms other methods with a maximal genuine data rate of 0.91.

cs.CR↗

arXiv2020

Marginally Trapped Surfaces in Spherical Gravitational Collapse

This paper deals with a detail study of gravitational collapse of dust and viscous fluids under the assumptions of spherical symmetry. Our main goal is to closely analyze the horizons which arise during this gravitational phenomenon. To this end, we examine the formation and evolution of trapped surfaces in these spacetimes, with special attention to trapped regions and cylinders foliated by marginally trapped surfaces. The time evolution of trapped surfaces, collapsing shell as well as the event horizon are identified analytically as well as numerically. Using different density profiles of matter, we analyze, how the nature of the marginally trapped surfaces modify as we change the energy momentum tensor. These studies reveal that depending on the mass function and the mass profile, it is possible to envisage situations where dynamical horizons, timelike tubes or isolated horizons may arise.

gr-qc↗

arXiv2020

Link Capacity Distributions and Optimal Capacities for Competent Network Performance

This work addresses the problem of evaluating optimal link capacities of a packet-flow network for the objective of congestion minimization. We present a simple model of packet flow in networks and present a numerical approach to evaluate packet flow probability mass function at any arbitrary edge of the network for a given routing algorithm and traffic rate. We further discuss techniques of assigning optimal capacity at each edge for attaining desired minimized congestion and discuss related trade-offs. Our framework is built around the assumption of Poisson traffic, however the numerical approach fits for any general distribution of packet influx. Lastly, we define metrics of global performance of link capacities allocation and discuss the effect of network structure on capacity allocation and performance.

cs.NI↗

arXiv2019

Effective Quantum Theory of Black Hole Horizons

In this paper, we develop an effective quantum theory of black hole horizons using only the local horizon geometry. On the covariant phase space of the Holst action admitting Weak Isolated Horizon as an inner boundary, we construct Hamiltonian charges corresponding to Lorentz symmetries. We show that horizon area is the Hamiltonian charge corresponding to Lorentz boosts as well as that for Lorentz rotation which acts on $2$-sphere cross-sections of the horizon. Using this expression of area as a generator of Lorentz rotation, and the fact that quantum states residing on the horizon cross-sections carry a representation of $ISO(2)$, we derive the spectrum of area operator on the horizon. The eigenstates of this area operator are shown to be labelled by integers or half integers. The entropy is obtained completely in terms of these \emph{area quanta} residing on the horizon, and is shown to have exponentially suppressing corrections to the area law. The formalism is also extended to non-minimally coupled scalar fields, where the area operator gets modified due to the value of the scalar field on the horizon.

gr-qc↗

arXiv2018

Joining Spacetimes on Fractal Hypersurfaces

The theory of fractional calculus is attracting a lot of attention from mathematicians as well as physicists. The fractional generalisation of the well-known ordinary calculus is being used extensively in many fields, particularly in understanding stochastic process and fractal dynamics. In this paper, we apply the techniques of fractional calculus to study some specific modifications of the geometry of submanifolds. Our generalisation is applied to extend the Israel formalism which is used to glue together two spacetimes across a timelike, spacelike or a null hypersurface. In this context, we show that the fractional extrapolation leads to some striking new results. More precisely we demonstrate that, in contrast to the original Israel formalism, where many spacetimes can only be joined together through an intermediate thin hypersurface of matter satisfying some non- standard energy conditions, the fractional generalisation allows these spacetimes to be smoothly sewed together without any such requirements on the stress tensor of the matter fields. We discuss the ramifications of these results for spacetime structure and the possible implications for gravitational physics.

gr-qc↗

arXiv2018

Quasilocal first law of black hole dynamics from local Lorentz transformations

Quasilocal formulations of black hole are of immense importance since they reveal the essential and minimal assumptions required for a consistent description of black hole horizon, without relying on the asymptotic boundary conditions on fields. Using the quasilocal formulation of Isolated Horizons, we construct the Hamiltonian charges corresponding to local Lorentz transformations on a spacetime admitting isolated horizon as an internal boundary. From this construction, it arises quite generally that the \emph{area} of the horizon of an isolated black hole is the Hamiltonian charge for local Lorentz boost on the horizon. Using this argument further, it is shown that, observers at a fixed proper distance $l_{0}$, very close to the horizon, may define a notion of horizon energy given by $E=A/8πG l_{0}$, the surface gravity is given by $κ=1/l_{0}$, and consequently, the first law can be written in the quasilocal setting as $δE=(κ/8πG)δA$..

gr-qc↗

arXiv2015

Quasilocal rotating conformal Killing horizons

The formulation of quasi-local conformal Killling horizons(CKH) is extended to include rotation. This necessitates that the horizon be foliated by 2-spheres which may be distorted. Matter degrees of freedom which fall through the horizon is taken to be a real scalar field. We show that these rotating CKHs also admit a first law in differential form.

gr-qc↗

arXiv2015

Quasilocal conformal Killing horizons: Classical phase space and the first law

In realistic situations, black hole spacetimes do not admit a global timelike Killing vector field. However, it is possible to describe the horizon in a quasilocal setting by introducing the notion of a quasilocal boundary with certain properties which mimic the properties of a black hole horizon. Isolated horzons and Killing horizons are examples of such kind. In this paper, we construct a boundary of spacetime which is null and admits a conformal Killing vector field. Furthermore we construct the space of solutions (in general theory of relativity) which admits such quasilocal conformal Killing boundaries. We also establish a form of first law for these quasilocal horizons.

gr-qc↗