N. M. Saad

Tone mapping of HDR images: A review

Real world contains a wide range of intensities that cannot be captured with traditional imaging devices. Moreover, even if these images are captured with special procedures, existing display devices cannot display them. This paper presents a comparative study of most famous tone mapping algorithms. Tone mapping is the process of compressing high dynamic range images into a low dynamic range so they can be displayed by traditional display devices. The study implements six tone mapping algorithms and performs a comparison between them by visual rating. Independent participant were asked to rate these images based on a given rating scheme. The study concluded that Reinhard tone mapping operators are the best in term of visual pleasure and maintaining image integrity. In addition, exponential tone mapping operators have achieved better rating compared the logarithmic operators.

Fuzzy logic based vertical handover algorithm between LTE and WLAN

In the future there is a need to provide seamless mobility to the heterogeneous wireless network user while on the move. To achieve this there is a need to design an efficient vertical handover mechanism. User preference and system condition should be taken into consideration for efficient vertical handover. As the 3GPP Long-term evolution or LTE is the upcoming WWAN technology, performing an efficient vertical handover between LTE and next generation wireless LAN will be the challenge for future research. In this paper a fuzzy based vertical handover algorithm NG-VDA is proposed to provide an efficient vertical handover between LTE and WLAN to the user on the basis of multiple parameters.

Routing strategies in hierarchical cluster based mobile wireless sensor networks

Ubiquitous communication networks is a keystone for New Generation Network (NWGN). Mobile Wireless Communication Networks (MWSN) is a viable solution to accomplish the requirements of NWGN. Due to mobility of sensor nodes, the data reliability and end-to-end delay with energy efficiency in the network is an enormous concern. Various real-time and delay sensitive applications enforced to use both environments mobile and fixed sensor nodes, whereas the others claims an entire mobile sensors environments in network. Packet loss ratio and end-to-end delay happened because of the nodes mobility which is directly impact to degrade the quality of service, network lifetime and energy consumption. This paper enlightens a comprehensive comparison between single and multi hop inter-cluster routing strategy from cluster head to base station. Moreover, the performance of multi hop routing is calculated and compared with single hop LEACH routing strategy. The simulation results reveal that multi hop routing strategy is to increase the sensor nodes throughput and network lifetime but not efficient approach for delay sensitive and data reliable applications.

An overview of evaluation metrics for routing protocols in wireless sensor networks

With the maturity and development of Wireless Sensor Networks, a large body of research is being assembled and several routing protocols have been developed for wireless sensor networks. Routing metric is very important for the performance of wireless sensor networks. But a little attention has been paid by the researchers to the evaluation metrics and design principles for routing protocols that should never be neglected while designing and evaluating routing protocols for wireless sensor networks. This paper depicts some vital evaluation metrics that are essential while designing, developing and evaluating the performance of routing protocols for wireless sensor networks. This research is an effort towards hoarding all the general metrics and guiding the researchers for designing efficient, professional and valuable routing protocols.

Distributed Clone Detection in Static Wireless Sensor Networks: Random Walk with Network Division

Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads.

An overview of vertical handoff decision policies for next generation wireless networks

Future wireless networks will allow users to seamlessly roam among heterogeneous wireless networks. To provide services anywhere and anytime in such a diverse networking environment, vertical handoff is still a crucial target. In this paper we propose non-real time services vertical handoff decision algorithm NRS-VDA. NRS-VDA is an intelligent vertical handoff decision algorithm that can manage efficient vertical handoff initiation and decision procedure between UMTS and WL AN networks. NRS-VDA ensures the avoidance of unnecessary and detrimental vertical handoffs and provides high throughput and low blocking probability. NRS-VDA is defined for upward and downward vertical handoff scenarios. The proposed algorithm takes several metrics into account such as velocity of mobile terminal, bandwidth, and Received Signal Strength (RSS) of the network. It is suggested that NRS-VDA will improve the overall efficiency of vertical handoff in Next Generation Networks (NGN).

A novel mechanism for restoring actor connected coverage in wireless sensor and actor networks

Provisioning network survivability is especially crucial in wireless sensor and actor network (WSAN) because nodes deployed in hostile environments are prone to frequent failures. Failure of an actor significantly impact actor connected coverage which is essential for effective network operation. Existing mobility-based recovery schemes are either geared towards restoring inter-actor connectivity or area coverage. None of them consider sustaining actor coverage (i.e., having sensors reachable to actors) while restoring inter-actor connectivity. This paper presents RACE, a novel mechanism to Restore Actor Connected Coverage with reduced recovery overhead. RACE distinguishes critical/non-critical actors based on 2-hop information to better assess the scope of the failure and optimize the recovery procedure. Neighbors of a failed actor employ a cooperative failure detection scheme and only perform a limited-scale network reconfiguration to adopt any bereaved sensors left unreachable (uncovered by an actor) due to failure of a non-critical actor. In case a critical actor fails, RACE substitutes it with a non-critical neighbor that has the least impact on coverage (i.e., number of sensors). If it is necessary to engage critical actors in the recovery, RACE is recursively applied by relocating actors until a non-critical node is picked. Simulation results confirm the performance advantage of RACE compared to the best contemporary schemes.

Scene classification for aerial images based on CNN using sparse coding technique

ABSTRACT Aerial scene classification purposes to automatically label aerial images with specific semantic categories. However, cataloguing presents a fundamental problem for high-resolution remote-sensing imagery (HRRS). Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. The article has two major sections: the first describes the extraction of dense multiscale features (multiple scales) from the last convolutional layer of a pre-trained CNN models; the second describes the encoding of extracted features into global image features via sparse coding to achieve scene classification. The authors compared experimental outcomes with existing techniques such as Scale-Invariant Feature Transform and demonstrated that features from pre-trained CNNs generalized well with HRRS datasets and were more expressive than low- and mid-level features, exhibiting an overall 90.3% accuracy rate for scene classification compared to 85.4% achieved by SIFT with sparse coding. Thus, the proposed CNN-based sparse coding approach obtained a robust performance that holds promising potential for future applications in satellite and UAV imaging.

Heart rate estimation using facial video: A review

Abstract Photoplethysmography and Ballistocardiography are two concepts that are used to measure heart rate from human, by using facial videos. Heart rate estimation is essential to determine the physiological and pathological state of a person. This paper presents a critical review of digital camera based heart rate estimating method on facial skin. This review extends the investigation on to the principles and theory behind photoplethysmography and ballistocardiography. The article contains reviews on the significance of the methods and contributions to overcome challenges such as; poor signal strength, illumination variance, and motion variance. The experiments were conducted to validate the state of the art methods on a challenging database that is available publicly. The implemented methods were validated using the database, on 27 subjects for a range of skin tones from pearl white, fair, olive to black. The results were computed using statistical methods such as: mean error, standard deviation, the root mean square error, Pearson correlation coefficient, and Bland-Altman analysis. The results derived from the experiments showed the reliability of the state of the art methods and provided direction to improve for situations involving illumination variance and motion variance.

Efficient cluster head selection scheme in Mobile Data Collector based routing protocol

Mobile Wireless Sensor Network (mWSN) is one of the rising and emerging technologies for various application of NWGN. The enormous concerns of these networks are energy efficiency and data aggregation within the network. The aim of data aggregation is that eliminates redundant data transmission and enhances the lifetime of energy in mWSN. In this paper, we propose, analyze and validate efficient cluster head selection scheme in Mobile Data Collector based routing protocol for data aggregation, which is based on multi-hop routing strategy. Moreover, our approach is better than traditional LEACH in terms of energy consumption of sensor nodes and enhances the network lifetime due to less energy consumption during data transmission.