The sustainability of the hydrological and ecological ecosystems of any region requires continuous monitoring of the water bodies. Recent advancements in satellite-based remote optical sensors, big data analysis and cloud computing have given new dimensions to the field of water body studies including their detection as well as analysis. The present study extends the existing methods to assess the contemporary surface water detection and monitoring techniques via remote sensing. The proposed technique implies an improved hybrid approach for the purpose along with the calculation of the boundary areas. The study has been carried out on the Manchar Lake, the largest natural freshwater lake in Pakistan as well as in South Asia. The proposed hybrid water index along with the different existing water body detection indices and spectral bands have been worked out on the satellite images retrieved from the Google Earth Engine to detect and analyze the area/flow changes in the water body. Based on the 7 years of data, the proposed algorithm calculates the water body area more precisely. With limited availability of metadata about the study area, the results have been validated both qualitatively through national-met data and statistically. These results aid to better preserve and improve the quality of the water resource.

In this paper we address the basic limitation of Siammask -the state of the art single object tracking and segmentation algorithm. SiamMask requires semi-supervision in that it needs a bounding box to be drawn manually around the object that has to be tracked. This is however not always possible or feasible, and slows down the pipeline even in the best case. We overcome this limitation by using state-of-the-art object detection algorithms: Detectron and YOLO to automatically detect the object and then track using Siammask. We note that YOLO gives better and more meaningful detection of objects in the scene. However, Detectron gives a higher detection speed than YOLO, making the overall detection and tracking process faster.

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With the technological advancements in the field of networking and information technology in general, organizations are enjoying the technological blessings and simultaneously under perpetual threats that are present in the form of attacks, designed especially to disable organizations and their infrastructure, as the gravest cyber threats in recent times. Compromised computers or BOTNETs are unarguably the most severe threat to the security of internet community. Organizations are doing their best to curb BOTNETs in every possible way, spending huge amount of their budget every year for available hardware and software solutions. This paper presents a survey on the security issues raised by the BOTNETs, their future; how they are evolving and how they could be circumvent to secure the most valuable resource of the organizations which is data. The compromised systems may be treated like viruses in the network which are capable of performing substantial loss to the organization including theft of confidential information. This paper highlights the parameters that should be considered by the organizations or Network administrators to find out the anomalies that may point to the presence of BOTNET in the network. The early detection may reduce the impact of damage by taking timely actions against compromised systems.

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