Conference Papers (July 2021)
School of Applied Sciences
Sahoo, S., Devi, M., and Das, S.K. (2021), Study of adsorption of Methylene blue in aqueous solution onto activated carbon prepared using low-cost domestic oven-based heating system, International Virtual Conference on Recent Trends in Materials Science (IVCRTMS 2020) 16 November 2020,IOP Conference Series: Materials Science and Engineering,1124, DOI:10.1088/1757-899X/1124/1/012001
Abstract: In this work activated carbon was prepared from teak wood charcoal using very lowcost oven based heating system. Firstly, charcoals were grinded with a domestic grinder and then activated with 25% CaCl2 solution and then heated with 250C for different times. And then experiment was carried out through 2.5×10-5 methylene blue aqueous solution by taking activated Charcoal into it and kept one hour for adsorption. Adsorption capacity was estimated by taking the different amount of activated carbon. The result indicates that prepared activated carbon be effectively used for water purification application through adsorption of the dye.
School of Computer Engineering
1. Panigrahi, S., Barik, R.K., Mukherjee, P., Pradhan, C., Patro, R. and Patra, S.S., Optimization Policy for Different Arrival Modes in IoT Assisted Geospatial Fog Computing Environment, In: IEEE International Conference on Emerging Technology (INCET), Belagavi, India, pages 269-282, 2021.
For improving the run time performance of geospatial fog applications, two technical issues must be addressed. The first one is the load balancing of requests among the available resources and second is the provisioning of the resources which optimally adjusts the resources to adapt the time-varying workload. In this paper, we propose a fog framework to process geospatial applications in automation for both kind of tasks such as storage and computational tasks. Various performance measures have also been illustrated and the optimal cost policy is depicted comprising of numerical results.
2. Datta, S., Roy, M., and Kar P., Application of IoT in Smart Epidemic Management( in context of Covid-19), In International Conference on High Performance Switching and Routing” ( IEEE HPSR) , IEEE Flagship Conference, 7th -10th June 2021, Paris, France.
Covid-19 also, data shows that its contagious nature is increasing along with its various mutant strains. There are already many existing epidemic models, to predict and track the spread of the disease, it is evident from the difference in the rates of infection and fatalities in different countries, that a uniform set of parameters is not sufficient to accurately predict the curves. We have suggested some additional benchmarks that could be considered and at a higher granularity for more accurate predictions at more local levels. We also propose an IoT-based framework for the collection of such types of data.
3. Shi, J., Sheng, W., Kar P., Roy M., and Datta S., A Novel Framework for Predicting the Spread of Covid-19 by Contact Tracing through Smartphones, In 17th Int. Wireless Communications & Mobile Computing Conference, IWCMC 2021, 28th June-2nd July, 2021, Harbin, China.
Covid-19 is the most serious epidemic disease and it needs to be controlled ASAP. In this paper, we have triedto further increase the accuracy of the predictions, by combiningthree models that are widely used in this field: the mobilitymodel, the social network model, and the SEIR model. Initially,the mobility model could identify a person’s mobility patternson weekdays and weekends, and also between day and night.Then, by combining this data with the social network model, wecould classify people into various categories, with a more accurateprobability of a person being infected.
4. Chatterjee, P. S., A Systematic Survey for Detecting and Counteracting PUE Attacks in CWSNs, In: IEEE Global Conference for Advancement in Technology (GCAT), Bangalore, India, 2021.
Cognitive Wireless Sensor Networks (CWSN) uses the spectrum resources in an intelligent manner in comparison to a normal Wireless Sensor Network (WSN). The technique which enables CWSNs in this regard is known as Opportunistic Spectrum Sensing (OSS) for data transfer. The OSS process significantly reduces the collisions and the delays for data delivery in a network. This OSS process is vulnerable to several security threats. A Primary User Emulation (PUE) attack in CWSN is a sort of Denial of Service (DoS) attack wherein hostile Secondary Users (SU) strive to imitate Primary Users (PUs) in effort to expand their
5. Naik, M., Barik, L., Kandpal, M., Patra, S. S., Jena, S., and Barik, R. K., EVMAS: An Energy-aware Virtual Machine Allocation Scheme in Fog Centers, In 2021 2nd International Conference for Emerging Technology (INCET), IEEE, pages 1-6, 2021.
Due to the rapid growth of the Industrial IoT (IIoT), social media and digitization, and wireless communication technology in various sectors, data volume is increasing rapidly. Cloud computing is an emerging solution with fog computing assistance for handling and processing a huge volume of data. This paper proposes EVMAS, i.e., an energy-aware VM allocation scheme based on Lagrange’s Multiplier.
6. Barik, R. K., Patra, S. S., Patro, R., Mohanty, S. N., and Hamad, A. A., GeoBD2: Geospatial Big Data Deduplication Scheme in Fog Assisted Cloud Computing Environment. In 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom), IEEE, pages 35-41, 2021.
With the speedy expansion of Internet of Spatial Things, the enormous volume of geospatial big data is produced by the IoT devices. It gives rise to the new challenges for real time geospatial data processing and storing of reliable data in cloud system. The traditional geospatial cloud computing system is not efficient enough to process large volumetric of concurrent geospatial data. Consequently, fog assisted cloud computing environment has come into picture for achieving secure geospatial big data deduplication scheme. In this paper, the geo-deduplication structure to build an efficient geospatial bigdata deduplication scheme on fog assisted cloud computing framework.
7. Barik, R. K., Patra, S. S., Kumari, P., Mohanty, S. N., and Hamad, A. A., A New Energy Aware Task Consolidation Scheme for Geospatial Big Data Application in Mist Computing Environment. In 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom), IEEE, pages 48-52, IEEE, 2021.
The Internet of Spatial Things (IoST) are expanding rapidly for geospatial big data applications in today’s digital world. A large volume of geospatial data is produced between IoST and the mist assisted cloud environment. It employs the metaphor-less Rao-1 algorithm and studies the behaviour of the algorithm with earlier evolutionary algorithms. It also reveals better performance in terms of maximizing CPU utilization.
8. Al Ahmad, M., Patra, S. S., Bhattacharya, S., Rout, S., Mohanty, S. N., Choudhury, S., and Barik, R. K., Priority Based VM Allocation and Bandwidth Management in SDN and Fog Environment. In 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom), IEEE, pages 29-34, 2021.
Fog assisted cloud is a dominant field of computing where data centers are engaged in providing services to various applications having distinct resource needs and priorities. Congestion in the network causes performance degradation in the applications. Some mission-critical applications need to data transfer even during the congestion period. In Software Defined Networks (SDN) clouds, there is a possibility of reconfiguration of the network flows dynamically to avoid such congestions for critical applications. In this paper, a priority-based virtual machine (VM) placement algorithm is proposed which takes care of the hosts and the network configuration.
9. Dutta, A., Misra, C., Patra, S. S., Singh, K., and Bhattyacharyya, A., Performance Analysis of Millimetre Wave Antenna Arrays for 5G Cellular Applications. In Applications of Advanced Computing in Systems, Springer, Singapore, pages 117-124, 2021.
The new technologies under research and development in the current scenario of mobile broadband have been categorically focused on the next generation of spectrum specifications, ie 5G. The new generation has been targeting the use of spectrum of 28 GHz and above. The paper has been designed to discuss some of the technologies which can be used in order to layout the foundation for 5G standard. The paper discusses about the
concept of colossal MIMO which uses antenna arrays and large beam formation technology.
10. Harshvardhan, G. M., Gourisaria, M. K., Sahu A, Rautaray, S. S., and Pandey, M., Topic Modelling Twitterati Sentiments using Latent Dirichlet Allocation during Demonetization, In 2021 8th International Conference on Computing for Sustainable Global Development, INDIACom 2021, pages 811–815, 9441418, 2021. DOI :10.1109/INDIACom51348.2021.00145.
In this paper, we attempt to apply a topic modelling technique, namely Latent Dirichlet Allocation (LDA) on tweets to analyse and come up with pertinent topics with the most relevant words that describe the topics most aptly. The tweets contain the demonetization hashtag to help us understand sentiments of people about demonetization. Leveraging this sort of statistical topic modelling can be quite useful to researchers to correctly identify primary components of huge textual corpora for any kind of further analysis. We measure the inter-topic distances via multidimensional scaling and review words and topics through metrics such as saliency and relevance.
11. Parida, P.P., Gourisaria, M.K., Pandey, M., and Rautaray, S.S. Hybrid Movie Recommender System – A Proposed Model, In Third International Conference Futuristic Trends in Networks and Computing Technologies (FTNCT-2020), Communications in Computer and Information Science, 1395 CCIS, pages 475–485, 2021. DOI :https://doi.org/10.1007/978-981-16-1480-4_43
Traditional Recommender System approach like content and collaborative filtering show some demerits like the data sparsity, cold start, scalability, etc. Thus to tackle these demerits, the paper focuses on a hybrid approach that integrates the approaches of content-based and collaborative, employed with a singular value prediction algorithm. In addition , a systematic study and a proposed model is presented along with the machine learning algorithm. The study shows that the cosine similarity indexing, ranking, and the SVD algorithm can achieve better research objectives. Promising validation results are produced by the experiments done over the public database.
12. Mishra, S., Pandey, M., Rautaray, S.S., and Gourisaria, M.K., A Proposal for Early Detection of Heart Disease Using a Classification Model, In Third International Conference Futuristic Trends in Networks and Computing Technologies (FTNCT-2020), Communications in Computer and Information Science, 1395 CCIS, pages 360–367, 2021. DOI:https://doi.org/10.1007/978-981-16-1480-4_32.
This paper focuses on several features of people and eventually predicts the patient’s health status mentioning preventive measures to avoid any risk of cardiovascular disease. With the help of our proposed model, data scientists predict the health condition of the person. The output is a multiclass classification which will give values ranging between 0 to 4 with 0 indicating the absence of any heart problem, 1 indicates slight abnormal behaviour in the heart’s functioning, and so on with class 4 indicating a critical state. The results of this paper shows that Random forest algorithm gives the highest accuracy of 89.13%.
13. Behera, A.P., Gaurisaria, M.K., Rautaray, S.S., and Pandey, M., Predicting future call volume using ARIMA models, In the Proceedings – 5th International Conference on Intelligent Computing and Control Systems, ICICCS 2021, pages 1351–1354, 9432314, 2021. DOI: 10.1109/ICICCS51141.2021.9432314.
This work focus on Time-series Analysis using ARIMA models in the financial sector. This work forecast the future call activity by using a calculated method and predict some future condition and an event. This paper shows the feature of financial time series so-called group variances. Therefore, using the ARIMA model forecasting the number of calls received in a day or a week means the future call so that they engage that number of employees to handle the queries of customers with less waiting time. A prediction of the future is not only helpful but provides precise inventory and profit.
School of Electrical Engineering
1. Chowdary, K.V.S.SR., Kumar, K., and Kumar, R.R., Impact of onboard DC-DC Converter for Dynamic Wireless Charging of Electric Vehicle, 1st International Conference on Power Electronics and Energy (ICPEE), Bhubaneswar, India, pages 1–5, 2021. doi: 10.1109/ICPEE50452.2021.9358799.
Dynamic wireless charging (DWC) system is a promising contender for the implementation of charging infrastructure and uphold the consumer prejudices. In this paper, the main emphasis is on the impact of onboard DC-DC converter for the DWC application. The purpose of carrying out this work is to understand the footraces of load independent operation and zero phase angle operation. These characteristics are very much essential for the better, efficient, and safe design of the DWC system to charge the battery from the supply grid.
2. Jena, S., Naik, A. K., Neha, Panigrahi, C. K. and Sahu, P. K., Impact of Environmental Factors on The Performance of Solar PV Cells: An Experimental Study, 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON), Bhubaneswar, India, pages 1–5, 2021. DOI: 10.1109/ODICON50556.2021.9428999.
Nowadays the conventional generation system is not able fulfil the exponential growth of electricity demand and in the other hand, the conventional resources are diminishing at a faster rate. To meet the future energy, demand the use of renewable energy sources has increasing considerably. Among all sources, the use of solar energy is increasing rapidly due to its availability and advancement in Photovoltaic technology. But the main drawback of the photovoltaic system is its low efficiency. In this paper effect of natural factors on the output of solar panel and how they co-related to each other is analysed by an experimental work.
3. Patel, R., Samal, P., Panda, A. K., and Guerrero, J. M., Implementation of Bio-inspired flower pollination algorithm in distribution system harmonic mitigation scheme, 1st International Conference on Power Electronics and Energy (ICPEE), Bhubaneswar, India, pages 1-6, 2021. DOI: 10.1109/ICPEE50452.2021.9358509.
The conventional p-q (Instantaneous Active and Reactive Power) control strategy is chosen here with recently developed Flower Pollination Algorithm (FPA). To maintain the DC link voltage constant the Proportional-Integral controller is being employed in the DC side of active power filter which is used to minimize the error between the reference voltage (Vdc*) and actual value (Vdc). The FPA is used here to get the best proportional constant and integral constant value of PI controller. Furthermore, Particle Swarm Optimization (PSO) and conventional Zeigler Nichols method based APF with p-q control strategy have been evaluated to give a comparison.
4. Bonela, R., Ghatak, S. R., Hayat, N., Swain, S.C., and Mohapatra, A., Techno-Economic planning framework of three phase unbalanced distribution system using multiple DG and Capacitor, 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON), Bhubaneswar, India, pages 1-6, 2021. DOI: 10.1109/ODICON50556.2021.9428933.
Distribution systems across many parts of the globe have the problem of high system loss, high voltage unbalance and poor maintenance of system voltage profile. The major aim in allocating Distributed Generation (DG) and Shunt Capacitor is to reduce line loss, decrease voltage unbalance and to maintain the voltage profile in the practical unbalanced distribution system. In this paper DG and Shunt Capacitor are injected at identified weak bus and performance in terms of technical and economic parameters are analyzed. To validate the proposed methodology IEEE 13 bus unbalanced network is chosen.
5. Ray, M., Samal, P., and Panigrahi, C. K., Comparative analysis of algorithm based automatic efficacy enhancement of lighting control system, 1st International Conference on Power Electronics and Energy (ICPEE), Bhubaneswar, India, pages 1-5, 2021. DOI: 10.1109/ICPEE50452.2021.9358510.
Lighting establishes a remarkable part in load management. Different lighting control systems helps to enhance energy saving by using efficient lamps with more luminous efficacy which depends on different factors like occupancy, human satisfaction level, natural sunlight etc. Different sensors and different intelligent control techniques are there which have important contribution in lighting control. The technologies and techniques differ in their single objective or multi objective parameters, the models used, simulating software and control algorithm. This paper represents different control system models, associated technologies, their savings, the factors affecting their performance and the daylight effect.
School of Mechanical Engineering
1. Gouda, D., Panda, A., Nanda, B. K., Kumar, R., Sahoo, A. K., and Routara, B. C., Recently evaluated Electrical Discharge Machining (EDM) process performances: a research perspective,Materials Today: Proceedings, 44 (1),pages 2087-2092, 2021.
Recently, cutting edge machining approaches are used extensively for answering multifarious issues in manufacturing sectors that consist of machining larger strength materials, manufacture of intricate shaped profiles, improve surface characteristics, and lower production time. In this scenario, the development of Electro Discharge Machining (EDM) is rapidly taking place. In addition, the concluding observations turn out with defined underlines and technological research gaps making this review article useful to related academic and scientific research community with proper identification of EDM process factors, advance work materials, material electrode tools and sustainable dielectric for achieving favorable outcomes as a frontier machining technology.
2. Dhal, A. K., Panda, A., Kumar, R., and Sahoo, A. K., Different machining environments impact analysis for Ti-6Al-4V alloy (Grade 5) turning process: A scoping review, Materials Today: Proceedings, 44 (1),pages 2342-2347, 2021.
The analysis for a new methodology for improving performance and the implications needs to be explored further in this advanced aerospace alloy steel. The application of this titanium alloy revealing a great perspective in the field of the aeronautical realm. With this backdrop, this scoping review work aims for the apples-to-apples comparison machining conditions, characterization techniques, and influence of main cutting input parameters on output efficiencies during the turning process. A state of art recent technologies, issues, challenges, and with this the machining of material is also illustrated along with the possible research future directions.
School of Management
1. Jha R.S. and Sahoo P.R., (2020), Influence of Big Data Capabilities in Knowledge Management—MSMEs, Advances in Intelligent Systems and Computing:5th International Conference on ICT for Sustainable Development, ICT4SD 2020, Goa, India, pp. 513-524.
In recent time innovation of open-source technologies, commodity hardware, cloud computing, data-driven application, visualization techniques have paved their way for revolutionary changes in business models and data technology space. This has resulted in creating the enormous opportunities for human creativity to produce novel insights. In the “Era of Information” where huge amount of complexity and varied of data being generated every day from multiple sources or point of sales making business requirements/decisions more composite and time intensive. In information dominated Era, Big data (emerging frontier) plays an instrumental role in offering, insight and prediction is at the heart of almost every scientific/business discipline. The discovery of insights and value from data is the central focus of the industry to create new products and services to meet the changing demands. In digital driven economy, Big Data capabilities and offering have been relentlessly empowering organizations knowledge management platforms to ease knowledge management practices including acquisition, creation, sharing storage and transfer to meet organizations near term and future goals and accelerate toward success path.
2. Singh, S and Kar, B.B., (2021) Navigating the Pandemic Crisis by a banking Industry-A Case Study of ICICI Bank, Case Presentation in International Summit on Management Case Studies- IIM Ranchi11th-13th June 2021, Ranchi, India.
The unprecedented lockdown and shutdown to contain the spread of Covid-19 pandemic posed a unique set of challenges for business continuity. Banking being notified as essential services, has to be up and operational to mobilize financial resources to fight the invisible enemy at large and fuel the $ 3.00 trillion Indian economy. Banking fraternity at large devised ways and means to continue the banking operation with modified rules and regulations to enable transactions. Banks managed to meet client’s demands through their exemplary service and innovative solutions within the ambit of regulatory guidelines. Being one of the largest private sector banks in India, ICICI bank holds up to 14.76 trillion INR consolidated asset as on 30th September 2020. It has a widespread network of 5,288 branches whereas the bank offers different banking services through its 15,158 ATMs across the nation. ICICI bank has been recognized by RBI as one amongst the three systemically important banks for the country.