Browsing by Author "S.K. Basu"

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A Continuum Model and Numerical Simulation for Avascular Tumor Growth
(Springer Nature, 2020) Sounak Sadhukhan; S.K. Basu; Naveen Kumar
A spatio-temporal continuum model is developed for avascular tumor growth in two dimensions using fractional advection-diffusion equation as the transportation in biological systems is heterogeneous and anomalous in nature (non-Fickian). The model handles skewness with a suitable parameter. We study the behavior of this model with a set of parameters, and suitable initial and boundary conditions. It is found that the fractional advection-diffusion equation based model is more realistic as it provides more insightful information for tumor growth at the macroscopic level. © 2020, Springer Nature Switzerland AG.
A model for neuro-computing
(Publ by IEEE, 1991) S.K. Basu; Bhabani P. Sinha
The authors propose a new model for neural computation based solely on a pattern recognition mechanism. By using pattern recognition as the basis of neurocomputing, the authors demonstrate that such a model can solve nonnumeric problems quickly, but it becomes very slow in solving numeric problems. Decisions in problem solving are also made through pattern matching. The outcome of matching is weighted to reflect appropriately the neurological basis. The complexity of computation is defined in terms of pattern matching operations.
A multi-scale agent-based model for avascular tumour growth
(Elsevier Ireland Ltd, 2021) Sounak Sadhukhan; P.K. Mishra; S.K. Basu; J.K. Mandal
In this paper, we have developed a multi-scale, lattice-free, agent based model of avascular tumour growth in epithelial tissue. The model integrates different events to identify the underlying diversity within intracellular, cellular, and extracellular layer dynamics. The model considers every cell as an agent. A cellular agent may proliferate, spawns two identical daughter agents, or it may be transformed into other phenotypes during its life time depending on its internal proteins′ activity as well as its external microenvironment. In this context, a simplified age-structured cell cycle model is adopted from the existing literature. The model considers that the intracellular events are regulated by p27 gene expression. In this model, p27 protein controls the overall tumour growth dynamics. Moreover, p27 is controlled by the external oxygen and nutrients that are modelled with the reaction-diffusion equations. The model also considers several biophysical forces which directly effect on the tumour growth dynamics. This modelling framework offers biologically realistic outcomes and also covers important criteria of the hallmarks of cancer which include oxygen and nutrient consumptions, micro-environmental heterogeneity, tumour cell proliferation by avoiding growth suppressor signals, replication of tumour cells at an abnormally faster rate, and resistance of apoptosis. The avascular tumour growth model is validated with immunohistochemistry and histopathology data. The outcome of the proposed model is very close to the range of the patient data, which concludes that the model is capable enough to mimic these complex biophysical phenomena. © 2021 Elsevier B.V.
A naive genetic approach for non-stationary constrained problems
(2006) S.K. Basu; A.K. Bhatia
An algorithm to be effective for solving non-stationary problems should be robust, adaptive to the changing environment and efficient. Genetic algorithms (GAs) are increasingly being used to solve non-stationary problems. We use GA with a new approach of gene induction (Bhatia and Basu in Soft Comput 8(1):1-9, 2003) to solve non-stationary constrained problems. The approach combines high value genes to form chromosomes from the initial population itself. The efficacy of the method is demonstrated on non-stationary versions of 0/1 knapsack and pure-integer programming problems. The results obtained with the approach are compared with those obtained with feedback thermodynamical genetic algorithm (FTDGA) (Mori et al. in 5th parallel problem solving from nature, number 1498 in LNCS, pp 149-157, 1998). It shows that gene-induction approach is more accurate and requires less time compared to the FTDGA. © Springer-Verlag 2005.
Active queue management using modified stochastic fair blue algorithm
(2007) V. Kushwaha; P.K. Chakravarty; S.K. Basu
In order to protect responsive flows against non-responsive flows to a higher extent than that provided by the Stochastic Fair Blue (SFB) technique, we describe and evaluate a new active queue management algorithm, Modified Stochastic Fair Blue (MSFB). MSFB makes two major improvements in SFB by dynamically changing marking probability increment factor and restricting non-responsive flows to a fixed polluted region. MSFB reduces the probability of misclassification and memory requirements. Simulation results show significant improvements in throughput, fairness, end-to-end delay and memory requirements.
Application of fractal theory in assessing soil aggregates in Indian tropical ecosystems
(Springer Nature, 2012) S.K. Tripathi; C.P. Kushwaha; S.K. Basu
Soil aggregation varies according to climatic and management factors, and is difficult to measure because of irregular shapes and sizes of soil aggregates. We applied fractal theory to assess soil aggregation as affected by (1) land use change from forest to savanna, (2) nutrient additions in forest, ecotone, and savanna ecosystems, and (3) tillage practice and residue treatments in an agro-ecosystem. We used fractal dimensions nonlinear (Dnon-lin) and linear (Dlin) based on number of aggregates (N) and mass of aggregates (M) (the range of values were 2.6-2.89 and 2.69-3.41, respectively) to capture the variations in the sizes of soil aggregates due to land use and treatments/management in these ecosystems. The variation in the values of non-linear fractal dimension based on mass (DMnon-lin) was smaller in forest and savanna ecosystems with and without nutrient additions, while the variation was wider in agro-ecosystems with different management practices. Linear fractal dimensions based on number (DNlin) and mass (DMlin) of aggregates varied marginally in these ecosystems and did not capture the variations in soil aggregates well. The variations in non-linear fractal dimension indicate that continued nitrogen loading in forest accelerates the formation of macro-aggregates, whereas in savanna the situation was reversed. The values of non-linear fractal dimensions did not show significant change after 6 years of nutrient additions in the ecotone; reflecting a buffering mechanism of this system in soil aggregate formation. On the basis of non-linear fractal dimension values, we conclude that residue retention and minimum tillage are appropriate for proper maintenance of soil aggregate stability for sustained crop production in the Indian dry land agro-ecosystems. © 2012 Northeast Forestry University and Springer-Verlag Berlin Heidelberg.
Avascular tumour growth models based on anomalous diffusion
(Springer, 2020) Sounak Sadhukhan; S.K. Basu
In this study, we model avascular tumour growth in epithelial tissue. This can help us to understand that how an avascular tumour interacts with its microenvironment and what type of physical changes can be observed within the tumour spheroid before angiogenesis. This understanding is likely to assist in the development of better diagnostics, improved therapies, and prognostics. In biological systems, most of the diffusive processes are through cellular membranes which are porous in nature. Due to its porous nature, diffusion in biological systems are heterogeneous. The fractional diffusion equation is well suited to model heterogeneous biological systems, though most of the early studies did not use this fact. They described tumour growth with simple diffusion-based model. We have developed a spherical model based on simple diffusion initially, and then the model is upgraded with fractional diffusion equations to express the anomalous nature of biological system. In this study, two types of fractional models are developed: one of fixed order and the other of variable order. The memory formalism technique is also included in these anomalous diffusion models. These three models are investigated from phenomenological point view by measuring some parameters for characterizing avascular tumour growth over time. Tumour microenvironment is very complex in nature due to several concurrent molecular mechanisms. Diffusion with memory (fixed as well as variable) formation may be an oversimplified technique, and does not reflect the detailed view of the tumour microenvironment. However, it is found that all the models offer realistic and insightful information of the tumour microenvironment at the macroscopic level, and approximate well the physical phenomena. Also, it is observed that the anomalous diffusion based models offer a closer description to clinical facts than the simple model. As the simulation parameters get modified due to different biochemical and biophysical processes, the robustness of the model is determined. It is found that the anomalous diffusion models are moderately sensitive to the parameters. © 2020, Springer Nature B.V.
Better-fit heuristic for one-dimensional bin-packing problem
(2009) A.K. Bhatia; M. Hazra; S.K. Basu
This paper reports a study on better-fit heuristic for classical bin-packing problem, proposed in [1]. Better-fit replaces an existing object from a bin with the next object in the list, if it can fill the bin better than the object replaced. It takes 0(n2m) time where n is the number of objects and m is the number of distinct object sizes in the list. It behaves as off-line as well as on-line heuristic with the condition of permanent assignment of objects to a bin removed. Experiments have been conducted on representative problem instances in terms of expected waste rates. It outperforms off-line best-fit-decreasing heuristic on most of the instances. It always performs better than the on-line best-fit heuristic. ©2009 IEEE.
Cancer Diagnostics and Therapeutics: Current Trends, Challenges, and Future Perspectives
(Springer Nature, 2022) S.K. Basu; Chinmay Kumar Panda; Subrata Goswami
This book presents multiple facets of cancer biology, including cancer diagnosis, therapeutics to the latest developments in cancer informatics, and applications of artificial intelligence for improving oncologic care. The initial section of the book discusses factors contributing to the development and causes of cancer. The subsequent sections discuss the basic principle of imaging and therapeutic techniques, including MRI, CT, and positron emission tomography (PET) Scan. The book further, explores the implications of cancer chemotherapy on the immune system and emphasizes the effective management of cancer-related pain. Towards the end, it covers recent advancements in cancer treatment, including targeted therapy, immunotherapy, interventional radiotherapy, and stem cell-based therapy. Lastly, it summarizes essential strategic elements of cancer informatics for improving patient outcome. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.
CCT: a new VLSI architecture for parallel processing
(IEEE, 1994) S.K. Basu; J. Dattagupta; R. Dattagupta
In this paper, we propose a VLSI implementable architecture called Cube Connected Tree having advantages of both tree and hypercube. This structure has fixed low degree nodes for any size of the network unlike hypercube, where the node degree is dependent on the size of the hypercube. Complexity of VLSI layout of this structure has been addressed within the grid model of Thompson. By using spare links and PE's, fault-tolerance capabilities of the system has been enhanced. Easy programmability of this structure has been demonstrated by designing polylogarithmic algorithms for sorting and Discrete Fourier Transform.
Computer Simulation of Long-Term Vegetation Status in Landslide-Prone Areas in the Himalayan Region
(2004) S.K. Basu; A. Roy
The long-term vegetation pattern in landslide-prone regions is studied using simulation and modeling. A simulator is developed to study the impact of landslides on vegetation status. The first part of the model deals with simulation of the effects of rainfall, earthquakes, and deforestation in the creation of landslides and the concomitant damage to vegetation. The second part is a deterministic model of vegetation regeneration. The authors assume that the interarrival time of earthquakes, the intensity of these earthquakes, and rainfall intensity are stochastic in nature and that the earthquake frequency is independent of earthquake intensity. An estimate is made of the damage to vegetation due to the occurrence of landslides under the combined influence of earthquakes, rainfall, and deforestation. After the ecosystem parameters get modified due to the damage, the vegetation status is recalculated for the annual change according to the vegetation regeneration model. © 2004, Sage Publications. All rights reserved.
Design considerations of a medical expert system for differential diagnosis of low back pain (Eslbp )
(Springer, 2020) Debarpita Santra; J.K. Mandal; S.K. Basu; Subrata Goswami
Low back pain is a communal musculoskeletal ailment that deprives many individuals worldwide of doing their daily and normal activities. With the absence of external biomarkers, most of the symptoms of low back pain diseases seem similar, making the diagnosis process quite difficult. Application of artificial intelligence is beneficial in this regard. The paper deals with the design of an efficient knowledge base and a reliable inference engine for a medical expert system for treatment of low back pain. As many low back pain diseases have common clinical signs, consideration of only the dissimilar patterns of the diseases in the design of knowledge base would surely overcome the problem of processing the same symptoms over and over. The acquired knowledge is represented with a discernibility matrix that captures only the disparities among low back pain diseases. An inference mechanism has also been proposed, which uses the discernibility matrix for offering the diagnostic conclusions in a timely manner. The designed system has been tested with patient records empirically selected from the repository of ESI Hospital Sealdah, Kolkata. The test results show that the diagnostic inference generated by the proposed inference engine conforms to the conclusions made by the expert physicians. © Springer Nature Singapore Pte Ltd. 2020.
Design of Control Circuit of an Automated Elevator Employing Mathematical Logic
(1970) S. Choudhuri; S.K. Basu; S.P. Patra
The control circuit necessary for the operation of an automatic elevator which starts and stops at specified places and at specified time is presented. At present the elevator operations are generally controlled by electromechanical relays with a large number of contacts and limit switches. Here it has been tried to dispense with relays and their contacts, limit switches etc., by the introduction of semiconductor logical and switching devices. Electronic counting technique has also been suitably used. Different logical and switching schemes to be used have been developed by writing all the logical and sequential operations in the form of constraint equations, then solving them with the help of Boolean algebra. Boolean operations are performed by different logical and switching circuits. The entire control circuit has been constructed and tested, and the results were found to be in conformity with the predicted operations. All the facilities provided in an operatorless automatic elevator are also provided by this static control circuit. It is not, however, claimed that this is the only static control circuit possible or that the circuitry used is optimum. The authors only feel that such an approach will help the elevator engineers in finding out the easiest solution to any elevator operation problem. This is surely not possible by looking at different operations as completely isolated and their circuit arrangements mutually independent. Copyright © 1970 by The Institute of Electrical and Electronics Engineers, Inc.
DHT: Diagonally hybridized tree is an efficient VLSI structure for parallel computation
(Publ by IEEE, 1990) S.K. Basu
A new tree-based VLSI architecture called a diagonally hybridized tree (DHT) is proposed. DHT requires less hardware in terms of number of processors, connecting links and layout area compared to a mesh-of-tree of comparable size. By mapping a number of representative problems on DHT, the suitability of DHT for parallel computation is demonstrated. The results show that DHT with a sequential host can be used as a general-purpose parallel computer. A scheme is also given to tolerate faults in DHT by using spare processing elements (PEs) and links. It is shown that, asymptotically, DHT can tolerate O(N) faults by using O(N) spare PEs and O(N) spare links.
Electrolytes in surgical patients: the effect of pre‐operative starvation and environmental temperature
(1977) D.K. Banerjee; R. Misra; S.K. Basu; K. Pandey
[No abstract available]
Empirical analysis of some cryptographic algorithms
(2011) S.K. Basu; Prahlad Kumar Singh; Somenath Sit
In this paper we have carried out some experimental analysis of two cryptographic algorithms RSA and DES and checked the strength of these algorithms against brute force cracking. The testing has been done on different file sizes ranging from 62 Bytes to 92.7 Kilobytes. From the experiments, it is found that the RSA (using random method of prime number generation) is more secure and robust than the DES algorithm but the RSA algorithm using Euclid method is most susceptible to hacking.
Fighting with Cancer: A Common Man's Dilemma
(Springer Nature, 2022) S.K. Basu; Santanu Basu; Subrata Goswami; Saurabh Joshi
The impact of cancer diagnosis on the patient and the families is immense. The term cancer is quite frightening. It brings along a series of complicated thoughts about the disease, its course, treatment, associated difficulties, financial burden, social status, and existential issues. It traps the sufferers in a vicious loop of thoughts related to life, end of life, and thereafter. Another aspect that is mostly overlooked is the spiritual distress that comes along with the diagnosis of cancer. All these thoughts get amplified and increase psychological morbidity, which further gets compounded due to lack of knowledge and awareness about the disease and the ways to deal with it. This chapter broadly outlines the epidemiology and mechanism of the disease, types of cancer, various terminologies that are used, investigations that are undertaken, treatment options, and coping strategies during and beyond the process of disease and disability. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.
Formulating diversity vector for ecosystem comparison
(2004) A. Roy; S.K. Tripathi; S.K. Basu
Extensive variations in the taxonomic variety and morphology of living organisms and their spatial distribution have created a major problem for precise assessment of biodiversity. Biodiversity is fundamentally a multidimensional concept and cannot be reduced sensibly to a single number [Purvis, A., Hector, A., 2000. Getting the measure of biodiversity. Nature 405, 212-219]. A number of diversity indices are available but each has its own limitations, as they are not adequate for comprehensive representation of biodiversity of an ecosystem. We propose a vector for making a comprehensive quantitative and qualitative description of ecosystem diversity. This vector gives a fair idea about the physical and biological aspects of the ecosystem and can be used for modeling and comparison of intra- and inter-ecosystem diversity in the form of concise numerical information. The diversity vector has five components: environmental index, life-form index, Shannon-Weiner index, taxonomic index and functional index. The scheme takes care of species abundance, taxonomic variety and satisfies monotonicity. Moreover, these components can be easily calculated. Field data from two contrasting ecosystems are used to explain the scheme. Though we have confined to the plant kingdom, the scheme can be logically extended to incorporate the animal kingdom. © 2004 Elsevier B.V. All rights reserved.
High-spin states in the odd-odd nucleus146Tb
(American Physical Society, 2004) Krishichayan; A. Chakraborty; S.S. Ghugre; R. Goswami; S. Mukhopadhyay; N.S. Pattabiraman; S. Ray; A.K. Sinha; S. Sarkar; P.V. Madhusudhana Rao; U. Garg; S.K. Basu; B.K. Yogi; L. Chaturvedi; A. Dhal; R.K. Sinha; M. Saha Sarkar; S. Saha; R. Singh; R.K. Bhowmik; A. Jhingan; N. Madhavan; S. Muralithar; S. Nath; R.P. Singh; P. Sugathan
The odd-odd 146Tb nucleus has been investigated using the 115In(34S,3n) reaction at 140 MeV incident energy using an array of eight Compton-suppressed Clover detectors. Based on the observed γ- γ coincidences, the level structure of 146Tb has been extended up to Ex∼ 10 MeV. Linear polarization measurements have been combined with angular correlations of the observed γ rays to assign the electromagnetic nature to the transitions. Probable origin of a cascade of M1 transitions observed around 8 MeV excitation energy has been discussed.
Implicit elitism in genetic search
(Springer Verlag, 2006) A.K. Bhatia; S.K. Basu
We introduce a notion of implicit elitism derived from the mutation operator in genetic algorithms. Probability of mutation less than 1/l (l being the chromosome size) along with probability of crossover less than one induces implicit elitism in genetic search. It implicitly transfers a few chromosomes with above-average fitness unperturbed to the population at next generation, thus maintaining the progress of genetic search. Experiments conducted on one-max and 0/1 knapsack problems testify its efficacy. Implicit elitism in combination with traditional explicit elitism enhances the search capability of genetic algorithms. © Springer-Verlag Berlin Heidelberg 2006.