Volume-5 Issue-6

S. No

Volume-5 Issue-6, January 2016, ISSN: 2231-2307 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Stephen Diang’a, Wanyona Githae, Ng’ang’a Kibe

Paper Title:

Assessment of Health and Safety Management on Construction Sites in Kenya

Abstract:       The construction industry is an important part of the economy in many countries and is often seen as a driver of economic growth especially in developing countries. Owing to its relatively labour intensive nature, construction works provide opportunities for employment for a wide range of people skilled, semi-skilled and unskilled. Despite its importance, construction industries are considered risky with frequent accidents rates and ill health problems to workers, practitioners and end users. However, knowledge on how health and safety risks are managed on public construction sites in Kenya is limited. This study therefore, aims to find out the current practice of health and safety management on public construction sites in Nairobi County, Kenya, A cross sectional descriptive study was carried out in randomly selected public construction sites. Questionnaires were used for collection of qualitative and quantitative data from contractors and workers on public construction sites. Descriptive statistics was used for data analysis. The study concludes that the most common cause of injuries is tools and equipments, slips and over extortion respectively, with fire explosion and electricity and transport trailing the list, the management teams were commitment toward implementing the safety measures. Training influences the implementation health and safety measures

Keywords: industry, Owing, countries, implementation, Descriptive statistics, respectively, Kenya

References:
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1-3

2.

Authors:

Afolayan Abimbola Helen, Ojokoh Bolanle A., Falaki Samuel O.

Paper Title:

Comparative Analysis of Rainfall Prediction Models Using Neural Network and Fuzzy Logic

Abstract:     Rainfall is a stochastic process, whose upcoming event depends on some precursors from other parameters such as temperature, surface pressure and other atmospheric parameters.Accurate information about rainfall is necessary for the use and management of water resources. Nonetheless, rainfall is one of the most complex and difficult elements in hydrology due to the tremendous range of variation over a wide range of scales both in space and time. Forecasting techniques such as Artificial Neural Network (ANN) and Fuzzy Logic (FL) have been used to study rainfall. This research work is motivated by the need to compare ANN and FL models to know which one is more efficient in predicting rainfall. The rainfall datasets used in this research work were collected from an automatic weather station in Iju, a town in Akure North Local Government Area of Ondo State for the period of four years (2007-2010). The model comparison is based on four criteria; the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), prediction error, and the prediction accuracy. The error measures are comparable for the two models. The analysis of the models accuracy, shows that, overall, the ANN model perform slightly better than the FL model in terms of PE, RMSE, MAE andaccuracy.

Keywords: Forecasting, Fuzzy Logic, Neural Networks, ,Rainfall

References:
1.          Agboola A. H, Iyare O,Falaki S.O (2012). An Artificial Neural Network Model for Rainfall Forecasting in South-Western Nigeria. Canadian Journal on Computing in Mathematics, Natural Sciences, Engineering and Medicine, Vol. 3 No. 6, pages 188-196, November 2012.
2.          Agboola A.H, Gabriel A.J., Aliyu E.O. and Alese B.K. (2013). Development of a Fuzzy Logic Based Rainfall Prediction Model. International Journal of Engineering and Technology, Volume 3 No. 4, April, 2013.
3.          Akinyokun, O.C. (2002); “Neuro-fuzzy Expert system for Evaluation of Human Resources  Performance”: First Bank of Nigeria PLC Endowment Fund Lecture, The Federal University of Technology Akure, Nigeria.
4.          Bardossy, A., Duckstein L. and Bogardi I. (1995); “Fuzzy rule-based classification of atmospheric circulation patterns”: Int. J. Climatol., 15: 1087-1097.
5.          Baum, B.A., Tovinkere V., Titlow J. and Welch R.M. (1997) “Automated cloud classification of global AVHRR data using a fuzzy logic approach”: J. Applied Meteorol., 36: 1519-1540.
6.          Chin, E.H (1977); “Modeling daily precipitation occurrence process with Markov chain”: Water Resources Research 13: 949-956.
7.          Edvin and Yudha (2008); “Application of Multivariate ANFIS for Daily Rainfall Prediction: Influences Of Training Data Size”:Makara, Sains, Volume 12, No. 1, April 2008: 7-14 7.
8.          Fujibe F. (1989); “Short-term precipitation patterns in central Honshu, Japan-classification with the fuzzy c-means method”: J. Meteorol. Soc. Jap., 67: 967-982.
9.          Galambosi, A., Duckstein L., Ozelkan E. and I. Bogardi, 1999. Fuzzified effect of ENSO and macro circulation patterns on precipitation: An Arizona case study. Int. J. Climatol., 19: 1411-1426.
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12.       Halide, H. and Ridd P. (2002): “Modeling inter-annual variation of a local rainfall data using a fuzzy logic technique”: Proceedings of International Forum on Climate Prediction, 2002, James Cook Universiy, Australia, pp: 166-170.
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4-7

3.

Authors:

D. Mondal, R. Bera, M. Mitra

Paper Title:

Design and Implementation of an IntegratedRadar and Communication System for Smart Vehicle

Abstract:    This paper addresses the development efforts towards realization of Smart vehicle. Commercial Vehicles with multiple radars has the limitation of more false detection as the  detection technology is based on ‘ Skin’ mode of radar operation and the radar receives its transmitted energy after reflection from the body of the target vehicles. The ‘Transponder’ mode of radar operation will definitely improve the false detection leading to CAWAS system (Collision Avoidance and Warning System). The Vehicles will be the ‘friends’ to each other by integrating the local radar mounted on each vehicle with Vehicular Communication. The authors have developed one such CAWAS model utilizing the VLSI based advanced development platforms. This paper will highlight the achievements and limitations of the developed model.

Keywords: CAWAS system (Collision Avoidance and Warning System)., Intra Vehicle Link (IVL)  Short range ( SRR) and Long range ( LRR), ACC (Adaptive Cruise Control)., VLSI ,Vector Signal Generator (VSG) , Software Defined Radio (SDR), Time Correlation Function(TCF) 

References:
1.             ECC REPORT 56, ‘Compatibility of Automotive collision warning short range radar operating at 79 GHz with radio communication services’,  Stockholm, October 2004.
2.             Intelligent Transport System and CALM, ITU-T Technology watch report 1 , Oct 2007.
3.             Barrientos et al, ‘CAWAS: Collision Avoidance and Warning system for Automotives based on Satellite’, 8th International IEEE Conference on Intelligent Transportation Systems Vienna, Austria, September 13-16, 2005.
4.             http:www.lyrtech.com
5.             A Menhajyx et al., ‘A new collision avoidance radar system using correlation receiver and compressed pulses’ , Meas. Sci. Technol. 9 (1998) 283–286, IOP Publishing Ltd.  

8-12

4.

Authors:

Patrick Kanini Ngata, Githae Wanyona, Anthony Kiplimo

Paper Title:

Assessment of Strategies for Practices of Quality Management in Construction Projects. A Review of the Knowledge for Practice

Abstract:    Strategic planning is a tool for organizing the present on the basis of the projections of the desired future. That is, a strategic plan is a road map to lead an organization from where it is now to where it would like to be in five or ten years in the future. In Kenya, there is failure in construction to achieve quality as seen in the frequent occurrence of building failure and collapsing (Mutoro, 2011). The aim of this study is to investigate the strategic factors that would enhance quality management implementation in the construction process. As the key to value creation, construction firms are deemed to treat quality as a strategic issue (Agbenyega, 2014). The main methods used in this journal is collection of data by survey, where questionnaires were distributed to 52 construction projects in progress within Kiambu County and then the data acquired was sorted  using SPSS software. The writer approached the study using the positivist paradigm which enabled the researcher to make an objective analysis. This stance facilitated the researcher to use the quantitative research strategy and also questionnaire survey as the main data collection instrument for soliciting information from construction firms registered with the National Construction Authority and professionals registered with professional bodies recognised by the Kenyan government. The aim of the study was to describe strategic factors applied to quality management on construction projects.

Keywords: Quality, Strategies, Practices, Quality management.

References:
1.        Abdel-Razek, R.H., El-Dosouky, A.I. and Solaiman, A.M. (2001). A Proposed Method to Measure Quality of the Construction Project. International Exhibition
Conference for Building & Construction, Egypt.
2.        Adams &Bradt (2002). Construction Management. In Debella (2004) Construction Delivery Systems: A comparative Analysis of the Systems. Unpublished Thesis.
3.        Atkinson, G. (2005). Construction Quality and Quality Standards, The European Perspective, London: E & FN SPON
4.        Atkin, B., Borgbrant, J., & Josephson, P. E. (Eds.). (2008). Construction process improvement. John Wiley & Sons.
5.        Australian government (2014), your home, Retrieved 29th September2014, retrieved from http://www.yourhome.gov.au/
6.        Babbie.E. (2004). The Practice of Social Research. 10th Edition. Thomson-Wadsworth.
7.        Barrett, P. (2000). Systems and Relationship for Construction Quality. International Journal of Quality & Reliability Management, Vol.17 No. 4/5
8.        Berg, B. L., Lune, H., & Lune, H. (2004). Qualitative research methods for the social sciences (Vol. 5). Boston, MA: Pearson.
9.        Chan, A. P., & Chan, A. P. (2004). Key performance indicators for measuring construction success. Benchmarking: an international journal, 11(2), 203-221.
10.     Chartered Institute of Building.(2002). Code of Practice for Project Management for Construction and Management. Third Edition. Blackwell
11.     Chung, H. (1999) Understanding Quality Assurance in Construction – A practical guide to ISO 9000. Bodmin: Spon.
12.     Clarke, T. (2003) Managing Health and Safety in Building and Construction. Heinemann.
13.     Construx, (2003), ‘Defining a Quality Plan’ (www.sasqag.org/pastmeetings/QualityPlans.pdf. (Accessed on 2nd September, 2013)
14.     Dale, B. G., Van Der Wiele, T., & Van Iwaarden, J. (2013). Managing quality. New York: John Wiley & Sons.
15.     David L. Goetsch, & Davis, S. (2010). Quality management for organizational excellence: Introduction to total quality. New York: Pearson Education International.
16.     Delgado-Hernandez, DJ and Aspinwall, E (2008) Quality management case studies in the UKconstruction industry. Total Quality Management and Business Excellence,Abingdon: 19 (9).
17.     Evans, J. R., & Lindsay, W. M. (2005). The management and control of quality (pp. pp-687). Mason, OH: South-Western.
18.     Egan, J (1998) Rethinking Construction. Report of the Construction task force on the scopefor improving the quality and efficiency of UK construction, London: DETR. Fewings, P. (2013). Construction Project Management: an integrated approach. New York:  Routledge.
19.     Fryer, B, Egbu, C, Ellis, R and Gorse, C (2004) The Practice of Construction Management, 4th Ed, Blackwell Publishing.
20.     Guide, A. (2008). PROJECT MANAGEMENT BODY OF KNOWLEDGE (PMBOK® GUIDE). In Project Management Institute.
21.     Griffith, A and Bhutto, K. (2009) Managing quality, safety and environment as one. Proceedings of Institution of Civil Engineers, 162, 11.
22.     Griffith, A and Howarth, T (2001) Construction Health and Safety Management, Longman.
23.     Griffith, A and Watson, P. (2004) Construction Management – Principles and Practice, Palgrave MacMillan.
24.     Harris, F., & McCaffer, R. (2013). Modern construction management. New York: John Wiley & Sons.
25.     Haupt, TC and Whiteman, DE (2004) Inhibiting factors of implementing total qualitymanagement on construction site. The TQM Magazine, 16 (3), 166.
26.     Hughes, W., Champion, R., & Murdoch, J. (2007). Construction contracts: law and management. New York: Routledge.
27.     Joppe, M. (2000). The research process. New York: Routledge.
28.     Juran, J.M. and Gyrna, F.M., (1999). Quality Planning and Analysis.  McGraw-Hill.
29.     Kaynak, H. (2003). The relationship between total quality management practices and their effects on firm performance. Journal of operations management, 21(4), 405-435.
30.     Karim, S. B. A., (2007).  Management in Construction and Researchers Association (MICRA). Meetings and Conference, 28-29 Aug 2007, Shah Alam, Selangor, Malaysia.
31.     Kelessidis, V. (2000). Report produced for the EC funded Project INNOREGIO-Benchmarking. Thessaloniki, Technology Park.
32.     Kivaa P.M (2008). A system dynamics model of construction output in Kenya. Melbourne: RMIT university press.
33.     Kuta, J., & Nyaanga, D. M. (2013) the effect of competence of contractors on the construction of substandard buildings in Kenya. Nairobi: Nairobi university press
34.     Latham, Sir M (1994) Constructing the Team, London: HMSO.
35.     Marasini, R., & Quinnell, P. (2010). Investigation of Quality Management practices in Building Construction Sites in the UK. London: Oxford publishers
36.     March, C (2009) Operations Management for Construction, Spon Press- Taylor and Francis.
37.     McCaffer, R., & Harris, F. (2001). Modern construction management. London: Oxford publishers
38.     McGeorge, D., & Zou, P. (2012). Construction management: new directions. New York: John Wiley & Sons.
39.     Mugenda, O. M. & Mugenda, A. G. (1999). Research Methods. Quantitative and Qualitative Approaches. Nairobi: Acts Press.
40.     Mutai B.K. (2000). How to Write Quality Research Proposal: A Complete and Simplified Recipe. Thelley
41.     Skogestad, S., & Postlethwaite, I. (2007). Multivariable feedback control: analysis and design (Vol. 2). New York: Wiley.

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5.

Authors:

Elias Nyaga Nelson, Ahmad Omar Alkizim, Anthony Kiplimo Mutai

Paper Title:

An Assessment of the Significant Bottlenecks Towards Adoption of Information and Communication Technology by Kenyan Building Contractors

Abstract:    In the competitive market of the construction industry, construction firms attempt to implement projects within the least cost and time, and the highest quality. One of the factors that has been established to affect these parameters is the utilization of information and communication technology (ICT) Many ICT platforms have been developed to help in execution of projects. Kenyan construction firms have attempted to utilize several of them. However, many of the contractors have not managed to adopt many of the available ICT platforms This research explored the factors that hinder the Kenyan building contractors from achieving higher levels of ICT adoption. Eighty construction firms were selected mainly in class NCA1 and NCA2 through sampling. Practitioners directly involved in project implementation within various construction firms were interviewed to establish the factors that hinder them from achieving higher levels of this ICT adoption. The responses were analyzed and a narrative interpretation developed which established that the most prevalent factor hindering adoption is the rapid changes in ICT technologies, high cost of employing ICT professionals, satisfaction with the existing method of working, Inadequate knowledge about return on ICT investment, high cost of training ICT professionals and inadequate financial resources.

Keywords: Construction, Information and communication technology

References:
1.          Ahuja V. (2009) Study of ICT adoption for building project management in the Indian construction industry,   Automation in Construction, 18, 415-23,
2.          Ardagh, (2007) “a strategic view of RFID in construction”, RFID Centre Ltd in association with Construction Industry Computing Association. October, 2007.
3.          Arif, A. A. & Karam, A. A. 2001. Architectural Practices and their use of IT in the Western Cape province, South Africa.Itcon, 6, 17-33. at http://itcon.org/2001
4.          Barrie, D. S. & Paulson, B. C. (1992). Professional construction management: including CM, design-construct, and general contracting., 3rd ed. London: McGraw-Hil
5.          Becerik (2004), A review on past, present and future of web based project management & collaboration tools and their adoption by the US AEC industry”, International Journal of IT in Architecture, Engineering and Construction, Volume 2, Issue #, October 2004, P 233- 248
6.          Chen,Y., and Kamara, J. (2008). “The mechanisms of information communication on construction sites.”
7.          Cohen, J. (1992). A power primer. Psychological bulletin, 112(1), 155
8.          Dainty et al. ( 2006). Communication in construction: Theory and practice.
9.          Egbu, C.O. and Botterill, K. (2002) Information technologiesfor knowledge management: their use and effectiveness. Electronic Journal of Information Technology in Construction(ITcon), 7,
10.       El-Ghandour W. and Al-Hussein. (2004). Information technology applications in construction”, Construction Innovation, 3, 83-98
11.       Enshassi et al.( 2003).Contributors to construction delays in Palestine, The Journal of American institute of constructors, Vol. 27, No. 2, pp. 45-53
12.       Field J. (2005). Social capital and lifelong learning Bristol: policy press
13.       Financial Stability report for 2011, Central Bank of Kenya
14.       Goh B. (2005). IT barometer 2003: Survey of the Singapore construction industry and a comparison of results. Journal of Information Technology in Construction (ITcon), Vol. 10, No. 1, 1-13.
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22-27

6.

Authors:

Saadi Turied Kurdi, Hassan Abad al-wahab Anjal, Hussein Ahmed Abd Yaqoob

Paper Title:

Experimental Investigation of Performance Parameters of Direct Injection Diesel Engine Fuelled with Diesel and Ethanol Blends

Abstract:     An experimental study of the measurement of performance parameters of a single cylinder four stroke diesel engine using diesel fuel produced in Iraq and blended with ethanol was carried out. The test fuels were used in this study included E0 Beji (100 % diesel Beji fuel), E0 Basra (100 % diesel Basra fuel), E0 Daura (100 % diesel Daura fuel), E8 blended (8% ethanol and 92% diesel Basra fuel  in vol.), and E10 blended (10% ethanol and 90% diesel Basra  fuel in vol.). The experimental measurements were performed at compression ratio of 22.5 at engine speed ranging from 1100 to 2600 rpm with an increment of 500 rpm, and engine torque ranging from 2 to 10 N.m with an increment of 2 N.m. Brake specific fuel consumption, brake thermal efficiency, brake power, mechanical efficiency, brake mean effective pressure and exhaust gas temperature were studied in this research. The experimental data from engine during test have been saved on the computerized program (ECA 100, VDAS) connected to the unit.The results show that the E8 blended fuel type registered the high value of brake specific fuel consumption .There were about 28.02 % for E8 blended fuel, 20.88 % E0 Beji fuel, 19.2 % for E0 Basra fuel,  and 8.24% for E10 blended fuel higher of brake specific fuel consumption than that E0 Daura fuel. E0 Daura fuel type registered the high value of brake thermal efficiency followed by E0 Basra, E10 blended, and other types. E0 Daura fuel type recorded the high value of mechanical efficiency. E10 slightly recorded the higher value of brake mean effective pressure for all torques and speeds. E0 Basra diesel fuel gives higher exhaust gas temperature for all torques and speeds.

Keywords: Diesel fuel; ethanol; Brake Specific Fuel Consumption; Indicated Power; Exhaust Gas Temperature .

References:
1.       Creating Markets for Renewable Energy Technologies EU RES Technology Marketing Campaign," Bioethanol Production and Use", EUROPEAN BIOMASS INDUSTRY ASSOCIATION, pp.63-65, Rue d’Arlon, B-1040 Brussels,2006  
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28-34

7.

Authors:

Peter Dabnichki, Dilshat Djumanov

Paper Title:

On-line Computer Test System for Remote Assessment of Neurological Patients: Part A Standard Computer Interface Application

Abstract:      The work presents a development of an on-line system for neurological tests. A variety of congruent, non-congruent and bradikinesia tests are described. The system is aimed at patients with a variety of neurological disorders and has been tested on Multiple Sclerosis and Parkinson Disease sufferers. The current implementation uses standard PC/laptop/tablet interface and is considered appropriate for conducting unsupervised in house tests. The main aim of this development is to facilitate a link between patient, personal clinician and specialist neurologist to allow speedy assessment of treatment effectiveness and on-time interventions. The main achievement is improved accuracy of time measurement allowing for the better differentiation in the disease progression assessment and/or earlier diagnosis.

Keywords: presents, development, disease progression assessment and/or earlier diagnosis..

References:
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35-41

8.

Authors:

Peter Dabnichki, Damian Poveda, Dilshat Djumanov

Paper Title:

On-line Computer Test System for Remote Assessment of Neurological Patients: Part B Dedicated Device and Web Portal

Abstract:    The work presents a proprietary development of a device specifically designed to be used in conjunction with the on-line system for neurological tests presented in part A of this work. The device was specifically developed for supervised tests where patients are asked to complete a sequence of tests for potential early diagnosis of neurological conditions. The device achieves very good accuracy of 2-5 ms and further allows measuring the applied force in real time. The software connects to a web portal allowing remote participation of a neurologist and is expected to enable better group differentiation among patients in terms of disease type, progression and treatment response.

Keywords: presents a proprietary development, differentiation among patients in terms of disease type

References:
1.           Pervasive computing systems for medical monitoring Proceedings of the 1st WSEAS international conference on Biomedical electronics and biomedical informatics, D. Djumanov, P. Dabnichki, R. Arezina, World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA, ISBN: 978-960-6766-93-0, 2008, pp. 168-172
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42-47

9.

Authors:

S. Sujatha, P. Raja, P. Dananjayan

Paper Title:

Modified SLM Combined with Interleaving and Pulse Shaping Method for PAPR Reduction using DCT and IDCT in MIMO-OFDM System

Abstract:     Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is a most enthralling technology which has been recently proposed in wireless communication. It provides high data rate services and offer better system performances. It improves data throughput and delivers highest capacity as well. However, MIMO-OFDM suffers with the disadvantage of high peak-to-average power ratio (PAPR) for the large number of subcarriers which can effect the system output. Therefore, to overcome the problem of high PAPR in OFDM systems, an effective technique called Modified selective mapping (SLM) is used along with Inverse Discrete Cosine Transform (IDCT) matrix combined with interleaveing and pulse shaping to reduce the peak-to-average power ratio on both transmitter and receiver sides. By simulation results, it is seen that the proposed technique reduces PAPR.

Keywords: MIMO-OFDM,interleaving,pulseshaping, IDCT, PAPR

References:
1.          K. Muralibabu and Dr. M .Sundhararajan, “DCT Based PAPR and ICI Reduction Using Companding Technique in MIMO-OFDM System”, International Journal of Advanced Research in Computer Science and Software Engineering 3(8), August – 2013.
2.          Mehboob Ul Amin, Randhir Singh and Javaid.A.Skeikh, “A New Method for PAPR Reduction in MIMOOFDM Using Combination of OSTBC Encoder and DCT Matrix”, International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-2, Issue-2, May 2013.
3.          Karima El Mouhib and Ahmed Oquour, “PAPR Reduction Using BPSO/PTS and STBC in MIMO OFDM System”, Journal of Computer Science 7.4 (2011).
4.          Emmanuel MANASSEH, Shuichi OHNOy and Yong JIN, “Minimization of PAPR in MIMO-OFDM Systems by Tone Reservation Techniques and Pilot Tones”, APSIPA ASC 2011.
5.          Narmatha.T and Sathish Kumar.K, “An Enhanced Algorithm for Papr Reduction in MIMO OFDM/A”, IJARCST 2014.
6.          P.Mukunthan and P.Dananjayan, “A Modified PTS Combined with Interleaving and Pulse Shaping Method Based on PAPR Reduction for STBC MIMO-OFDM System”, WSEAS Transactions on Communications 12.3 (2013). 7.          Seyran Khademi and Alle-Jan van der Veen, “Constant Modulus Algorithm for Peak-to-Average Power Ratio (PAPR) Reduction in MIMO OFDM/A”, IEEE Signal Processing Letters, Vol. 20, No. 5, May 2013.
8.          Gamal Mabrouk Abdel–Hamid, Sahar Abdel- Rahman and Hala Gaber Farrag, “Performance Improvement of MIMO-OFDM Wireless Systems using PAPR Reduction Techniques”, International Journal of Computer Applications (0975 – 8887) Volume 53– No.18, September 2012.
9.          ÖĞR.GÖR. MURAT TÖREN, “PAPR Reduction with Wavelet Transform and Different PAPR Reduction Tecniques in MIMO-OFDM Systems”, Journal of Engineering and Architecture, Vol. 1 No. 2, December 2013.
10.       Chin-Liang Wang, Shun-Sheng Wang and Hsiao-Ling Chang, “A Low-Complexity SLM Based PAPR Reduction Scheme for SFBC MIMO-OFDM Systems”, Wireless Communications and Networking Conference (WCNC), 2011 IEEE.
11.       Seyran Khademi, Alle-Jan Van der Veen and Thomas Svantesson, “Precoding Technique for Peak-To-Average-Power-Ratio (Papr) Reduction in Mimo Ofdm/A Systems”, Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on IEEE 2012.
12.       Christoph Stude and Erik G. Larsson, “PAR-Aware Large-Scale Multi-User MIMO-OFDM Downlink”, IEEE Journal on Selected Areas in Communications, Vol. 31, No. 2, February 2013.
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48-55

10.

Authors:

Duong Trong Luong, Nguyen Minh Duc, Nguyen Tuan Linh, Nguyen Thai Ha, Nguyen Duc Thuan

Paper Title:

Advanced Two-State Compressing Algorithm: A Versatile, Reliable and Low-Cost Computational Method for ECG Wireless Applications

Abstract:      Compressing the ECG signal is considered a feasible solution for supporting a system to manipulate the package size, a major factor leading to congestion in an ECG wireless network. Hence, this paper proposes a compression algorithm, called the advanced two-state algorithm, which achieves three necessary characteristics: a) flexibility towards all ECG signal conditions, b) the ability to adapt to each requirement of the package size and c) be simple enough. In this algorithm, the ECG pattern is divided into two categories: “complex” durations such as QRS complexes, are labelled as low-state durations, and “plain” durations such P or T waves, are labelled as high-state durations. Each duration type can be compressed at different compression ratios, and Piecewise Cubic Spline can be used for reconstructing the signal. For evaluation, the algorithm was applied to 48 records of the MIT-BIH arrhythmia database (clear PQRST complexes) and 9 records of the CU ventricular tachyarrhythmia database (unclear PQRST complexes). Parameters including Compression Ratio (CR), Percentage Root mean square Difference (PRD), Percentage Root mean square Difference, Normalized (PRDN), root mean square (RMS), Signal-to-noise Ratio (SNR) and a new proposed index called Peak Maximum Absolute Error (PMAE) were used to comprehensively evaluate the performance of the algorithm. Eventually, the results obtained were positive with low PRD, PRDN and PMAE at different compression ratios compared to many other loss-type compressing methods, proving the high efficiency of the proposed algorithm. All in all, with its extremely low-cost computation, versatility and good-quality reconstruction, this algorithm could be applied to a number of wireless applications to control package size and overcome congested situations.

Keywords: ECG compression, Telemedicine, ECG pattern classification, adaptive package size.

References:
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11.

Authors:

Kh. Sh. Mohamed, Xiong Yan, Zhengxue Li, Z. A. Habtamu, Abdrhaman. M. Adam

Paper Title:

Boundedness and Convergence of Batch Gradient Method for Training Pi-Sigma Neural Network with Inner-Penalty and Momentum

Abstract:       In the process industries convergence of  a batch gradient method with inner-penalty and adaptive momentum is inspection  for training pi-sigma neural networks. The role of the usual penalty is considered, which is a term proportional to the norm of the weights to control the magnitude of the weights and improve the generalization performance of the network. The monotonicity theorem and two convergence theorems of our gradient algorithm with inner-penalty term is guaranteed during the training iteration.

Keywords:  Convergence, pi-sigma neural network,  batch gradient method,  inner-penalty, momentum, boundedness

References:
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12.

Authors:

Fagun Vankawala, Amit Ganatra

Paper Title:

Modified Landweber Algorithm for Deblur and Denoise Images

Abstract: In this paper, we introduced modified algorithm based on traditional Landweber deblurring algorithm for reducing amount of blur and noise from satellite images. Blur image is general issue in image processing and it is hard to avoid. Image enhancement in terms of deblurring and denoising are necessary to reduce blur amount as well as noise from the image. There are few deblurring algorithms exist to deblur an image. However, if noise is present, they perform poorly. By using proposed algorithm, we get better results in terms of PSNR, execution time and complexity with blurry as well as noisy images.

Keywords:    Image Deblurring, Image Denoising, Convolution, Point Spread Function (PSF), Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE).

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