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  • Saving the Bandwidth of IPv6 Networks Using the Fields of the Packet Header
  • Abstract IPv6 protocol is the future of IP networks due to its large IP address capacity. One of the key consequences of this large capacity is that the IP protocol header has enlarged from 20-byte in IPv4 to 40-byte in IPv6. This will consume a considerable share of the bandwidth (BW) for VoIP applications, which produce small packets in tens of bytes only. To handle this issue, we have introduced an efficient technique to use the superfluous fields in the VoIP packet header, including the IPv6 header, to hold the voice data of the packet. This introduced technique is called the…
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  • Early Detection of Alzheimer’s Disease Using Graph Signal Processing and Deep Learning
  • Abstract Many methods have been proposed in the literature for diagnosis of Alzheimer's disease (AD) in the early stages, among which the graph-based methods have been more popular, because of their capability to utilize the relational information among different brain regions. Here, we design a novel graph signal processing based integrated AD detection model using multimodal deep learning that simultaneously utilizes both the static and the dynamic brain connectivity based features extracted from resting-state fMRI (rs-fMRI) data to detect AD in the early stages. First, our earlier proposed state-space model (SSM) based graph connectivity dynamics characterization method is used to design…
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  • Bcvop2p: Decentralized Blockchain-Based Authentication Scheme for Secure Voice Communication
  • Abstract Peer-to-peer VoIP applications are exposed to threats in the Internet environment as they carry out conversations over the Internet, which is an electronic communication line, and its security has always been largely a matter of concern. Authentication of the caller is the first line of defense among the security principles and is an important principle to provide security in VoIP application. Authentication methods in VoIP applications are usually based on trusted third parties or through centralized architecture. This situation creates problems in terms of single point of failure and privacy in call security over IP based communications. However, blockchain technology…
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  • GDPR Compliance IoT Authentication Model for Smart Home Environment
  • Abstract The Internet of things (IoT) became quickly one of the most popular and most discussed topics in research. Studies paid attention to the Internet stuff, primarily to new products that aim to achieve greater efficiency and simplicity in life. IoT may cover several fields of the smart environment. Because of the data exposure that occurs when data is transferred via various channels, data protection issues have become a major problem as the company continues to expand. When user privacy and property are taken into consideration, the situation may become much worse. As a result, the authentication process for communicating entities…
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  • A Learning-Based Fault Localization Approach Using Subset of Likely and Dynamic Invariants
  • Abstract Fault localization is one of the main tasks of software debugging. Developers spend a lot of time, cost, and effort to locate the faults correctly manually. For reducing this effort, many automatic fault localization techniques have been proposed, which inputs test suites and outputs a sorted list of faulty entities of the program. For further enhancement in this area, we developed a system called SILearning, which is based on invariant analysis. It learns from some existing fixed bugs to locate faulty methods in the program. It combines machine-learned ranking, program invariant differences, and spectrum-based fault localization (SBFL). Using the execution…
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  • Detection and Avoidance of Clone Attack in IoT Based Smart Health Application
  • Abstract The deployment of wireless sensors in the hostile environment makes them susceptible to malicious attacks. One of the most harmful attacks is the clone attack in which a malicious node illegitimately claims the identity of a genuine node in the network and eventually tries to capture the entire network. This attack is also termed as node replication attack. The mobile nature of wireless sensor network (WSN) in smart health environment increases the vulnerability of node replication attack. Since the data involved in smart health system are highly sensitive data, preserving the system from the attack by malicious nodes is a…
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  • Optimal Path Planning for Intelligent UAVs Using Graph Convolution Networks
  • Abstract Unmanned Aerial Vehicles (UAVs) are in use for surveillance services in the geographic areas, that are very hard and sometimes not reachable by humans. Nowadays, UAVs are being used as substitutions to manned operations in various applications. The intensive utilization of autonomous UAVs has given rise to many new challenges. One of the vital problems that arise while deploying UAVs in surveillance applications is the Coverage Path Planning(CPP) problem. Given a geographic area, the problem is to find an optimal path/tour for the UAV such that it covers the entire area of interest with minimal tour length. A graph can…
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  • An Enhanced Routing and Lifetime Performance for Industrial Wireless Sensor Networks
  • Abstract Industrial Wireless Sensor Networks (IWSNs), especially energy resources, are scarce. Since sensor nodes are usually very dense, and the data sampled by the sensor nodes have high redundancy, data aggregation saves energy, reduces the number of transmissions, and eliminates redundancy. Many applications can be used in IIWSNs, and a new technique is introduced to detect multiple sensors embedded in different sensor nodes. Packets created by different applications have different properties. Sensors are resource-constrained devices because it is necessary to find effective reaction analysis methods and transfer sensed data to base stations. Since sensors are resource-constrained devices, efficient topologies require data…
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  • Classification Similarity Network Model for Image Fusion Using Resnet50 and GoogLeNet
  • Abstract The current trend in Image Fusion (IF) algorithms concentrate on the fusion process alone. However, pay less attention to critical issues such as the similarity between the two input images, features that participate in the Image Fusion. This paper addresses these two issues by deliberately attempting a new Image Fusion framework with Convolutional Neural Network (CNN). CNN has features like pre-training and similarity score, but functionalities are limited. A CNN model with classification prediction and similarity estimation are introduced as Classification Similarity Networks (CSN) to address these issues. ResNet50 and GoogLeNet are modified as the classification branches of CSN v1,…
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  • Analysis of Software Success Through Structural Equation Modeling
  • Abstract Determining factors influencing the success of software projects has been the emphasis of extensive research for more than 40 years. However, the majority of research in this domain has focused on developed countries, with little attention paid to underdeveloped and developing countries. The primary objective of this article was to assess the effect of critical elements on the success of software projects in underdeveloped countries (like Pakistan), because enterprise environmental factors and staff working habits, as well as their experience and expertise level, all have an effect on a project's success. For this purpose, data were collected from 339 senior…
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