iosr-JECE   Volume-10 ~ Issue-4 ~ July-August 2015

Abstract: Future cellular communication systems will be designed to support a wide ranges of data rates, high data coverage, larger capacity and challenging throughput with a complex quality of service matrix. It is becoming more challenging to optimize the radio resource management and maximize the system capacity by meeting the required quality of service from user's point of view. This paper addresses the influence of multi-cell interference, BER, path loss and the effect of QAM on overall radio communication. This project sets a new direction for future research on resource scheduling strategies in a multi-cell system.

[1]. Moinuddin A.A. and Singh S (2007), Accurate Path Loss Prediction in Wireless Environment, The Institution of Engineers (India) Volume 88, July2007, Pp: 09-13.
[2]. Rappaport T. S.(1996), Wireless Communications: Principles and Practice, Prentice Hall PTR, Upper Saddle River, New Jersey, 1996.
[3]. Rappaport, T. S. (2002). Wireless communications: Principles and practice. Prentice Hall communications engineering and emerging technologies series. Upper Saddle River, NJ: Prentice Hall PTR.
[4]. Yong soo cho,jaekwon kim won young yang, chung-gu kang. MIMO- OFDM Wireless Communication with MATLAB
[5]. http://1000projects.org/performance-analysis-of-adaptive-algorithms-in-future-cellular-networks.html www.mathworks.com

Abstract: Segmentation of anatomical regions of brain is that the elementary problem in medical image analysis. The aim of this work is to style an automatic tool for tumor quantification mistreatment imaging image information sets. A tumor segmentation methodology must be developed and validate segmentation on 2nd & 3D imaging information. This methodology doesn't need associate the degree data format whereas the others need an data format within the growth. In this, when a manual segmentation procedure the growth identification, the investigations has been created for the potential use of imaging information for up brain tumor form approximation and 2nd & 3D mental image for surgical designing and assessing tumor.

[1]. Pranita Balaji Kanade, prof. P.P Gumaste, ― Brain tumor detection using MRI images‖, International journal of Innovative Research in Electrical, Electronics, Instrumentation and control engineering, vol 3, Issue 2, Feb 2015.
[2]. Komal Sharma, Akwinder Kaur, Shruti Gujral, ―A review on various brain tumor detection techniques in Brain MRI images‖, IOSR, 2014.
[3]. Senthilkumaran N, Thimmiaraja J, ―Histogram Equalization for image enhancement using MRI brain Images‖, World Congress on computing and communication technologies, IEEE, 2014.
[4]. V. Zeljkovic, C. Druzgalski, Y.Zhang, Z. Zhu, Z. XU, D. Zhang, P. Mayorga, ―Automatic Brain Tumor Detection and Segmentation in MR images‖, PAN American Health Care Exchanges (PAHCE) Conference, 2014.
[5]. Rushabh R. Shah, Dr. Priyanka Sharma, ―Performance Analysis of Region of Interest Based Compression Method For Medical Images‖, Fourth International conference on Advanced computing & communication Technologies, IEEE,2014.

Abstract: The new Joint Video Team (JVT) video coding standard has garnered increased attention recently. Generally, motion estimation computing array (MECA) performs up to 50% of computations in the entire video coding system, and is typically considered the computationally most important part of video coding systems. For a commercial chip, a video coding system must introduce design for testability (DFT), especially in an MECA. The objective of DFT is to increase the ease with which a device can be tested to guarantee high system reliability. Among these techniques, BIST has an obvious advantage in that expensive test equipment is not needed and tests are low cost. Moreover, BIST can generate test simulations and analyze test responses without outside support, making tests and diagnoses of digital systems quick and effective. However, as the circuit complexity and density increases, the BIST approach must detect the presence of faults and specify their locations for subsequent repair.

[1]. Built- in self-detection/correction architecture for Motion Estimation Computing Arrays", Chun-lung Hsu, chang-Hsin Cheng, and
Yu Liu.VOL.18, No2, February 2010.
[2]. High Throughput and Efficient VLSI Architecture of Integer Motion Estimation for H.264/AVC, Meihua GU, Ningmei YU, Lei
ZHU, Wenhua JIA. (1315-1316).
[3]. Biresidue Error- Correcting Codes for Computer Arithmetic", Thammavarapu R.N Rao, Member, IEEE.
[4]. VLSI Test Principles and Architectures", Laung-Terng.
[5]. Flash memory testing and built-in self-diagnosis with march-like test algorithms," J. C. Yeh, K. L. Cheng, Y. F. Chou, and C. W.
Wu.
[6]. P.Gallagher, V. Chickermane, S. Gregor, and T. S. Pierre, "A building block BIST methodology for SOC designs: A case study," in
Proc. Int.Test Conf., Oct. 2001, pp. 111–120.
[7]. Design of Programmable Logic-BIST Structures Using Verilog for Digital VLSI Circuits", Ramesh Bhakthavatchalu, Archana K R.

Abstract: This paper explores the potential of ultra-high frequency low noise InAlAs/InGaAs/InAlAs double gate high electron mobility transistor (DG-HEMT) for mixer applications. A comprehensive analytical approach is developed for InAlAs/InGaAs/InAlAs separate gate geometry DG-HEMT based mixer. Heterogeneous mixer configuration is employed in which both the signals, the local oscillator (LO) signal as well the radio frequency (RF) signal are applied at the same gate (gate 1). The dc offset is also applied at the
other gate (gate 2) for better charge control.

[1]. S. A. Mass, Microwave Mixer (Artech House, Inc 2003)
[2]. I.A.Gover, S. R. Pennock and P. R. Shepherd, Microwave Device circuits and subsystems for communications engineering (John Wiley & Sons, Ltd., 2005)
[3]. H. Y. Yang, J. H. Tsai, C. H. Wang, C. S. Lin, W. H. Lin, K. Y. Lin, T. W. Huang, and H. Wang, Design and analysis of a 0.8–77.5 GHz ultra-broadband distributed drain mixer using 0.13-m CMOS technology, IEEE Transactions on Microwave Theory and Techniques, 57(3), 2009, 562-572.
[4]. H. L. Kao, B. H. Wei, and Y. C. Lee, A 3.5 GHz Low-Noise Amplifier in 0.35 μm GaN HEMT on Si-Substrate for WiMAX Applications, International Journal of Electronics and Electrical Engineering, 3(1), 2015, 61-65.
[5]. F. Amrouche, R. Allam, J-M. Paillot, Microwave Low Noise HEMT Gate Mixers, DICS 2004, 619-623.

Abstract: Data comparison is widely used in computing systems to perform many operations such as tag matching in cache memory, virtual to physical address translation in TLB. Because of such prevalence it is important to implement the comparison circuit with low hardware complexity. Data Fix has developed a series of algorithms and programs that utilize token-based matching in conjunction with various fuzzy-matching functions. For a given block of source data each token is compared to records from the target dataset. The data comparison usually resides in the critical path of the components that are devised to increase system performance.

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Abstract: Grading and classification of fruits is based on observations and through experiences. The system utilizes image-processing techniques to classify and grade quality of fruits. Two dimensional fruit images are classified on shape and colour based analysis methods. However, different fruit images may have similar or identical colour and shape values. Hence, using colour or shape features analysis methods are still not effective enough to identify and distinguish fruits images.

[1]. Naganur and sannakki, "Fruits Sorting and Grading using Fuzzy Logic", International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 1, Issue 6, August 2012.
[2]. Sagare, Sunil N. Kore, "Fruits Sorting and Grading Based on Color and Size", International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS), IJETCAS 12-333.
[3]. Effendi,Z ;Ramli,R. ;Ghani,J.A. ;Rahman, "Pattern Recognition System of Jatropha curcas Fruits using Back Propagation", signal and image processing applications (ICSIPA), 2009 IEEE International Conference on Kuala Lumpur.
[4]. Zhao, J.T., J. Katupitiya, J., "On-tree Fruit Recognition using Texture properties and Color data", International conference on Intelligent Robots and Systems. 2005, IEEE: Edmonton Canada. p. 263-268.
[5]. Lopez Jose J., Cobos Maximo and Aguilera Emanuel, "Computer-based Detection and Classification of flaws in Citrus Fruits", International conference on natural image Processing (ICONIP-2009).

Abstract: Speech coding is an algorithm used to analyze the special, non- stationary and intelligent speech signal in order to extract its important parameters and to compress it for the maximum utilization of available bandwidth. To achieve this, various speech coding algorithms have been effectively used. Out all these algorithms, Linear Predictive Coding (LPC) is the most powerful one as it provides accurate estimation of speech parameters and is computationally effective and used to represent the speech signal at reduced bit rates while preserving the quality of the signal. Voice- excited LPC is the algorithm proposed in this paper. This algorithm has been implemented using Hindi and English male and female voices and trade- offs between bit rates, delay, power signal to noise ratio and complexity are analyzed. It results in low bit-rates and better signal to noise ratio.

[1]. L.R.Rabiner and R. W. Schafer, "Theory and Application of Digital Speech Processing Preliminary Edition".
[2]. The newest breeds trade off speed, energy consumption, and cost to vie for an ever bigger piece of the action. BY JENNIFER EYRE Berkeley Design Technology Inc.
[3]. B. S. Atal, M. R. Schroeder, and V. Stover, "Voice- Excited Predictive Coding System for Low Bit-Rate Transmission of Speech", Proc. ICC, pp.30-37 to 30-40, 1975.
[4]. M. H Johnson and A. Alwan, "Speech Coding: Fundamentals and Applications", to appear as a chapter in the encyclopedia of telecommunications, Wiley, December 2002.
[5]. Sukriti Sharma, Charu, "Lossless Linear Predictive Coding For Speech Signals", International Journal of Science, Technology & Management, Volume No 04, Special Issue No. 01, March 2015, ISSN (online): 2394-1537.
[6]. Orsak, G.C rt al, "Collaborative SP education using the internet and MATLAB" IEEE Signal Processing Magazine, Nov, 2009 vol 12, no6, pp 23-32.
[7]. H. Huang, H. Shu, and R. Yu, "Lossless Audio Compression In The New IEEE Standard For Advanced Audio Coding", IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) 2014, pp 6984-6988.

Abstract: In recent years face recognition system play an important role in security systems used for wide range of applications like passport/ID card authentication, home security, criminal screening, surveillance, enterprise security and government events security. From the past three decades many algorithms were developed to face recognition. But, implementation and maintenance of this is still remained very challenging in real time applications due to high cost of hardware, software and maintenance. Keeping this in view an attempt has been made in the developed a low cost and portable an embedded system for facial recognition system. For implementation of hardware, UDOO quad board with camera used and for software, android kitkat-v.4.4.2 used.

[1]. Facial recognition applications," Animetrics. Retrieved, june 4,2008.
[2]. W.Zhao, R.Chellapa,A.Resenfeld and P.J. Phillips, "Face recognition: A literature survey," ACM Computing surveys, pp.399-458,2003.
[3]. T. Ojala and M. Pietikainen. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns, IEEE Trans on Pattern Analysis and Machine Intelligence, Vol. 24. No.7, July, 2002.
[4]. Hadid, M. Pietikainen and T. Ahonen. A Discriminative Feature Space for Detecting and Recognizing Faces. Proc of CVPR 2004.
[5]. S. Shihavuddin, M. M. N. Arefin, M.N. Ambia, SH.A. Haque and T. Ahammad, "Development of Real Time Face Detection System Using Haar-Like Features and AdaBoost Algorithm," Int. J. Computer Science and Network Security (IJCSNS), vol.10, no.1, January 2010.

Abstract: UAE Road accidents have increased significantly with an average of two people killed on the roads every day [1]. The impact of accidents are further more in dune buggy ,specifically when the driver involves in a high speed accident without wearing a helmet and seat belt. It is highly dangerous and can cause death. Wearing a seat belt and helmet can reduce shock from the impact and may save a life. The aim of this research work is to development of smart helmet detection system and seat belt detection system for dune buggy to avoid or reduce the accident fatigue on drivers during accident.

[1]. UAE road accidents [online] March 11 2015. http://7days.ae/two-killed-day-uae-road-accidents. [2]. Seat belt is the new ignition switch [online] February 21, 2012. [3]. http://www.thenational.ae/news/uae-news/seat-belt-is-the-new-ignition-switch-in-sharjah-tests [4]. Manjesh, Prof.Sudarshan Raj, Smart Helmet sing GSM & GPS technology for Accident Detection
[5]. And Reporting System, International Journal of Electric and Electronic Research, ISSN 2348-6988, Vol.2 Issue 4, Pages 122-127. [6]. Road accident happened in UAE [online] February 10, 2013.

Abstract: In this paper a novel configuration of dual slot based arraymicrostrip patch antennaof 32×46 mm² for C band application is simulated andanalyzed. Microstrip feed line location is optimized to get minimum return loss. Antenna characteristics were simulated using a Finite Integral Technique (FIT) based Computer Simulation Technology (CST). Antenna performance in term of return loss, radiationpattern and gain are analyzed. It is found that the antenna is resonant at 6GHzwith a return loss of -33dB and a stable radiation patterns. This antenna predict for successful satellite systems.

Keywords: C- band, RPAM, satellite, slotted, FIT.

[1]. H. M. Alam, M. R. Islam, S. Khan, "Design and analysis of UWB rectangular patch antenna," App. Elec. APACE 2007. Asia-Pacific Conference on, issue 1, pp. 1-3, Dec. 2007.
[2]. H. Okabe, C. Caloz, and T. Itoh, "A compact enhanced-bandwidth hybrid ring using a left-handed transmission line," IEEE Trans. Microw. Theory Tech., Vol. 52, No. 3, pp. 798-804, Mar. 2004.
[3]. W.L. Stutzman, G.A. Thiele, "Antenna Theory and design", John Wiley & Sons, 2nd Ed., New York, 1998.
[4]. C. A. Balanies, "Antenna Theory: Analysis & Design," John Willey & Sons, Inc., Boston, Dec. 1997.
[5]. S. Bhunia, "Microstrip Patch Antenna‟s Limitation and Some Remedies," International Journal of Electronics & Communication Technology, Vol. 4, ISSN: 2230-7109, Jan. – Mar. 2013.

Abstract: Historically, Telecom Networks were a Mixture of TDM/Circuit Switched and Packet/Datagram based and used techniques such as TDMoIP and IPoTDM for internetwork communication. Voice and Data Networks were separate. NGN was envisioned as a pathway towards a converged ALL-IP network capable to cater to Voice, Video and Data services. Around 2005, newer services such as SAN's, NAS's, CDN's, WSNs, Location Aware Services, BYOD, Data Centers, Cloud-Based Services, Big Data, XaaS, Internet of Things, Over-the-Top Content etc. were developed that required a more Flexible and Scalable network infrastructure. These services are Application Focused and require the network to be more Service-Centric than Infrastructure-Centric.

[1] Moindze, S.M. ; Konate, K. "A survey of the distributed network management models and architectures: Assessment and challenges", IEEE 6th International Conference on Adaptive Science & Technology (ICAST), 2014.
[2] Zhibo Pang ; Kan Yu ; Akerberg, J. ; Gidlund, M. , "An RTOS-based architecture for industrial wireless sensor network stacks with multi-processor support " IEEE International Conference on Industrial Technology (ICIT), 2013.
[3] Wang, Guixin ; Kang, Guixia ; Wang, Hao "Design and FPGA Implementation of MAC-PHY Interface Based on PCI Express for Next-Generation WLANs " 8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), 2012.
[4] Subin Shen ; Carugi, M. "Standardizing the Internet of Things in an evolutionary way ", Proceedings of the ITU Kaleidoscope Academic Conference: Living in a converged world - Impossible without standards, 2014.
[5] Stepanenko, A. and Constantinou, C. "Novel Topological Framework for Adaptive Routing ", IEEE Global Telecommunications Conference-GLOBECOM, 2009.

Abstract: Shadows cause problems in image processing. In this paper, a new methodology for shadow removal based on Strong Edge Detection (SED) method is proposed. The strong shadow edges are recognized by learning the patch based characteristics of shadow edges and then image features are analyzed to guide a Shadow Edge Classifier. Also, spatial patch smoothing is used to enforce uniformity between adjacent patches. The entropy and standard deviation results of both earlier Patch based Shadow Edge Detection Method and proposed SED method are calculated and compared with each other. The results show that the proposed SED method is better than the previous Patch Based Shadow Edge Detection method.

Keywords: Strong Edge Detection, Shadow Removal, Shadow Edge Classifier, Shadow Edges, Shadow Removal

[1]. Arbel E., Hel-Or H., Shadow Removal Using Intensity Surfaces and Texture Anchor Points, IEEE Transactions on Pattern Analysis and Machine Intelligence,33(6), 2011, 1202-1216.
[2]. Qi Wu, Wende Zhang and B.V.K. Vijaya Kumar, Strong Shadow Removal via Patch-Based Shadow Edge Detection, IEEE International Conference on Robotics and Automation, 2012, 2177-2182.
[3]. Huihui Song, Bo Huang; Kaihua Zhang, Shadow Detection and Reconstruction in High-Resolution Satellite Images via Morphological Filtering and Example-Based Learning, IEEE Transactions on Geoscience and Remote Sensing, 52(5), 2014, 2545-2554.
[4]. Khare M., Srivastava R.K., Khare A., Moving shadow detection and removal – a wavelet transform based approach, Computer Vision, IET, 8(6), 2014, 701-717.
[5]. Jaynes C., Webb S., Steele R.M., Camera-based detection and removal of shadows from interactive multiprojector displays, IEEE Transactions on Visualization and Computer Graphics, 10(3), 2004, 290-301.

Abstract: This paper is a part of an ongoing research on handover performance when a user seamlessly moves between different accesses technologies is called Vertical heterogeneous handover.It discussed some of the advances that have been made to reduce vertical handover (VHO) latency for successful handover especially in heterogeneous network environments. Video streaming and voice conversation across different network environment could pose serious challenges to the quality of service during handover. This is the reason why it is imperative that mechanism for maintaining quality of service during handover is considered seriously. This investigation is aimed at adopting a VHO Mobile IP schemeto Furtherreduce handover latency in heterogeneous wireless networks composed of WLAN and GPRS or 3G networks for increased QoS for video and voice streaming.

[1]. Abd-ElhamidTaha, M., HossamHassanein, S. and Hussein Mouftah, T. "Vertical handoffs as a radio resource management tool", Elsevier, Computer Communications, Vol. 31, pp. 950–961, 2008.
[2]. M. Vegni, M. Carli, A. Neri, and G. Ragosa, "QoS-based Vertical Handover in heterogeneous networks", in Proc. on Wireless PersonalMultimedia Communication, WPMC 2007, Jaipur, India, 4-6 Dec. 2007.
[3]. Banerjee N, Basu K, Das SK (2003). Hand-off delay analysis in SIPbased mobility management in wireless networks. IEEE International Conference on Parallel and Distributed Processing Symposium in USA, pp. 8-12.
[4]. Ben-Jye Chang and Jun-Fu Chen "Cross-Layer-Based Adaptive Vertical Handoff with Predictive RSS in Heterogeneous Wireless Networks", IEEE Transactions on Vehicular Technology, Vol. 57, No. 6, pp. 3679-3692, 2008.
[5]. Berezdivin R, Breinig R, Topp R (2002). Next-generation wireless communications concepts and technologies. Communications Magazine, IEEE, 40(3): 108-116.

Abstract: The Traffic causes major concern in many of the developing as well as developed countries. The proposed system is designed to get the smooth and efficient traffic flow for daily life as wellas emergency conditions and also to provide safety in public transport. It is installed at the traffic signal intersection which controls the traffic light signal at the intersection.The proposed system provide the timing to traffic light signal depending upon the densities on the road instead of the fixed time frames, so which resultsheavily loaded side turned on for longer time as compare to the other lanes.

[1]. Farooq, U.; Atiq, H.M.; Asad, M.U.; Iqbal, A.; Azmat, Z., "Design and Development of an Image Processing Based Adaptive Traffic Control System with GSM Interface," Machine Vision, 2009. ICMV '09. Second International Conference on , vol., no., pp.166,171, 28-30 Dec. 2009
[2]. Ospina, E.; Tascon, E.; Valencia, J.; Madrigal, C., "Traffic flow control using artificial vision techniques," Computing Congress (CCC), 2011 6th Colombian , vol., no., pp.1,4, 4-6 May 2011.
[3]. Zhijun Qiu; An, D.; Yao, D.; Zhou, D.; Bin Ran, "An adaptive Kalman predictor applied to tracking vehicles in the traffic monitoring system," Intelligent Vehicles Symposium, 2005. Proceedings. IEEE , vol., no., pp.230,235, 6-8 June 2005
[4]. Lei Xie; Guangxi Zhu; Yuqi Wang; Haixiang Xu; Zhenming Zhang, "Real-time vehicles tracking based on Kalman filter in a video-based ITS," Communications, Circuits and Systems, 2005. Proceedings. 2005 International Conference on , vol.2, no., pp.,886, 27-30 May 2005.