SONG STRUCTURE IDENTIFICATION OF JAVANESE GAMELAN MUSIC BASED ON ANALYSIS OF PERIODICITY DISTRIBUTION

Size: px
Start display at page:

Download "SONG STRUCTURE IDENTIFICATION OF JAVANESE GAMELAN MUSIC BASED ON ANALYSIS OF PERIODICITY DISTRIBUTION"

Transcription

1 SOG STRUCTURE IDETIFICATIO OF JAVAESE GAMELA MUSIC BASED O AALYSIS OF PERIODICITY DISTRIBUTIO D. P. WULADARI, Y. K. SUPRAPTO, 3 M. H. PUROMO,,3 Insttut Teknolog Sepuluh opember, Department of Electrcal Engneerng, Surabaya 60 Indonesa E-mal: 3 ABSTRACT In a song played by multple nstruments, there s dstrbuton of perodctes that comes from dfferent playng patterns among groups of nstruments. We propose a vsualzaton of ths dstrbuton for analyzng song structure of Javanese gamelan musc. A predefned number of perodctes along wth ther confdence levels are obtaned usng comb flter resonator. The flter s appled to the auto-correlaton functon of overlappng analyss frames of the muscal track. We cluster the dstrbuton based on the proxmty of two parameters, whch are perodcty and confdence level. In ths way, we assume that each cluster center represents the perodcty of a group of nstruments. We observe four features of the vsualzaton, namely the wdth and the average heght of perodcty dstrbuton, the pattern of domnant perodctes, and the fluctuaton of the most domnant perodcty. Those features mplctly gve us nformaton regardng the strength appled to the notes, the estmated number of nstruments, and the accent of song accordng to those features, from whch we make an nference about the structure. We provde the experment wth a database of thrty Javanese gamelan songs and compare the analyss of lancaran, ladrang, and ketawang song structures. The results show that usng ths method, lancaran receved the hghest performance, whch s 0.94 F-measure, followed by ketawang and ladrang wth F- measure of 0.90 and 0.75 respectvely. Keywords: Comb Flter Resonator, Confdence Level, Perodcty Dstrbuton, Song Structure Analyss, Javanese Gamelan Musc. ITRODUCTIO Javanese gamelan musc s wdely used as accompanment of cultural events, lke weddng ceremony, art show, and of many relgous ones []. Each of the events has ts own story plot and therefore t requres an accompanment of dfferent sequence of song structures. For example, n a shadow puppet show, the orchestra starts playng smple yet dynamc structure of lancaran n the begnnng. Before the story goes to a new scene, the orchestra slows the tempo, softens the nstrument playng, and prepares to move nto more elaborate songs, lke those of ladrang or ketawang, gvng the audence an elegant mpresson. There are many knds of song structure n Javanese gamelan musc, whch are categorzed as gendhng alt, gendhng madya, and gendhng ageng []. Ths research focuses on three types of song structures whch fall nto gendhng alt category, namely lancaran, ladrang, and ketawang, snce these structures are among the most frequently used ones. Javanese gamelan musc dvdes a song nto several parts, called part A, part B, part C (f any), etc. In each part, every nstrument has dfferent playng pattern. We use the term pattern to represent a combnaton of notaton and perodctes arse between notes. There are nonstrct rules of determnng the structure of Javanese gamelan song based on the number of lnes contaned n each part and the presence of partcular nstruments sounds (lke kenong, kethuk, and kempul). Moreover, the players may repeat each part as many as they lke dependng on the stuaton (the flow of the story). But apart from these facts, Javanese gamelan experts are able to dfferentate the song structure by recognzng the pattern as well as by feelng the rhythm. In a Javanese gamelan ensemble there are several nstrument groups. For the reason of smplcty we would lke to menton three groups of nstruments as an example, whch are saron, pekng, and gong. Saron group for example, conssts of several saron nstruments. Saron s 39

2 usually played accordng to the notaton, whereas pekng s usually played by strkng each note n the notaton twce, and gong s stroke only at the end of each lne. Therefore these three groups may generate dfferent perodctes. We vsualze perodcty dstrbuton of a song and analyze the structure mpled by the pattern appears n the dstrbuton. The song s frstly dvded nto short overlappng frames. Each frame s consdered as the basc unt of perodcty analyss. Perodctes of a frame are enhanced by employng a comb flter resonator [4]. We cluster the perodctes based on two parameters, the perodcty tself and the correspondng confdence level. Each cluster conssts of neghborng perodctes whch have relatvely close confdence level. In ths way, we assume the centers as a representaton of perodcty of an nstrument group. Clusterng s carred out n order to overcome rrelevant varatons that may present n a song. Ths paper s organzed as follows, Secton I descrbes the background and outlne the contrbuton of the research, Secton II explans prevous works related to the topc of ths research, Secton III proposes a new method to analyze the structure of Javanese gamelan song, Secton IV shows the expermental evaluaton of the proposed method, Secton V presents the analyss of the expermental results, and Secton VI concludes the analyss.. RELATED WORKS Ths research s a contnuaton of the prevous ones regardng Javanese gamelan musc transcrpton. A number of methods were mplemented to transcrbe the notaton of Javanese gamelan musc, such as the use of flter to extract nstrument sound [5-7], and the use of onset detecton method to transcrbe saron notatons, [8-0]. Some other researches related to Javanese gamelan musc performed nstrument sound segmentaton [, ], nstrument tmbre analyss [3, 4], and beat trackng [5]. Our proposed method of song structure analyss supports nformaton retreval and recognton of Javanese gamelan musc whch s an applcaton of musc transcrpton [6]. Many applcatons of muscal sgnal processng are based on perodcty, such as n ptch trackng, beat trackng, tempo estmaton, and furthermore, n understandng rhythm. The algorthms developed for perodcty detecton are manly bult upon tme-doman perodcty and frequency-doman perodcty [6]. The majorty of the algorthms fall nto the frst approach, lke [7] and [8]. A research that studed perodcty based on spectral autocorrelaton was proposed by [9] whle that whch based on autocorrelaton of log spectrum was proposed by [0], where both appled to speech sgnals. In ths research, we adopt beat perod nducton method usng comb flter resonator [4]. But nstead of selectng the most confdent perodcty among hypotheses and consder t as the beat perod of an analyss frame, we vsualze the confdence levels of all perodctes n a track and make analyss about the song structure. In general, beat trackng algorthms conssts of two stages, whch are the generaton of drvng functon from drect processng of audo sgnals and the detecton of perodctes n these drvng functons to fnd tempo estmates []. For generatng drvng functons we have compared several reducton functons based on spectral features and we conclude that spectral flux functon s the best ft for our database [8]. Javanese gamelan nstruments are manly percussve, thus t yelds more dscrmnatve drvng functons compared to those resulted from wnd and bow nstruments, lke flute and voln. But on the other hand, defnng the structure of Javanese gamelan songs s qute trcky theoretcally. The song structure can be dstngushed by the number of lnes (where a lne conssts of four bars) n each song part, whle the song part can be dfferentated from each other by observng the playng pattern of the nstruments. Snce each nstrument group has ts own pattern, thus t delvers dfferent perodctes from the other group. Ths research attempts to address ths problem by representng the vsualzaton of perodcty dstrbuton along a muscal pece for rhythmc structure analyss. 3. METHOD There are three man stages conducted n ths research, as depcted n Fg.. We take a collecton of Javanese gamelan musc as audo nput and perform preprocessng stage. Ths stage ams to enhance relevant features whle t attenuates the rrelevant ones for the next stage. The second stage s beat perod nducton. We pass the autocorrelaton matrx of audo sgnal to a bank of comb flter resonators. These resonators serve as a bank of weghted perodcty templates, where the delays of delta functons represent perodctes that may be contaned n a muscal track. The output s a dstrbuton of perodctes based on ther confdence level. 40

3 Fgure System Overvew Fgure Preprocessng The thrd stage s the tempo clusterng and vsualzaton. We propose to explot perodcty dstrbuton to analyze the rhythmc pattern of a song. Each group of perodctes wth relatvely close dstance n the dstrbuton s assumed to belong to a certan nstrument group. The clusterng method s used to fnd the center of the group n order to cope wth varatons that exst wthn an nstrument group. 3. Preprocessng Detals on the preprocessng stage are shown n Fg.. The audo sgnals were recorded at 4400 Hz samplng frequency and are represented n tmefrequency doman usng Short-tme Fourer Transform (STFT). We mantan tme-frequency resoluton by applyng wndow length of 89 samples for the Fourer Transform and hop length of 44 samples, provdng 5.4 Hz frequency resoluton and 0 ms tme resoluton. For feature extracton, we use onset reducton functon that has been proven to be stable wth respect to frequency resoluton for Javanese gamelan musc [8], namely spectral flux (SF). Equaton and show the formulaton of SF functon. SF + ( n) = H( X(, n) X( ω, n ) ) ω= ω () x + x H( x) = () X s the magntude spectrum of the sgnal resulted from STFT; ω s the frequency bn and n s tme sample. H(x) s half wave rectfer. SF functon measures the change of magntude over tme for each frequency bn. Through the use of half wave rectfer, t defnes the detecton functon as the postve change of spectral flux across frequences. We consder the presence of tempo fluctuaton n Javanese gamelan musc. Thus the muscal track s dvded nto short analyss frames. And snce the analyss must accommodate tempo change that mght occur n a frame, the followng frame must overlaps the prevous one. The analyss frame must be long enough to be able to represent the longest beat perod n the track, whle the hop must be short enough to track tempo change. We refer to [4] to set the ncrement step (L f ) 5% of the frame length (L h ), provdng 75% overlap, as shown by Eq. 3. SF( n) n = + ( ) Lh... Lf + ( ) Lh F( n) = (3) 0 otherwse F (n) s the -th analyss frame. We apply the value of L h = 04 DS and L f = 56 DS to adapt wth Javanese gamelan musc. DS stands for detecton sample, and s a unt sample of the onset detecton functon. As we have mentoned n the prevous secton, each nstrument n Javanese gamelan ensemble has ts own tempo pattern. The nstrument whch has the longest duraton between two consecutve notes s gong, whose notatons appear at the end of a lne. Snce the objectve of ths research s to vsualze the tempo cluster dstrbuton whch comes from all nstruments playng n a song, then we set the length of the analyss frame to be able to present the longest beat perod of nstrument. A lne of notaton n Javanese gamelan musc conssts of sxteen beats, and based on our observaton, the duraton between two beats s approxmately 0.5 s. Thus the duraton of two gongs notes s at least 8 s. Snce the resoluton of DS n the analyss frame s 0 ms accordng to STFT settngs, then the requred length of the analyss frame s at least 800 DS. We choose the value of 04 DS for the reason of convenence. 4

4 Fgure 4 Perodcty Dstrbuton of a Sngle Frame Fgure 3 Perodcty Inducton From ths we also set the hop length at 56 DS to reflect the perod of a bar, whch s one fourth of the perod of a lne, snce a lne conssts of four bars. In order to remove nosy peaks that usually appear n the onset detecton sgnal, we apply a movng mean threshold and a half wave rectfer to the sgnal, as shown n eq. 4 and 5. Q n+ F ( n) = F( q) (4) Q q= n ~ F( n) = H( F( n) F( n)) (5) Q s the length of wndow whch s set to be 6 DS [4]. H(x) s half wave rectfer functon as mentoned n Eq.. Perodctes exst n the audo sgnal are then enhanced usng autocorrelaton functon descrbed n Eq. 6. Lf ~ F ~ ( n). F( n l) n= A( l) = l Lf l =,..., L f (6) 3.. Perodcty Inducton The autocorrelaton matrx resulted from prevous stage s consdered as the drvng functon where the perodcty analyss takes place. Fgure 3 shows the beat perod nducton based on [4]. The frst step s to create a comb template. Ths template serves as a reflecton of perodcty at several metrcal level and s represented by the sum of weghted delta functons at nteger multples of a perodcty, as shown by Eq. 7. Each comb template has a wdth proportonal to the perodcty and has a heght normalzed by ts wdth. We set the longest perodcty to be the same as the hop length of analyss frames, to derve at least one beat from each analyss frame. l ( l) = 4 p δ( τp + v) l p λ (7) p= v= p A Raylegh dstrbuton functon was used as a weghtng curve to approxmate pror dstrbuton of beat perod hypotheses. Ths functon has hgh ncrease for short lags whle t slowly decays for longer lags after the peak. Ths functon was selected snce t prefers shorter lags to be beat perods than the longer ones. τ τ β R ( τ) = e τ =,..., β L h (8) β s a parameter that sets the locaton of the peak. Daves et al used β = 43 to represent the common tempo of 0 bpm [4]. The product of comb template and Raylegh functon results n a shft nvarant comb flter bank, as shown n Eq. 9. Fnally, ths comb flter bank s used to generate beat perod dstrbuton by multplyng t wth the autocorrelaton functons of all analyss frames. Ths means that we take the dot product of the autocorrelaton functon of each analyss frame wth each beat perod hypotheses, as descrbed n eq. 0. The output matrx represents the beat perod dstrbuton of all analyss frames. C( l, τ ) = R( τ) λ ( l) (9) τ 4

5 clusterng algorthm s based on the mnmzaton of fuzzy c-means functonal as denoted n Eq.. c m J( Z; U, V) = ( µ ) z v () = k= k k B Fgure 5 Tempo Clusterng And Vsualzaton L f Y( ) = A( l) C( l, τ) τ (0) l= Fgure 4 depcts an example of beat perod dstrbuton of the frst analyss frame of a Javanese gamelan song n database. The man dfference between ths paper and that of Daves et al s on the pont of vew on ths beat perod dstrbuton. In ther paper, they chose the lag whch corresponds to the hghest confdence level as the beat perod of that partcular analyss frame, whch s around 40 DS n the example. They consder ths chosen lag as the beat perod whch s strongly contaned n the song, or n another words, t s contaned n all nstrument notatons. Whle n ths research, we use all beat perod dstrbutons nstead of choosng the most confdent one. We consder that each beat perod that has non-zero value of confdence level s contaned n the song frame and belongs to any of the nstrument notatons. The followng sub secton descrbes the utlzaton of beat perod dstrbuton for vsualzaton. 3. Clusterng and Vsualzaton Durng playng muscal nstruments or sngng a song, humans are naturally unable to follow the exact tempo repettvely. It s lke when we record a person s speech of the same utterance for several tmes, and we compare all the results, then we wll end up by havng many varatons n the sgnals. There wll always be tempo bas when humans play musc as well. Some neghborng beat perods may represent varatons to the reference value. Therefore we propose to use clusterng algorthm to overcome ths problem. We use fuzzy clusterng algorthm whch s capable of defnng membershp functon for all data to each cluster based on C- Mean objectve functon []. The flow of ths stage s depcted n Fg. 5. Fuzzy C-Means (FCM) Z s data, B s fuzzy subset, U s fuzzy partton matrx whch contans values of the -th membershp functon of B of Z. c s the number of cluster, and s the number of data. V s a vector of cluster centers that s to be determned,. n [ v, v,..., ] R V = v c, v () Followng fuzzy partton rules, we obtan condtons n Eq c = U c = B Z = (3) µ [ 0,], µ =, 0 < µ < (4) k k k= Where < < c and < k <. The mnmzaton s based on the squared nner product dstance norm as shown n Eq. 5. D kb k = z v (5) The mnmum pont of fuzzy objectve functon can be obtaned by takng the frst dervatve of Eq. 6 by settng the dervatve wth respect to U, V, λ to zero. J( Z; U, V, λ) = c = k= µ m kdkb + B c λk k= = k µ k That s when these followng condtons are met. k = c = D D kb jkb ( m ) (6) µ (7) 43

6 v k= = µ z k= m k µ m k k (8) The cluster center v s determned by takng a weghted mean of data that belongs to cluster, usng the membershp degrees of data to the cluster as the weghts. The membershp degree may vary from zero to one, provdng a soft clusterng, where each datum may have probablty to belong to more than one cluster. The algorthm was used to cluster the confdence level of beat perod hypotheses. The clusterng s performed n two dmenson space, where the frst axs s the beat perod and the second axs s the confdence level. We assume that there s no outler snce the data are of tme seres. (a) Sde vew of perodcty dstrbuton 4. EXPERIMETS Dataset contanng thrty Javanese gamelan songs s provded for experments. It conssts of three song structures categorzed as gendhng alt n Javanese gamelan musc, whch are lancaran, ladrang, and ketawang. The songs contan multple nstrument sounds, ncludng snger voces. There are three experments carred out n ths research. The frst experment amed to compare two settngs of analyss frame length and hop length. Fgure 6 shows the results. The second experment nvestgates the sutable number of perodcty cluster to represent nstrument groups, and t s depcted n Fg. 7. Whle Fg. 8 0 show the results of the thrd experment, whch s the analyss of song structure of Javanese gamelan musc contaned n dataset. We conducted frst experment wth two dfferent parameter settngs, whch are analyss frame length and hop length. Frst, we adopted the settng of [4], usng 5 DS analyss frame and 8 DS hop length. We compare the results wth those of our settng whch s based on the characterstc of Javanese gamelan musc. We have mentoned n prevous secton, that n order to adjust the frame length to the beat perod of gong, we need to set t to the length of a lne n Javanese gamelan musc, that s 04 DS approxmately. Snce a lne n Javanese gamelan musc conssts of four bars, we also set the beat perod hypotheses to be up to 56 DS. (b) Topvew of perodcty dstrbuton usng 5/8settng, showng a dstrbuton clp over the longer perodctes (c) Top vew of perodcty dstrbuton usng 04/56 settng, showng unclpped dstrbuton Fgure 6 Comparson of 5/8 Settng and 04/56 Settng 44

7 (a) Vsualzaton wth 0 Perodcty Clusters (b) Vsualzaton wth 30 Perodcty Clusters Fgure 7 Comparsons on the umber of Clusters And n order to derve at least one beat per frame, the number of beat perod hypotheses must be equal wth the hop length. The upper graph n Fg 6 represents perodcty dstrbuton usng 5/8 settng whle the lower one represents perodcty dstrbuton usng 04/56 settng. Usng the frst settng, the long perodctes (the upper part of dstrbuton) seems to get clpped. Whle usng the second settng, the dstrbuton shows all perodctes contaned n each frame and t s ndcated by the zero value of confdence levels n the upper part of the graph. Fgure 6(a) shows vsualzaton of perodcty dstrbuton along the track observed from sde vew. Fgure 6(b) and fg. 6(c) observe perodcty dstrbuton of the song from top vew n order to compare the dstrbuton usng general settng (5/8) and customzed settng (04/56). The lower sde of the graph represents faster perodcty whle the upper sde represents longer perodcty. Usng the frst settng, we obtan larger number of analyss frames and for the reason of clarty; we present the frst half of the frames n the graph. From both graphs we conclude that the general settng s not sutable for Javanese gamelan musc snce t caused dstrbuton clp that does not allow perodctes larger than 8 DS to appear, whch actually present n Javanese gamelan musc. Therefore we used the customzed settng to vsualze perodcty dstrbutons n the followng experments. The clp no longer appears when we enlarged the frame length and hop length accordng to our prevous calculaton. The clusterng process s conducted to address too many perodcty varatons caused by humans whle playng the nstruments. But on the other sde, the less number of clusters we determne, the more nformaton loss we get. The second reason of clusterng s to represent the perodcty of an nstrument group through the center of each cluster. Upon decdng the optmum number of perodcty cluster, we consder the number of nstrument groups that may present n an orchestra. In total, there are about ten nstrument groups n a complete gamelan set [3]. Each group can be dvded nto two or three small groups, so a complete set may have almost thrty nstrument groups. Fgure 7 depcts a comparson between vsualzaton wth 0 clusters and that wth 30 clusters. Fgure 7(a) represents perodcty dstrbuton wth more nformaton loss compared to that of Fg. 7(b). Ths can be seen from the pattern of domnant perodctes whch are marked by orange, grey and yellow colors. Fgure 7 has detaled shape of these colors whch may help analyzng the pattern of perodcty n a song. Therefore, we chose to set the number of cluster to be thrty, so that each cluster may conssts of 8-9 perodcty varatons from the total of 56 perodcty hypotheses. The thrd experment was carred out on a dataset of thrty Javanese gamelan songs, that conssts of three types of song structure, whch are lancaran, ladrang, and ketawang. Fgure 8-0 show representatves of each song structure n dataset. There are four features of nterest that we would present from the vsualzaton, whch are the wdth of dstrbuton, the average heght of dstrbuton, the pattern of domnant perodctes, and the value of tempo (perodcty wth hghest level of confdence) and ts fluctuaton along the track. The followng secton explans each of the features and how t can be used to analyze the structure of a Javanese gamelan song, as well as dscusses the analyss of the experment results. 5. DISCUSSIO Each of Javanese gamelan song structure has typcal characterstc that can be seen from the number of kethuk, kenong, and kempul notes and 45

8 ther postons n a notaton [, 3]. Unfortunately, detectng the sounds of these nstruments s very dffcult due to low sgnal ampltude compared to those of other nstruments. evertheless, gamelan experts and practtoners are able to recognze the song structure and dstngush t from the other ones by lstenng to the song, wthout havng the notaton. Therefore we propose to present a vsualzaton of perodcty dstrbuton and to explot some of ts features as a mean of analyss of Javanese gamelan song structures. For analyss purpose, we tested the normalty of the vsualzaton of perodcty dstrbutons of all songs n our database. Based on the central lmt theorem, as the number of sample drawn from a populaton s gettng large, whle the varance of the sample dstrbuton s fnte, the dstrbuton of the average of the random sample wll be approachng normal [4]. We used Lllefors for normalty test, whch s sutable for condton where the parameters of hypotheszed dstrbuton are not completely known [5]. The null hypothess s that the perodcty dstrbuton of all frames s a normal dstrbuton. The result s a logcal value h, whch can be 0 that accept the null hypothess, or t can be that rejects the null hypothess, at 5% sgnfcance level. The results proof that all songs have non normal dstrbuton, as ndcated by four varables, test result, h = ; p-value, p = 0; and the value of test statstcs s greater than that of crtcal value. There s hgh non lnearty n the sgnals whch makes the analyss much more complex and therefore we propose a vsualzaton approach for song structure analyss of Javanese gamelan musc. Analyzng the song structure of Javanese gamelan musc based on perodcty dstrbuton, brngs us back to the above-mentoned features that present n the vsualzaton. The frst feature s the wdth of dstrbuton. The term wdth refers to the perodcty clusters whch have sgnfcant value. We take an average value of confdence level for each cluster along the track. The sgnfcance of the value of each cluster s determned by a threshold. The clusters whose values are below the threshold are consdered as nsgnfcant. The wdth of a dstrbuton s the number of sgnfcant clusters. The threshold s calculated by followng Eq. 9. (a) Perodcty Dstrbuton of Kebo Gro (b) Fluctuaton of Tempo (c) Fluctuaton of Tempo Loudness Fgure 8 Representaton of Lancaran Song Structure 46

9 T S α = Y( t, s) TS φ (9) t= s= Y (t,s) s the perodcty dstrbuton, where t s perodcty cluster, s s analyss frame, 0 < α <. Wder dstrbuton means the song contans more varous perodcty contents. Snce dfferent nstrument generates dfferent perodcty, wder dstrbuton represents more number of nstruments than that of the narrower one. Songs whch fall nto lancaran structure have vbrant and flowng rhythm. Ths dynamc mpresson s bult by the nvolvement of many nstruments and by the relatvely fast and flat tempo. That s why songs of ths structure are usually put at the openng of events or ceremones. By fgurng out the wdth of perodcty dstrbuton, we may expect to whch structure the song has a closer relaton wth. The second feature s the average heght of perodcty dstrbuton. Ths feature depends on the magntude of tme-frequency representaton of audo sgnal. It s affected by the number of nstruments and the playng style, both of whch contrbute to the loudness of sound. Louder sound may mply hgher passon and therefore songs wth louder sound may relate to lancaran structure. The heght of confdence level n the vsualzaton s shown n the legend of each graph. Domnant perodctes are marked by dfferent colors n the vsualzaton, whch are orange, grey and yellow colors. We categorze the pattern of domnant perodctes nto sparse or dense, and short or long. Please note that ths s the only feature that s not numercally quantzed, but s vsually perceved. The last feature s based on the value of tempo and ts fluctuaton along the track. We wll present two graphs for ths feature, one that shows the fluctuaton of tempo value, and one that shows the fluctuaton of tempo loudness that s represented by the confdence level. From these two graphs, we analyze the change of the most confdent perodcty cluster that may ndcate song part transton and furthermore, may mply the rhythmc pattern of the song. We present n Fg. 8 - Fg. 0 three perodcty dstrbutons of Javanese gamelan songs, each of whch represents lancaran, ladrang, and ketawang song structures respectvely. Each perodcty dstrbuton s supported by two charts showng the fluctuaton of the most domnant perodcty (also known as tempo), and the fluctuaton of tempo loudness along the track. In (a) Perodcty Dstrbuton of Kutut Manggung (b) Fluctuaton of Tempo (c) Fluctuaton of Tempo Loudness Fgure 9 Representaton of Ladrang Song Structure 47

10 each chart we compare the fluctuaton wth a regresson lne to show the trend and we also put the equaton of the lne. From all analyss frames n a song, we only present one hundred consecutve analyss frames whose perodcty dstrbuton represents the rhythmc structure of the song for the reason of clarty. Fgure 8 depcts an example of lancaran song structure, whch s Kebo Gro. Based on calculaton usng Eq., we obtaned dstrbuton wdth of 3 clusters. Whle the other lancaran songs n dataset may have dstrbuton wdth n the range of -4 clusters. The average heght of dstrbuton s 4, whle the maxmum heght s almost 000 (Fg. 8(c)). Domnant perodctes are dense n the frst twenty analyss frames, but they are gettng sparser afterwards, as shown n Fg. 8(a). By observng Fg. 8(b) we could notce that the tempo fluctuates from 4 to but t mantans constant trend (ncreasng wth small gradent of 0.004), whle the loudness of tempo s decreasng (Fg. 8(c)). We could conclude that the playng style was strong at the begnnng but then t was gettng softer to the end, producng more sparse dstrbuton and lower confdence level of tempo. However, ths condton does not ndcate song part transston and t s supported by the fact that Kebo Gro s n the type of lancaran nban. Lancaran nban n ths case, mantans the rhythmc pattern untl the end of the song snce t usually conssts of one song part (part A) whch s played repettvely. Ladrang song structure has relatvely narrower perodcty dstrbuton n each analyss frame, as shown n Fg. 9 wth dstrbuton wdth of clusters. Fgure 9(a) s a vsualzaton of perodcty dstrbuton of Kutut Manggung, whose average heght of dstrbuton s We could see from the dstrbuton that the values of wdth and average heght of ladrang example are less than those of lancaran example. We may conclude from these facts that the number of nstruments played n the frst structure s less than that n the second structure. Ths supports softer mpresson that arses from ladrang songs generally [3]. Domnant perodctes are dense but are not contnuous along the song. The dscontnuty of the pattern ndcates song part transtons, whle the densty of domnant perodctes ndcates the densty of notaton pattern, where note appears at almost every beat n the song []. (a) Perodcty Dstrbuton of Ibu Pertw (b) Fluctuaton of Tempo (c) Fluctuaton of Tempo Loudness Fgure 0 Representaton of Ketawang Song Structure 48

11 Song structure Table Performance Measure TP FP F P R F- measure Lancaran Ladrang Ketawang Song transtons are also depcted by the drops of tempo loudness n Fg. 9(c). The trend of tempo fluctuaton decreases as shown by negatve gradent of lnear equaton n Fg. 9(b). Ths means that tempo gets faster to the end (shorter perodcty mples faster tempo). An example of ketawang song structure s represented n Fg. 0, whch s Ibu Pertw. The perodcty dstrbuton s 3 cluster wdth and has an average heght of Compared to the abovementoned structures, ketawang has relatvely smlar varaton of perodcty contents as lancaran, whch s mpled by the same dstrbuton wdth. But ketawang has softer playng style than that of lancaran, as shown by smaller value of average heght of dstrbuton. Vsually, we can observe from Fg. 0(a) that domnant perodoctes (marked by orange color) are dense durng the frst 50 frames, but they become sparse durng the rest frames. Ths change of pattern ndcates song part transtons, although the appearance s not as clear as that of ladrang. The trend lne of tempo fluctuaton s decreasng, as depcted by Fg. 0(b), showng that tempo gets faster to the end of the song. Whle the loudness of tempo shows a constant trend (Fg. 0(c)), wth two bg peaks ndcatng song part transtons. Performance s measured for each type of song structure. The evaluaton s based on the value of precson (P) and recall (R) whch s called F measure, as explaned by eq TP P = (0) TP + FP TP R = () TP + F PR F measure = () P + R TP or true postve represents correctly dentfed song structure, FP or false postve represents ncorrectly dentfed song structure, and F or true negatve represents ncorrectly rejected song structure. Thus, precson represents how good the dentfcaton s. And recall represents how good s the features of perodcty dstrbuton. Table shows the overall results. The best performance s obtaned by lancaran wth F measure of It s followed by ketawang and ladrang wth F measure of 0.90 and 0.75 respectvely. The hghest precson value s obtaned by lancaran, whle the hghest recall value s obtaned by ketawang. From these results we may conclude that ths method s most confdent to dentfy lancaran song structure, but on the other sde ths method s most senstve to dentfy ketawang song structure. These results are supported by the fact that the features of perodcty dstrbuton belong to lancaran are more dscrmnatve than those of other song structures. 6. COCLUSIOS We have presented a method of analyzng song structure of Javanese gamelan musc based on vsualzaton of perodcty dstrbuton. The exstence of non-lnearty n the audo sgnals has been proofed usng Lllefors test of normalty. Therefore we propose to utlze some vsual features n tempo dstrbuton to make nferences regardng the song structure of Javanese gamelan musc. We conclude that there are features of perodcty dstrbuton from whch we may use to dstngush the structure of a Javanese gamelan song. Although the analyss n ths research s manly qualtatve and vsually perceved, these results are useful for our future research. We may mplement a classfcaton of Javanese gamelan song structure based on these features, usng one of machne learnng technques. We also note that n order to obtan convergent results, we need to mprove our data selecton, for example the qualty of recordng. We found that there are data whch are qute nosy, and the analyss on the perodcty dstrbutons of these data s msleadng. The other mportant rule s to make sure that the songs are of classcal type. Ths wll guarantee that we obtan clear and dscrmnatve rhythmc patterns. REFERECES: [] Wardono, Soewondo, Teor Karawtan Jawa. Madun, Indonesa: Warga (984). [] Palgunad, B. Karawtan Jaw, Bandung, Indonesa: Penerbt ITB (00). [3] Supanggah, R. Bothekan Karawtan II: Garap, Solo, Indonesa: ISI Press Surakarta (009). [4] Daves, M. E. P., Plumbley, M. D., Contextdependent beat trackng of muscal audo, IEEE Transactons on Audo, Speech, and Language Processng, 5, (007). 49

12 [5] Suprapto, Y. K., Wulandar, D. P., and Tjahyanto, A., Saron musc transcrpton usng LPF-cross correlaton, Journal of Theoretcal and Appled Informaton Technology, 3, 7-79 (0). [6] Suprapto, Y. K., Harad, M., and Purnomo, M. H., Tradtonal Musc Sound Extracton Based on Spectral Densty Model usng Adaptve Cross-correlaton for Automatc Transcrpton, IAEG Internatonal Journal of Computer Scence, 38, -8 (0). [7] Suprapto, Y. K. Spectral Densty Based on Phase Shftng for Musc otaton. Jurnal Ilmah Kursor, 6, (0). [8] Wulandar, D. P., Tjahyanto, A., and Suprapto, Y. K., Gamelan Musc Onset Detecton based on Spectral Features. Telkomnka,, 078 (03). [9] Wulandar, D.P., Suprapto, Y.K., and Purnomo, M.H., Gamelan musc onset detecton usng Elman etwork, IEEE Internatonal Conference on Computatonal Intellgence for Measurement Systems and Applcatons (CIMSA), 996 (0). [0] Wulandar, D. P., Suprapto, Y. K., and Tjahyanto, A., Saron transcrpton based on tme-frequency analyss of onset detecton usng Short-tme Fourer Transform, Proceedngs of Internatonal Conference and Workshop on Basc and Appled Scences (ICOWOBAS), (0). [] Suprapto, Y. K., Purnomo, M. H., and Harad, M., Segmentaton of Identcal and Smultaneously Played Tradtonal Musc Instruments usng Adaptve, IPTEK The Journal of Technology and Scence, 0, 889 (009). [] Wntart, A., Suprapto, Y. K., and Wrawan, Independence test of gamelan nstrument sgnal n tme doman and frequency doman. Jurnal Ilmah Kursor, 7, (03). [3] Tjahyanto, A., Suprapto, Y. K., and Wulandar, D. P., Spectral-based Features Rankng for Gamelan Instruments Identfcaton usng Flter Technques. Telkomnka,, (03). [4] Tjahyanto, A., Suprapto, Y. K., Purnomo, M. H., and Wulandar, D. P., FFT-based features selecton for Javanese musc note and nstrument dentfcaton usng support vector machnes, IEEE Internatonal Conference on Computer Scence and Automaton Engneerng (CSAE), (0). [5] Wulandar, D. P., Tjahyanto, A., Suprapto, Y. K., Sudarma, M., Beat-trackng of Javanese Gamelan Muscal Audo based on Comb Flter Resonator, Semnar on Intellgent Technology and Its Applcatons (SITIA), (04). [6] Klapur, A., Davy, M., Sgnal Processng Methods for Musc Transcrpton, Sprnger, (006). [7] Talkn, D., A robust algorthm for ptch trackng, Speech Codng and Synthess, Amsterdam: Elsever Academc Press, (995). [8] de Chevegn e, A., Kawahara, H., YI, a fundamental frequency estmator for speech and musc, Journal of the Acoustcal Socety of Amerca,, (00). [9] Lahat, M., ederjohn, R., and Krubsack, D., A spectral autocorrelaton method for measurement of the fundamental frequency of nose-corrupted speech. IEEE Transactons on Acoustcs, Speech and Sgnal Processng, 35, (987). [0] Kuneda,., Shmamura, T., and Suzuk, J., Robust method of measurement of fundamental frequency by ACLOS: autocorrelaton of log spectrum, IEEE Internatonal Conference on Acoustcs, Speech, and Sgnal Processng,, 3-35 (996). [] McKnney, M. F., Moelants, D., Daves, M. E. P., Klapur, A., Evaluaton of audo beat trackng and musc tempo extracton algorthms. Journal of ew Musc Research, 36, -6 (007). [] Bezdek, J. C., Ehrlch, R., Full, W., FCM: The fuzzy c-means clusterng algorthm. Computers & Geoscences, 0, 9-03 (984). [3] Sumarsam. Gamelan: cultural nteracton and muscal development n central Java, Chcago, Unted States: Unversty of Chcago Press, (995). 50

13 [4] DeGroot, M.H., Schervsh, M.J., Probablty and statstcs, Boston: Pearson Educaton Inc., 893 (0). [5] Razal,. M., Wah, Y. B., and Scences, M., Power comparsons of Shapro-Wlk, Kolmogorov-Smrnov, Lllefors and Anderson-Darlng tests, Journal of Statstcal Modelng and Analytcs,, 33 (0). 5

Following a musical performance from a partially specified score.

Following a musical performance from a partially specified score. Followng a muscal performance from a partally specfed score. Bryan Pardo and Wllam P. Brmngham Artfcal Intellgence Laboratory Electrcal Engneerng and Computer Scence Dept. and School of Musc The Unversty

More information

Statistics AGAIN? Descriptives

Statistics AGAIN? Descriptives Cal State Northrdge Ψ427 Andrew Answorth PhD Statstcs AGAIN? What do we want to do wth statstcs? Organze and Descrbe patterns n data Takng ncomprehensble data and convertng t to: Tables that summarze the

More information

System of Automatic Chinese Webpage Summarization Based on The Random Walk Algorithm of Dynamic Programming

System of Automatic Chinese Webpage Summarization Based on The Random Walk Algorithm of Dynamic Programming Send Orders for Reprnts to reprnts@benthamscence.ae The Open Cybernetcs & Systemcs Journal, 205, 9, 35-322 35 Open Access System of Automatc Chnese Webpage Summarzaton Based on The Random Walk Algorthm

More information

RIAM Local Centre Woodwind, Brass & Percussion Syllabus

RIAM Local Centre Woodwind, Brass & Percussion Syllabus 8 RIAM Local Centre Woodwnd, Brass & Percusson Syllabus 2015-2018 AURAL REQUIREMENTS AND THEORETICAL QUESTIONS REVISED FOR ALL PRACTICAL SUBJECTS AURAL TESTS From Elementary to Grade V ths area s worth

More information

A STUDY OF TRUMPET ENVELOPES

A STUDY OF TRUMPET ENVELOPES A STUDY OF TRUMPET ENVELOPES Roger B. Dannenberg, Hank Pellern, and Istvan Dereny School of Computer Scence, Carnege Mellon Unversty Pttsburgh, PA 15213 USA rbd@cs.cmu.edu, hank.pellern@andrew.cmu.edu,

More information

Optimized PMU placement by combining topological approach and system dynamics aspects

Optimized PMU placement by combining topological approach and system dynamics aspects Optmzed PU placement by combnng topologcal approach and system dynamcs aspects Jonas Prommetta, Jakob Schndler, Johann Jaeger Insttute of Electrcal Energy Systems Fredrch-Alexander-Unversty Erlangen-Nuremberg

More information

LOW-COMPLEXITY VIDEO ENCODER FOR SMART EYES BASED ON UNDERDETERMINED BLIND SIGNAL SEPARATION

LOW-COMPLEXITY VIDEO ENCODER FOR SMART EYES BASED ON UNDERDETERMINED BLIND SIGNAL SEPARATION LOW-COMPLEXITY VIDEO ENCODER FOR SMART EYES BASED ON UNDERDETERMINED BLIND SIGNAL SEPARATION Jng Lu, Fe Qao *, Zhjan Ou and Huazhong Yang Department of Electronc Engneerng, Tsnghua Unversty ABSTRACT Ths

More information

Instructions for Contributors to the International Journal of Microwave and Wireless Technologies

Instructions for Contributors to the International Journal of Microwave and Wireless Technologies Instructons for Contrbutors to the Internatonal Journal of Mcrowave and Wreless Technologes Frst A. Author 1, Second Author 1,2, Thrd Author 2 1 Cambrdge Unversty Press, Ednburgh Buldng, Shaftesbury Road,

More information

QUICK START GUIDE v0.98

QUICK START GUIDE v0.98 QUICK START GUIDE v0.98 QUICK HELP Q A 1 STEP BY STEP 3 GLOSSARY 2 A B C 1 INSTALLATION 1. Make sure that the hardware nstallaton s performed by a certfed vendor 2. Install OTOTRAK app from Apple s App

More information

Modeling Form for On-line Following of Musical Performances

Modeling Form for On-line Following of Musical Performances Modelng Form for On-lne Followng of Muscal Performances Bryan Pardo 1 and Wllam Brmngham 2 1 Computer Scence Department, Northwestern Unversty, 1890 Maple Ave, Evanston, IL 60201 2 Department of Math and

More information

Automated composer recognition for multi-voice piano compositions using rhythmic features, n-grams and modified cortical algorithms

Automated composer recognition for multi-voice piano compositions using rhythmic features, n-grams and modified cortical algorithms Complex Intell. Syst. (2018) 4:55 65 https://do.org/10.1007/s40747-017-0052-x ORIGINAL ARTICLE Automated composer recognton for mult-voce pano compostons usng rhythmc features, n-grams and modfed cortcal

More information

Decision Support by Interval SMART/SWING Incorporating. Imprecision into SMART and SWING Methods

Decision Support by Interval SMART/SWING Incorporating. Imprecision into SMART and SWING Methods Decson Support by Interval SMART/SWING Incorporatng Imprecson nto SMART and SWING Methods Abstract: Interval judgments are a way of handlng preferental and nformatonal mprecson n multcrtera decson analyss.

More information

tj tj D... '4,... ::=~--lj c;;j _ ASPA: Automatic speech-pause analyzer* t> ,. "",. : : :::: :1'NTmAC' I

tj tj D... '4,... ::=~--lj c;;j _ ASPA: Automatic speech-pause analyzer* t> ,. ,. : : :::: :1'NTmAC' I ASPA: Automatc speech-pause analyzer* D. GERVERt and G. DNELEY Unversty of Durham, Durham, England ASPA: The Programs Snce the actual detals of nterface samplng, dsk storage routnes, etc., wll depend upon

More information

The UCD community has made this article openly available. Please share how this access benefits you. Your story matters!

The UCD community has made this article openly available. Please share how this access benefits you. Your story matters! Provded by the author(s) and Unversty College Dubln Lbrary n accordance wth publsher polces., Please cte the publshed verson when avalable. tle Dynamc Complexty Scalng for Real-me H.264/AVC Vdeo Encodng

More information

Hybrid Transcoding for QoS Adaptive Video-on-Demand Services

Hybrid Transcoding for QoS Adaptive Video-on-Demand Services 732 IEEE Transactons on Consumer Electroncs, Vol. 50, No. 2, MAY 2004 Hybrd Transcodng for QoS Adaptve Vdeo-on-Demand Servces Ilhoon Shn and Kern Koh Abstract Transcodng s a core technque that s used n

More information

Failure Rate Analysis of Power Circuit Breaker in High Voltage Substation

Failure Rate Analysis of Power Circuit Breaker in High Voltage Substation T. Suwanasr, M. T. Hlang and C. Suwanasr / GMSAR Internatonal Journal 8 (2014) 1-6 Falure Rate Analyss of Power Crcut Breaker n Hgh Voltage Substaton Thanapong Suwanasr, May Thandar Hlang and Cattareeya

More information

Why Take Notes? Use the Whiteboard Capture System

Why Take Notes? Use the Whiteboard Capture System Why Take Notes? Use the Whteboard Capture System L-we He Zhengyou Zhang and Zcheng Lu September, 2002 Techncal Report MSR-TR-2002-89 Mcrosoft Research Mcrosoft Corporaton One Mcrosoft Way Redmond, WA 98052

More information

Simple VBR Harmonic Broadcasting (SVHB)

Simple VBR Harmonic Broadcasting (SVHB) mple VBR Harmonc Broadcastng (VHB) Hsang-Fu Yu ab, Hung-hang Yang a, Y-Mng hen c, -Mng Tseng a, and hen-y Kuo a a Dep. of omputer cence & Informaton Engneerng, atonal entral Unversty, Tawan b omputer enter,

More information

Anchor Box Optimization for Object Detection

Anchor Box Optimization for Object Detection Anchor Box Optmzaton for Object Detecton Yuany Zhong 1, Janfeng Wang 2, Jan Peng 1, and Le Zhang 2 1 Unversty of Illnos at Urbana-Champagn 2 Mcrosoft Research 1 {yuanyz2, janpeng}@llnos.edu, 2 {janfw,

More information

Small Area Co-Modeling of Point Estimates and Their Variances for Domains in the Current Employment Statistics Survey

Small Area Co-Modeling of Point Estimates and Their Variances for Domains in the Current Employment Statistics Survey Small Area Co-Modelng of Pont Estmates and Ther Varances for Domans n the Current Employment Statstcs Survey Jule Gershunskaya, Terrance D. Savtsky U.S. Bureau of Labor Statstcs FCSM, March 2018 Dsclamer:

More information

Technical Information

Technical Information CHEMCUT Techncal Informaton CORPORATION Introducton The Chemcut CC8000 etcher has many new features desgned to reduce the cost of manufacturng and, just as mportantly, the cost of ownershp. Keepng the

More information

Integration of Internet of Thing Technology in Digital Energy Network with Dispersed Generation

Integration of Internet of Thing Technology in Digital Energy Network with Dispersed Generation Amercan Scentfc Research Journal for Engneerng, Technology, and Scences (ASRJETS) ISS (Prnt) 2313-4410, ISS (Onlne) 2313-4402 Global Socety of Scentfc Research and Researchers http://asrjetsjournal.org/

More information

Novel Quantization Strategies for Linear Prediction with Guarantees

Novel Quantization Strategies for Linear Prediction with Guarantees Smon S. Du* Ychong Xu* Yuan L Hongyang Zhang Aart Sngh Pulkt Grover Carnege Mellon Unversty, Pttsburgh, PA 15213, USA *: Contrbute equally. SSDU@CS.CMU.EDU YICHONGX@CS.CMU.EDU LIYUANCHRISTY@GMAIL.COM HONGYANZ@CS.CMU.EDU

More information

A Quantization-Friendly Separable Convolution for MobileNets

A Quantization-Friendly Separable Convolution for MobileNets arxv:1803.08607v1 [cs.cv] 22 Mar 2018 A Quantzaton-Frendly Separable for MobleNets Abstract Tao Sheng tsheng@qt.qualcomm.com Xaopeng Zhang parker.zhang@gmal.com As deep learnng (DL) s beng rapdly pushed

More information

arxiv: v1 [cs.cl] 12 Sep 2018

arxiv: v1 [cs.cl] 12 Sep 2018 Powered by TCPDF (www.tcpdf.org) Neural Melody Composton from Lyrcs Hangbo Bao, Shaohan Huang 2, Furu We 2, Le Cu 2, Yu Wu 3, Chuanq Tan 3, Songhao Pao, Mng Zhou 2 School of Computer Scence, Harbn Insttute

More information

A Comparative Analysis of Disk Scheduling Policies

A Comparative Analysis of Disk Scheduling Policies A Comparatve Analyss of Dsk Schedulng Polces Toby J. Teorey and Tad B. Pnkerton Unversty of Wsconsn* Fve well-known schedulng polces for movable head dsks are compared usng the performance crtera of expected

More information

MODELING AND ANALYZING THE VOCAL TRACT UNDER NORMAL AND STRESSFUL TALKING CONDITIONS

MODELING AND ANALYZING THE VOCAL TRACT UNDER NORMAL AND STRESSFUL TALKING CONDITIONS MODELING AND ANALYZING THE VOCAL TRACT UNDER NORMAL AND STRESSFUL TALING CONDITIONS Ismal Shahn and Naeh Botros 2 Electrcal/Electroncs and Comuter Engneerng Deartment Unversty of Sharjah, P. O. Box 27272,

More information

THE IMPORTANCE OF ARM-SWING DURING FORWARD DIVE AND REVERSE DIVE ON SPRINGBOARD

THE IMPORTANCE OF ARM-SWING DURING FORWARD DIVE AND REVERSE DIVE ON SPRINGBOARD THE MPORTANCE OF ARM-SWNG DURNG FORWARD DVE AND REVERSE DVE ON SPRNGBOARD Ken Yokoyama Laboratory of Bomechancs Faculty ofeducaton Kanazawa Unversty Kanazawa, Japan J unjro Nagano Department of Physcal

More information

Error Concealment Aware Rate Shaping for Wireless Video Transport 1

Error Concealment Aware Rate Shaping for Wireless Video Transport 1 Error Concealment Aware Rate Shapng for Wreless Vdeo Transport 1 Trsta Pe-chun Chen and Tsuhan Chen 2 Abstract Streamng of vdeo, whch s both source- and channel- coded, over wreless networks faces the

More information

Study on the location of building evacuation indicators based on eye tracking

Study on the location of building evacuation indicators based on eye tracking Study on the locaton of buldng evacuaton ndcators based on eye trackng Yue L Tsnghua Unversty yue-l5@malstsnghuaeducn Png hang Tsnghua Unversty zhangp@malstsnghuaeducn Hu hang Tsnghua Unversty, zhhu@tsnghuaeducn

More information

AMP-LATCH* Ultra Novo mm [.025 in.] Ribbon Cable 02 MAR 12 Rev C

AMP-LATCH* Ultra Novo mm [.025 in.] Ribbon Cable 02 MAR 12 Rev C AMP-LATCH* Ultra Novo Applcaton Specfcaton Receptacle Connectors for 114-40056 0.64 mm [.025 n.] Rbbon Cable 02 MAR 12 All numercal values are n metrc unts [wth U.S. customary unts n brackets]. Dmensons

More information

Detecting Errors in Blood-Gas Measurement by Analysiswith Two Instruments

Detecting Errors in Blood-Gas Measurement by Analysiswith Two Instruments CLIN. CHEM. 33/4, 512-517 (1987) Detectng Errors n Blood-Gas Measurement by Analysswth Two Instruments LouIs F. Metzger, Wllam B. Stauffer, Ann V. Kruplnskl, Rchard P. MIIlman,3 George S. Cembrowskl,2

More information

Multi-Line Acquisition With Minimum Variance Beamforming in Medical Ultrasound Imaging

Multi-Line Acquisition With Minimum Variance Beamforming in Medical Ultrasound Imaging IEEE Transactons on Ultrasoncs, Ferroelectrcs, and Frequency Control, vol. 60, no. 12, Decemer 2013 2521 Mult-Lne Acquston Wth Mnmum Varance Beamformng n Medcal Ultrasound Imagng Ad Ranovch, Zv Fredman,

More information

SKEW DETECTION AND COMPENSATION FOR INTERNET AUDIO APPLICATIONS. Orion Hodson, Colin Perkins, and Vicky Hardman

SKEW DETECTION AND COMPENSATION FOR INTERNET AUDIO APPLICATIONS. Orion Hodson, Colin Perkins, and Vicky Hardman SKEW DETECTION AND COMPENSATION FOR INTERNET AUDIO APPLICATIONS Oron Hodson, Coln Perkns, and Vcky Hardman Department of Computer Scence Unversty College London Gower Street, London, WC1E 6BT, UK. ABSTRACT

More information

Accepted Manuscript. An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time

Accepted Manuscript. An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time Accepted Manuscrpt An mproved artfcal bee colony algorthm for flexble ob-shop schedulng problem wth fuzzy processng tme Ka Zhou Gao, Ponnuthura Nagaratnam Suganthan, Quan Ke Pan, Tay Jn Chua, Chn Soon

More information

AN INTERACTIVE APPROACH FOR MULTI-CRITERIA SORTING PROBLEMS

AN INTERACTIVE APPROACH FOR MULTI-CRITERIA SORTING PROBLEMS AN INTERACTIVE APPROACH FOR MULTI-CRITERIA SORTING PROBLEMS A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY BY BURAK KESER IN PARTIAL FULFILLMENT

More information

Reduce Distillation Column Cost by Hybrid Particle Swarm and Ant

Reduce Distillation Column Cost by Hybrid Particle Swarm and Ant From the SelectedWorks of Dr. Sandp Kumar Lahr Summer July 20, 2016 Reduce Dstllaton Column Cost by Hybrd Partcle Swarm and Ant Dr. Sandp k lahr chnmaya lenka Avalable at: https://works.bepress.com/sandp_lahr/33/

More information

Analysis of Subscription Demand for Pay-TV

Analysis of Subscription Demand for Pay-TV Analyss of Subscrpton Demand for Pay-TV Manabu Shshkura Researcher Insttute for Informaton and Communcatons Polcy 2-1-2 Kasumgasek, Chyoda-ku Tokyo 110-8926 Japan m-shshkura@soumu.go.jp Tel: 03-5253-5496

More information

Lost on the Web: Does Web Distribution Stimulate or Depress Television Viewing?

Lost on the Web: Does Web Distribution Stimulate or Depress Television Viewing? Lost on the Web: Does Web Dstrbuton Stmulate or Depress Televson Vewng? Joel Waldfogel The Wharton School Unversty of Pennsylvana August 10, 2007 Prelmnary comments welcome Abstract In the past few years,

More information

Simon Sheu Computer Science National Tsing Hua Universtity Taiwan, ROC

Simon Sheu Computer Science National Tsing Hua Universtity Taiwan, ROC Mounr A. Tantaou School of Electrcal Engneerng and Computer Scence Unversty of Central Florda Orlando, FL 3286-407-823-393 tantaou@cs.ucf.edu Interacton wth Broadcast Vdeo Ken A. Hua School of Electrcal

More information

Quantization of Three-Bit Logic for LDPC Decoding

Quantization of Three-Bit Logic for LDPC Decoding Proceedngs of the World Congress on Engneerng and Computer Scence 2011 Vol II, October 19-21, 2011, San Francsco, USA Quantzaton of Three-Bt Logc for LDPC Decodng Raymond Moberly and Mchael E. O'Sullvan

More information

Modular Plug Connectors (Standard and Small Conductor)

Modular Plug Connectors (Standard and Small Conductor) Modular Plug Connectors (Standard and Small Conductor) Applcaton Specfcaton 114-6016 04 APR 11 All numercal values are n metrc unts [wth U.S. customary unts n brackets]. Dmensons are n mllmeters [and nches].

More information

A Scalable HDD Video Recording Solution Using A Real-time File System

A Scalable HDD Video Recording Solution Using A Real-time File System H. L et al.: A Scalable HDD Vdeo Recordng Soluton Usng A Real-tme Fle System A Scalable HDD Vdeo Recordng Soluton Usng A Real-tme Fle System Hong L, Stephen R. Cumpson Member, IEEE, Robert Jochemsen, Jan

More information

Simple Solution for Designing the Piecewise Linear Scalar Companding Quantizer for Gaussian Source

Simple Solution for Designing the Piecewise Linear Scalar Companding Quantizer for Gaussian Source 94 J. NIKOIĆ, Z. PERIĆ,. VEIMIROVIĆ, SIMPE SOUTION FOR DESIGNING THE PIECEWISE INEAR SCAAR Smle Soluton for Desgnng the Pecewse near Scalar Comandng Quantzer for Gaussan Source Jelena NIKOIĆ, Zoran PERIĆ,

More information

User s manual. Digital control relay SVA

User s manual. Digital control relay SVA User s manual Dgtal control relay DISIBEINT ELECTRONIC S.L, has been present n the feld of the manufacture of components for the ndustral automaton for more than years, and mantans n constant evoluton

More information

Product Information. Manual change system HWS

Product Information. Manual change system HWS Product Informaton HWS HWS Flexble. Compact. Productve. HWS manual change system Manual tool change system wth ntegrated ar feed-through and optonal electrc feed-through Feld of applcaton Excellently sutable

More information

Product Information. Manual change system HWS

Product Information. Manual change system HWS Product Informaton HWS HWS Flexble. Compact. Productve. HWS manual change system Manual tool change system wth ntegrated ar feed-through and optonal electrc feed-through Feld of applcaton Excellently sutable

More information

Craig Webre, Sheriff Personnel Division/Law Enforcement Complex 1300 Lynn Street Thibodaux, Louisiana 70301

Craig Webre, Sheriff Personnel Division/Law Enforcement Complex 1300 Lynn Street Thibodaux, Louisiana 70301 DATE OF APPLCATON: Craig Webre, Sheriff Personnel Division/Law Enforcement Complex 1300 Lynn Street Thibodaux, Louisiana 70301 N GENERAL EMAL ADDRESS: For Local Calls - (985) 532-4380 (985) 446-2255 (985)

More information

Critical Path Reduction of Distributed Arithmetic Based FIR Filter

Critical Path Reduction of Distributed Arithmetic Based FIR Filter Crtcal Path Reducton of strbuted rthmetc Based FIR Flter Sunta Badave epartment of Electrcal and Electroncs Engneerng.I.T, urangabad aharashtra, Inda njal Bhalchandra epartment of Electroncs and Telecommuncaton

More information

TRADE-OFF ANALYSIS TOOL FOR INTERACTIVE NONLINEAR MULTIOBJECTIVE OPTIMIZATION Petri Eskelinen 1, Kaisa Miettinen 2

TRADE-OFF ANALYSIS TOOL FOR INTERACTIVE NONLINEAR MULTIOBJECTIVE OPTIMIZATION Petri Eskelinen 1, Kaisa Miettinen 2 Internatonal Conference 20th EURO Mn Conference Contnuous Optmaton and Knowledge-Based Technologes (EurOPT-2008) May 20 23, 2008, Nernga, LITHUANIA ISBN 978-9955-28-283-9 L. Saalausas, G.W. Weber and E.

More information

current activity shows on the top right corner in green. The steps appear in yellow

current activity shows on the top right corner in green. The steps appear in yellow Browzwear Tutorals Tutoral ntroducton Ths tutoral leads you through the best practces of color ways operatons usng an llustrated step by step approach. Each slde shows the actual applcaton at the stage

More information

T541 Flat Panel Monitor User Guide ENGLISH

T541 Flat Panel Monitor User Guide ENGLISH T541 Flat Panel Montor User Gude ENGLISH Frst Edton (June / 2002) Note : For mportant nformaton, refer to the Montor Safety and Warranty manual that comes wth ths montor. Ths publcaton could contan techncal

More information

Cost-Aware Fronthaul Rate Allocation to Maximize Benefit of Multi-User Reception in C-RAN

Cost-Aware Fronthaul Rate Allocation to Maximize Benefit of Multi-User Reception in C-RAN Cost-Aware Fronthaul Rate Allocaton to Maxmze Beneft of Mult-User Recepton n C-RAN Dora Bovz, Chung Shue Chen, Sheng Yang To cte ths verson: Dora Bovz, Chung Shue Chen, Sheng Yang. Cost-Aware Fronthaul

More information

Scalable QoS-Aware Disk-Scheduling

Scalable QoS-Aware Disk-Scheduling Scalable QoS-Aware Dsk-Schedulng Wald G. Aref Khaled El-Bassyoun Ibrahm Kamel Mohamed F. Mokbel Department of Computer Scences, urdue Unversty, West Lafayette, IN 47907-1398 anasonc Informaton and Networkng

More information

Improving Reliability and Energy Efficiency of Disk Systems via Utilization Control

Improving Reliability and Energy Efficiency of Disk Systems via Utilization Control Ths paper appeared n the Proceedngs of the 2th IEEE Symposum on Computers and Communcatons (ISCC'08, Marrakech, Morocco, July 2008. Improvng Relablty and Energy Effcency of Dsk Systems va Utlzaton Control

More information

Expressive Musical Timing

Expressive Musical Timing Axel Berndt, Tlo Hähnel Department of Smulaton and Graphcs Otto-von-Guercke Unversty of Magdeburg {aberndt tlo}@sg.cs.un-magdeburg.de Abstract. Tmng s crucal for the qualty of expressve musc performances.

More information

AIAA Optimal Sampling Techniques for Zone- Based Probabilistic Fatigue Life Prediction

AIAA Optimal Sampling Techniques for Zone- Based Probabilistic Fatigue Life Prediction AIAA 2002-383 Optmal Samplng Technques or Zone- Based Probablstc Fatgue Le Predcton M. P. Enrght Southwest Research Insttute San Antono, TX H. R. Mllwater Unversty o Texas at San Antono San Antono, TX

More information

Correcting Image Placement Errors Using Registration Control (RegC ) Technology In The Photomask Periphery

Correcting Image Placement Errors Using Registration Control (RegC ) Technology In The Photomask Periphery Correctng Image Placement Errors Usng Regstraton Control (RegC ) Technology In The Photomask Perphery Av Cohen 1, Falk Lange 2 Guy Ben-Zv 1, Erez Gratzer 1, Dmtrev Vladmr 1 1. Carl Zess SMS Ltd., Karmel

More information

Discussion Paper Series

Discussion Paper Series Doshsha Unversty Center for the Study of the Creatve Economy Dscusson Paper Seres No. 2013-04 Nonlnear Effects of Superstar Collaboraton: Why the Beatles Succeeded but Broke Up Tadash Yag Dscusson Paper

More information

Production of Natural Penicillins by Strains of Penicillium chrysogenutn

Production of Natural Penicillins by Strains of Penicillium chrysogenutn Producton of Natural Pencllns by Strans of Pencllum chrysogenutn a J. FUSK and ЬЕ. WELWRDOVÁ ^Department of Mcrobology and Bochemstry, Slovak Techncal Unversty, Bratslava b Botka, Slovenská Ľupča Receved

More information

Clock Synchronization in Satellite, Terrestrial and IP Set-top Box for Digital Television

Clock Synchronization in Satellite, Terrestrial and IP Set-top Box for Digital Television Clock Synchronzaton n Satellte, Terrestral and IP Set-top Box for Dgtal Televson THESIS Submtted n partal fulflment of the requrements for the degree of DOCTOR OF PHILOSOPHY by MONIKA JAIN Under the Supervson

More information

The Traffic Image Is Dehazed Based on the Multi Scale Retinex Algorithm and Implementation in FPGA Cui Zhe1, a, Chao Li2, b *, Jiaqi Meng3, c

The Traffic Image Is Dehazed Based on the Multi Scale Retinex Algorithm and Implementation in FPGA Cui Zhe1, a, Chao Li2, b *, Jiaqi Meng3, c 3rd Internatonal Conference on Mechatroncs and Industral Informatcs (ICMII 2015) The Traffc Image Is Dehazed Based on the Mult Scale Retnex Algorthm and Implementaton n FPGA Cu Zhe1, a, Chao L2, b *, Jaq

More information

INSTRUCTION MANUAL FOR THE INSTALLATION, USE AND MAINTENANCE OF THE REGULATOR GENIUS POWER COMBI

INSTRUCTION MANUAL FOR THE INSTALLATION, USE AND MAINTENANCE OF THE REGULATOR GENIUS POWER COMBI NSTRUCTON MANUAL FOR THE NSTALLATON, USE AND MANTENANCE OF THE REGULATOR GENUS POWER COMB (TRANSLATON OF THE ORGNAL NSTRUCTON MANUAL N TALAN) PRELMNARY VERSON WARRANTY The devce s guaranteed 24 months

More information

Color Monitor. L200p. English. User s Guide

Color Monitor. L200p. English. User s Guide Color Montor L200p User s Gude Englsh Frst Edton (February / 2003) Note : For mportant nformaton, refer to the Montor Safety and Warranty manual that comes wth ths montor. Contents ENGLISH Safety (Read

More information

Conettix D6600/D6100IPv6 Communications Receiver/Gateway Quick Start

Conettix D6600/D6100IPv6 Communications Receiver/Gateway Quick Start Conettx / Communcatons Recever/Gateway Quck Start.0 Parts Lst able : Conettx System Components Qty. Descrpton Conettx Communcatons Recever/Gateway AC power cord Battery cable P660 I/O cable P660 Rack mount

More information

Environmental Reviews. Cause-effect analysis for sustainable development policy

Environmental Reviews. Cause-effect analysis for sustainable development policy Envronmental Revews Cause-effect analyss for sustanable development polcy Journal: Envronmental Revews Manuscrpt ID er-2016-0109.r2 Manuscrpt Type: Revew Date Submtted by the Author: 24-Feb-2017 Complete

More information

S Micro--Strip Tool in. S Combination Strip Tool ( ) S Cable Holder Assembly (Used only

S Micro--Strip Tool in. S Combination Strip Tool ( ) S Cable Holder Assembly (Used only Instructon Sheet LghtCrmp* Plus LC 408-10103 (for Jacketed Cable) Connectors 18 AUG 09 Rear Protectve Cap Termnaton CoverG Boot Connector Assembly Crmp Eyelet Duplex Clp G Connector kt s shpped wth these

More information

FPGA Implementation of Cellular Automata Based Stream Cipher: YUGAM-128

FPGA Implementation of Cellular Automata Based Stream Cipher: YUGAM-128 ISSN (Prnt) : 2320 3765 ISSN (Onlne): 2278 8875 Internatonal Journal of Advanced Research n Electrcal, Electroncs and Instrumentaton Engneerng An ISO 3297: 2007 Certfed Organzaton Vol. 3, Specal Issue

More information

Sealed Circular LC Connector System Plug

Sealed Circular LC Connector System Plug Sealed Crcular LC Connector System Plug Instructon Sheet Kt 1828618- [ ], Receptacle Kt 1828619- [ ], 408-10079 and EMI Receptacle Kt 1985193- [ ] 07 APR 11 Plug Kt 1828618 -[ ] Cable Fttng Receptacle

More information

CASH TRANSFER PROGRAMS WITH INCOME MULTIPLIERS: PROCAMPO IN MEXICO

CASH TRANSFER PROGRAMS WITH INCOME MULTIPLIERS: PROCAMPO IN MEXICO FCND DP No. 99 FCND DISCUSSION PAPER NO. 99 CASH TRANSFER PROGRAMS WITH INCOME MULTIPLIERS: PROCAMPO IN MEXICO Elsabeth Sadoulet, Alan de Janvry, and Benjamn Davs Food Consumpton and Nutrton Dvson Internatonal

More information

3 Part differentiation, 20 parameters, 3 histograms Up to patient results (including histograms) can be stored

3 Part differentiation, 20 parameters, 3 histograms Up to patient results (including histograms) can be stored st Techncal Specfcatons Desgned n France Wth a rch past and a professonal experence bult-up over 35 years, SFRI s a French nvatve company commtted to developng preon In Vtro Dst solutons. SFRI has bult

More information

Printer Specifications

Printer Specifications : Characterfonts:! Fort Pont 7P 0.5 pl Ptch 5cpl, Ocpl, 2cpl Proptlonel Epson Draf!o 0 lo j Epson Cower 0 0 0 Epson Roman O O O 0 Epson San6 Sent 0 O O O Epson Presllge j0 0 ~Epson Scnpt O 0 Epson Sormt

More information

User Manual. AV Router. High quality VGA RGBHV matrix that distributes signals directly. Controlled via computer.

User Manual. AV Router. High quality VGA RGBHV matrix that distributes signals directly. Controlled via computer. User Manual AV Router Hgh qualty VGA RGBHV matrx that dstrbutes sgnals drectly. Controlled va computer. Notce: : The nmaton contaned n ths document s subject to change wthout notce. SmartAVI makes no warranty

More information

Fast Intra-Prediction Mode Decision in H.264/AVC Based on Macroblock Properties

Fast Intra-Prediction Mode Decision in H.264/AVC Based on Macroblock Properties Fast Intra-Predcton Mode Decson n H.264/AVC Based on Macroblock Propertes Abstract Intra-predcton s a wdely used tecnque n ntra codng. H.264/AVC adopts rate-dstorton optmzaton (RDO) tecnque to obtan te

More information

User Manual ANALOG/DIGITAL, POSTIONER RECEIVER WITH EMBEDDED VIACCESS AND COMMON INTERFACE

User Manual ANALOG/DIGITAL, POSTIONER RECEIVER WITH EMBEDDED VIACCESS AND COMMON INTERFACE User Manual ANALOG/DIGITAL, POSTIONER RECEIVER WITH EMBEDDED VIACCESS AND COMMON INTERACE CONTENTS. Safety nstructons -------------------------------------------------------------------. eatures -------------------------------------------------------------------------------.

More information

in Partial For the Degree of

in Partial For the Degree of 37q h8( sta. co AN ANALYSS OF ROBERT NATHANEL DETT'S N THE BOTTOMS THESS Presented to the Graduate ouncl of the North Texas State Unversty n Partal Fulfllment of the Requrements For the Degree of MASTER

More information

Product Information. Universal swivel units SRU-plus

Product Information. Universal swivel units SRU-plus Product Informaton Unversal swvel unts SRU-plus SRU-plus Unversal swvel unts Robust. Fast. Hgh Performance. SRU-plus unversal rotary actuator Unversal unt for pneumatc swvel and turnng movements. Feld

More information

Social Interactions and Stigmatized Behavior: Donating Blood Plasma in Rural China

Social Interactions and Stigmatized Behavior: Donating Blood Plasma in Rural China Socal Interactons and Stgmatzed Behavor: Donatng Blood Plasma n Rural Chna X Chen Yale Unversty and IZA Davd E. Sahn Cornell Unversty and IZA Xaobo Zhang Pekng Unversty and IFPRI March 2018 Abstract Despte

More information

(12) Ulllted States Patent (10) Patent N0.: US 8,269,970 B2 P0lid0r et a]. (45) Date of Patent: Sep. 18, 2012

(12) Ulllted States Patent (10) Patent N0.: US 8,269,970 B2 P0lid0r et a]. (45) Date of Patent: Sep. 18, 2012 US008269970B2 (12) Ulllted States Patent (10) Patent N0.: P0ld0r et a]. (45) Date of Patent: Sep. 18, 12 (54) OPTICAL COMPARATOR WITH DIGITAL 6,945,652 B2 9/05 sakqta et a1 GAGE 7,058,109 B2* 6/06 Davs.....

More information

Turn it on. Your guide to getting the best out of BT Vision

Turn it on. Your guide to getting the best out of BT Vision Avalable n Bralle, large prnt and audo CD. Please call FREE on 8 8 15 for your copy. Turn t on Your gude to gettng the best out of www.bt.com/btvson V.2 28656 Enchantng flms to entertan all the famly Flms

More information

Product Bulletin 40C 40C-10R 40C-20R 40C-114R. Product Description For Solvent, Eco-Solvent, UV and Latex Inkjet and Screen Printing 3-mil vinyl films

Product Bulletin 40C 40C-10R 40C-20R 40C-114R. Product Description For Solvent, Eco-Solvent, UV and Latex Inkjet and Screen Printing 3-mil vinyl films Product Bulletn 40C Revson D, Effectve February 2016 (Replaces C, Apr. 15) 40C-10R 40C-20R 40C-114R Product Descrpton For Solvent, Eco-Solvent, UV and Latex Inkjet and Screen Prntng 3-ml vnyl flms Quck

More information

IN DESCRIBING the tape transport of

IN DESCRIBING the tape transport of Apparatus For Magnetc Storage on Three-Inch Wde Tapes R. B. LAWRANCE R. E. WILKINS R. A. PENDLETON IN DESCRIBING the tape transport of the DATAmatc 1, t s perhaps well to begn by revewng the nfluental

More information

DT-500 OPERATION MANUAL MODE D'EMPLOI MANUAL DE MANEJO MANUAL DE OPERA(_._,O. H.-,lri-D PROJECTOR PROJECTEUR PROYECTOR PROJETOR

DT-500 OPERATION MANUAL MODE D'EMPLOI MANUAL DE MANEJO MANUAL DE OPERA(_._,O. H.-,lri-D PROJECTOR PROJECTEUR PROYECTOR PROJETOR TM PROJECTOR PROJECTEUR PROYECTOR PROJETOR DT-500 OPERATION MANUAL MODE D'EMPLOI MANUAL DE MANEJO MANUAL DE OPERA(_._,O 8 f f 8 H.-,lr-D _I_H DEFINmON_TIM_IA I_T_RFACE Before usng the projector, please

More information

User guide. Receiver-In-Ear hearing aids. resound.com

User guide. Receiver-In-Ear hearing aids. resound.com User gude Recever-In-Ear hearng ads resound.com 400786011US-17.07-Rev.A.ndd 1 20-07-2017 12:52:40 Left Hearng Ad Rght Hearng Ad Seral number Seral number Model number Model number Recever type Recever

More information

Product Information. Miniature rotary unit ERD

Product Information. Miniature rotary unit ERD Product Informaton ERD ERD Fast. Compact. Flexble. ERD torque motor Powerful torque motor wth absolute encoder and electrc and pneumatc rotary feed-through Feld of applcaton For all applcatons wth exceptonal

More information

GENERAL AGREEMENT ON MMra

GENERAL AGREEMENT ON MMra RESTRICTED GENERAL AGREEMENT ON MMra TARIFFS AND TRADE Speeal Dstrbuton Agrculture Commttee A. Remarks IMPORT MEASURES Varable Leves and Other Specal Charges Addendum SWITZERLAND Imports of the products

More information

INTERCOM SMART VIDEO DOORBELL. Installation & Configuration Guide

INTERCOM SMART VIDEO DOORBELL. Installation & Configuration Guide INTERCOM SMART VIDEO DOORBELL Installaton & Confguraton Gude ! Important safety nformaton Read ths manual before attemptng to nstall the devce! Falure to observe recommendatons ncluded n ths manual may

More information

CONNECTIONS GUIDE. To Find Your Hook.up Turn To Page 1

CONNECTIONS GUIDE. To Find Your Hook.up Turn To Page 1 CONNECTIONS GUIDE To Fnd Your Hook.up Turn To Page 1 Connectng TV to Antenna (or Cable Wthout Cable Box) and No VCR (Hook-up 1A)... 2 Monaural VCR (Hook-up 1B)... 3 StereoVCR (Hook-up 1C)... 4 Cable Wth

More information

User guide. Receiver-In-The-Ear hearing aids, rechargeable Hearing aid charger. resound.com

User guide. Receiver-In-The-Ear hearing aids, rechargeable Hearing aid charger. resound.com User gude Recever-In-The-Ear hearng ads, rechargeable Hearng ad charger resound.com 400973011US-18.08-Rev.A.ndd 1 01-08-2018 14:18:12 Left Hearng Ad Rght Hearng Ad Seral number Seral number Model number

More information

V (D) i (gm) Except for 56-7,63-8 Flute and Oboe are the same. Orchestration will only list Fl for space purposes

V (D) i (gm) Except for 56-7,63-8 Flute and Oboe are the same. Orchestration will only list Fl for space purposes Measure # 1 2 3 5 6 7 8 9 10 11 12 13 1 15 16 17 18 Intro Motve 1 A Motve 1 B - "Wakarathe" Dynamcs mp terraced dymancs to mm.7 p Moderately fast and lght (quarter=96) 3 G Mnor motve 1 con't mp melody

More information

User guide. Receiver-In-The-Ear hearing aids, rechargeable Hearing aid charger. resound.com

User guide. Receiver-In-The-Ear hearing aids, rechargeable Hearing aid charger. resound.com User gude Recever-In-The-Ear hearng ads, rechargeable Hearng ad charger resound.com Seral number Model number Recever type Left Hearng Ad Low Power Medum Power Hgh Power Ultra Power Seral number Model

More information

SWS 160. Moment loading. Technical data. M x max Nm M y max Nm. M z max Nm

SWS 160. Moment loading. Technical data. M x max Nm M y max Nm. M z max Nm Moment loadng M x max. 7170 Nm M y max. 7170 Nm M z max. 3800 Nm Ths s the max. sum of all forces and moments (from acceleraton forces and moments, process forces or moments, emergency stop stuatons, etc.)

More information

Tempo and Beat Analysis

Tempo and Beat Analysis Advanced Course Computer Science Music Processing Summer Term 2010 Meinard Müller, Peter Grosche Saarland University and MPI Informatik meinard@mpi-inf.mpg.de Tempo and Beat Analysis Musical Properties:

More information

CONNECTIONS GUIDE. To Find Your Hook.up Turn To Page 1

CONNECTIONS GUIDE. To Find Your Hook.up Turn To Page 1 CONNECTIONS GUIDE To Fnd Your Hook.up Turn To Page 1 Connectng TV to Antenna (or Cable Wthout Cable Box) and No VCR (Hook-up 1A)...2 Monaural VCR (Hook-up 1B)...3 Stereo VCR (Hook-up 1C)... 4 Cable Wth

More information

Emotional Metaphors for Emotion Recognition in Chinese Text

Emotional Metaphors for Emotion Recognition in Chinese Text Emotonal Metaphors for Emoton Recognton n Chnese Text Xaox Huang 1, Yun Yang 2 and Changle Zhou 1,2 1 College of Computer Scence, Zhejang Unversty, 310027, P.R. Chna tshere@zju.edu.cn 2 Insttute of Artfcal

More information

include a comment explaining the reason and the portions of the pending application that are being

include a comment explaining the reason and the portions of the pending application that are being Page 1 of8 Federal Communications Commission Approved by OMB Washington, D.C. 20554 3060-1115 (February 2009) FCC 388 DTV Quarterly Activity Station Report FOR FCC USE ONLY 1 FOR COMMSSON USE ONLY "LE

More information

zenith Installation and Operating Guide HodelNumber I Z42PQ20 [ PLASHATV

zenith Installation and Operating Guide HodelNumber I Z42PQ20 [ PLASHATV Installaton and Operatng Gude HodelNumber I Z42PQ20 PLASHATV To vew the extended verson of owner's manual that contans the advanced features of ths TV set, vst our webste at http://www.enthservce.com Ths

More information

9! VERY LARGE IN THEIR CONCERNS. AND THEREFORE, UH, i

9! VERY LARGE IN THEIR CONCERNS. AND THEREFORE, UH, i 340 WELL, alack PAJAMAS WAS A SOMEWHAT METAPHORCAL 2 TERM. MANY VETNAMESE PEASANTS TENDED TO WEAR 3 BLACK PAJAMAS, BUT WHAT AM REFERRNG TO S THAT 4 OUTSDE OF THE NORTH VETNAMESE UNTS AND ~OME OF 5 THE

More information

MC6845P I 1.5. ]Vs ,.~

MC6845P I 1.5. ]Vs ,.~ MC6845 - CRT CONTROLLER (CRTC) The MCW5 CRT controller performs the nterface between an MPU and a raster-scan CRT dsplay. t s ntended for use n MPU-based controllers for CRT termnals n stand-alone or cluster

More information

Loewe bild 7.65 OLED. Set-up options. Loewe bild 7 cover Incl. Back cover. Loewe bild 7 cover kit Incl. Back cover and Speaker cover

Loewe bild 7.65 OLED. Set-up options. Loewe bild 7 cover Incl. Back cover. Loewe bild 7 cover kit Incl. Back cover and Speaker cover Product nformaton Loewe bld 7.65 Page of March 07 Loewe bld 7.65 OLED EU energy effcency class: B Screen dagonal (n cm) / Screen dagonal (n nch): 64 / 65 Power consumpton ON (n W): 80 Annual energy consumpton

More information