Review of Energy Efficient Techniques of IoT

The network across which the information is sensed by the sensor devices and then forwarded to the sink is known as Internet of Things (IoT). Even though this system is deployed in several applications, there are certain issues faced in it due to its dynamic nature. The internet of things is derived from the wireless sensor networks. The sensor nodes which are deployed to sense environmental conditions are very small in size and also deployed on the far places due to which energy consumption is the major issue of internet of things. This research work related to reduce energy consumption of the network so that lifetime can be improved. In the existing system the approach of multilevel clustering is used for the data aggregation to base station. In the approach of multilevel clustering, the whole network is divided into clusters and cluster heads are selected in each cluster. The energy efficient techniques of internet of things are reviewed and analyzed in terms of certain parameters

Fault diagnosis of wind turbine with SCADA alarms based multidimensional information processing method

This paper presents a first attempt to use Dempster-Shafer (D-S) evidence theory for the fault diagnosis of wind turbine (WT) on SCADA alarm data. As two important elements in D-S evidence theory, identification framework (IF) and Basic Probability Assignment (BPA) are derived from WT maintenance records and SCADA alarm data. A procedure of multi-dimensional information fusion for WT fault diagnosis is presented. The diagnosis accuracy using BPAs obtained from a sample WT and from the wind farm are compared and evaluated. The result shows that D-S evidence theory as a multidimensional information processing method is useful for WT fault diagnosis. Compared to previous SCADA alarms processing methods, the approach proposed predominates at aspects of simple calculation, superior capability on dealing with large volume of alarms through quantifying fault probabilities. It has the advantages of being easy to perform, low cost and explainable, which make it ideal for online application. A self-BPA-generating procedure for future online application with this approach is also provided in this paper. It is concluded that D-S evidence theory applied to SCADA alarm analysis is a valuable approach to intelligent wind farm management

Distributed compression for condition monitoring of wind farms

A good understanding of individual and collective wind farm operation is necessary for improving the overall performance of the wind farm “grid,” as well as estimating in real time the amount of energy that can be generated for effectively managing demand and supply over the smart grid. This paper proposes a scheme for compressing wind speed measurements exploiting both temporal and spatial correlation between the readings via distributed source coding. The proposed scheme relies on a correlation model based on true measurements. Two compression schemes are proposed, both of low encoding complexity, as well as a particle-filtering-based belief propagation decoder that adaptively estimates the nonstationary noise of the correlation model. Simulation results using realistic models show significant performance improvements compared to the scheme that does not dynamically refine correlation

The Compression Of Electric Signal Waveforms For Smart Grids: State Of The Art And Future Trends

In this paper, we discuss the compression of waveforms obtained from measurements of power system quantities and analyze the reasons why its importance is growing with the advent of smart grid systems. While generation and transmission networks already use a considerable number of automation and measurement devices, a large number of smart monitors and meters are to be deployed in the distribution network to allow broad observability and real-time monitoring. This situation creates new requirements concerning the communication interface, computational intelligence and the ability to process data or signals and also to share information. Therefore, a considerable increase in data exchange and in storage is likely to occur. In this context, one must achieve an efficient use of channel communication bandwidth and a reduced need of storage space for power system data. Here, we review the main compression techniques devised for electric signal waveforms providing an overview of the achievements obtained in the past decades. Additionally, we envision some smart grid scenarios emphasizing open research issues regarding compression of electric signal waveforms. We expect that this paper will contribute to motivate joint research efforts between electrical power system and signal processing communities in the area of signal waveform compression. © 2010-2012 IEEE.51291302Gu, I.Y.-H., Styvaktakis, E., Bridge the gap: Signal processing for power quality applications (2003) Signal processing, 66 (1), pp. 83-96. , JulRibeiro, M.V., Szczupak, J., Iravani, M.R., Gu, I.Y.-H., Dash, P.K., Mamishev, A.V., Emerging signal processing techniques for power quality applications (2007) EURASIP J. Adv. Signal Process, 2007 (2), pp. 16-16. , http://dx.doi.org/10.1155/2007/87425, Jun. [Online]. AvailableBollen, M.H.J., Gu, I.Y.-H., Santoso, S., McGranaghan, M.F., Crossley, P.A., Ribeiro, M.V., Ribeiro, P.F., Bridging the gap between signal and power (2009) IEEE Signal Process. Mag., 26 (4), pp. 12-31. , JulBollen, M.H.J., Ribeiro, P.F., Gu, I.Y.-H., Duque, C.A., Trends, challenges and opportunities in power quality research (2009) Eur. Trans. Electr. Power, 4 (1), pp. 2-18Bollen, M.H.J., (2000) Understanding Power Quality Problems-Voltage Sags and Interruptions, , Piscataway, NJ USA: IEEE PressBollen, M.H.J., Gu, I.Y.-H., (2006) Signal Processing of Power Quality Disturbances, , New York: Wiley-IEEE PressMehta Ketan, Data compression for digital data from power systems disturbances: Requirements and technique evaluation (1989) IEEE Transactions on Power Delivery, 4 (3), pp. 1683-1688. , DOI 10.1109/61.32659Toivonen, L., Morsky, J., Measurement and processing of distortion quantities in a portable, multi-purpose analyzer (1993) IEEE Trans. Power Del., 8 (4), pp. 1736-1746. , Oct(2011) Smart Grid, , http://www.oe.energy.gov/smartgrid.htm, U.S. Department of Energy, Jun. [Online]. AvailableAmin, S.M., Wollenberg, B., Toward a smart grid: Power delivery for the 21st century (2005) IEEE Power Energy Mag., 3 (5), pp. 34-41. , Sep.-OctVu, K., Begouic, M.M., Novosel, D., Grids get smart protection and control (1997) IEEE Comput. Apps. Power, 10 (4), pp. 40-44. , OctVojdani, A., Smart integration (2008) IEEE Power Energy Mag., 6 (6), pp. 71-79. , Nov.-DecIpakchi, A., Albuyeh, F., Grid of the future (2009) IEEE Power Energy Mag., 7 (2), pp. 52-62. , Mar.-Apr(2011) Smart Grid Demonstration-integration of Distributed Energy Resources, , http://www.smartgrid.epri.com/Demo.aspx, EPRI [Online]. Available JunAlbu, M.M., Neurohr, R., Apetrei, D., Silvas, I., Federenciuc, D., Monitoring voltage and frequency in smart distribution grids. A case study on data compression and accessibility (2010) Proc. IEEE PES Gen. Meet., pp. 1-6Abart, A., Lugmair, A., Schenk, A., Smart metering features for managing low voltage distribution grids (2009) Proc. 20th CIRED-Part, 2, p. 1Zhang, D., Bi, Y., Zhao, J., A new data compression algorithm for power quality online monitoring (2009) Proc. SUPERGEN'09, pp. 1-4Chicco, G., Challenges for smart distribution systems: Data representation and optimization objectives (2010) Proc. 12th OPTIM, pp. 1236-1244Albu, M.M., Neurohr, R., Apetrei, D., Silvas, I., Federenciuc, D., Monitoring voltage and frequency in smart distribution grids. A case study on data compression and accessibility (2010) Proc. PES Gen. Meet., pp. 1-6Ning, J., Wang, J., Gao, W., Liu, C., A wavelet-based data compression technique for smart grid (2011) IEEE Trans. Smart Grid, 2 (1), pp. 212-218. , MarDas, S., Rao, P., Principal component analysis based compression scheme for power system steady state operational data (2011) IEEE PES Innov. Smart Grid Technol.-India, pp. 95-100Parseh, R., Acevedo, S.S., Kansanen, K., Molinas, M., Ramstad, T.A., Real-time compression of measurements in distribution grids (2012) Proc. IEEE 3rd Int. Conf. Smart Grid Commun. (SmartGridComm.), pp. 223-228Recommended practice on monitoring electric power quality (2009) Ieee p1159/p6Bingham, R.P., Kreiss, D., Santoso, S., Advances in data reduction techniques for power quality instrumentation (1995) Proc. 3rd Eur. Power Quality Conf., , Bremen, GermanyWilkinson, W.A., Cox, M.D., Discrete wavelet analysis of power system transients (1996) IEEE Transactions on Power Systems, 11 (4), pp. 2038-2044Pillay, P., Bhattacharjee, A., Application of wavelets to model short-term power system disturbances (1996) IEEE Trans. Power Syst., 11 (4), pp. 2031-2037. , NovToivonen, L., Morsky, J., Measurement and processing of distortion quantities in a portable, multi-purpose analyzer (1993) IEEE Trans. Power Del., 8 (4), pp. 1736-1746. , OctKhan, A.K., Monitoring power for the future (2001) Power Engineering Journal, 15 (2), pp. 81-85Heydt, G.T., Gunther, E., Post-measurement processing of electric power quality data (1996) IEEE Trans. Power Del., 11 (4), pp. 1853-1859. , OctSantoso, S., Powers, E.J., Grady, W.M., Power quality disturbance data compression using wavelet transform methods (1997) IEEE Trans. Power Del., 12 (3), pp. 1250-1257. , JulHsieh, C.-T., Huang, S.-J., Huang, C.-L., Data reduction of power quality disturbances - A wavelet transform approach (1998) Electric Power Systems Research, 47 (2), pp. 79-86. , PII S0378779698000431Chung, J., Powers, E.J., Grady, W., Bhatt, S.C., Variable rate power disturbance signal compression using embedded zerotree wavelet transform coding (1999) Proc. 1999 IEEE Power Eng. Soc. Winter Meet., 2, pp. 1305-1309. , Jan.-4 FebLittler, T.B., Morrow, D.J., Wavelets for the analysis and compression of power system disturbances (1999) IEEE Trans. Power Del., 14 (2), pp. 358-364. , AprHeydt, G.T., Bhatt, S.C., Present and future trends and needs in electric power quality sensors and instrumentation (1999) Elect. Mach. Power Syst., 27 (7), pp. 691-700Hamid, E.Y., Kawasaki, Z.-I., Wavelet-based data compression of power system disturbances using the minimum description length criterion (2002) IEEE Transactions on Power Delivery, 17 (2), pp. 460-466. , DOI 10.1109/61.997918, PII S0885897702032776Panda, G., Dash, P.K., Pradhan, A.K., Meher, S.K., Data compression of power quality events using the slantlet transform (2002) IEEE Transactions on Power Delivery, 17 (2), pp. 662-667. , DOI 10.1109/61.997957, PII S0885897702011755Hsieh, C.-T., Huang, S.-J., Disturbance data compression of a power system using the huffman coding approach with wavelet transform enhancement (2003) IEE Proc. Gener., Transm., Distrib., 150 (1), pp. 7-14. , JanDash, P.K., Panigrahi, B.K., Sahoo, D.K., Panda, G., Power quality disturbance data compression, detection, and classification using integrated spline wavelet and s-transform (2003) IEEE Trans. Power Del., 18 (2), pp. 595-600. , AprWu, C.-J., Fu, T.-H., Huang, C.-P., Data compression technique in recording electric arc furnace voltage and current waveforms for tracking power quality (2003) Proc. IEEE PES Transm. Distrib. Conf. Expo., 1, pp. 383-388Shang, L., Krebs, J.J.R., Efficiency analysis of data compression of power system transients using wavelet transform (2003) Proc. IEEE Bologna Power Tech. Conf., 4, p. 6Meher, S.K., Pradhan, A.K., Panda, G., An integrated data compression scheme for power quality events using spline wavelet and neural network (2004) Elect. Power Syst. Res., 69 (2-3), pp. 213-220Gerek, O.N., Ece, D., 2-d analysis and compression of power-quality event data (2004) IEEE Trans. Power Del., 19 (2), pp. 791-798. , AprHuang, S.-J., Jou, M.-J., Application of arithmetic coding for electric power disturbance data compression with wavelet packet enhancement (2004) IEEE Trans. Power Syst., 19 (3), pp. 1334-1341. , AugLorio, F., Magnago, F., Analysis of data compression methods for power quality events (2004) 2004 IEEE Power Engineering Society General Meeting, 1, pp. 504-509. , 2004 IEEE Power Engineering Society General MeetingYuan, Y., Yu, X., Du, H., Power system fault data compression using the wavelet transform and vector quantification (2006) Proc. IEEE POWERCOM, Oct., pp. 1-6Gerek, O.N., Ece, D.G., Compression of power quality event data using 2D representation (2008) Electric Power Systems Research, 78 (6), pp. 1047-1052. , DOI 10.1016/j.epsr.2007.08.006, PII S0378779607001769Qing, A., Hongtao, Z., Zhikun, H., Zhiwen, C., A compression approach of power quality monitoring data based on two-dimension dct (2011) Proc. ICMTMA'11, 1, pp. 20-24Lovisolo, L., Da Silva, E.A.B., Rodrigues, M.A.M., Diniz, P.S.R., Efficient coherent adaptive representations of monitored electric signals in power systems using damped sinusoids (2005) IEEE Transactions on Signal Processing, 53 (10), pp. 3831-3846. , DOI 10.1109/TSP.2005.855400Tcheou, M.P., Lovisolo, L., Da Silva, E.A.B., Rodrigues, M.A.M., Diniz, P.S.R., Optimum rate-distortion dictionary selection for compression of atomic decompositions of electric disturbance signals (2007) IEEE Signal Processing Letters, 14 (2), pp. 81-84. , DOI 10.1109/LSP.2006.882117Lovisolo, L., Tcheou, M.P., Da Silva, E.A.B., Rodrigues, M.A.M., Diniz, P.S.R., Modeling of electric disturbance signals using damped sinusoids via atomic decompositions and its applications (2007) EURASIP J. Adv. Signal Process, 2007, p. 15. , Article ID 29 507Ribeiro, M.V., Romano, J.M.T., Duque, C.A., An enhanced data compression method for applications in power quality analysis (2001) IECON Proceedings (Industrial Electronics Conference), 3, pp. 676-681Ribeiro, M.V., Duque, C.A., The word length influence on waveform coding techniques based on wavelet transform applied to disturbance compression (2002) Proc. 10th IEEE ICHQP, 1, pp. 139-143Ramos, F.R., Riberto, M.V., Romano, J.M.T., Duque, C.A., On signal processing approach for event detection and compression applied to power quality evaluation (2002) Proc. 10th EEE ICHQP, 1, pp. 133-138Ribeiro, M.V., Romano, J.M.T., Duque, C.A., An improved method for signal processing and compression in power quality evaluation (2004) IEEE Trans. Power Del., 19 (2), pp. 464-471. , AprRibeiro, M.V., Park, S.H., Romano, J.M.T., Mitra, S.K., A novel MDL-based compression method for power quality applications (2007) IEEE Transactions on Power Delivery, 22 (1), pp. 27-36. , DOI 10.1109/TPWRD.2006.887091Yun, Z., Xiaoming, L., Lingxu, A., Jian, S., Lihui, W., Research on encoding/decoding method of electric physical information based on lms-adpcm algorithm (2011) Proc. Int. Conf. Adv. Power Syst. Autom. Protection, 1, pp. 795-800Kraus, J., Tobiska, T., Bubla, V., Looseless encodings and compression algorithms applied on power quality datasets (2009) Proc. 2nd IEEE CIRED-Part 1, pp. 1-4Kraus, J., Stepan, P., Kukacka, L., Optimal data compression techniques for smart grid and power quality trend data (2012) Proc. IEEE ICHQP, pp. 707-712Recommended Practice for the Transfer of Power Quality Data, , IEEEP1159.3/D9Tse, N.C.F., Chan, J.Y.C., Lai, L.L., Development of a smart metering scheme for building smart grid system (2009) Proc. 8th APSCOM, pp. 1-5Zhang, M., Li, K., Hu, Y., A high efficient compression method for power quality applications (2011) IEEE Trans. Instrum. Meas., 60 (6), pp. 1976-1985. , JunXu, W., Component modeling issues for power quality assessment (2001) IEEE Power Eng. Rev., 21 (11), pp. 12-15. , 17 NovRibeiro, M.V., Pereira, J.L.R., Classification of single and multiple disturbances in electric signals (2007) EURASIP J. Adv. Signal Process., 2007 (2), p. 18. , JunInterharmonics: Theory and modeling (2007) IEEE Trans. Power Del., 22 (4), pp. 2335-2348. , IEEE Task Force on Harmonics Modeling and Simulation OctIeee, , http://grouper.ieee.org/1433, IEEE PES Working Group 1433 Power Quality [Online]. AvailableSchweitzer Edmund, O., Hou Daqing, Filtering for protective relays (1993) Communications, Computers and Power in the Modern Environment, pp. 15-23Wiot, D., A new adaptive transient monitoring scheme for detection of power system events (2004) IEEE Trans. Power Del., 19 (1), pp. 42-48Lobos, T., Rezmer, J., Koglin, H.-J., Analysis of power systems transients using wavelets and prony method (2001) Proc. IEEE Porto Power Tech. Conf., 4, pp. 1-4Tawfik, M.M., Morcos, M.M., ANN-based techniques for estimating fault location on transmission lines using prony method (2001) IEEE Transactions on Power Delivery, 16 (2), pp. 219-224. , DOI 10.1109/61.915486, PII S0885897701015394Bujanowski, B.J., Pierre, J.W., Hietpas, S.M., Sharpe, T.L., Pierre, D.A., A comparison of several system identification methods with application to power systems (1993) Proc. 36th MWSCAS, 1, pp. 64-67Galli, A.W., Heydt, G.T., Ribeiro, P.F., Exploring the power of wavelet analysis (1996) IEEE Comput. Appl. Power, 9 (4), pp. 37-41. , OctChung, J., Powers, E.J., Grady, W.M., Bhatt, S.C., Electric power transient disturbance classification using wavelet-based hidden Markov models (2000) Proc. IEEE ICASSP, 6, pp. 3662-3665Pillay, P., Bhattachrjee, A., Application of wavelets to model shortterm power systemdisturbances (1996) IEEE Trans. Power Syst., 11 (4), pp. 2031-2037. , NovPoisson, O., Rioual, P., Meunier, M., Detection and measurement of power quality disturbances using wavelet transforms (2000) IEEE Trans. Power Del., 15 (3), pp. 1039-1044. , JulLiao, H.Y.C., A de-noising scheme for enhancing wavelet-based power quality monitoring systems (2001) IEEE Trans. Power Del., 16 (3), pp. 353-360. , JulSantoso, S., Grady, W.M., Powers, E.J., Lamoore, J., Bhatt, S.C., Characterization of distribution power quality events with fourier and wavelets transforms (2000) IEEE Trans. Power Del., 15 (1), pp. 247-254. , JanKarimi, M., Mokhtari, H., Iravani, M.R., Wavelet based on-line disturbance detection for power quality applications (2000) IEEE Transactions on Power Delivery, 15 (4), pp. 1212-1220. , DOI 10.1109/61.891505Anis Ibrahim, W.R., Morcos, M.M., Artificial intelligence and advanced mathematical tools for power quality applications: A survey (2002) IEEE Transactions on Power Delivery, 17 (2), pp. 668-673. , DOI 10.1109/61.997958, PII S0885897702027474Gosh, A.K., Lubkeman, D.L., The classification of power system disturbance waveforms using a neural network approach (1995) IEEE Trans. Power Del., 10 (1), pp. 109-115. , JanLovisolo, L., Figueiredo, K.T., Laporte Menezes, L.De., Neto, J.A.M., Dos Santos Rocha, J.C., Location of faults generating short duration voltage variations in distribution systems regions from records captured at one point and decomposed into damped sinusoids IET Gener., Transm., Distrib., , Accepted for publicationYang, Q., Wang, J., Sima, W., Chen, L., Yuan, T., Mixed over-voltage decomposition using atomic decompositions based on a damped sinusoids atom dictionary (2011) Energies, 4 (9), pp. 1410-1427Ribeiro, M.V., Marques, C.A.G., Duque, C.A., Cerqueira, A.S., Pereira, J.L.R., Detection of disturbances in voltage signals for power quality analysis using HOS (2007) EURASIP J. Adv. Signal Process., 2007 (2), p. 13. , JunSayood, K., (2000) Introduction to Data Compression, , 2nd ed. San Francisco, CA, USA: Morgan KaufmanBell, T.C., Witten, I.H., Cleary, J.G., (1990) Prentice Hall, , Text Compression/Timothy C. Bell, John G. Cleary, Ian H. Witten. Englewood Cliffs, NJ, USA: Prentice-HallQing, A., Hongtao, Z., Zhikun, H., Zhiwen, C., A compression approach of power quality monitoring data based on two-dimension dct (2011) Proc. 3rd ICMTMA, 1, pp. 20-24Tcheou, M.P., Miranda, A.L., Lovisolo, L., Da Silva, E.A., Rodrigues, M.A., Diniz, P.S., How far can one compress digital fault records analysis of a matching pursuit based algorithm (2012) Digit. Signal Process., 22 (2), pp. 288-297Nascimento, F.A.O., Data compression algorithm for transient recording system (1997) Proc. IEEE ISIE, 3, pp. 1126-1130Mallat, S., (1998) A Wavelet Tour of Signal Processing, , 2nd ed. San Diego, CA, USA: AcademicDaubechies, I., (1991) Ten Lectures on Wavelets, , Philadelphia PA USA: SIAMShapiro, J.M., Embedded image coding using zerotrees of wavelet coefficients (1993) IEEE Trans. Signal Process, 41 (12), pp. 3445-3462. , DecLiu, S., An adaptive Kalman filter for dynamic estimation of harmonic signals (1998) Proc. 8th IEEE ICHQP, 2, pp. 636-640Romano, J.M.T., Bellanger, M., Fast least squares adaptive notch filtering (1988) IEEE Trans. Acoust., Speech, Signal Process, 36 (9), pp. 1536-1540. , SepDiniz, P.S.R., (2008) Adaptive Filtering: Algorithms and Practical Implementations, , 3rd ed. Boston, MA, USA: SpringerCheng, Y.T., TMS320C62x Algorithm: Sine wave generation (2000) Texas Instruments, Dallas, TX, USA, Tech. Rep., , NovSaito, N., Simultaneous noise suppression and signal compression using a library of orthonormal bases and the minimum description length criterion (1994) Wavelets in Geophysics, pp. 299-324. , San Diego, CA, USA: AcademicKrim, H., Tucker, D., Mallat, S., Donoho, D., On denoising and best signal representation (1999) IEEE Transactions on Information Theory, 45 (7), pp. 2225-2238. , DOI 10.1109/18.796365Krim, H., Schick, I.C., Minimax description length for signal denoising and optimized representation (1999) IEEE Trans. Inf. Theory, 45 (3), pp. 898-908. , AprHansen, M., Yu, B., Wavelet thresholding via MDL for natural images (2000) IEEE Trans. Inf. Theory, 46 (5), pp. 1778-1788. , AugChang, S.G., Yu, B., Vitterli, M., Adaptive wavelet thresholding for image denoising and compression (2000) IEEE Trans. Image Process, 9 (9), pp. 1532-1546. , SepRissanen, J., Modeling by shortest data description (1978) Automatica, 14, pp. 465-471Barron, A., Rissanen, J., Yu, B., The minimum description length principle in coding and modeling (1998) IEEE Transactions on Information Theory, 44 (6), pp. 2743-2760. , PII S0018944898052845Mallat, S., Zhang, Z., Matching pursuitswith time-frequency dictionaries (1993) IEEE Trans. Signal Process, 41 (12), pp. 3397-3415. , DecGalli, S., Scaglione, A., Wang, Z., For the grid and through the grid: The role of power line communications in the smart grid (2011) Proc. IEEE, 99 (6), pp. 998-1027. , JunGharavi, H., Hu, B., Multigate communication network for smart grid (2011) Proc. IEEE, 99 (6), pp. 1028-1045. , JunSauter, T., Lobashov, M., End-to-end communication architecture for smart grids (2011) IEEE Trans. Ind. Electron., 58 (4), pp. 1218-1228. , AprGomez-Exposito, A., Abur, A., Jaen Villa A.De, La., Gomez Quiles, C., A multilevel state estimation paradigm for smart grids (2011) Proc. IEEE, 99 (6), pp. 952-976. , JunArnold, G.W., Challenges and opportunities in smart grid: A position article (2011) Proc. IEEE, 99 (6), pp. 922-927. , Junhttp://www.powermonitors.com, Power Monitors Inc. [Online]. Available(1998) Method for Objective Measurements of Perceived Audio Quality, , ITU-R Rec. BS.1387 Geneva, Switzerland ITUWang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., Image quality assessment: From error visibility to structural similarity (2004) IEEE Trans. Image Process., 13 (4), pp. 600-612. , AprKezunovic, M., Rikalo, M., Automating the analysis of faults and power quality (1999) IEEE Comput. Appl. Power, 12 (1), pp. 46-50. , JanStankovic, V., Stankovic, L., Shuang, W., Cheng, S., Distributed compression for condition monitoring of wind farms (2013) IEEE Trans. Sustain. Energy, 4 (1), pp. 174-181. , Ja