Abstract: Plant viruses can cause loss of yield and quality in a
lot of important crops. Symptoms of pathogens are variable
depending on the cultivars and virus strain. Selection of resistant
potato varieties would reduce the risk of virus transmission and
significant economic impact. Other way to avoid reduced harvest
yields is regular potato seed production sampling and testing for viral
infection. The aim of this study was to determine the occurrence and
distribution of viral diseases according potato cultivars for further
selection of virus-free material in Georgia. During the summer 2015-
2016, 5 potato cultivars (Sante, Laura, Jelly, Red Sonia, Anushka) at
5 different farms located in Akhalkalaki were tested for 6 different
potato viruses: Potato virus A (PVA), Potato virus M (PVM), Potato
virus S (PVS), Potato virus X (PVX), Potato virus Y (PVY) and
potato leaf roll virus (PLRV). A serological method, Double
Antibody Sandwich-Enzyme linked Immunosorbent Assay (DASELISA)
was used at the laboratory to analyze the results. The result
showed that PVY (21.4%) and PLRV (19.7%) virus presence in
collected samples was relatively high compared to others. Researched
potato cultivars except Jelly and Laura were infected by PVY with
different concentrations. PLRV was found only in three potato
cultivars (Sante, Jelly, Red Sonia) and PVM virus (3.12%) was
characterized with low prevalence. PVX, PVA and PVS virus
infection was not reported. It would be noted that 7.9% of samples
were containing PVY/PLRV mix infection. Based on the results it
can be concluded that PVY and PLRV infections are dominant in all
research cultivars. Therefore significant yield losses are expected.
Systematic, long-term control of potato viral infection, especially
seed-potatoes, must be regarded as the most important factor to
increase seed productivity.
Abstract: This paper presents a real time video surveillance system which is capable of tracking multiple real time objects using Polar Vector Median (PVM) and Block Coding Modes (BCM) with Global Motion Compensation (GMC). This strategy works in the packed area and furthermore utilizes the movement vectors and BCM from the compressed bit stream to perform real time object tracking. We propose to do this in view of the neighboring Motion Vectors (MVs) using a method called PVM. Since GM adds to the object’s native motion, for accurate tracking, it is important to remove GM from the MV field prior to further processing. The proposed method is tested on a number of standard sequences and the results show its advantages over some of the current modern methods.
Abstract: This paper deals with dynamic load balancing using PVM. In distributed environment Load Balancing and Heterogeneity are very critical issues and needed to drill down in order to achieve the optimal results and efficiency. Various techniques are being used in order to distribute the load dynamically among different nodes and to deal with heterogeneity. These techniques are using different approaches where Process Migration is basic concept with different optimal flavors. But Process Migration is not an easy job, it impose lot of burden and processing effort in order to track each process in nodes. We will propose a dynamic load balancing technique in which application will intelligently balance the load among different nodes, resulting in efficient use of system and have no overheads of process migration. It would also provide a simple solution to problem of load balancing in heterogeneous environment.