A Heuristic Method of the Optimal Matching for the Two Unstructured Systems

Transcription

1 Proceedngs of the 0th WSEAS Internatonal Conference on SYSTEMS, Voulagmen, Athens, Greece, July 0-2, 2006 (pp ) A Heurstc Method of the Optmal Matchng for the Two Unstructured Systems Huay Chang Department of Informaton Management Chhlee Insttute of Technology #33 Wen-Hua Rd., Panchao Tawan Abstract: - In ths paper, we presented a heurstc method to fnd the best optmal matchng of the two unstructured systems; the Brand Musc for the Brand ogo. In the begnnng, the plot-test was held on the comparson of varous dfferent brand logos and musc wth dfferent characterstcs attrbutes by the experts. Ths process establshes the common mage vocabulary recognton space of the brand logo and brand musc. Consequently, the common mage vocabulary space adjectve pars were extracted through the Factor Analyss. Then, we use the Correlaton Coeffcent Crtera Prncpal and the Mnmum Norm Projecton Prncpal to evaluate the correspondng degree on Brand ogo and Brand Musc. Fnally, through the smulaton, the proposed method s effcent and obtans some successful results. ey words: Brand ogo, Brand Musc, Factor Analyss Method, Optmal Match Algorthm, Characterstc Attrbute Introducton. Research Background Today, based on the wdely used of mult-functon and mult-varety hgh-tech vdeo and audo broadcastng medums, musc plays an mportant role n the nformaton broadcastng process. For those consumers, product brand means a knd of feelng, a knd of relance and a knd of servce. Musc establshes an magnng space for the consumers and also establshes the specfc relatonshps for the brand and the product. Musc also hghly nfluence the concept of the consumers aganst the product. The type of musc helps the consumers assume the characterstcs of the product brand that the musc attempts to express..2 Research Motve Today, the brands of the busnesses use the mode of concept, text, symbol and musc to represent the varous products and varous servce of the busnesses. Brand seems become the communcaton medum that can t be absent between the consumers and the busnesses. Besdes the Brand ogo brngs the maxmum satsfacton for the consumers. We also realze that the Brand ogo can utlze the Brand Musc to transmt the busness nformaton. In ths research, we would lke to fnd out the ndex value of the relatonshp establshment between the brand logo and brand musc of the busness..3 Research Purpose The purpose of ths research s to fnd out the optmal matchng characterstc attrbute brand musc for the brand logo. We would lke to combne the Expert System, Factor Analyss, Correlaton Coeffcent Crtera Prncpal and the Mnmum Norm Projecton Prncpal to evaluate the correspondng degree on Brand ogo and Brand Musc. And we would lke to fnd out the best matchng Characterstc Attrbute Index Value of the brand musc for the brand logo. The heurstc method submtted n our research would become the bass for the busness n selectng the brand musc..4 Research Scope We submtted the followng three research tems:.4. Brand ogo Sample We collected the famous brand logos (for those can be feasbly represented by text or graph), local and foregn, for further researchng..4.2 Brand Musc Sample We collected the famous brands brand musc and those own dfferent musc structured elements (rhythm, melody, tmber) as the research targets..5 Operatonal Defnton

2 Proceedngs of the 0th WSEAS Internatonal Conference on SYSTEMS, Voulagmen, Athens, Greece, July 0-2, 2006 (pp ) There are some operaton defntons n the research:.5. Brand Musc In the research, the musc means that can be broadcasted by mult-meda equpments. The musc doesn t nclude the lyrc. Not only the varous knds of nstruments but the natural sound s allowed to be used whle desgnng the musc..5.2 Brand ogo The Brand ogo descrbed n ths research means that s the specfc part, t can be seen but can t be expressed by speakng. It s the graph representaton of the brand, such as: symbols, desgn, specal color or alphabets. These brand logos are usually used as an mportant communcaton medum between the busness and the consumers. The paper s organzed n the followng manner. The terature Revew s presented n Secton II. In Secton III, we propose a Heurstc Method for the Optmal Match between the Brand ogo and Brand Musc. The Smulaton and concluson are gven n Secton VI. 2 terature Revew 2. Musc Structured Elements The famous descrpton of musc: The content of musc s the exercsng type of musc s sad by Hanslck Eduar [] n nneteen century. He thought the orgn element of musc s the regular and good lstenng voce, the prncple of the pleasant musc s usng rhythm, the element of wrtng songs are tone, harmony and rhythm. And the contnung melody s combned wth the basc elements those create the basc structure of the musc. Manfred Clynes [2] ponted out the sutable structured musc can effcently help human s bran reacton and emoton reacton. Me-Nyu Gwo [3] ponted out musc s the art and scence, s created by human nature development. Me-Nyu Gwo [4] also ponted out all the musc s basc prncples are structured by rhythm, melody, harmony and tmbre. The followng lterature revew focuses on rhythm, melody and tmbre. 2.. Rhythm Gwo, Me-Nyu [4] thnks rhythm s the exercse of the realstc status. Ths exercse represents a procedure and an order. The rhythm represents the basc component elements of the musc. Hanslck Eduard [] ponts that there are wde defnton and narrow defnton of the rhythm. The wde defnton of the rhythm ncludes the natural status of the unversal operaton, the physcal status, movements and languages of the human body. The narrow defnton means that the rhythm becomes the regulatory varaton status wthn the fxed length of tme and the fxed perodc tme. Then, the rhythm plays a repeatedly length, speed and strength. Due to the varous knds of musc, the speed becomes dfferent. People modulate the playng speed correctly by usng the metronome. We lsted the sx types of the speed n Table : Table Types of the Speed Rhythm Adago Md-Adago moderato Speed/ Mn Md- Allegro allegro allegretto (Data source: Chang, Jng-Hwung, 982) 2..2 Melody Melody s algned and assocated by many tones. Therefore, the muscal sound s created by formal rhythm. Ths muscal sound owns steady assocaton status. The organzatonal ntegraton of the global status becomes the melody. Due to the dfference of tme, countres, natons and composers background, the muscal sounds wth dfferent melodes make people create dfferent feelng. The muscal style strongly represents the types of melody and rhythm of the muscal sound. u, Jau [5] lsted 24 Styles of Musc, as lsted n Table 2: Table 2 24 Styles of Musc NO Name NO Name Jazz Swng 3 Mam Rock 2 Jazz Waltz 4 Pop Ballad 3 Waltz 5 Pop Ballad 2/8 4 Country 2/8 6 Mlly Pop 5 Country 4/4 7 Bouncy 6 Country 2/8 8 Ethnc 7 Blues Shuffle 9 Funk Bossa 8 Blues Straght 20 Cha Cha 9 Shuffle Rock 2 Bossa Nova 0 te Rock 22 Irsh Medum Rock 23 Rumba 2 Rock 24 Reggae (Data Source: u, Jau, 200) 2..3 Tmbre Jyangyuan, Mng-ang [6] ponts that the tmbre not only ncludes the sound that s made by the muscal nstruments but also nclude the sound that s resulted from human bengs and natural world. The representaton type of the musc s dvded nto Vocal Musc and Instrumental Musc. Vocal Musc uses the gfted voce to demonstrate the musc

3 Proceedngs of the 0th WSEAS Internatonal Conference on SYSTEMS, Voulagmen, Athens, Greece, July 0-2, 2006 (pp ) wthout any muscal nstruments. The Instrumental Musc uses any nstruments those can make sound to create the musc. The muscal nstruments nclude the followng three basc types: Strnged nstruments, aero phone and percusson. The detaled ntroducton s lsted below: Strnged Instruments use the vbraton of the strng to create the muscal sound. Due to the dfferent numbers of the strngs and the dfferent vbraton method, there are three types of the strnged nstruments: bowstrng nstrument, spndle nstrument and flexble-bowstrng nstrument. Jyangyuan, Mng-ang [6] ponts the bowstrng nstrument ncludes voln and voln cello; the spndle nstrument ncludes gutar; the flexblebowstrng nstrument ncludes the pano and the harp. Aero phone use the ar floatng vbraton nsde the tube to create the muscal sound. The aero phone ncludes the wood-wnd nstruments, the steel-wnd nstruments, the organ and the reed. Jyangyuan, Mng-ang [6] ponts that the wood-wnd nstruments ncludes the flute and the Englsh horn; the steel-wnd nstruments nclude the trumpet; the organ ncludes the organ tself; the reed ncludes mouth organ and the accordon. Percusson use the vbraton by knockng dfferent knds of materals to create the muscal sound. Jyangyuan, Mng-ang [6] ponts that the percusson ncludes the gamelan, the carllon and the kettledrum. Chang, Jng-Hwung [7] ponts that the nstruments can dvded nto three parts: hgh-tone, mddle-tone and low-tone. As lsted n Table 3: Table 3 The Hgh-tone, Mddle-tone and ow-tone of the Instruments Strnged Wood-Wnd Hgh-ow Tone Instrument Instrument The Hghest Tone Hgh Tone Volne Volne Pccolo Clarnet Flute Hautbos Clarnet Trumpet Cornet Horn Mddle Tone Vola da bracco Englsh horn Bass Clarnet French Horn ow Tone Volncello Bassoon The owest tone Contrabass Contrabassoon (Data Source: Chang, Jng-Hwung, 200)[7] 2.2 Brand ogo Wthn the brand concept, the Brand ogo can be dentfed by the sense of the eye. But the Brand ogo can t be expressed by speakng. The Brand ogo can be represented by the brand graphs, such as: symbols, desgnng, specfc color or alphabets. Su, Yong and Jng, Shn-Mn [8] ponts that whle people are recevng the outer nformaton, more than 83% of the nformaton s receved by the sense of seeng. It s around % of the nformaton s receved by the sense of hearng. It s about 3.5% of the nformaton s receved by the sense of smellng. Therefore, the brand logo surely can create the maxmum satsfacton of the sense of the seeng for the consumers. Su, Yong and Jng, Shn-Mn [8] ponts that the brand logo brngs the gant nfluence durng the purchasng decson process. We can also dscover that the world-wdely known famous brand not only owns a well-known brand name, they also own a specfc brand logo. It s crucal to fnd the best match brand musc for the brand logo. In the followng, we wll propose a heurstc method for the optmal match between the Brand ogo and the Brand Musc. Whle the busness selects the rght Brand ogo and the Brand Musc those would promote the busness s competton power. 3 A Heurstc Method of the Optmal Matchng between the Brand ogo and Brand Musc In ths secton, we would combne the Expert System and the Factor Analyss to submt the Optmal Heurstc Method to fnd out the Brand ogo s Best Matchng Characterstc Attrbute of the Brand Musc. Frst, there s a plot test toward the brand logo and the Characterstc Attrbute of the brand musc. Then, we use the Factor Analyss to extract the Common Imagery Vocabulary Recognton Space Adjectve of the brand logo and the brand musc. Then, we submt two prncples: the Correlaton Coeffcent Prncple and the Mnmum Norm Projecton Prncple. Then, based on the prncples, we submt the Optmal Match Algorthm we dscover the best correspondng characterstcs attrbutes of Brand Musc by the Brand ogo through laboratory desgn. 3. Plot Test The purpose of the Plot Test s to establsh the Common Imagery Vocabulary Recognton Space Adjectves of the brand logo and the brand musc. Frst, we wdely select the magery vocabulary samples of the brand logo and the brand musc. Second, we nvte the experts to execute the flterng and leave the 60% of the samples those are approved by the experts.

4 Proceedngs of the 0th WSEAS Internatonal Conference on SYSTEMS, Voulagmen, Athens, Greece, July 0-2, 2006 (pp ) 3.. Samples of Brand ogo We select 60 brand logos (wth dfferent products) and group them nto sx groups by the brand logo experts. One representatve s selected n each group. As lsted n Table 4: Table 4 Samples of Brand ogo Groups of Brand ogo Representatve Fast-Food S Watch S 2 Cosmetcs S3 Electrc Communcaton S 4 Electrc Applance S5 Clothes S Sample of Brand Musc We collect the 90 samples of the brand musc those own dfferent characterstc attrbutes (rhythm, melody and tmbre). The length of each sample s 30 seconds. Those samples are grouped nto 9 groups by the muscal experts. One representatve s chosen by the muscal experts. Therefore, nne samples ms, ms 2,..., ms9 are recorded n the CD as the brand musc sample of the plot test. Ths CD s stored n Huay Chang s Ph.D. Thess [9]. The numbers of the samples of each group s lsted n Table 5: Table 5 Samples of Brand Musc Groups of Brand Musc Musc Samples of Each Groups 3..3 Imagery Vocabulary The magery vocabulary ncludes musc magery vocabulary and brand logo magery vocabulary. Accordng to Frarnsworth s correcton table aganst Hevner Adjectve Crcle, there are 52 dfferent adjectves of brand musc. Accordng to Chen Jau-Je s [0] product desgnng evaluaton, there are 48 adjectve vocabulares. The total 200 adjectve vocabulares are used n the plot test by the experts. Then, 40 adjectve vocabulares are chosen as the common sense magery vocabulary adjectve. These 40 adjectve vocabulares are embedded to create the opposte adjectve vocabulares. The x ~ x pars of common sense magery vocabulary adjectves are created. As lsted n Table 6: Table 6 Forty Pars of Common Sense Imagery Vocabulary Adjectve x n Imagnery Vocabulary Imagnery Vocabulary x Adjectve Par n Adjectve Par x fruty -- acuate x 2 rapd -- slow x 2 acton -- standpat x 22 heroc -- buckram x 3 complcate -- smple x 23 calm -- uncalm x 4 taste -- ordnary x 24 knd -- chlly x 5 natural artfcal x 25 energetc -- weak x 6 personalze popular x 26 dream -- realty x 7 easy -- nervous x 27 young -- steady comfortable -- x 8 uncomfortable x 28 generous -- stngy x 9 fashon -- tradton x 29 specal -- routne x 0 borng -- exctng x 30 chldsh -- mature x attractng -- dull x 3 serous -- happy x 2 restore -- future x 32 zeal -- detached x 3 youthful -- old x 33 rght -- loosen x 4 male -- female x 34 cold-- warm x 5 changeable -- accurate x 35 cheer -- sad new fashon -- x 6 out of date x 36 leasure -- formal x 7 senstve -- blunt x 37 trflng -- organzed x 8 strong -- tender x 38 honorable -- humble x 9 carefree -- rapd x 39 playful -- cautous x 20 brght -- dark x 40 heavy -- lght 3.2 Factor Analyss Method The Factor Analyss Method s the Statstcal method that s used to extract the latency factors y, y2,..., y from the N behavoral varables x, x2,..., x N. Among them, < N. The N varables are observable. The latency factors are unobservable and must be extracted by the Factor Analyss Method. And the determnaton of the numbers of the factors s adopted by aser Method and Scrap Test Method aboratory Plannng of Factor Analyss In the followng, we would lke to explan the laboratory of how to apply the Factor Analyss Method to extract the common magery vocabulary adjectve pars of the brand logo and brand musc. We desgned a questonnare [Huay Chang Ph.D. Thess 9]. The 40 pars of adjectves are used toward the 6 brand logo samples s, s 2,..., s 6 and 9 brand musc samples ms, ms 2,..., ms9 n ths questonnare. The nvestgaton method s executed by the e-mal and the 7-step kert Scale SD Method s used as the evaluaton scale. 500 questonnares are sent and the 34 useable questonnares are returned. The returnng rate s 68.2%.

5 Proceedngs of the 0th WSEAS Internatonal Conference on SYSTEMS, Voulagmen, Athens, Greece, July 0-2, 2006 (pp ) Test Result of Factor Analyss The SD evaluaton value s ganed by the former questonnares. The determnaton of the numbers of the factors s adopted by the aser prncple and the Scrap Test prncples. The Factor Structure Matrx of the Factor Analyss result show that there are ( = 2) factors those characterstc values are greater than. Based on the former Factor Analyss, the latency factors those have 2 greater correlaton coeffcent values. 3.3 Optmal Match Algorthm In ths secton, we submt the Optmal Match Algorthm. The purpose s to dscover the Optmal Match Characterstc Attrbutes of the brand musc toward the busness s brand logo. In prevous secton, we have fnshed and collected the 2 pars of the Common Imagery Vocabulary Adjectves of the brand log and the brand musc by the Expert System Plot Test and the Factor Analyss Method. Ths Common Imagery Vocabulary establshes the ( = 2) space. We project the sngle brand logo and the brand musc those own dfferent characterstc attrbute to the space. Then, we apply the Optmal Match Algorthm to dscover the Characterstc Attrbute of the brand musc that best matches the brand logo. In the followng, we wll descrbe the Correlaton Coeffcent Crtera Prncpal and the Mnmum Norm Projecton Prncpal The Correlaton Coeffcent Crtera Prncpal The Correlaton Analyss s to analyze the varaton drecton of two varables. The Coeffcent of Correlaton ssued to evaluate the strength of the relaton. The range of the Coeffcent of Correlaton s ~ +. The hgher value means the hgher relance. Mark [] ponts the crtcal value s 0.6. If the value s hgher than 0.6, the same drecton relaton s close. The Mnmum Norm Projecton Prncple The Mnmum Norm Projecton Prncple s to calculate the Eucldean Dstance of two varables those project nto the specfc space. We project the brand logo ( ) and the I numbers of musc ( m, m2,..., m I ) those have dfferent characterstc attrbutes nto the Common Imagery Vocabulary Space. The brand musc that has shorter m Eucldean Dstance from the brand logo ( ) represents the hgher relatons wth the brand logo Optmal Match Algorthm We propose the Optmal Match Algorthm n ths research. Ths Algorthm s used n the followng ssues: For a gven busness brand logo ( ), whle t meets the Correlaton Coeffcent Prncple, t can be used by the Mnmum Norm Projecton Prncple to fnd out ts Optmal Match Characterstc Attrbute of the Brand Musc. The descrpton s as follows: m E k k 2 2 mn d m = [ ( m ) ], =,2,..., I m k= subject to R R () m c Among them, I : stands for the total numbers of brand musc wth dfferent characterstc attrbutes. k : stands for the SD evaluaton average value of the k tem adjectve par of the gven brand logo ( ) n the degree Common Imagery Vocabulary Space. m : stands for the tem of the characterstc attrbute of the brand musc. k m : stands for the SD evaluaton average value of the k tem adjectve par of the tem of the characterstc attrbute of the brand musc ( m ) n the degree Common Imagery Vocabulary Space. R : stands for the correlaton coeffcent value of the m brand logo ( ) and the tem characterstc attrbute brand musc ( m ) those project nto the degree common magery vocabulary space. R c : stands for the assgned correlaton coeffcent crtcal value E : stands for the Eucldean Dstance of the brand d m logo ( ) and the tem characterstc attrbute brand musc ( m ) those project nto the degree common magery vocabulary space. The meanng of Eq. () s to focus an assgned brand logo ( ), the crtera of ts optmal match characterstc attrbute of the ( m ) brand musc are to project, m, =,2,.., I nto the degree

6 Proceedngs of the 0th WSEAS Internatonal Conference on SYSTEMS, Voulagmen, Athens, Greece, July 0-2, 2006 (pp ) common magery space. Whle the crtera of the correlaton coeffcent s met, the m owns the mnmum Eucldean Dstance s the Optmal Match characterstc attrbute brand musc. Furthermore, we can dscover the ndex value of the rhythm, melody and tmbre of the optmal match brand musc. The Optmal Match Algorthm: Step 0 Gven Brand ogo ( ), and brand musc ( m, =,2,.., I ), gven the adjectve pars of the common magery vocabulary of the degree space, assgn the crtcal value of correlaton coeffcent R c. Step Use the SD method to project the, m,( =,2,..., I) to the degree common magery vocabulary space and obtan k, m k, =,2,..., I,, k =,2,...,. Step 2 Calculate R m, =,2,..., I. Step 3 Fnd the m from the set of Rm Rc. Select the and re-algn the by ascendng order, and set them as the new group m ~ j, j =,2,..., J. Step 4 Calculate E k k d m~ 2 2 m~ j = [ ( j ) ], j =,2,..., J. Step 5 Fnd the k= m ~ of the j mn d E m ~ j. The m ~ j s the optmal match characterstc attrbute brand musc of the brand logo. The m ~ that m matches the brand musc ndcatng the characterstc attrbute ndex value. j Classcal Condtonng Approach, Journal of Marketng, Vol.46, 982, pp [2] Clynes,M., N. Nethem, The vng Qualty of Musc: Neurobologc Bass of Communcatng Feelng, M. Clynes. Musc, Mnd, and Bran: The Neuropsychology of Musc,Plenum Press, 982. [3] Gwo, Me-Nyu, The Bass of Musc Educaton- Audo Sense Teachng, Journal of CoursesandTeachng, 999, pp.20 [4] Gwo, Me-Nyu, The Audo and Musc Educaton, Wu-Nan Publcaton mted Company, 2000, pp [5] u, Jau, The Musc, Wu-Nan Publcaton mted Company, 985, pp [6] Jyangyuan, Mng-ang, Instruments Introducton, Da-u Publcaton Book mted Company, 984, pp [7] Chang, Jng-Hwung, The New Basc Musc Theoretcal Introducton, Da-u Publcaton Book mted Company, 200, pp [8] Su, Yong and Jng, Shn-Mn, Modern Company Famous Brand Polcy, Shangtung: People s Publcaton Bookstore, 999, pp [9] Huay Chang, Usng a Quanttatve Verfcaton Model n Analyzng the Brand Poston Nche Theory And Brand Musc, The Thess of Fu-Dan Unversty, [0] Chen, Jau-Je, The Study of Product Modelng Evaluaton Adjectve Vocabulares, the Industral Desgn Graduate School of Natonal Chen-ung Unversty, 994. [] Johnson, Mark E., Multvarate Statstcal Smulaton, New York: JohnWley & Sons, Incorporated, Smulaton and concluson In ths paper, we propose a heurstc method for the optmal matchng between the two unstructured systems; the Brand logo and the Brand musc. We use the Correlaton Coeffcent Crtera Prncpal and the Mnmum Norm Projecton Prncpal to evaluate the correspondng degree on Brand ogo and Brand Musc. Through the smulaton, the proposed method s effcent and obtans some attractve features References: [] Eduar, Hanslck Gorn, Gerald J. The Effects of Musc n Advertsng on Choce Behavor: A