Securing Mobile Ad Hoc Networks Against Packet Dropping Attack

Need of infrastructure less, self operating, self configuring, communication networks have resulted in the formation of mobile ad hoc networks (MANET). MANET has proved very useful over traditional networks in disastrous conditions. In MANET all mobile devices work cooperatively for route discovery and data transmission. Due to its broadcast nature of transmission, and cooperative model of working, routing the traffic is a tedious task in MANET. Routing protocols are constantly targeted by attackers to cause damage to network. Routing protocols in MANET needs to be robust against various security threats. Ad hoc on-demand distance vector routing (AODV) protocol is widely used and studied in the area of mobile ad hoc networks. In this work, we present a secure AODV protocol to mitigate Black Hole Attack. In black hole attack a node maliciously diverts the data to route through it, and then drops the data packets, which results in lower packet delivery ratio. For this we have introduced a decision module in routing algorithm, which scans the RREP messages coming from a node before forwarding them towards the sender. Decision module has been build to exploit the black hole attack model. We check for the freshness and the path length mentioned in the reply message. Depending upon these values we decide whether to forward this reply or not. Thus eliminating the false replies. We simulated this proposed scheme to measure its effectiveness using NS-3. The results shows that our proposed algorithm shows better performance in terms of higher packet delivery ratio

Transition of Urban Neighbourhoods: Case of Nagpur, India

Change is inevitable, but how this change affects the user, decides its success. Neighbourhoods are the heart of a city and transition in a neighbourhood reflects the city’s transition. This study seeks to: 1) Understand the transition of the city Nagpur, India. It shows the transition that the city underwent using various maps as evidence. The exploration of the transition from the past to the present helped in understanding the morphology of the place. 2) Investigate six neighbourhoods from different parts of the city established at different times. Therefore, the neighbourhoods are selected based on their existence in a certain time frame. 3) Explore the residents’ satisfaction by mapping the amenities and their opinion about the neighbourhood. The results show how the transition of a city takes place with changes in the administration and the needs of the people. The study provides a methodology for investigating the transition of neighbourhoods over a given period to the present. It also functions as a guide on factors that affect the transition of a neighbourhood. The socio-spatial exploration will guide the stakeholder through decision-making in urban planning

Berkeley wavelet transform and improved YOLOv7-based classification technique for brain tumor severity prediction

Abnormality in brain tissues is a life-threatening illness in humans Un-bias to gender and age if it is unrecognized and untreated within time, will lead to severe complications and extreme conditions. The brain tumor is mainly influenced by a variety of unpredicted and unavoidable reasons. Its evaluation, spread pattern, and identification involves complex assignment. Its early grading and the proper classification ensure effective treatment. The proposed work attempts to extract and classify the tumor region using an automatic classification system for magnetic resonance imaging (MRI) brain tumors. A deep learning convolutional neural network-based architecture YOLO is employed to classify and detect the tumor from brain MR images. The proposed method resulted in superior segmentation, and classification performance in terms of subjective visualization and objective metrics as compared to state of art approaches. The proposed YOLO-based method collectively achieved 98.89% classification accuracy on the BRAINIX and Kaggle datasets

Neighbourhood Satisfaction andDensity Perception in Indian Cities of Bhopal and Nagpur

Density is an important urban form component. It is a tool that has been used for guiding the way cities are planned for living. Indian cities have been following high-density living, but some researchers showcase that high-density has negative effects. An investigation is necessary to verify the crowding effect and NH sustainability. The paper aims to find if residents are satisfied with the high-density living in the Indian cities of Bhopal and Nagpur. The study identifies context-specific NH satisfaction indicators using Analytical Hierarchy Process (AHP). Based on indicators, data is collected from differing density neighbourhoods. It uses Descriptive as well as Inferential analysis to arrive at results.Further, sensitivity analysis is made using Aggregated Index (AI). Descriptive analysis found a trend of density variation as per each indicator. Inferential statistics (MANOVA) confirms that public perception about density mostly differs in NHs of varying density. The results show that high density proves to be sustainable for variables like NH quality, Community wellbeing and Social equity.The study discusses certain NH interventions that can be useful in deriving future NH design guidelines and framing housing policies in India. Neighbourhood (NH) satisfaction assessment can comment upon the sustainability in a NH. The method can be a starting point to test the sustainability NHs for Indian citie

EXPLOITATION OF HETEROSIS FOR BIOETHANOL PRODUCTION IN SWEET SORGHUM (SORGHUM BICOLOR L. MOENCH.) HYBRIDS

A study was conducted in sweet sorghum to estimate the magnitude of heterosis for bio-ethanol and biomass yield, thirty F1 hybrids derived from five Lines x Six testers cross combinations were evaluated in kharif 2012 along with their parents and check (CSH 22 SS) for heterosis to identify promising hybrids of sweet sorghum for bioethanol characters at three different locations viz: Allahabad (E1), Solapur (E2) and Hyderabad (E3). Heterosis over mid parent, better parent and standard check were studied for bio-ethanol and biomass yield traits. Hybrid NSS 1016 A x UK 81 had shown (354.10% and 282.52%), (507.94% and 365.94%), (306.81% and 214.79%) highest heterobeltiosis and economic heterosis in E1, E2 and E3 respectively. Whereas, for biomass yield trait, the hybrid NSS 8 A x SSV 84 had shown (251.14% and 186.40%), ICSA 675 X UK 81 (285.90% and 244.82% ) and PMS71A X SSV 84 (193.80% and 137.56% ) had shown highest heterobeltiosis and economic heterosis in environment E1, E2 and E3 respectively. These two hybrids were found to be promising hybrids for further breeding programme as they exhibited significant positive heterobeltiosis and economic heterosis for bio-ethanol and biomass yield related traits. Hence, it can be concluded that heterosis would be more reliable in identification and isolation of superior hybrids

Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction Using Biologically Inspired BWT and SVM

The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated Berkeley wavelet transformation (BWT) based brain tumor segmentation. Furthermore, to improve the accuracy and quality rate of the support vector machine (SVM) based classifier, relevant features are extracted from each segmented tissue. The experimental results of proposed technique have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 96.51% accuracy, 94.2% specificity, and 97.72% sensitivity, demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 0.82 dice similarity index coefficient, which indicates better overlap between the automated (machines) extracted tumor region with manually extracted tumor region by radiologists. The simulation results prove the significance in terms of quality parameters and accuracy in comparison to state-of-the-art techniques

GUI Database – A Review

This paper will explain the concept of creating a Graphical User Interface for Relational Database Management Systems. This is a general-level GUI, which can be connected to the database system i.e SQL server. As a result, the database manipulation can be performed using single interface. Moreover, the queries can be executed very easily, since the user needs not  to  type  any  queries,  but  can  simply select the appropriate options according to their requirements. Thus, this software can be used by a person with no knowledge of SQL. This software is developed using .net as front end and SQL Server as backend. This paper provide only the operations most commonly required, thereby reducing complexity. Code optimization is the refining process in database administration and it helps to bring down speed of execution. Some object-oriented languages allows to express queries explicitly in the code, which are optimized using the query optimization techniques from the database domai

Supernumerary Teeth in Primary Dentition and Early Intervention: A Series of Case Reports

Supernumerary teeth are considered as one of the most significant dental anomalies during the primary and early mixed dentition stages. They are of great concern to the dentists and parents because of the eruption, occlusal, and esthetic problems they can cause. Supernumerary teeth occur more frequently in the permanent dentition but rarely in primary dentition. Mesiodens is the most common type of supernumerary teeth but rarely seen in lower arch. Early recognition and diagnosis of supernumerary teeth is important to prevent further complications in permanent dentition. Four cases of supernumerary teeth with mesiodens in upper and lower arch in primary dentition and their management have been discussed

Development of Sorghum Genotypes for Improved Yield and Resistance to Grain Mold Using Population Breeding Approach

The infection caused by grain mold in rainy season grown sorghum deteriorates the physical and chemical quality of the grain, which causes a reduction in grain size, blackening, and making them unfit for human consumption. Therefore, the breeding for grain mold resistance has become a necessity. Pedigree breeding has been widely used across the globe to tackle the problem of grain mold. In the present study, a population breeding approach was employed to develop genotypes resistant to grain mold. The complex genotype × environment interactions (GEIs) make the task of identifying stable grain mold-resistant lines with good grain yield (GY) challenging. In this study, the performance of the 33 population breeding derivatives selected from the four-location evaluation of 150 genotypes in 2017 was in turn evaluated over four locations during the rainy season of 2018. The Genotype plus genotype-by-environment interaction (GGE) biplot analysis was used to analyze a significant GEI observed for GY, grain mold resistance, and all other associated traits. For GY, the location explained a higher proportion of variation (51.7%) while genotype (G) × location (L) contributed to 21.9% and the genotype contributed to 11.2% of the total variation. For grain mold resistance, G × L contributed to a higher proportion of variation (30.7%). A graphical biplot approach helped in identifying promising genotypes for GY and grain mold resistance. Among the test locations, Dharwad was an ideal location for both GY and grain mold resistance. The test locations were partitioned into three clusters for GY and two clusters for grain mold resistance through a “which-won-where” study. Best genotypes in each of these clusters were selected. The breeding for a specific cluster is suggested. Genotype-bytrait biplots indicated that GY is influenced by flowering time, 100-grain weight (HGW), and plant height (PH), whereas grain mold resistance is influenced by glume coverage and PH. Because GY and grain mold score were independent of each other, there is a scope to improve both yield and resistance together