High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination by considering the traffic segment status when choosing the next intersection. RTISAR presents a new formula for assessing segment status based on connectivity, density, load segment, and cumulative distance toward the destination. A verity period mechanism is proposed to denote the projected period when a network failure is likely to occur in a particular segment. This mechanism can be calculated for each collector packet to minimize the frequency of RTISAR execution and to control the generation of collector packets. As a result, this mechanism minimizes the communication overhead generated during the segment status computation process. Simulations are performed to evaluate RTISAR, and the results are compared with those of intersection-based connectivity aware routing and traffic flow oriented routing. The evaluation results provided evidence that RTISAR outperforms in terms of packet delivery ratio, packet delivery delay, and communication overhead.
Digital forensic is part of forensic science that implicitly covers crime related to computer and other digital devices. It‟s being for a while that academic studies are interested in digital forensics. The researchers aim to find out a discipline based on scientific structures that defines a model reflecting their observations. This paper suggests a model to improve the whole investigation process and obtaining an accurate and complete evidence and adopts securing the digital evidence by cryptography algorithms presenting a reliable evidence in a court of law. This paper presents the main and basic concepts of the frameworks and models used in digital forensics investigation.
Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio
... Show MoreToday with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned
is at an all-time high in the modern period, and the majority of the population uses the Internet for all types of communication. It is great to be able to improvise like this. As a result of this trend, hackers have become increasingly focused on attacking the system/network in numerous ways. When a hacker commits a digital crime, it is examined in a reactive manner, which aids in the identification of the perpetrators. However, in the modern period, it is not expected to wait for an attack to occur. The user anticipates being able to predict a cyberattack before it causes damage to the system. This can be accomplished with the assistance of the proactive forensic framework presented in this study. The proposed system combines
... Show MoreThe revolution of multimedia has been a driving force behind fast and secured data transmission techniques. The security of image information from unapproved access is imperative. Encryptions technique is used to transfer data, where each kind of data has its own special elements; thus various methods should to be used to conserve distributing the image. This paper produces image encryption improvements based on proposed an approach to generate efficient intelligent session (mask keys) based on investigates from the combination between robust feature for ECC algebra and construction level in Greedy Randomized Adaptive Search Procedure (GRASP) to produce durable symmetric session mask keys consist of ECC points. Symmetric behavior for ECC
... Show MoreCurrently voting process is paper based form, by using voting card or paper; thus the counting method is done manually, which exhausts a lot of time. Obsolete votes may be possibly occurring. This paper introduced a system in which voting and counting is done with the help of computer. The election process would be easier, it saves time, avoid errors while counting and obsolete votes are reduced. Electronic voting (E-voting) system is a voting system in which the election related data is stored and handled digitally, it would become the quickest, cheapest, and the most efficient way to administer election and count vote it is considered a means to further enhance and strengthen the democratic processes in modern information societies. Th
... Show MoreArabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio
... Show MoreA study has been performed to compare the beddings in which ductile iron pipes are buried. In water transmission systems, bends are usually used in the pipes. According to the prescribed layout, at these bends, unbalanced thrust forces are generated that must be confronted to prevent the separation of the bend from the pipe. The bed condition is a critical and important factor in providing the opposite force to the thrust forces in the restraint joint system. Due to the interaction between the native soil and the bedding layers in which the pipe is buried and the different characteristics between them. Also, the interaction with the pipe material makes it difficult to calculate the real forces opposite to the thrust forces and the way they
... Show MoreThe habitat type and food availability always influence the population size of many
organisms. Bird’s feeding pattern should be abstracted to complete avian community structure
data. The agronomy main research farm of Orissa University of Agriculture and Technology
is a well-managed multi-crop agro-ecosystem which provides a suitable ground for ecological
research. In a multi-crop farmland, the association of Barn Swallow Hirundo rustica Linnaeus,
1758, with the Indian mustard Brassica juncea (L.) Czernajew, 1859 crops have been
recorded for the first time while hovering only on this field. A flock of Barn swallows was
recorded in 32 field visits while flying continuously over the Indian mustard field after
flow
The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen
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