http://localhost:80/xmlui/handle/123456789/8561 Sun, 05 Apr 2026 14:25:07 GMT 2026-04-05T14:25:07Z http://localhost:80/xmlui/handle/123456789/7415 Title: Using Blockchain In Intermittently Connected Network Environments Authors: Basu, Souvik; Chowdhury, Soumyadip; Bit, Sipra Das Abstract: This chapter explores the possible integration of blockchain technology with intermittently connected networks, towards exploiting the utility and availability ot blockchain technology in intermittently connected network environments. It also identifies the challenges of such integration and possible solutions using off-the-shelf technology. Finally, thc chapter identifies open research areas in the domain ol using blockchain in intermittently connected network environments that would foster new research avenues in both industry and academia. Fri, 01 Jan 2021 00:00:00 GMT http://localhost:80/xmlui/handle/123456789/7415 2021-01-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/4850 Title: Reliable Post Disaster Services over Smartphone Based DTN : An End-to-End Framework Authors: Basu, Souvik; Roy, Siuli; Das Bit, Sipra Tue, 01 Jan 2019 00:00:00 GMT http://localhost:80/xmlui/handle/123456789/4850 2019-01-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/4849 Title: A Graph-Based Approach for Finding the Dengue Infection Pathways in Humans Using Protein–Protein Interactions Authors: Dey, Lopamudra; Mukhopadhyay, Anirban Abstract: Abstract Dengue virus (DENV) is one of the deadly arboviruses, which is primarily transmitted by Aedes aegypti, and causes dengue infection to the humans. According to WHO, every year around 390 million humans are affected by DENV, of which around 50 million deaths are reported. Knowledge of the various diseases caused by the DENV would greatly encourage to understand the infection mechanism and help to design new antiviral drug discovery. We propose a quasi-clique and quasi-biclique algorithm to classify infection gateway proteins of the human body and possible pathways of DENV leading to various diseases. For this, we have examined three networks, dengue-human protein–protein interaction network, human protein interaction network, and human proteins-disease association network. The prediction result states that DENV may lead to various diseases in the human body, including cancer, asthma, ulcerative colitis, multiple sclerosis, premature birth, and so on. Some of the results have recently been validated experimentally. This study may endow with potential targets for more effective anti-dengue remedial contribution. Fri, 01 May 2020 00:00:00 GMT http://localhost:80/xmlui/handle/123456789/4849 2020-05-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/4846 Title: Post-disaster map builder: Crowdsensed digital pedestrian map construction of the disaster affected areas through smartphone based DTN Authors: Bhattacharjee, Suman; Roy, Siuli; Bit, Sipra Das Abstract: Constructing digital pedestrian maps of the disaster affected areas is a vital requirement for post-disaster relief operation. Digital maps help disaster management agencies in decision making and mobilizing the manpower and resources in the disaster affected areas. However, due to the intermittent connectivity after large scale natural disasters, the existing web based digital mapping systems remain inaccessible in the disaster affected areas. Moreover, the road networks in such areas change drastically because of disaster (for instance waterlogging due to flood, structural collapse or incidental destructions like a landslide). Hence, existing analog (paper based) route maps of such areas become obsolete. In this work, we propose Post-Disaster Map Builder, a crowdsenced digital pedestrian map construction system over smartphone based DTN. The proposed system generates digital pedestrian maps of the disaster affected areas using battery powered mobile handheld devices. Here, trajectory traces collected by the volunteers are periodically shared among the other volunteers of the disaster affected area through smartphone based DTN. Pedestrian maps of the disaster affected areas are gradually constructed in the mobile handheld devices of the volunteers by combining the collected traces over time. The proposed system is thoroughly evaluated through simulation and testbed implementation. The results reveal that our proposed system can automatically construct digital pedestrian maps of disaster affected areas with high accuracy at the cost of marginal delay. Tue, 15 Jan 2019 00:00:00 GMT http://localhost:80/xmlui/handle/123456789/4846 2019-01-15T00:00:00Z