Semi-supervised superpixel classification for medical images segmentation: application to detection of glaucoma disease

Glaucoma is a disease characterized by damaging the optic nerve head, this can result in severe vision loss. An early detection and a good treatment provided by the ophthalmologist are the keys to preventing optic nerve damage and vision loss from glaucoma. Its screening is based on the manual optic cup and disc segmentation to measure the vertical cup to disc ratio (CDR). However, obtaining the regions of interest by the expert ophthalmologist can be difficult and is often a tedious task. In most cases, the unlabeled images are more numerous than the labeled ones.We propose an automatic glaucoma screening approach named Super Pixels for Semi-Supervised Segmentation “SP3S”, which is a semi-supervised superpixel-by-superpixel classification method, consisting of three main steps. The first step has to prepare the labeled and unlabeled data, applying the superpixel method and bringing in an expert for the labeling of superpixels. In the second step, We incorporate prior knowledge of the optic cup and disc by including color and spatial information. In the final step, semi-supervised learning by the Co-forest classifier is trained only with a few number of labeled superpixels and a large number of unlabeled superpixels to generate a robust classifier. For the estimation of the optic cup and disc regions, the active geometric shape model is used to smooth the disc and cup boundary for the calculation of the CDR. The obtained results for glaucoma detection, via an automatic cup and disc segmentation, established a potential solution for glaucoma screening. The SP3S performance shows quantitatively and qualitatively similar correspondence with the expert segmentation, providing an interesting tool for semi-automatic recognition of the optic cup and disc in order to achieve a medical progress of glaucoma disease.     

Non-local total bounded variation scheme for multiple-coil magnetic resonance image restoration

In this paper, we design a variational model for restoring multiple-coil magnetic resonance images (MRI) corrupted by non-central Chi distributed noise. The energy functional corresponding to the restoration problem is derived using the maximum a posteriori (MAP) estimator. Optimizing this functional yields the solution, which corresponds to the restored version of the image. The non-local total bounded variation prior is being used as the regularization term in the functional derived using the MAP estimation process. Further, the split-Bregman iteration scheme is being followed for fast numerical computation of the model. The results are compared with the state of the art MRI restoration models using visual representations and statistical measures.     

A cross-layer analysis of TCP/link adaptation technologies over free-space optical links with Markov error model

This paper presents a comprehensive cross-layer framework on the performance of transmission control protocol (TCP) over a free-space optical (FSO) link, which employs automatic repeat request (ARQ) and adaptive modulation and coding (AMC) schemes. Not similar to conventional works in the literature of FSO, we conduct a Markov error model to accurately capture effects of burst errors caused by atmospheric turbulence on cross-layer operations. From the framework, we quantify the impacts of different parameters/settings of ARQ, AMC, and the FSO link on TCP throughput performance. We also discuss several optimization aspects for TCP performance.     

Speech authentication and content recovery scheme for security communication and storage

With the rapid development of Internet, it brings a lot of conveniences. However, the data transmission and storage are faced with some security issues that seem to be obstacles to overcome, such as privacy protection and integrity authentication. In this paper, an efficient speech watermarking algorithm is proposed for content authentication and recovery in encrypted domain. The proposed system consists of speech encryption, watermark generation and embedding, content authentication and recovery. In the encryption process, chaotic and block cipher are combined to eliminate the positional correlation and conceal the statistical feature. In the watermark embedding process, approximation coefficients of integer wavelet transform are used to generate watermark and the detail coefficients are reserved to carry watermark. Theoretical analysis and simulation results show that the proposed scheme has high security and excellent inaudibility. Compared with previous works, the proposed scheme has strong ability to detect de-synchronization attacks and locate the corresponding tampered area without using synchronization codes. Meanwhile, the selective encryption will not influence the selective watermarking operation. Similarly, the operation of watermarking will not affect the decryption of the encrypted speech. Additionally, the tampered samples can be recovered without any auxiliary watermark information.     

Radio resource management for LTE-A relay-enhanced cells with spatial reuse and max–min fairness

One of the major issues in LTE-Advanced (LTE-A) systems is the poor capacity at the cell edge. This is mainly due to the interference experienced by the users as a result of the aggressive frequency reuse usually implemented. Relaying offers an attractive solution for this problem by offering better links than those with the eNodeB (eNB) for the terminals suffering from high path loss or high interference. However, adding relays complicates the resource allocation problem at the eNB and therefore the need for more efficient schemes arises. This is also aggravated by the reuse of resource blocks (RBs) by the relays to fully exploit the scarce spectrum, which, in turn, leads to intra-cell interference. In this paper, we study the joint power and resource allocation problem in LTE-A relay-enhanced cells that exploit spatial reuse. To guarantee fairness among users, a max–min fair optimization objective is used. This complex problem is solved using coordinate ascent and the difference of two convex functions (DC) programming techniques and the proposed scheme indeed converges to a local-optimum quickly. This is shown to be a satisfactory solution according to the simulation results that indicate an almost sevenfold increase in the 10th percentile capacity when compared to previously proposed solutions.     

Computationally Efficient Motion Estimation Algorithm for HEVC

In this paper, we present a novel computationally efficient motion estimation (ME) algorithm for high-efficiency video coding (HEVC). The proposed algorithm searches in the hexagonal pattern with a fixed number of search points at each grid. It utilizes the correlation between contiguous pixels within the frame. In order to reduce the computational complexity, the proposed algorithm utilizes pixel truncation, adaptive search range, sub-sampling and avoids some of the asymmetrical prediction unit techniques. Simulation results are obtained by using the reference software HM (e n c o d e r_l o w d e l a y_P_m a i n and e n c o d e r_r a n d o m a c c e s s_m a i n profile) and shows 55.49% improvement on search points with approximately the same PSNR and around 1% increment in bit rate as compared to the Test Zonal Search (TZS) ME algorithm. By utilizing the proposed algorithm, the BD-PSNR loss for the video sequences like B a s k e t b a l l P a s s_416 × 240@50 and J o h n n y_1280 × 720@60 is 0.0804 dB and 0.0392 dB respectively as compared to the HM reference software with the e n c o d e r_l o w d e l a y_P_m a i n profile.     

Performance analysis of opportunistic CSMA schemes in cognitive radio networks

In this paper, we consider underlay cognitive radio (CR) networks where an amount of interference caused by secondary stations (STAs) has to be kept below a predefined level, which is called interference temperature. We propose opportunistic p-persistent carrier sense multiple access schemes for the CR networks, which opportunistically exploit wireless channel conditions in transmitting data to the secondary access point. We also devise an adaptive interference-level control technique to further improve quality-of-service of a primary network by limiting the excessive interference due to collisions among STAs. The performances of the proposed schemes are mathematically analyzed, and they are validated with extensive computer simulations. The simulation results show that the proposed schemes achieve near optimal throughput of the secondary network while they are backward-compatible to the conventional p-persistent CSMA scheme.     

Physical layer multi-user key generation in wireless networks

Secret key generation by extracting the shared randomness in the wireless fading channel from physical layer is an interesting topic of practical value. Previous works have focused on the study of physical layer key generation with two nodes from the view point of key generation rate (KGR). Information theoretic limits and the KGRs in implementation have been derived. However, in real-world applications, the physical layer key generation problem involving multiple nodes is the common case, which lacks sufficient study so far. Multi-node case differs from two-node case in that there are two more important considerations: (1) the trade-off between KGR and probing efficiency at individual node pair; (2) channel probing schedule among multiple node pairs. This paper aims at minimizing the Overall Waiting Time of physical layer key generation with multiple users (shorten as OWT) through the optimization of probing rates at individual node pair and channel probing schedule. The theoretical lower bound of OWT is derived first, then a practical method (MUKEM) is proposed to compute reasonable probing rates and channel probing schedule for multiple node pairs to obtain a short OWT. Simulations are conducted to evaluate the effectiveness of our method. The results show that 70 % of OWT can be reduced by using our method comparing with one-by-one key generations; while it is only about 8 % longer than the lower bound of OWT.     

A Dual Ring Connectivity Model for VANET Under Heterogeneous Traffic Flow

Vehicular ad-hoc network (VANET) is characterized as a highly dynamic wireless network due to the dynamic connectivity of the network nodes. To achieve better connectivity under such dynamic conditions, an optimal transmission strategy is required to direct the information flow between the nodes. Earlier studies on VANET’s overlook the characteristics of heterogeneity in vehicle types, traffic structure, flow for density estimation, and connectivity observation. In this paper, we have proposed a heterogeneous traffic flow based dual ring connectivity model to enhance both the message disseminations and network connectivity. In our proposed model the availability of different types of vehicles on the road, such as, cars, buses, etc., are introduced in an attempt to propose a new communication structure for moving vehicles in VANETl under cooperative transmission in heterogeneous traffic flow. The model is based on the dual-ring structure that forms the primary and secondary rings of vehicular communication. During message disseminations, Slow speed vehicles (buses) on the secondary ring provide a backup path of communication for high speed vehicles (cars) moving on the primary ring. The Slow speed vehicles act as the intermediate nodes in the aforementioned connectivity model that helps improve the network coverage and end-to-end data delivery. For the evaluation and the implementation of dual-ring model a clustering routing scheme warning energy aware cluster-head is adopted that also caters for the energy optimization. The implemented dual-ring message delivery scheme under the cluster-head based routing technique does show improved network coverage and connectivity dynamics even under the multi-hop communication system.     

Q-MOHRA: QoS Assured Multi-objective Hybrid Routing Algorithm for Heterogeneous WSN

Quality of Service (QoS) assurance in Wireless Sensor Network (WSN) is a tough task, and it is more exciting due to the scarcity of resources. The requirement of different WSN applications running over has different constraints. In QoS, routing protocol the network has to balance the traffic. This paper presents a novel heuristic routing algorithm known as QoS assured Multi-objective Hybrid Routing Algorithm (Q-MOHRA) for Heterogeneous WSN. Q-MOHRA takes into account the link (energy, hop count, link quality indicator etc.) and path (jitter) metrics for optimal path selection. The performance of Q-MOHRA is evaluated through intensive simulation and equated with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-objective Routing Algorithm (DyMORA). The metrics such as average energy consumption, residual energy, packet delivery ratio, jitter, and normalized routing load are used for comparison. The performance of Q-MOHRA has been observed to outclass SHRP and DyMORA. It improves the packet delivery ratio by 24.31% as compared to SHRP and 11.86% as compared to DyMORA. Q-MOHRA outperforms DyMORA in terms of average energy consumption by a factor of 8.27%.