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International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 8, August 2016

Optimized Coating Design of Energy Saving Glass Using Binary Harmony Search for Better Transmission Signal M.I. Jasmi Optimisation, Modelling, Analysis, Simulation and Schedulling (OptiMASS) Research Group Universiti Teknikal Malaysia Melaka 76100 Durian Tunggal, Melaka, Malaysia. [email protected]

A.F.N.A. Rahman Optimisation, Modelling, Analysis, Simulation and Schedulling (OptiMASS) Research Group Universiti Teknikal Malaysia Melaka 76100 Durian Tunggal, Melaka, Malaysia. [email protected]

Z.A. Abas Optimisation, Modelling, Analysis, Simulation and Schedulling (OptiMASS) Research Group Universiti Teknikal Malaysia Melaka 76100 Durian Tunggal, Melaka, Malaysia. [email protected]

A.S. Shibghatullah Optimisation, Modelling, Analysis, Simulation and Schedulling (OptiMASS) Research Group Universiti Teknikal Malaysia Melaka 76100 Durian Tunggal, Melaka, Malaysia. [email protected]

Abstract—In recent years, buildings are designed with conventional glass for window and roof top as the outer shell that brings exposure from dangerous UV rays / dangerous hazard light/ heat. Instead of using existing type of glass, a special coated glass is applied to the surface of the window in order to maintain internal temperature at a suitable condition and also to save energy. In fact, the coated glass not only protects the building from extreme temperature but also attenuates the transmission of GSM, GPS and communication signal in wireless connection. However, the problem of attenuation in transmission signal occurred contributes to poor communication within the buildings when the regular shape design of energy saving glass coating is used. Therefore, to overcome the attenuation problem, a new technique is introduced, which a new glass coating design is implemented, based on the mathematical formulation model using optimization approach. The optimization technique used in this research is the harmony search that optimizes the coating design structure on the glass with the binary contribution which enhanced the transmission signal. Moreover, the new design of the coated glass that optimized the designed in binary structure is laminated as a glass coating design at the CST Microwave Studio. The result from the experiments conducted showed that parameter of frequency, return loss, s- parameter, transmission coefficient and efficiency have been measured which the outcome of this research has contribute to efficiency of 99.83%. As a whole, the impact of this new invention of energy saving glass design using harmony search able to save cost, easy maintenance and help to reduce the electricity usage in future.

I.

INTRODUCTION

The wide application of coated glasses in the construction of buildings and vehicle is vital because proven heat-reducing ability which maintains the temperature level inside the buildings. The presences of the glass have benefited the user by providing thermal insulation. The technology was introduced in the late 1980s under the Green Technology by the innovation of one-side coated glass with a thin metallic-oxide known as low emissivity glass (low-e). Once the low emissivity glass installed, isolated thermal within premise is regulated. At the same time the coating itself works as an infrared radiation block due to the heat from outside of the building, and is transparent to visible light [1]. The disadvantages are towards wireless communication such as global positioning system (GPS), mobile communication system (GSM,UMTS,3G), wireless network and broadband (Wi-fi, WiMax, LTE) which these signals have to face the consequences of being attenuated due to the metal oxide coating on the energy saving glass [2]. A study by Yahya (2011) [16] which work on the 2.4GHz frequency band, he introduces a new element to be patch on the antenna. The new patch is developing using genetic algorithm and the result is improved on the specific frequency mentioned. In addition a work by Sobuz et al,(2013) [17] which also work on developing an antenna by using a triple band X shape design. Both paper works on the antenna design to improve the signal gain. However, an intermediate medium such as wall or glass will attenuate the signal. Therefore, the energy

Keywords—coating design, energy saving glass, harmony search, optimization

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International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 8, August 2016

saving glass is introduce, instead of reducing the energy consumption on purpose it the coating design on the also affect the transmission signal. The presence of coated layer made of metallic-oxide which causes the attenuation of usefull signal as mentioned by Sohail et al [2] and Kiani et al [1].

by Zong Woo Geem [5] in which it is claimed to be an efficient algorithm in the field of combinatorial optimization [5] and [6] due to its simplicity and efficiency. HS is a metaheuristic algorithm inspired by mimicking the music improvisation. In general, music improvisation is the process of achieving the perfect state of harmonies played simultaneously by various music instruments. With this regards, HS is a population-based solution because improvisation of the pitch occurs iteratively using a set of solution in Harmony Memory (HM).

It must be noted that the design of the coating is one of the current issues. Some researchers propose to use optimization techniques such as Genetic Algorithm (GA) in order to come out with optimized design. Using the same approach of applying optimization techniques, this paper proposes to use Harmony Search (HS) technique. HS is becoming a recognized tool that is widely applied to solve optimization problems that cannot be simplified using conventional techniques [3][4]. It was introduced

A set of parameters are used in HS in order to create a new vector of harmony memory and achieve the global optimization. As a rule of thumb, there are five (5) basic phases involved in HS as illustrated in Fig. 1.

Step 1 Initialization of the parameter of HS (HMCR, PAR,BW..)

Step 2 HM initialization

Step 3 Improvise a new harmony No

The New Harmony realizes a better optimization Yes

No

Step 4 Update the HM

Step 5 Stopping Criteria Yes End

Fig 1: Harmony Search Phases (Romero et al. 2011) [15] Based on the Fig. 1, HS is considered as the best optimization due to its existing vector and the insensitivity to value and fast convergence [7]. In the optimization, HS is likely similar to GA which purposely to find the best fitness value. In this paper, HS is proposed as the tool of improvement for the return loss

and transmission coefficient in evaluation of the glass coating design by optimizing the binary design structure. There was a previous research on solving the water pump switch using similar binary approach known as Binary Harmony Search (BHS) [8].

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II.

ISSUES ON THE ENERGY SAVING GLASS

A bigger size of coated layer is meant to reflect more signals than the uncoated where a small amount is left. Hence, the size of both the uncoated and coated layer plays crucial roles for the signal transmission. In this regard, various methods can be adopted to increase the transmission. One of it is through the installation of additional network device such as repeater. Nevertheless, this method may cause an increment of cost and manpower even for better signal transmissions.

It is proven that a layer or coating of metallic oxide in energy saving glass causes the attenuation of useful signals including GSM, Wi-Fi, GPS and other personal communications [2]. The attenuation primarily causes low signal transmission. The coating design engraved on the glass would reflect the signals from going into most of the regular-shaped buildings. Based on the findings of the previous research, there have been various types of coating design. The common design is cross dipole, circular loop, hexagon, square and tripole, where these are the most common geometric shapes used to engrave onto the energy-saving glass [1].

The current studies demonstrate that regular shape can be applied to energy-saving glass without hesitation because to date, there is no new shape being introduced. Based on Sohail et al. [2], signal transmission may improve when 10% of the coated area is removed, while cross dipole shape illustrates transmission loss at 25dB.

Instead of letting the signals penetrate through the engraved space, the coated glass would reflect the signal.

Fig. 2: Regular Shape of Coating (Johar et al,. 2014) [10] obtained design. However, there could be a possibility for physical designing which is beyond the scope of this paper.

From Fig. 2, a genetic algorithm (GA) is applied to energy-saving glass for the optimization solution [9]. GA has been proven to ease the problem of energy-saving glass for design structure by improving the capability of the glass to allow more signals for penetration. Instead of fully operating the process of structure design using GA, only 5% up to 15% is applied by [10] to randomly generate the coated and uncoated side. The results showed better improvement than the regular-shaped coating. In this paper, HS is introduced as another metaheuristic technique to create a new design coating structure. BHS is applied due to binary representation of ‘1’ and ‘0’ in the design structure which will be further explained in the next section. Individual selection strategy, and NOT gate, is introduced as a strategy to improvise the harmony and as an operator for pitch adjustment [11]. In designing and analysing the design structure obtained from applying HS for optimization, Computer Simulation Technology (CST) is employed. CST is software which works for microwave and signal performance evaluation. By using CST, it ease the performance measuring of the current and obtained design. What will be measure for this paper is the return loss (S11) and transmission coefficient (S21) for the

III.

PROPOSED SOLUTION

Harmony search algorithm is implemented in this study as a new approach to obtain a new coating design for energy saving glass. This optimization algorithm has been widely used in various ranges of problems. Some studies such as in Mansor et al.(2014) [12] and Shaffei et al,(2014) [13] that HS already assists in scheduling timetable and a number of other problems. In spite of its good reputation among researchers, HS is still considered a new metaheuristic algorithm which is widely used in an array of real-life optimization methods because it can employ some degree of randomness in searching for a result [14]. The reason for HS being used in this research as an optimization technique is because HS considers all existing vectors rather than starts with two parent nodes as in GA. HS is also a fast convergence and is slightly insensitive to initial values. Regardless of the differences,

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International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 8, August 2016

HS is adapting to the similar process that works with binary in this paper.

square representing the design area is firstly created. The next process is to determine which area to be coated and which area to be left uncoated. Therefore, the whole coating layer design is divided into NxN dimension grid as illustrated in Fig. 3.

The main objective of this study is to generate a new kind of coating design via the use of HS as the global process and addition of the adaptive binary harmony search (ABHS) [13]. In order to create a new design, a

j=1

j=2

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j=N

i=1

W1

i=2

W2

i=3

W3

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i=N

WN

Fig 3: Dimension Grid Representing the Whole Coating Layer Design From Fig. 3, index i and j both denote the row and the column number respectively where i = 1,2,3… N and j =1,2,3.. N . Each element of the grid must be categorized as coated and uncoated. Therefore, bit ‘1’ is assigned as coated element while bit ‘0’ is assigned as the uncoated element on the grid. The specification of the design structure is that there must be only 40% of the whole area are coated while the rest are left uncoated.

TABLE I GOOD FITNESS POINT

Along row i , each bit 0 encounter in the grid successively will be group together. Each group is known as ti , k where i represents row number and k represent the group number in the respective row i . This group will be assigned with good fitness point as shown in Table 1. Is must be noted that, the assigned values of good fitness point is following [10]. Once all the ti , k are identified in every row, the weightage Wi for each row i will be computed.

Number of Zero’s

Points

0 00 000 0000

1 2 3 2

00000+

1

Fig. 4 illustrates an example to obtain the value of weightage at row 2. It can be seen that there are three groups of k with assigned good fitness values: Group 1: t2,1  1 Group 2: t2,2  3 Group 3: t2,3  2

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International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 8, August 2016

t2,1 1

t2,2  3

t2,3  2

i=1

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W2   t2,k

j=1 j=2 j=3 j=4 j=5 j=6 j=7 j=8 j=9 j=10 Fig. 4: Weightage Computation The value of weightage for row 2 is

 xij  0.4

W2   t2,k

N2

W2  t2,1  t2,2  t2,3

K

Wi   ti ,k ; i

The optimum design structure is the one with the minimum total weightage values as denoted in equation (1). Equation (2) is the constraint specifying that the grid element is either 1 or 0 for coated and uncoated respectively. Equation (3) is the constraint where the whole coated area must be equal to 40%. Equation (4) is the weighting value assigned to each row based on the coated formulation. The mathematical model is solved using HS algorithm. It starts by initializing the random generated bits ‘1’ and ‘0’ only at the NxN dimension grid. The process of improvisation is done iteratively until the stopping criteria is met as illustrated in Fig. 1. The optimum binary result of the dimensional grid will be converted into energy saving glass coating design in CST Studio (Microwave) software. The design is evaluated based on the performance of return loss and transmission coefficient.

6

Therefore, the weightage for row 2 is 6. The weightage is calculated for every row. The summation of all the rows

Wi need to be determined. In this work,

Wi is choosen to be the criteria to determine whether the resulted design is optimum or not. Hence, the mathematical model for the design of coating layer structure is formulated as follows: N

Min Wi

(4)

k 1

 1 3  2

weightage,

(3)

(1)

i 1

subject to: IV.

RESULT AND ANALYSIS

The illustrations of the experimental results are presented in this section to interpret the efficiency of the method applied. The use of HS generates a set of random

(2)

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International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 8, August 2016

number of bit ‘0’ and ‘1’ in 20 by 20 dimensions resulted in 400bits. The results were obtained from the programmed of HS with 100 iterations. The total good fitness value which obtained from Wi measured is 178 points. The results in binary are tabulated and shown in Fig. 5. The overall energy saving glass coating design structure obtained from the binary results is shown in Fig.

6(a). It can be seen that all the grid elements that are numbered as ‘1’ in Fig. 5 are translated as coated element grid in CST software, highlighted in coloured as shown in Fig. 6(a). On the other hand, the grid elements that are numbered as ‘0’ in Fig. 5 are translated as uncoated element grid with no coloured as shown in Fig 6(a).

Fig. 5: Bit ‘1’ and ‘0’ Obtained

(a)

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International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 8, August 2016

(b)

(c) Fig 6 : (a) Result of binary number was converted into design in CST, (b) result of return loss at 2.305GHz show -32.02 dB. (c) Result of transmission coefficient was at -0.007 dB. Based on the resulted coating design structure for energy saving glass, it can be seen that the best frequency for this design is at 2.305GHz. The return loss, S11 for this experiment is at -32.02 dB, which is considered as an ideal return loss. Meanwhile, the transmission coefficient is at -0.007 dB. The return loss signal, S11, is considered as an ideal return loss based on the s-parameter which governs that -10dB is a passable value of the return loss. The transmission coefficient, which was recorded at S21, is determined to be the efficiency of the coating where the best value of the graph is nearly 0 dB, considered as the best value. From the 6(c) graph, the value obtained is calculated for its efficient percentage as shown below:

log10  -0.007 = 10 log10  S2, 1 = 10

E = 0.9983 x100 E = 99.83% V.

CONCLUSION

In this paper, a new design of coating for energy saving glass is created. An optimization of harmony search was applied with binary in order to obtain a result where it mimicked the real situation according to the

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physical state of the energy-saving glass that is used in cell and bit topology. The goal of this study is to have an optimize design in consideration of the return loss (S11) and transmission loss (S21). In this paper, the results of the optimization of energy saving glass coating design are demonstrated. The optimum design is acquired using the optimization technique instead of the traditional way of creating the design. The enhancement of harmony search would be useful in the coating design. Future work may aim to test for the variation in frequency that is usable and would improve the transmission signal in different ways.

[11]

[12]

[13]

[14]

ACKNOWLEDGEMENTS This research is funded by the Ministry of Education and Universiti Teknikal Malaysia Melaka (UTeM) under the Fundamental Research Grant Scheme FRGS/2/2013/ICT07/FTMK//02/7/F00190.

[15]

[16]

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Kiani, G. I., Olsson, L. G., Karlsson, A., & Esselle, K. P. Transmission of infrared and visiblewavelengthsthrough energysaving glass due to etching of frequency-selective surfaces. Microwaves, Antennas & Propagation, IET, 4(7), 955961, 2010 [2] Sohail, S. I., Kiani, G. I., & Esselle, K. P. Enhancing RF/microwave efficient transmission through energy saving glass windows using Frequency Selective surface. In Antennas and Propagation (APSURSI), 2011 IEEE International Symposium on (pp. 2262-2263). IEEE. 2011 [3] Geem, Z. W., & Choi, J. Y.. Music composition using harmony search algorithm. In Applications of Evolutionary Computing (pp. 593-600). Springer Berlin Heidelberg, 2007 [4] Geem, Z. W. . Harmony search algorithm for solving sudoku. In Knowledge-Based Intelligent Information and Engineering Systems (pp. 371-378). Springer Berlin Heidelberg, 2007 [5] Geem, Z. W., Kim, J. H., & Loganathan, G. V. A new heuristic optimization algorithm: harmony search. Simulation, 76(2), 6068 , 2001 [6] Mansor, N. F., Abas, Z. A., Rahman, A. F. N. A., Shibghatullah, A. S., & Sidek, S. An Optimization Solution Using A Harmony Search Algorithm. International Symposium on Research in Innovation and Sustainability 2014 (ISoRIS ’14) 15-16 October 2014, Malacca, Malaysia [7] Wang, L., Yang, R., Xu, Y., Niu, Q., Pardalos, P. M., & Fei, M. An improved adaptive binary harmony search algorithm. Information Sciences, 232, 58-87, 2013 [8] Geem, Z. W. Harmony search in water pump switching problem. In Advances in natural computation (pp. 751-760). Springer Berlin Heidelberg, 2005 [9] Shibghatullah, A. S., Nor Fadilah Rahamad, and Farah Ayuni Azmin. "The Development of Complex Coating Shape for Energy-Saving Glass using Harmony Search Algorithm." International Conference On “Innovative Trends in Multidisciplinary Academic Research” ( ITMAR 2014) 20-21 October 2014,Istanbul, Turkey [10] Johar, F. M., Azmin, F. A., Shibghatullah, A. S., Suaidi, M. K., Ahmad, B. H., Aziz, M. A., ... & Shukor, M. M. Application of Genetic Algorithm to the Design Optimization of Complex Energy Saving Glass Coating Structure. In Journal of Physics:

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Conference Series (Vol. 495, No. 1, p. 012031). IOP Publishing, 2014 Ibtissem, B., & Hadria, F. Unsupervised Clustering of Images Using Harmony Search Algorithm. Journal of Computer Sciences and Applications,1(5), 91-99. 2013 Mansor, N. F., Abal Abas, Z., Rahman, A., Nizam, A. F., Shibghatullah, A. S., & Safiah, S. An analysis of the parameter modifications in varieties of harmony search algorithm. International Review on Computers and Software (IRECOS), 9(10), 1736-1749 Shaffiei, Z. A., Abal Abas, Z., Rahman, A., Nizam, A. F., Shibghatullah, A. S., & Hussin, B. Optimization in driver’s scheduling for university shuttle bus using harmony search. Science International, 1879-1882. 2014 Abal Abas, Z., Shaffiei, Z. A., Rahman, A., Nizam, A. F., & Shibghatullah, A. S. (2014). Using harmony search for optimising university shuttle bus driver scheduling for better operational management. International Conference On “Innovative Trends in Multidisciplinary Academic Research” ( ITMAR 2014) 20-21 October 2014,Istanbul, Turkey Romero, V. M., Tomes, L. L., & Yusiong, J. P. T. Tetris Agent Optimization Using Harmony Search Algorithm. International Journal of Computer Science Issues, 8(1), 22-31, 2011 Yahya, S. H. Design of 4 elements rectangular microstrip patch antenna with high gain for 2.4 GHz applications. Modern applied science,6(1), 68. 2011 Sobuz, M. S., Islam, M. T., & Mandeep, J. S. Triple band X shape microstrip patch antenna for Ku/K band applications. Modern Applied Science, 7(8), 70, 2013

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