Sabira Khatun

EXPERIMENTAL BREAST TUMOR DETECTION USING NN-BASED UWB IMAGING

This paper presents a system with experimental comple-ment to a simulation work for early breast tumor detection. The ex-periments are conducted using commercial Ultrawide-Band (UWB) ntransceivers, Neural Network (NN) based Pattern Recognition (PR) software for imaging and proposed breast phantoms for homogenous and heterogeneous tissues. The proposed breast phantoms (homoge-neous and heterogeneous) and tumor are constructed using available low cost materials and their mixtures with minimal e®ort. A speci¯c glass is used as skin. All the materials and their mixtures are con-sidered according to the ratio of the dielectric properties of the breast tissues. Experiments to detect tumor are performed in regular noisy nroom environment. The UWB signals are transmitted from one side of the breast phantom (for both cases) and received from opposite side diagonally repeatedly. Using discrete cosine transform (DCT) of these received signals, a Neural Network (NN) module is developed, trained nand tested. The tumor existence, size and location detection rates for both cases are highly satisfactory, which are approximately: (i) 100%,95.8% and 94.3% for homogeneous and (ii) 100%, 93.4% and 93.1% for heterogeneous cases respectively. This gives assurance of early de- ntection and the practical usefulness of the developed system in near future.

3d experimental detection and discrimination of malignant and benign breast tumor using nn-based uwb imaging system

This paper presents both simulation and experimental study to detect and locate breast tumors along with their classification as malignant and/or benign in three dimensional (3D) breast model. The contrast between the dielectric properties of these two tumor types is the main key. These dielectric properties are mainly controlled by the water and blood content of tumors. For simulation, electromagnetic simulator software is used. The experiment is conducted using commercial Ultrawide-Band (UWB) transceivers, Neural Network (NN) based Pattern Recognition (PR) software for imaging and homogenous breast phantom. The 3D homogeneous breast phantom and tumors are fabricated using pure petroleum jelly and a mixture of wheat flour and water respectively. The simulation and experimental setups are performed by transmitting the UWB signals from one side of the breast model and receiving from opposite side diagonally. Using discrete cosine transform (DCT) of received signals, we have trained and tested the developed experimental Neural Network model. In 3D breast model, the achieved detection accuracy of tumor existence is around 100%, while the locating accuracy in terms of (x, y, z) position of a tumor within the breast reached approximately 89.2% and 86.6% in simulation and experimental works respectively. For classification, the permittivity and conductivity detection accuracy are 98.0% and 99.1% in simulation, and 98.6% and 99.5% in experimental works respectively. Tumor detection and type specification 3D may lead to successful clinical implementation followed by saving of precious human lives in the near future.

Multicast-Unicast Data Delivery Method in Wireless IPv6 Networks

Multicast IPv6 is an efficient way of transmitting data simultaneously to a group of IPv6 users. It has the advantage of reducing the required bandwidth of IPv6 data delivery compared to unicast transmission. The data rate of multicast transmission over WLAN is confined by the user with the lowest rate in the multicast group, which is called the fixed base rate problem. This paper proposes a delivery method that incorporates both multicast and unicast transmissions to solve the fixed base rate problem. The proposed method divides the IPv6 network into two levels: multicast mode for the upper level of the network [IPv6 server to Access Point (AP)], and unicast mode for the lower level (AP to mobile nodes). To maintain the end-to-end multicast transmission, the AP is responsible for converting multicast packets to unicast packets. Such a combination enables the proposed method to inherit the advantages of both multicast and unicast transmissions. The performance of our proposed method is evaluated in a test-bed environment that considers the transmission of real-time video application. The proposed multicast-unicast is able to improve the throughput and video quality experienced by the end user, with low packet loss and transmission delay.

A Random search based effective algorithm for pairwise test data generation

Testing is a very important task to build error free software. As the resources and time to market is limited for a software product, it is impossible to perform exhaustive test i.e., to test all combinations of input data. To reduce the number of test cases in an acceptable level, it is preferable to use higher interaction level (t way, where t ≥ 2). Pairwise (2-way or t = 2) interaction can find most of the software faults. This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. Java program has been used to test the performance of the algorithm. The algorithm is able to support both uniform and non-uniform values effectively with performance better than the existing algorithms/tools in terms of number of generated test cases and time consumption.

Superposition Coding with Unequal Error Protection for the Uplink of Overloaded DS-CDMA System

The overloaded CDMA schemes exploited in direct sequence CDMA (DS-CDMA) systems are mainly to accommodate a greater number of users than the available spreading factor N. In this paper, a superposition coding CDMA (SPC-CDMA) with unequal error protection (UEP) is proposed as one of the overloaded CDMA schemes for the next generation mobile communication systems. It exploits the available power control in most base stations to adapt the transmitted power of active users in the uplink channel. In this scheme, the active users are divided into G groups and each group consists of K users. The K users share the same spreading sequence and are distinguished by different received power levels. At the receiver side, the system first performs despreading for group detection followed by multiuser receiver to estimate the K user signals in each group. It is shown through simulations that better performance are achieved compared to the conventional DS-CDMA and existing overloaded collaborative spreading CDMA (CS-CDMA) schemes, in additive white Gaussian noise (AWGN) and fading channels. Hence, the proposed scheme maximizes the system capacity K-fold compared to conventional DS-CDMA system without requiring extra spreading codes, with average signal to noise ratio (SNR) cost of only 1dB and 2 dB over AWGN and fading channels respectively at BER of 10−3. On the other hand, for the same N, K and power constraints, SPC-CDMA scheme achieves twofold increase in data rate with 0.7 and 4 dB gains over AWGN and fading channels respectively, compared with overloaded CS-CDMA scheme in the same system capacity. In addition, the proposed scheme can also attain different levels of UEP for different users’ requirements by adjusting their fractions of transmitted powers.

Reliable Key Management and Data Delivery Method in Multicast Over Wireless IPv6 Networks

Multicast is an efficient way to reduce the required bandwidth of transmitting data simultaneously to a group of users in wireless IPv6 networks. Nevertheless, multicast suffers from two main drawbacks which can be looked from two perspectives, namely security and QoS. With regard to security, the main challenge is to provide security protection to multicast data, which can be achieved by using a secure key management process. Considering a highly dense environment where connection of users to the network is changing frequently due to join or leave operations, key updating approach may burden a network devices with a huge amount of complex encryption/decryption processes. From the QoS perspective, multicast transmission over WLAN offers a tradeoff between the transmission rate and the coverage. The transmission rate of multicast is confined by the user with the lowest data rate in the group which is called fixed base rate problem. To address the above mentioned problems, we propose and implement a lightweight key management and data delivery scheme for multicast over wireless IPv6 networks. The proposed solution is envisaged to reduce the complexity of key updating, while at the same time is able to address the fixed base rate problem. The performance evaluation (by means of analytical and test-bed implementation) of the proposed key management method indicates its efficiency in reducing communication, computation, and storage costs, while maintaining both forward and backward securities. Moreover, the proposed data delivery method is able to improve the throughput and QoS, with low packet loss and transmission delay.

A Cross Layer Metric for Discovering Reliable Routes in Mobile Ad Hoc Networks

Host mobility in mobile ad hoc networks causes failure of wireless links between nodes and breaks all the routes that use these links. Consequently, route reconstructions are needed, which is one of the most critical problems for this type of wireless networks. The number of route reconstructions can be reduced if more reliable wireless links are used. Also by these links, stable clusters can be constructed as is needed in cluster based protocols. Reliable routing protocols for mobile ad hoc networks use many link reliability metrics for finding these links; four of the most commonly used are “Link Expiration Time”, “Probabilistic Link Reliable Time”, “Link Packet Error Rate” and “Link Received Signal Strength”. It is shown that these metrics enhance the reliability and reduce the number of route reconstructions, but to the best of our knowledge there is no report that compare their efficiencies. In this paper, we make this comparison in different network conditions and discuss their optimal applications. Then, a new cross layer metric is proposed that combines the aforementioned metrics according to their efficiency by means of a unit weight function. Simulation results show that by using all these metrics, the number of route reconstructions is reduced, and for the proposed one the result is better than the others.

A UWB imaging system to detect early breast cancer in heterogeneous breast phantom

This paper presents an experimental early breast cancer detection system in terms of heterogeneous breast phantom. The system consists of commercial Ultrawide-Band (UWB) transceivers and our developed Neural Network (NN) based Pattern Recognition (PR) software for imaging. A simple way to construct cancer- tissue and heterogeneous breast phantom using available low cost materials and their mixtures is also proposed here. The materials are: (i) A mixture of petroleum jelly, soy oil, wheat flour and water as heterogeneous tissue; (ii) A particular glass as skin; and (iii) A specific mixture of water and wheat flour as cancer- tissue. All the materials and their mixtures are considered according to the ratio of the dielectric properties of the breast tissues. To experimentally detect cancer, the UWB signals are transmitted from one side of the breast phantom and received from opposite side diagonally. By using discrete cosine transform (DCT) of the received signals, a Neural Network (NN) is trained, tested and interfaced with the UWB transceiver to form the complete system. The achieved detection rate of cancer cells existence, size and location are approximately 100%, 93.1% and 93.3% respectively.

Singular Value Decomposition Rank-Deficient-Based Estimators in TD-SCDMA Systems

This paper presents a new joint channel estimation method for Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) systems based on a Singular Value Decomposition (SVD) reduced-rank technique. The system capacity is increased by increasing the highest number of users in one time slot. The additional channel estimation processing required for the increasing number of users is solved by adopting the reduced-rank technique, which estimates a limited number of parameters that are needed to describe the channel matrix and reduce the dimensionality of this matrix. Simulation results prove the validity of the proposed reduced-rank technique for channel estimation accuracy enhancing. Additionally, it is shown that the detectors based on the reduced-rank estimators outperform traditional channel estimators, contributing to 7.8 and 6.9xa0dB BER performance improvements for indoor and vehicular channels, respectively.

Distributed cognitive radio detection using Waspmote sensor for Windows based PC/Laptop

All over the world, the existing spectrum is already been saturated with ever increasing demand. Every day huge number of users is joined to the existing fixed band frequency but the bandwidth is not increasing. To solve this issue the cognitive radio is the best choice. Spectrum or white space detection is an essential and very important issue in cognitive radio communication. The aim of channel detection is to find out efficiently the presence or absence of primary or licensed frequency. In this paper, we have developed a Libelium Waspmote sensor based cognitive radio detection scheme which is very easy to use, energy and cost effective. The reason for selecting this type of sensor is it supports IEEE 802.11 b/g and the Tx/Rx antenna transmission and reception sensitivity can be changed by the software. It can scan the available channel resource within its range and can store the data files. Also the security of this type of sensor supports the highest level of wireless security that is Wireless Protected Access V2 or WPA2. It is Windows based which is very common worldwide. The application runs in background without interrupting the PC/Laptop users. It is able to find efficient spectrum hole (Ideal channel) for a secondary or cognitive user to use the primary or licensed band without interrupting the primary user.