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8. Rethinking the Relationship between Recurrent and Non-Recurrent Neural Networks: A Study in Sparsity

Author

Hershey, Quincy, Paffenroth, Randy, Pathak, Harsh, and Tavener, Simon

Subjects
Computer Science - Machine Learning
Abstract

Neural networks (NN) can be divided into two broad categories, recurrent and non-recurrent. Both types of neural networks are popular and extensively studied, but they are often treated as distinct families of machine learning algorithms. In this position paper, we argue that there is a closer relationship between these two types of neural networks than is normally appreciated. We show that many common neural network models, such as Recurrent Neural Networks (RNN), Multi-Layer Perceptrons (MLP), and even deep multi-layer transformers, can all be represented as iterative maps. The close relationship between RNNs and other types of NNs should not be surprising. In particular, RNNs are known to be Turing complete, and therefore capable of representing any computable function (such as any other types of NNs), but herein we argue that the relationship runs deeper and is more practical than this. For example, RNNs are often thought to be more difficult to train than other types of NNs, with RNNs being plagued by issues such as vanishing or exploding gradients. However, as we demonstrate in this paper, MLPs, RNNs, and many other NNs lie on a continuum, and this perspective leads to several insights that illuminate both theoretical and practical aspects of NNs.

Published
2024

10. Clinical and biomarker results from a phase II trial of combined cabozantinib and durvalumab in patients with chemotherapy-refractory colorectal cancer (CRC): CAMILLA CRC cohort

Author

Saeed, Anwaar, Park, Robin, Pathak, Harsh, Al-Bzour, Ayah Nedal, Dai, Junqiang, Phadnis, Milind, Al-Rajabi, Raed, Kasi, Anup, Baranda, Joaquina, Sun, Weijing, Williamson, Stephen, Chiu, Yu-Chiao, Osmanbeyoglu, Hatice Ulku, Madan, Rashna, Abushukair, Hassan, Mulvaney, Kelly, Godwin, Andrew K., and Saeed, Azhar

Published
2024
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16. A window of opportunity trial evaluating intratumoral injection of Copaxone® in patients with percutaneously accessible tumors

Author

Baranda, Joaquina C., Mohyuddin, Ghulam Rehman, Bur, Andrés M., Shnayder, Yelizaveta, Sweeney, Kyle R., Kakarala, Kiran, Prouty, Megan, Pathak, Harsh, Puri, Rajni, Mitra, Amrita, Madan, Rashna, Forrest, M. Laird, Huang, Aric, Weir, Scott, Godwin, Andrew K., Alhakamy, Nabil A., Griffin, J. Daniel, and Berkland, Cory J.

Published
2023
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18. Efficient Super Resolution For Large-Scale Images Using Attentional GAN

Author

Pathak, Harsh Nilesh, Li, Xinxin, Minaee, Shervin, and Cowan, Brooke

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Single Image Super Resolution (SISR) is a well-researched problem with broad commercial relevance. However, most of the SISR literature focuses on small-size images under 500px, whereas business needs can mandate the generation of very high resolution images. At Expedia Group, we were tasked with generating images of at least 2000px for display on the website, four times greater than the sizes typically reported in the literature. This requirement poses a challenge that state-of-the-art models, validated on small images, have not been proven to handle. In this paper, we investigate solutions to the problem of generating high-quality images for large-scale super resolution in a commercial setting. We find that training a generative adversarial network (GAN) with attention from scratch using a large-scale lodging image data set generates images with high PSNR and SSIM scores. We describe a novel attentional SISR model for large-scale images, A-SRGAN, that uses a Flexible Self Attention layer to enable processing of large-scale images. We also describe a distributed algorithm which speeds up training by around a factor of five., Comment: Accepted by IEEE International Conference on Big Data, 2018

Published
2018

19. Cisplatin with veliparib or placebo in metastatic triple-negative breast cancer and BRCA mutation-associated breast cancer (S1416): a randomised, double-blind, placebo-controlled, phase 2 trial

Author

Rodler, Eve, Sharma, Priyanka, Barlow, William E, Gralow, Julie R, Puhalla, Shannon L, Anders, Carey K, Goldstein, Lori, Tripathy, Debu, Brown-Glaberman, Ursa A, Huynh, Thu-Tam, Szyarto, Christopher S, Godwin, Andrew K, Pathak, Harsh B, Swisher, Elizabeth M, Radke, Marc R, Timms, Kirsten M, Lew, Danika L, Miao, Jieling, Pusztai, Lajos, Hayes, Daniel F, and Hortobagyi, Gabriel N

Published
2023
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20. Correlation of serum anti-Müllerian hormone (AMH) levels on identification of premenopausal patients (pts) with hormone receptor positive (HR+), HER2-negative, node-positive breast cancer most likely to benefit from adjuvant chemotherapy in SWOG S1007 (RxPONDER).

Author

Kalinsky, Kevin, primary, Barlow, William E., additional, Pathak, Harsh B, additional, Gralow, Julie R., additional, Albain, Kathy S., additional, Hayes, Daniel F., additional, Lin, Nancy U., additional, Perez, Edith A., additional, Goldstein, Lori J., additional, Chia, Stephen K. L., additional, Rastogi, Priya, additional, Schott, Anne F., additional, Shak, Steven, additional, Tripathy, Debashish, additional, Hortobagyi, Gabriel N., additional, Meric-Bernstam, Funda, additional, Sharma, Priyanka, additional, Pusztai, Lajos, additional, Thompson, Alastair Mark, additional, and Godwin, Andrew K., additional

Published
2024
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22. Prospective longitudinal study of kinetics of humoral response to one, two, or three doses of SARS-CoV-2 vaccine in hematopoietic cell transplant recipients

Author

Khan, Qamar J., Bivona, Cory R., Liu, Ben, Nelson, Maggie, Martin, Grace A., Mushtaq, Muhammad Umair, Sharma, Priyanka, Streeter, Natalie R., Hoffmann, Marc, Doolittle, Gary C., Zhong, Cuncong, Mitchell, Laura, Li, Kevin H., Pessetto, Ziyan Y., Ghosh, Arnab, Pathak, Harsh B., Zhang, Jun, Godwin, Andrew K., and McGuirk, Joseph P.

Published
2022
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25. Non-convex Optimization Using Parameter Continuation Methods for Deep Neural Networks

Author

Nilesh Pathak, Harsh, Clinton Paffenroth, Randy, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Wani, M. Arif, editor, Khoshgoftaar, Taghi M., editor, and Palade, Vasile, editor

Published
2021
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28. Drug discovery using clinical outcome-based Connectivity Mapping: application to ovarian cancer

Author

Raghavan, Rama, Hyter, Stephen, Pathak, Harsh B, Godwin, Andrew K, Konecny, Gottfried, Wang, Chen, Goode, Ellen L, and Fridley, Brooke L

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Orphan Drug, Genetics, Ovarian Cancer, Rare Diseases, Biotechnology, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Antineoplastic Agents, Cell Line, Tumor, Computational Biology, Databases, Genetic, Disease Progression, Dose-Response Relationship, Drug, Drug Discovery, Drug Screening Assays, Antitumor, Female, Gene Expression Regulation, Neoplastic, Humans, Neoplasm Staging, Ovarian Neoplasms, Proportional Hazards Models, Recurrence, Gene expression signature, Time to recurrence, Bioinformatics, Connectivity Mapping, Drug discovery, Ovarian cancer, Biological Sciences, Information and Computing Sciences, Medical and Health Sciences, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundEpithelial ovarian cancer (EOC) is the fifth leading cause of cancer death among women in the United States (5 % of cancer deaths). The standard treatment for patients with advanced EOC is initial debulking surgery followed by carboplatin-paclitaxel combination chemotherapy. Unfortunately, with chemotherapy most patients relapse and die resulting in a five-year overall survival around 45 %. Thus, finding novel therapeutics for treating EOC is essential. Connectivity Mapping (CMAP) has been used widely in cancer drug discovery and generally has relied on cancer cell line gene expression and drug phenotype data. Therefore, we took a CMAP approach based on tumor information and clinical endpoints from high grade serous EOC patients.MethodsWe determined tumor gene expression signatures (e.g., sets of genes) associated with time to recurrence (with and without adjustment for additional clinical covariates) among patients within TCGA (n = 407) and, separately, from the Mayo Clinic (n = 326). Each gene signature was inputted into CMAP software (Broad Institute) to determine a set of drugs for which our signature "matches" the "reference" signature, and drugs that overlapped between the CMAP analyses and the two studies were carried forward for validation studies involving drug screens on a set of 10 EOC cell lines.ResultsOf the 11 drugs carried forward, five (mitoxantrone, podophyllotoxin, wortmannin, doxorubicin, and 17-AAG) were known a priori to be cytotoxics and were indeed shown to effect EOC cell viability.ConclusionsFuture research is needed to investigate the use of these CMAP and similar analyses for determining combination therapies that might work synergistically to kill cancer cells and to apply this in silico bioinformatics approach using clinical outcomes to other cancer drug screening studies.

Published
2016

30. DO CRUDE OIL PRICE FLUCTUATIONS AFFECT THE SECTORAL STOCK RETURNS? EVIDENCE FROM INDIA.

Author

Pathak, Harsh Raj and Kumar, Satish

Subjects
RATE of return on stocks, PETROLEUM sales & prices, COMMODITY exchanges, PETROLEUM, PRICE fluctuations, FINANCIAL market reaction, GRANGER causality test, MARKET volatility
Abstract

Crude oil is a vital energy source for industrialised and developing countries. Both investors who trade crude oil derivatives and firms that use oil as raw material for production monitor oil supply and demand. Disruption in the flow of oil in the commodity markets, therefore, leads to oil price volatility that affects major economies worldwide. Often, geopolitical and natural conditions could adversely impact the oil price and the financial markets react to such fluctuations in oil prices. This paper analyses the effects of oil price changes on sectorial stock returns in India. Using daily returns of S&P BSE Sensex, S&P BSE Oil & Gas and S&P BSE-Auto sectoral indices from January 2000 to March 2020, we examined the impact of Brent crude oil price fluctuations on the two major sectorial stock indices and overall market index. The results of the Granger causality test show significant results on S&P BSE-Sensex and S&P BSE-Oil and Gas Index Returns except S&P BSE-Auto Index Returns. Further for contemporaneous association between the oil price changes and sectorial returns, we operationalised the simple regression analysis. The results from the regression analysis show statistically significant impact of crude oil price fluctuations on the sectorial returns. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Auto-PCOS Classification Challenge

Author

Hub, Misa, primary, Handa, Palak, additional, Saini, Anushka, additional, Dutta, Siddhant, additional, Pathak, Harsh, additional, Choudhary, Nishi, additional, Goel, Nidhi, additional, and Dhanao, Jasdeep Kaur, additional

Published
2024
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38. Association of type and location of BRCA1 and BRCA2 mutations with risk of breast and ovarian cancer.

Author

Rebbeck, Timothy R, Mitra, Nandita, Wan, Fei, Sinilnikova, Olga M, Healey, Sue, McGuffog, Lesley, Mazoyer, Sylvie, Chenevix-Trench, Georgia, Easton, Douglas F, Antoniou, Antonis C, Nathanson, Katherine L, CIMBA Consortium, Laitman, Yael, Kushnir, Anya, Paluch-Shimon, Shani, Berger, Raanan, Zidan, Jamal, Friedman, Eitan, Ehrencrona, Hans, Stenmark-Askmalm, Marie, Einbeigi, Zakaria, Loman, Niklas, Harbst, Katja, Rantala, Johanna, Melin, Beatrice, Huo, Dezheng, Olopade, Olufunmilayo I, Seldon, Joyce, Ganz, Patricia A, Nussbaum, Robert L, Chan, Salina B, Odunsi, Kunle, Gayther, Simon A, Domchek, Susan M, Arun, Banu K, Lu, Karen H, Mitchell, Gillian, Karlan, Beth Y, Walsh, Christine, Lester, Jenny, Godwin, Andrew K, Pathak, Harsh, Ross, Eric, Daly, Mary B, Whittemore, Alice S, John, Esther M, Miron, Alexander, Terry, Mary Beth, Chung, Wendy K, Goldgar, David E, Buys, Saundra S, Janavicius, Ramunas, Tihomirova, Laima, Tung, Nadine, Dorfling, Cecilia M, van Rensburg, Elizabeth J, Steele, Linda, Neuhausen, Susan L, Ding, Yuan Chun, Ejlertsen, Bent, Gerdes, Anne-Marie, Hansen, Thomas VO, Ramón y Cajal, Teresa, Osorio, Ana, Benitez, Javier, Godino, Javier, Tejada, Maria-Isabel, Duran, Mercedes, Weitzel, Jeffrey N, Bobolis, Kristie A, Sand, Sharon R, Fontaine, Annette, Savarese, Antonella, Pasini, Barbara, Peissel, Bernard, Bonanni, Bernardo, Zaffaroni, Daniela, Vignolo-Lutati, Francesca, Scuvera, Giulietta, Giannini, Giuseppe, Bernard, Loris, Genuardi, Maurizio, Radice, Paolo, Dolcetti, Riccardo, Manoukian, Siranoush, Pensotti, Valeria, Gismondi, Viviana, Yannoukakos, Drakoulis, Fostira, Florentia, Garber, Judy, Torres, Diana, Rashid, Muhammad Usman, Hamann, Ute, Peock, Susan, Frost, Debra, Platte, Radka, Evans, D Gareth, Eeles, Rosalind, Davidson, Rosemarie, and Eccles, Diana

Subjects
CIMBA Consortium, Humans, Breast Neoplasms, Ovarian Neoplasms, Genetic Predisposition to Disease, Nucleotides, Risk Factors, Age of Onset, Heterozygote, Mutation, Genes, BRCA1, Genes, BRCA2, Adult, Middle Aged, Female, Cancer, Prevention, Rare Diseases, Breast Cancer, Clinical Research, Ovarian Cancer, General & Internal Medicine, Medical and Health Sciences
Abstract

ImportanceLimited information about the relationship between specific mutations in BRCA1 or BRCA2 (BRCA1/2) and cancer risk exists.ObjectiveTo identify mutation-specific cancer risks for carriers of BRCA1/2.Design, setting, and participantsObservational study of women who were ascertained between 1937 and 2011 (median, 1999) and found to carry disease-associated BRCA1 or BRCA2 mutations. The international sample comprised 19,581 carriers of BRCA1 mutations and 11,900 carriers of BRCA2 mutations from 55 centers in 33 countries on 6 continents. We estimated hazard ratios for breast and ovarian cancer based on mutation type, function, and nucleotide position. We also estimated RHR, the ratio of breast vs ovarian cancer hazard ratios. A value of RHR greater than 1 indicated elevated breast cancer risk; a value of RHR less than 1 indicated elevated ovarian cancer risk.ExposuresMutations of BRCA1 or BRCA2.Main outcomes and measuresBreast and ovarian cancer risks.ResultsAmong BRCA1 mutation carriers, 9052 women (46%) were diagnosed with breast cancer, 2317 (12%) with ovarian cancer, 1041 (5%) with breast and ovarian cancer, and 7171 (37%) without cancer. Among BRCA2 mutation carriers, 6180 women (52%) were diagnosed with breast cancer, 682 (6%) with ovarian cancer, 272 (2%) with breast and ovarian cancer, and 4766 (40%) without cancer. In BRCA1, we identified 3 breast cancer cluster regions (BCCRs) located at c.179 to c.505 (BCCR1; RHR = 1.46; 95% CI, 1.22-1.74; P = 2 × 10(-6)), c.4328 to c.4945 (BCCR2; RHR = 1.34; 95% CI, 1.01-1.78; P = .04), and c. 5261 to c.5563 (BCCR2', RHR = 1.38; 95% CI, 1.22-1.55; P = 6 × 10(-9)). We also identified an ovarian cancer cluster region (OCCR) from c.1380 to c.4062 (approximately exon 11) with RHR = 0.62 (95% CI, 0.56-0.70; P = 9 × 10(-17)). In BRCA2, we observed multiple BCCRs spanning c.1 to c.596 (BCCR1; RHR = 1.71; 95% CI, 1.06-2.78; P = .03), c.772 to c.1806 (BCCR1'; RHR = 1.63; 95% CI, 1.10-2.40; P = .01), and c.7394 to c.8904 (BCCR2; RHR = 2.31; 95% CI, 1.69-3.16; P = .00002). We also identified 3 OCCRs: the first (OCCR1) spanned c.3249 to c.5681 that was adjacent to c.5946delT (6174delT; RHR = 0.51; 95% CI, 0.44-0.60; P = 6 × 10(-17)). The second OCCR spanned c.6645 to c.7471 (OCCR2; RHR = 0.57; 95% CI, 0.41-0.80; P = .001). Mutations conferring nonsense-mediated decay were associated with differential breast or ovarian cancer risks and an earlier age of breast cancer diagnosis for both BRCA1 and BRCA2 mutation carriers.Conclusions and relevanceBreast and ovarian cancer risks varied by type and location of BRCA1/2 mutations. With appropriate validation, these data may have implications for risk assessment and cancer prevention decision making for carriers of BRCA1 and BRCA2 mutations.

Published
2015

43. Circulating Tumor Cell Subpopulations Predict Treatment Outcome in Pancreatic Ductal Adenocarcinoma (PDAC) Patients

Author

Freed, Ian M., primary, Kasi, Anup, additional, Fateru, Oluwadamilola, additional, Hu, Mengjia, additional, Gonzalez, Phasin, additional, Weatherington, Nyla, additional, Pathak, Harsh, additional, Hyter, Stephen, additional, Sun, Weijing, additional, Al-Rajabi, Raed, additional, Baranda, Joaquina, additional, Hupert, Mateusz L., additional, Chalise, Prabhakar, additional, Godwin, Andrew K., additional, A. Witek, Malgorzata, additional, and Soper, Steven A., additional

Published
2023
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45. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11

Author

Siddiq, Afshan, Couch, Fergus J, Chen, Gary K, Lindström, Sara, Eccles, Diana, Millikan, Robert C, Michailidou, Kyriaki, Stram, Daniel O, Beckmann, Lars, Rhie, Suhn Kyong, Ambrosone, Christine B, Aittomäki, Kristiina, Amiano, Pilar, Apicella, Carmel, Investigators, Australian Breast Cancer Tissue Bank, Baglietto, Laura, Bandera, Elisa V, Beckmann, Matthias W, Berg, Christine D, Bernstein, Leslie, Blomqvist, Carl, Brauch, Hiltrud, Brinton, Louise, Bui, Quang M, Buring, Julie E, Buys, Saundra S, Campa, Daniele, Carpenter, Jane E, Chasman, Daniel I, Chang-Claude, Jenny, Chen, Constance, Clavel-Chapelon, Françoise, Cox, Angela, Cross, Simon S, Czene, Kamila, Deming, Sandra L, Diasio, Robert B, Diver, W Ryan, Dunning, Alison M, Durcan, Lorraine, Ekici, Arif B, Fasching, Peter A, Study, Familial Breast Cancer, Feigelson, Heather Spencer, Fejerman, Laura, Figueroa, Jonine D, Fletcher, Olivia, Flesch-Janys, Dieter, Gaudet, Mia M, Consortium, The GENICA, Gerty, Susan M, Rodriguez-Gil, Jorge L, Giles, Graham G, van Gils, Carla H, Godwin, Andrew K, Graham, Nikki, Greco, Dario, Hall, Per, Hankinson, Susan E, Hartmann, Arndt, Hein, Rebecca, Heinz, Judith, Hoover, Robert N, Hopper, John L, Hu, Jennifer J, Huntsman, Scott, Ingles, Sue A, Irwanto, Astrid, Isaacs, Claudine, Jacobs, Kevin B, John, Esther M, Justenhoven, Christina, Kaaks, Rudolf, Kolonel, Laurence N, Coetzee, Gerhard A, Lathrop, Mark, Le Marchand, Loic, Lee, Adam M, Lee, I-Min, Lesnick, Timothy, Lichtner, Peter, Liu, Jianjun, Lund, Eiliv, Makalic, Enes, Martin, Nicholas G, McLean, Catriona A, Meijers-Heijboer, Hanne, Meindl, Alfons, Miron, Penelope, Monroe, Kristine R, Montgomery, Grant W, Müller-Myhsok, Bertram, Nickels, Stefan, Nyante, Sarah J, Olswold, Curtis, Overvad, Kim, Palli, Domenico, Park, Daniel J, Palmer, Julie R, and Pathak, Harsh

Subjects
Biological Sciences, Genetics, Clinical Research, Aging, Human Genome, Breast Cancer, Cancer, Aetiology, 2.1 Biological and endogenous factors, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Receptors, Estrogen, Australian Breast Cancer Tissue Bank Investigators, Familial Breast Cancer Study, GENICA Consortium, Medical and Health Sciences, Genetics & Heredity
Abstract

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10(-5) in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10(-8)) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10(-6)) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10(-9)), and with both ER-positive (OR = 1.09; P = 1.5 × 10(-5)) and ER-negative (OR = 1.16, P = 2.5 × 10(-7)) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.

Published
2012

48. Repetition-dependent adaptation and Prediction error signalling in Schizophrenia patients with auditory hallucinations: A Roving Mismatch Negativity Study

Author

Bose, Anushree, primary, Nayok, Swarna Buddha, additional, Pathak, Harsh, additional, Bagali, Kiran Basawaraj, additional, Chhabra, Harleen, additional, Suhas, Satish, additional, Shivakumar, Venkataram, additional, Sreeraj, Vanteemar S., additional, Narayanaswamy, Janardhanan C., additional, and Venkatasubramanian, Ganesan, additional

Published
2023
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50. Cyber Security in Power System: Challenges and Opportunities

Author

Mohit Kumar Maheshwari, Anurag Kumar Gupta, Pathak, Harsh Kumar, Khan, Hera, and Maurya, Arun Kumar

Subjects
Cyber security, PLC, SCADA, PHP device
Abstract

Modern power grids are not isolated from the outside world – disturbance on any system or in any component can cause instability or even blackout in the case of a power grid [ because all components of the control system of the power grid are not isolated is lords, they all are interconnected]. Cyber-attacks on the power grid could result in significant economic losses. In the present scenario, in Russia -Ukraine war, Russia wanted to destroy Ukraine's power grid system to break its energy supply and make the war easier for them. This power describes the power grid, Cyber security, Architecture of the power grid, Details about the Indian power grid present era of digital technologies, Requirements from cyber security for a power grid, and Type of cyber-attacks that could occur in our security scheme. Here we present a PV cell-based power grid model also to give you a clear view of the power grid. The short form we use in this paper: -PHP device (Hypertext processor), ASP (Active sensor page), OT system (Operational Technologies system), IT system (Information Technology System), PX data (Plotty Express), AMR system (Automated Meter Reading system), REMC (Renewable Energy Management Center), SCADA (Supervisory Control and Data Acquisition)., {"references":["1.\tMaurya, A. K., Rai, A. K., & Ahuja, H. (2022). Performance Analysis of a 40kWp Grid Connected Solar PV System in Northern India. Journal of Research and Advancement in Electrical Engineering, 4(3).","2.\tYe, J., Guo, L., Yang, B., Li, F., Du, L., Guan, L., & Song, W. (2020). Cyber–physical security of powertrain systems in modern electric vehicles: Vulnerabilities, challenges, and future visions. IEEE Journal of Emerging and Selected Topics in Power Electronics, 9(4), 4639-4657.","3.\tMaurya, A. K., Rai, A. K., & Ahuja, H. (2022, December). Comparative Analysis of Different MPPT Algorithms for Roof-Top Solar PV System. In 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) (pp. 1412-1417). IEEE.","4.\tBhattacharya, S., Saini, D., & Singh, N. Internet of Things (IoT) in smart cities: A review. In 2017 2nd International Conference for Convergence in Technology (I2CT) (pp. 386-391) IEEE, 2017.","5.\tMaurya, A. K., Tyagi, Y., Khan, H., Narang, D., & Ahuja, H. (2022, December). Components & Control Scheme used for Line of Sight Stabilization in Defence Applications. In 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) (pp. 1425-1431). IEEE.","6.\tCaragliu, A., Del Bo, C., & Nijkamp, P. (2009). Smart cities in Europe. Research Memoranda Series 0048 (VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics). J. Urban Technol, 18.","7.\tMaurya, A. K., Khan, H., Rai, A. K., & Ahuja, H. (2022, December). Load Frequency Control by using Different Controllers in Multi-Area Power System Networks. In 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) (pp. 1418-1424). IEEE.","8.\tTschorsch, F., & Scheuermann, B. (2013). An algorithm for privacy-preserving distributed user statistics. Computer Networks, 57(14), 2775-2787.","9.\tMaurya, A. K., & Khan, H. (2022). Converters' Topologies & Experimental Characteristics of Roof-top Solar PV System: A Comparative Analysis. Advancement and Research in Instrumentation Engineering, 5(3).","10.\tGubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future generation computer systems, 29(7), 1645-1660."]}

Published
2023
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