OBPF: Opportunistic Beaconless Packet Forwarding Strategy for Vehicular Ad Hoc Networks

[EN] In a vehicular ad hoc network, the communication links are unsteady due to the rapidly changing topology, high mobility and traffic density in the urban environment. Most of the existing geographical routing protocols rely on the continuous transmission of beacon messages to update the neighbors' presence, leading to network congestion. Source-based approaches have been proven to be inefficient in the inherently unstable network. To this end, we propose an opportunistic beaconless packet forwarding approach based on a modified handshake mechanism for the urban vehicular environment. The protocol acts differently between intersections and at the intersection to find the next forwarder node toward the destination. The modified handshake mechanism contains link quality, forward progress and directional greedy metrics to determine the best relay node in the network. After designing the protocol, we compared its performance with existing routing protocols. The simulation results show the superior performance of the proposed protocol in terms of packet delay and data delivery ratio in realistic wireless channel conditions.The authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for funding this research. The research is supported by Ministry of Education Malaysia (MOE) and conducted in collaboration with Research Management Center (RMC) at Universiti Teknologi Malaysia (UTM) under VOT NUMBER: QJ130000.2528.06H00.Qureshi, KN.; Abdullah, AH.; Lloret, J.; Altameem, A. (2016). OBPF: Opportunistic Beaconless Packet Forwarding Strategy for Vehicular Ad Hoc Networks. KSII Transactions on Internet and Information Systems. 10(5):2144-2165. https://doi.org/10.3837/tiis.2016.05.011S2144216510

Road-Aware Routing Strategies for Vehicular Ad Hoc Networks: Characteristics and Comparisons

[EN] Vehicular ad hoc networks (VANETs) are going to be an emerging multihop communication exploit among vehicles to deliver data packets. The special characteristics of vehicular network make the communication link between vehicles unreliable. To handle high mobility and environmental obstacles, most of geographical routing protocols do not consider stable links during packet transmission which lead to higher delay and packet dropping in network. In this paper, we propose road perception based geographical routing protocol named RPGR for VANET. The proposed routing protocol incorporates relative distance, direction, and midrange forwarder nodewith traffic density to forward the data toward destination in order to improve geographical forwarding between and at the intersections. Simulation results show that the proposed routing protocol performs better as compared to existing solutions.The research is supported by Ministry of Education Malaysia (MOE) and conducted in collaboration with Research Management Center (RMC) at Universiti Teknologi Malaysia (UTM) under VOT no. QJ130000.2528.06H00.Qureshi, KN.; Abdullah, AH.; Lloret, J.; Altameem, A. (2016). Road-Aware Routing Strategies for Vehicular Ad Hoc Networks: Characteristics and Comparisons. International Journal of Distributed Sensor Networks. 2016:1-19. https://doi.org/10.1155/2016/2617480S119201

Green Computing for Wireless Body Area Networks: Energy Efficient Link Aware Medical Data Dissemination Approach

Recent technological advancement- in wireless communication has invented Wireless Body Area Networks (WBANs), a cutting edge technology in healthcare applications. WBANs interconnect with intelligent and miniaturized biomedical sensor nodes placed on human body to un-attendant monitoring of physiological parameter of the patient. These sensors are equipped with limited resources in terms of computation, storage and battery power. The data communication in WBANs is a resource hungry process especially in terms of energy. One of the most significant challenges in this network is to design energy aware next-hop link selection framework. Towards this end, this paper presents a Green computing framework for WBANs focusing on Energy efficient Link aware approach (G-WEL). Firstly, a link efficiency oriented network model is presented considering beaconing information and network initialization process. Secondly, a path cost calculation model is derived focusing on energy aware link efficiency. A complete operational framework G-WEL is developed considering energy aware next hop link selection by utilizing the network and path cost model. The comparative performance evaluation attests the energy oriented benefit of the proposed framework as compared to the state-of-the-art techniques. It reveals a significant enhancement in body area networking in terms of various energy oriented metrics under medical environments

Breast Cancer Detection in Mammography Images Using Deep Convolutional Neural Networks and Fuzzy Ensemble Modeling Techniques

Breast cancer has evolved as the most lethal illness impacting women all over the globe. Breast cancer may be detected early, which reduces mortality and increases the chances of a full recovery. Researchers all around the world are working on breast cancer screening tools based on medical imaging. Deep learning approaches have piqued the attention of many in the medical imaging field due to their rapid growth. In this research, mammography pictures were utilized to detect breast cancer. We have used four mammography imaging datasets with a similar number of 1145 normal, benign, and malignant pictures using various deep CNN (Inception V4, ResNet-164, VGG-11, and DenseNet121) models as base classifiers. The proposed technique employs an ensemble approach in which the Gompertz function is used to build fuzzy rankings of the base classification techniques, and the decision scores of the base models are adaptively combined to construct final predictions. The proposed fuzzy ensemble techniques outperform each individual transfer learning methodology as well as multiple advanced ensemble strategies (Weighted Average, Sugeno Integral) with reference to prediction and accuracy. The suggested Inception V4 ensemble model with fuzzy rank based Gompertz function has a 99.32% accuracy rate. We believe that the suggested approach will be of tremendous value to healthcare practitioners in identifying breast cancer patients early on, perhaps leading to an immediate diagnosis

Clustered red blood cells splitting viaboundary analysis in microscopic thin blood smear digital images

Clustered Red Blood Cells are observed very frequently in the thin blood smear digital images. Separating clustered Red Blood Cells from the single Red Blood Cells and splitting of clustered Red Blood Cells into single Red Blood Cells is a challenging job in the computer-assisted diagnosis of blood for any disorder in many diseases like Complete Blood Count Test, Anemia, Leukemia and Malaria etc. The mentioned problems are highly laborious in manual microscopy for the hematologists. Many techniques currently existing for the solution suffer from both under- and over- splitting problems when highly complex clusters of Red Blood Cells occur. In addition, the existing techniques are not computationally efficient. In this paper, we address the aforementioned problems, firstly by considering the boundaries of the convex hulls of clustered Red Blood Cells and secondly, by splitting the boundaries according to the number of Red Blood Cells in relation to distance measures. Furthermore, we draw circles using a mid-point circle algorithm at each boundary cleavage to give an illusion of the Red Blood Cells. The test results of the proposed technique on a standard online dataset are presented in two ways. Statistically first of all by achieving an average recall of 0.964 and precision of 0.970 while their F-measure achieved is 0.962 as well as secondly through ground truth data with visual inspections

Research Article A Novel Approach to Enhance the Security of the LSB Image Steganography

Abstract: Forming a logical balance between the quality of the file and the scope of data that can be conveyed is the test of steganographic techniques to form such a balance. On top of that, the facts that cannot be covered up are the robustness of the method and security of the vague data. An insertion method which delivers a high level of visual quality and a huge amount of volume for the obscured data is called the Least Significant Bit (LSB), but the concealed message is poorly secured through this technique. In the recommended approach, the Vigenere encryption techniques initially used to encode the secret data to assure the safety of the concealed message. Later, the data is contracted through the Huffman coding method in order to decrease the occupational volume of the classified data. Then, each bit stream of the data is dispersed out onto the image to enhance the robustness of the technique by using the expanded knight tour algorithm. The outcomes show that apart from enhancing the visual quality of the stego image, the recommended technique enhances the safety and payload capacity issues of the simple LSB technique

Extreme facial expressions classification based on reality parameters

Extreme expressions are really type of emotional expressions that are basically stimulated through the strong emotion. An example of those extreme expression is satisfied through tears. So to be able to provide these types of features; additional elements like fluid mechanism (particle system) plus some of physics techniques like (SPH) are introduced. The fusion of facile animation with SPH exhibits promising results. Accordingly, proposed fluid technique using facial animation is the real tenor for this research to get the complex expression, like laugh, smile, cry (tears emergence) or the sadness until cry strongly, as an extreme expression classification that’s happens on the human face in some cases

Tears rendering in extreme expression by using SPH method and gravity parameters

The simulation of fluid generation and the Smooth Particle Hydrodynamic (SPH) method has been discussed as an explanation for extreme expression, followed by tears simulation which includes creating tears using SPH and tears effect rendering. Furthermore, the testing and the evaluation for creating tears simulation with different effects and cases were applied. Accordingly, this paper explains how to control the crying with the facial animation expressions which are used to simulate the extreme expressions. Additionally, the results of various aspects of this study and the different kinds of crying were simulated and explained. Finally, the measurements of frame rates for different parts of tears simulation by using Fraps software have been explored

Coverage Enhancement Algorithms for Distributed Mobile Sensors Deployment in Wireless Sensor Networks

Sensor nodes in wireless sensor networks are deployed to observe the surroundings for some phenomenon of interest. The fundamental issue in observing such environments is the area coverage which reflects how well the region is monitored. The nonuniform sensor nodes distribution in a certain region caused by random deployment might lead to coverage holes/gaps in the network. One of the solutions to improve area coverage after initial deployment is by sensor nodes mobility. However, the main challenge in this approach is how to increase area coverage with the least energy consumption. This research work aims to improve area coverage with minimal energy consumption and faster convergence rate. The Edge Based Centroid (EBC) algorithm is presented to improve the area coverage with faster convergence rate in a distributed network. The simulation based performance evaluations of the proposed algorithms are carried out in terms of area coverage, convergence rate, and energy efficiency. Compared to the existing works, EBC improved area coverage with faster convergence. It is concluded that the proposed algorithm has improved area coverage with faster convergence and minimal energy consumption

vTrust: An IoT-Enabled Trust-Based Secure Wireless Energy Sharing Mechanism for Vehicular Ad Hoc Networks

Vehicular Ad hoc Network (VANET) is a modern concept that enables network nodes to communicate and disseminate information. VANET is a heterogeneous network, due to which the VANET environment exposes to have various security and privacy challenges. In the future, the automobile industry will progress towards assembling electric vehicles containing energy storage batteries employing these resources to travel as an alternative to gasoline/petroleum. These vehicles may have the capability to share their energy resources upon the request of vehicles having limited energy resources. In this article, we have proposed a trust management-based secure energy sharing mechanism, named vTrust, which computes the trust degree of nodes to authenticate nodes. The proposed mechanism is a multi-leveled centralized approach utilizing both the infrastructure and vehicles to sustain a secure environment. The proposed vTrust can aggregate and propagate the degree of trust to enhance scalability. The node that requests to obtain the energy resources may have to maintain a specified level of trust threshold for earning resources. We have also evaluated the performance of the proposed mechanism against several existing approaches and determine that the proposed mechanism can efficiently manage a secure environment during resource sharing by maintaining average malicious nodes detection of 91.3% and average successful energy sharing rate of 89.5%, which is significantly higher in comparison to the existing approaches