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Volume 4 , Issue 11, November 2015 (Title of Paper ) |
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Authors: Sugiono, A. Raharjo, Sujatmiko Abstract-- Indonesia has many islands which make the distribution of electricity difficult, especially in power cable network. This problem can be solved by independent electrical generator which must be easy to operate and maintenance. The use of cyclone turbine as low capacity electrical generator offer big potential to solve this problem. Normally cyclone wind turbine alone cannot generate sufficient speed to turn the generator to produce sufficient electrical power. But with the help of focused solar reflector we can heating up the air in the column bellow the cyclone turbine, so the hot air can produce thermal difference between air in the column with the air outside. With the thermal difference there be pressure difference also, that fasten the air flow through the cyclone turbine, which in the end can make the cyclone turbine produce enough speed to turn the generator so it can produce sufficient electrical power. Our study shows that with the use of solar reflector the temperature in air column can reach 45oC, the angular speed of cyclone turbine reach 120 rpm and thus generate electrical power. Keywords- solar reflector, cyclone turbine, electrical power. References- [1] Phil Ligrani, “Aerodynamic Losses in Turbines with and without Film Cooling, as Influenced by Mainstream Turbulence, Surface Roughness, Airfoil Shape, and Mach Number,” Hindawi Publishing Corp. International Journal of Rotating Machinery. Volume 2012, Article ID 957421. [2] M.F. Voneschen, “Savonius Wind Generator,” La Veritat (2008). [3] Hermsvicencio, ” Design Calculation of Savonius Wind Turbine” Scribd (2012). [4] Sdenne, “Savonius Wind Turbine – Using an Altenator as a Motor” Scribd (2013). [5] Hugh Piggott “A Wind Turbine Recipe Book” NA Digital Ed. (2014). [6] Hugh Piggott “A Wind Turbine Recipe Book” NA Digital Ed. (2014). M.M. EL-Wahit “Power Elektronic “, Tata. McGrawHill Company, (1997). [7] M.M. EL-Wahit ”Powerplant Technology”, McGraw-Hill Book Company, 1984. [8] Edward Wilson Kimbart” Power System Stability”, vol. 1’ Element of Stability Calclition, (1984) |
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Authors: Unung Lesmanah, Margianto Abstract-- Steel is a material widely use in engineering, especially in industrial world. Because its wide application, usually we need to tailor its mechanical properties so it suit our needs. Sometimes we need to perform heat treatment to changes its mechanical properties. Principally heat treatment process is we heating up the material above its recrystallize temperature. The change in its microstructure then will depend on the length of holding temperature and the cooling rate. With specific length of holding temperature and specific cooling rate, heat treatment can tailoring the mechanical properties of steel to suit the needs. (Hari Amanto. Daryanto, tt : 82). Carburizing is heat treatment which aim is to increasing the hardness of material surface. In this study we varying the holding time and quenching media to increase steel hardness. Our longtime goal are to find a way to enhance the mechanical properties of steel to accommodate industrial needs. The research methodology are experiment method with holding time variation of 1 hour, 2 hours, 3 hours, 4 hours and 5 hours, and quenching media variation of water, lubricating oil, and air. The material used are low carbon steel. The data is analyze with ANOVA and T test. Resulting data showed increase in hardness in specimen with longer holding time and quenching media of lubricating oil, with hardness value are 61.33 HRc, 67.33 HRc, 70 HRc, 74.33 HRc, 76.33 HRc, quenching media of water, the hardness value are 55 HRc, 62.67 HRc, 64.33 HRc, 67.67 HRc, 71,33 HRc and quenching media of air, the hardness value are 31 HRc, 42.67 HRc, 45 HRc, 47.33 HRc, 52.67 HRc. Keywords- Mechanical properties of steel, Hardness, Carburizing, Holding Time, Quenching. References- [1] Alois Schonmetz and Gruber K. “Pengetahuan Bahan dalam Pengerjaan Logam” Penerbit Angkasa, Bandung. 1994. [2] Amstead B. H. et all, “Manufacturing Process, in Canada, Published Simultaneously, 7th ed. 1979. [3] Asfarizal, “Peningkatan Kekerasan Dengan Metoda Karburasi Pada Baja Karbon Rendah Dengan Media Kokas”Jurnal Teknika No. 30 Vol. 1 Thn.XV November 2008, ISSN : 0854-8471. [4] Bambang Kuswanto, “Peningkatan Kekuatan Tarik Maksimum Material BajaKarbon Rendah Menggunakan Proses Penambahan Karbon Padat,” Journal Teknis Vol. 5 No. 3 Desember 2010, hal. 117 – 120. [5] Bhattacharya, Richard, “Statistical Concepts and Methods,” John Willey & Sons, New York. 1999. [6] Dieter, George E. “Metalurgi Mekanik” Jilid 1, 4th ed. Erlangga, Jakarta. 1993. |
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Features Essential in a Music Tutoring System for Learning South Indian Classical Music Authors: Arnita Saini, S. Nikhil Siva, Pradeep Yammiyavar Abstract— This paper reports the work done in identification of the essential features for the design of a Music Tutoring System for learning the South Indian Classical Music and the conceptualization of its Graphical User Interface. For this, surveys were conducted in two phases to understand the teaching styles and problems faced in the initial stages of learning of Western and Indian Classical Music. Further, an analysis of two of the existing Western Music Tutoring Systems was carried out based on the available literature and a generic framework of music tutoring was determined for which, the Kolb’s model of Experiential Learning was used. This was then compared with the results of the survey. In this comparison, the cultural differences and the differences in the music styles of Western and South Indian Classical Music were considered and used to outline a set of contextualized characteristics that a tutor of South Indian Carnatic Music should incorporate into its framework. Based on these features and characteristics, implications for graphical user interface and interaction design of such a tutor is subsequently suggested. Keywords—Computer Assisted Musical Tutoring, South Indian Classical (Carnatic) Music, Customizing Learning environments, Cultural adaptation, Kolb’s Model of Learning, Graphical User Interface, User-centred Design. References- [1] Askenfeld, A. et. al., 2002. IMUTUS An Interactive Music Tuition System. In: Acoustical Society of America Journal, 2348. [2] Carnaticindia, 2006. Learn Carnatic Music Online [online]. Available from: http://www.carnaticindia.com/learn_music.html, [Accessed 8th February 2014]. [3] Carnatic Music Basics, Geethams & Varnams Audio Lessons Archive [online]. Available from http://www.shivkumar.org/music/varnams/index.html, [Accessed 8th February 2014] [4] Carnatic Web Ring. Sishya - Carnatic Music Tutor [online]. Available from: http://carnatic2000.tripod.com/sishya.htm, [Accessed 8th February 2014]. [5] Dannenberg, R., B., et. al., 1989. Computer-Based Multi-Media Tutor for Beginning Piano Students, Journal of New Music Research, 19(2-3), 1990, pp. 155-173. [6] Dannenberg, R., B. et. al., 1993. Results from the Piano Tutor Project, In: Proceedings of the Fourth Biennial Arts and Technology Symposium, Connecticut College, pp. 143-150. [7] David and Chandrakantha Courtney, 2012. Music of India [online]. Available from: http://chandrakantha.com/articles/indian_music/violin.html, [Accessed 8th February 2014]. [8] Experience Based Learning Systems, Inc., 2012. Learning styles and disciplinary differences [online]. Available from: http://learningfromexperience.com/media/2010/08/Learning-stylesand-disciplinary-difference.pdf, 235-236 [Accessed 9th March 2014]. [9] Hofstede, G., 2001. Culture‘s Consequences: Comparing Values, Behaviors, Institutions, and Organizations Across Nations, Second Edition, Thousand Oaks CA: Sage Publications. [10] Krishnaswamy, A., Multi-Dimensional Musical Atoms In South Indian Classical Music. [online] Available from: https://ccrma.stanford.edu/~arvindh/cmt/icmpc04.pdf, [Accessed 8th March 2014]. [11] Pesch, L.,2009. The Oxford Illustrated Companion to South Indian Classical Music. New Delhi: Oxford University Press. [12] Raptis, S. et. al., 2005. IMUTUS – An Effective Practicing Environment For Music Tuition. In: Proceedings of International Computer Music Conference, United States, 383-386. [13] Webster, P., R., 2005. Computer-Based Technology and Music Teaching and Learning [online]. Available from: http://www.peterrwebster.com/pubs/Bresler.pdf, [Accessed 9th March 2014]. |
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Acceleration Framework using MicroBlaze Soft-core Processors on FPGAs Authors: Shrikant Jadhav, Christopher Doss, Clay Gloster, Youngsoo Kim Abstract— Offloading the complex computational kernel from the processor is the common way to improve performance of embedded system. In our work we are using MicroBlaze softcore processor in design and implementation of acceleration framework. In acceleration framework MicroBlaze is coupled with co-processor with the help of communication bus. We can attach the co-processor to our design that can handle the computation part. This co-processor helps to offload the burden on the MicroBlaze and thus reduces clock cycles needed for computation. In this paper we provide the acceleration framework to compute floating point natural logarithm value. The hardware implemented floating point natural logarithm unit is connected as co-processor to MicroBlaze. Xilinx provide a way to connect MicroBlaze processor and co-processor with the help of Fast Simplex Link (FSL). The FSL is used as mode of communication between floating point natural logarithm unit (co-processor) to MicroBlaze processor. We have implemented this framework on Virtex 5 and Zynq-7000. Our design consumes 28% on Zynq-7000 and 59% on Virtex 5 of the resources on FPGA. We compared the time in milliseconds required to execute different number of samples on (MicroBlaze processor + co-processor) design, on MicroBlaze soft-core processor. Our acceleration framework has achieved approximately 527x speedup on Zynq 7000 (100 MHz) over MicroBlaze soft-core design. Keywords—Field Programmable Gate Arrays (FPGA); MicroBlaze processor; soft-core; co-processor; acceleration framework; Fast Simplex Link (FSL); Floating point Natural Logarithm Unit. References- [1] S. Borgio, D. Bosisio, F. Ferrandi, M. Monchiero,M. Santambrogio, D. Sciuto, and A. Tumeo. Hardware dwt accelerator for multiprocessor system-on-chip on fpga. In Embedded Computer Systems: Architectures, Modeling and Simulation, 2006. ICSAMOS 2006. International Conference on, pages 107–114, July 2006. [2] M. Calvio, S. Geninatti, and J. Benitez. Developing an mmx extension for the microblaze soft processor. In Reconfigurable Computing and FPttAs, 2008. ReConFig ’08. International Conference on, pages 91– 96, Dec 2008. [3] C. Choo, P. Padmanabhan, and S. Mutsuddy. An embedded adaptive filtering. [4] E.-H. El Mimouni and M. Karim. A microblazebased multiprocessor system on chip for real-time cardiac monitoring. In Multimedia Computing and Systems (ICMCS), 2014 International Conference on, pages 331–336, April 2014. [5] J. Kadlec, R. Bartosinski, and M. Danek. Accelerating microblaze floating point operations. In Field Programmable Logic and Applications, 2007. FPL 2007. International Conference on, pages 621–624, Aug 2007. [6] J. Lazanyi. Instruction set extension using microblaze processor. In Field Programmable Logic and Applications, 2005. International Conference on, pages 729–730, Aug 2005. [7] J. A. Nelder and R. Mead. A simplex method for function minimization. Computer Journal, 7:308–313, 1965. [8] M. Ouellette and D. Connors. Analysis of hardware acceleration in reconfigurable embedded systems. In Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS’05) - Workshop 3- Volume 04, IPDPS ’05, pages 168.1–, Washington, DC, USA, 2005. IEEE Computer Soc iety. [9] N. K. Pham, A. K. Singh, A. Kumar, and K. M. M. Aung. Design space exploration to accelerate neldermead algorithm using fpga. In Proceedings of the 2014 IEEE 22Nd International Symposium on FieldProgrammable Custom Computing Machines, FCCM ’14, pages 100–, Washington, DC, USA, 2014. IEEE Computer Society. [10] A. Tumeo, M. Monchiero, G. Palermo, F. Ferrandi, and D. Sciuto. A pipelined fast 2d-dct accelerator for fpga-based socs. In Proceedings of the IEEE Computer Society Annual Symposium on VLSI, ISVLSI ’07, pages 331–336, Washington, DC, USA, 2007. IEEE Computer Society. [11] S. Xu and H. Pollitt-Smith. A multi-microblaze based soc system: From systemc modeling to fpga prototyping. In Rapid System Prototyping, 2008. RSP ’08. The 19th IEEE/IFIP International Symposiumon,pages121–127,June2008. |
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CFD Analysis of Air Conditioning Equipment of CAD Lab for Enhancing its Performance Authors: K Vaseemul Rahaman , Prof. Shankar Kumar Abstract— Thermal displacement ventilation (TDV) is a promising technology for all types of buildings. The potential energy efficiency, health, and acoustic benefits offer promise government of various countries are prepared to spend billions on new educational institutes and major modernization. This paper presents some results from Computational fluid dynamics (CFD) analysis which is needed in order to model and study the complex flows associated with TDV.CFD is an established, state-of-the-art scientific approach for quantitative prediction and analysis of fluid flow, heat and mass transfer in a multiplicity of conditions. In 1995, the Government Accounting Office concluded that 25% of the nation’s schools are inundated by indoor air quality (IAQ) problems. A few years later the Environmental Protection Agency reported that an even higher percentage of buildings have IAQ problems. Most of these IAQ problems can be recognized to poor ventilation. TDV, which has been used since the late 1980s in Northern Europe and only more recently in U.S., disproves the common perception that improving IAQ in an air-conditioned space should effect the higher energy consumption. Keywords— TDV, CFD simulation, ventilation, heating, temperature, thermal comfort. References- [1] Guangyu Cao , HazimAwbi , Runming Yao, Yunqing Fan , Kai Sirén , RistoKosonen ,Jianshun (Jensen) Zhang , A review of the performance of different ventilation and airflow distribution systems in buildings, Building and Environment 73 (2014) 171-186. [2] Li Yang , Miao Ye, Bao-Jie he, CFD simulation research on residential indoor air quality, Science of the Total Environment 472 (2014) 1137–1144. [3] Delia D'Agostino*, Paolo Maria Congedo, CFD modeling and moisture dynamics implications of ventilation scenarios in historical buildings, Building and Environment 79 (2014) 181-193. [4] Simon J. Rees a, Philip Haves , An experimental study of air flow and temperature distribution in a room with displacement ventilation and a chilled ceiling, Building and Environment 59 (2013) 358-368. [5] Xiaozhou Wu a,b, Bjarne W. Olesen b, Lei Fang b, Jianing Zhao a,*, A nodal model to predict vertical temperature distribution in a room with floor heating and displacement ventilation, Building and Environment 59 (2013) 626-634. [6] Tomohiro Kobayashi, TomoyukiChikamoto, KeishiOsada, Tomohiro Kobayashi, TomoyukiChikamoto, KeishiOsada, Building and Environment 63 (2013) 20-30 [7] R. Tomasi, M. Krajˇcik , A. Simonec, B.W. OlesencExperimental evaluation of air distribution in mechanically ventilated residential rooms: Thermal comfort and ventilation effectiveness, Energy and Buildings 60 (2013) 28–37. [8] Wei-Hwa Chiang, Chia-Ying Wang, Jian-Sheng Huang, Evaluation of cooling ceiling and mechanical ventilation systems on thermal comfort using CFD study in an office for subtropical region, Building and Environment 48 (2012) 113-127. [9] Fatima ZohraChafi, Stephane Halle, Three dimensional study for evaluating of air flow movements and thermal comfort in a model room: Experimental validation, Energy and Buildings 43 (2011) 2156–2166. [10] R. Whalley, A. Abdul-Ameer, Heating, ventilation and air conditioning system modelling, Building and Environment 46 (2011) 643-656. [11] Fatima ZohraChafi, StéphaneHallé, Evaluating of air flow movements and thermal comfort in a model room with Euler equation: Two dimensional study, Building and Environment 46 (2011) 448-456 [12] K.-S. Kwon ,d, I.-B. Lee a , H.-T. Han, C.-Y. Shin, H.-S. Hwang, S.- W. Hong ,Jessie. P. Bitog , I.-H. Seo , C.-P. Han , Analyzing ventilation efficiency in a test chamber using age-of-air concept and CFD technology, i o s y s t ems engi n e e r i n g 1 1 0 ( 2 0 1 1 ) 4 2 1 -4 3 3 [13] A.C.K. Lai, K.W. Mui, L.T. Wong, L.Y. Law, An evaluation model for indoor environmental quality (IEQ) acceptance in residential buildings, Energy and Buildings 41 (2009) 930–936. [14] Anita Coulter Flowe, Ashok Kumar, Analysis of velocity fields and dispersive cavity parameters as a function of building width to building height ratio using a 3-D computer model for squat buildings, Journal of Wind Engineering and Industrial Aerodynamics 86 (2000) 87-122. [15] G. Einberg, K. Hagstrom, P. Mustakallio, H. Koskela, S. Holmberg, CFD modelling of an industrial air diffuser—predicting velocity and temperature in the near zone, Building and Environment 40 (2005) 601–615. [16] H. Lee, H.B. Awbi, E ect of internal partitioning on indoor air quality of rooms with mixing ventilation—basic study, Building and Environment 39 (2004) 127 – 141. [17] K. Visagaval, P.S.S. Srinivasan, Analysis of single side ventilated and cross ventilated rooms by varying the width of the window opening using CFD, Solar Energy 83 (2009) 2–5. [18] K.W. Mui, L.T. Wong, W.L. Ho, Evaluation on sampling point densities for assessing indoor air quality, Building and Environment 41 (2006) 1515–1521. [19] MiroslawZukowski, Modeling and designing heating and ventilation system withunderfloor air distribution, Energy and Buildings 38 (2006) 600–609 [20] Liang Zhou, FariborzHaghighat, Optimization of ventilation system design and operation in office environment, Part I: Methodology, Building and Environment 44 (2009) 651–656. [21] L.T. Tan, S.C. Sekhar , Optimization of cooling coil performance during operation stage for improved humidity control, Energy and Buildings 41 (2009) 229–233. [22] L.T. Wong_, K.W. Mui1, K.L. Shi, Energy impact of indoor environmental policy for air-conditioned offices of Hong Kong, Energy Policy 36 (2008) 714–721. [23] M.A. Hassan, N.M. Guirguis, M.R. Shaalan, K.M. El-Shazly, Investigation of effects of window combinations on ventilation characteristics for thermal comfort in buildings, Desalination 209 (2007) 251–260. [24] Monika Woloszyn, Joseph Virgone, Stephane Melen, Diagonal airdistribution system for operating rooms: experiment and modeling, Building and Environment 39 (2004) 1171 – 1178. [25] N.P. Gao, J.L. Niu, M. Perino, P. Heiselberg, The airborne transmission of infection between flats in high-rise residential buildings: Tracer gas simulation,Building and Environment 43 (2008) 1805-1817. [26] P. Rohdin, B. Moshfegh, Numerical predictions of indoor climate in large industrial premises.A comparison between different k–e models supported by field measurements, Building and Environment 42 (2007) 3872–3882. [27] P.S. Hui, L.T. Wong, K.W. Mui, Evaluation of professional choice of sampling locations for indoor air quality assessment, Building and Environment 42 (2007) 2900–2907. |
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Result on Fixed Point for Convex Metris Space taking Random Operator for Kannan type Mapping Authors: Nidhi Gargav, Rajesh Shrivastava, Rizwana Jamal Abstract-- The aim of the present paper is to prove the existence of fixed points for Kannan mappings in convex metric spaces for random operator. The results are generalization forms of some known results. Keywords-- Convex metric space, Common fixed point, Random operators, Kannan Type mappings. AMS Classifications: 47H10 References- [1] Beg, I. and Shahzad, N. “Random fixed points of random multivalued operators on Polish spaces” Nonlinear Anal. 20 (1993) no. 7, 835-847. [2] Beg, I. and Azam, AN. “fixed point theorems for Kannan Mappings”. Indian journal of Pure and applied mathematics17(11) (1986). 1270-1275. [3] Beg, I. and Shahzad, N. “Random fixed points of weakly inward operators in conical shells” J. Appl. Math, Stoch. Anal. 8(1995) 261- 264. [4] Bharucha –Reid, A.T. Fixed point theorems in probabilistic analysis, Bull. Amer. Math. Soc.82 (1976) 641-657. [5] Choudhary, B.S. and Ray, M. “Convergence of an iteration leading to a solution of a random operator equation” J. Appl. Math. Stochastic Anal. 12 (1999). No 2,161-168 . [6] Choudhary, B.S. and Upadhyay, A. “An iteration leading to random solutions and fixed points of operators” Soochow J. Math.25 (1999). No 4,395-400. [7] Choudhary, B.S. “A common unique fixed point theorem for two random operators in Hilbert spaces” I. J. M.M. S. 32 (2002) 177- 182. [8] Guay, M.D. ,Singh, K. L. and J. H. M. Whitfield, Proceedings, Conference on Nonlinear Analysis (ed. By S. P. Singh and J. H. Burry) Marcel Dekker Vol, 80, (1982), pp. 179-89 [9] Himmelbeg, C.J. “Measurable relations” Fund. Math.87 (1975) 53- 72. [10] Lin, T.C. “Random approximations and random fixed point theorems for continuous 1-set- contractive random amps” Proc. Amer. Math. Soc. 123(1995) 1167-1176. [11] O’Regan, D. “A continuous type result for random operators” Proc. Amer. Math. Soc. 126 (1998) 1963-1971 [12] Papageorgiou, N.S. “Random fixed point theorems for measurable multifunction in Banach space” Proc. Amer. Math. Soc.97 (1986), no. 3, 507-514. [13] Plubtieng, S., Kumam, P. and Wangkeeree, R. “Approximation of a common fixed point for a finite family of random operators” International J. of Math. And Mathematical sciences (2007) 1-12. [14] Sehgal, V.M. and Waters, C. “Some random fixed point theorems for condensing operators” Proc. Amer. Math. Soc. 90(1984), no.3, 425-429. [15] L. A. Talman, Kodai Math. Sem. Rep. 29(1973),62-70. [16] W. Takahashi, “A convexity in metric spaces and nonexpensive mappings” Kodai Math. Sem. Rep.22 (1970) 142-149. [17] Xu, H.K. “Some random fixed point theorems for condensing and nonexpansive operators” Proc. Amer. Math. Soc. 110 (1990), no.2395-400. |
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