There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

http://ieeexplore.ieee.org/iel2/815/3148/00100651.pdf

Robot vision

Ethnologue: Languages of the World

Pattern recognition

Software-defined network (SDN) has become one of the most important architectures for the management of largescale complex networks, which may require repolicing or reconfigurations from time to time. SDN achieves easy repolicing by decoupling the control plane from data plane. Thus, the network routers/switches just simply forward packets by following the flow table rules set by the control plane. Currently, OpenFlow is the most popular SDN protocol/standard and has a set of design specifications. Although SDN/OpenFlow is a relatively new area, it has attracted much attention from both academia and industry. In this paper, we will conduct a comprehensive survey of the important topics in SDN/OpenFlow implementation, including the basic concept, applications, language abstraction, controller, virtualization, quality of service, security, and its integration with wireless and optical networks. We will compare the pros and cons of different schemes and discuss the future research trends in this exciting area. This survey can help both industry and academia R&D people to understand the latest progress of SDN/OpenFlow designs.

/pdf/a-survey-on-software-defined-network-and-openflow-from-2w15cg0qir.pdf

A Survey on Software-Defined Network and OpenFlow: From Concept to Implementation

In the last few decades, many advanced technologies have been proposed, in which communications played a great role as well as telecommunications applications. The noise elimination in various environments became the most concerned as it greatly hindered the speech communication applications. The improvement of noisy speech interms of quality and intelligibility are taken into account without introducingany additional noise. Many speech enhancement algorithms have been proposed. Wiener filter is one of the classical algorithm that improve the noisy speech by reducing its noise components through selectively chosen Wiener gain. In this paper, compressive sensing method by randomize measurement matrix is combined with the Wiener filter to reduce the noisy speech signal to produce high signal to noise ratio. The PESQ is used to measure the quality of the proposed algorithm design. Experimental results showthe effectiveness of our proposed algorithm to enhance noisy signals corrupted by various noises compared to other traditional algorithms, in which high PESQ scores were achieved across various noises and different SNRs.

/pdf/speech-enhancement-based-on-wiener-filter-and-compressive-4uu9hjjfpy.pdf

Speech Enhancement based on Wiener Filter and Compressive Sensing

Effects of linear array antenna parameters to the performance of LMS beamforming algorithms

Joint channel assignment and routing is a well-known problem in multi-radio wireless mesh networks for which optimal configurations is required to optimize the overall throughput and fairness. However, other objectives need to be considered in order to provide a high quality service to network users when it deployed with high traffic dynamic. In this paper, we propose a re-configuration optimization model that optimizes the network throughput in addition to reducing the disruption to the mesh clients’ traffic due to the re-configuration process. In this multi-objective optimization model, four objective functions are proposed to be minimized namely maximum link-channel utilization, network average contention, channel re-assignment cost, and re-routing cost. The latter two objectives focus on reducing the re-configuration overhead. This is to reduce the amount of disrupted traffic due to the channel switching and path re-routing resulted from applying the new configuration. In order to adapt to traffic dynamics in the network which might be caused by many factors i.e. users’ mobility, a centralized heuristic re-configuration algorithm called State-Aware Joint Routing and Channel Assignment (SA-JRCA) is proposed in this research based on our re-configuration model. The proposed algorithm re-assigns channels to radios and re-configures flows’ routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. The ns-2 simulator is used as simulation tool and various metrics are evaluated. These metrics include channel-link utilization, channel re-assignment cost, re-routing cost, throughput, and delay. Simulation results show the good performance of SA-JRCA in term of packet delivery ratio, aggregated throughput and re-configuration overhead. It also shows higher stability to the traffic variation in comparison with other compared algorithms which suffer from performance degradation when high traffic dynamics is applied.

/pdf/state-aware-re-configuration-model-for-multi-radio-wireless-2fgkhz37mo.pdf

State-aware re-configuration model for multi-radio wireless mesh networks

In this paper, an algorithm to improve image stabilization process in 3D for multiple camera viewpoints from different angle is developed. It can automatically simplify the region of interest with unique key-points matching. Harris Laplace corner detection has been used to find accurate matching key points for different photometric changes, scaling in images. Spanning tree has been used to improve the connectivity of correct matching pairs by minimizing the global error value. Spanning tree is the key for stabilized randomly positioned camera viewpoints. It always gives successful stabilization output. This process doesn’t need to analyze the key-points twice. The results show that the proposed algorithm can process more than 120 camera viewpoints in less than two (<2) seconds. It shows a great consistency for different image sets for different viewpoints of cameras.

Robust Automatic Multi-Camera Viewpoint Stabilization using Harris Laplace corner detection and Spanning Tree

In recent years, the advantages offered by Image
Guided Surgery (IGS)/ Computer Aided Surgery (CAS) to
patients and medical professionals during a minimally-invasive
surgical operation are overwhelming. Imaging techniques have
had immense growth in their sophistication and can provide
the surgeon with high quality guidance. This notwithstanding
there is still room for improvement in almost all the areas of
IGS application and stages such area as computational time
which impedes its full deployment in intra-operative surgical
interventional, segmentation, registration, visualization, plus
IGS application software and instrumentation. This paper
presents a model for the attainment of a more effective
computational scheme by looking at possible computational
improvement at all stages of IGS procedure but focusing on
two aspects of IGS relating to intra-operative surgical
intervention. If implemented, it will result into fast and better
anatomical segmentation and fast computational scheme.

Othman Omran Khalifa

Papers

Speech Enhancement based on Wiener Filter and Compressive Sensing

Effects of linear array antenna parameters to the performance of LMS beamforming algorithms

State-aware re-configuration model for multi-radio wireless mesh networks

Robust Automatic Multi-Camera Viewpoint Stabilization using Harris Laplace corner detection and Spanning Tree

Toward effective computational archetype for image guided neuro-surgery