Is It Necesarily Have Music Background On Speed Painting

Introduction

The phrase "urban open space" tin can draw many types of open areas (Marcus and Francis, 1998). One definition holds that, equally the counterpart of evolution, urban open infinite is a natural and cultural resource, synonymous with neither unused land nor park and recreation areas. Another definition is that open space is land and/or water area with its surface open up to the heaven which has been consciously acquired or publicly regulated to serve conservation and urban shaping functions in add-on to providing recreational opportunities (Myers, 1975; Thompson, 2002). In modern cities, the benefits that urban open space provides to citizens tin be separated into three basic categories: recreation, ecology, and esthetic value (Brander and Koetse, 2011). Sound quality is considered to be a key role of the ecological/sustainable development of urban open spaces (Zhang et al., 2006). Notwithstanding, the sound surround of urban open up spaces is often not satisfactory because of a lack of consideration for human behavior during the planning and managing of the spaces (Meng and Kang, 2016). Therefore, research on the event of perception of the sound surround on crowd behavior will be of importance to landscape research in this field. Co-ordinate to the International Standards Organization, a "soundscape" is defined as an acoustic environment as perceived/experienced in context (ISO 12913-ane, 2014). Beliefs comes into play in soundscape cess in that the activities and behaviors of surrounding people course a fundamental facet of context.

Private behaviors by and large refer to the mental attitude or performance of a person in sure situations; their actions can exist largely random, bailiwick to the consequence of the environment (Jia, 2012). In contrast, crowd behaviors refer to the mental attitude or performance of a oversupply in an environment; they can be composed of certain regularities, subject to the consequence of the environment (Yuan and Tan, 2011; Xie et al., 2013). Thus, instead of individual behaviors, crowd behaviors are usually examined in studies on urban open spaces (Marušić, 2011; Lepore et al., 2016; Meng and Kang, 2016). Lewin et al. (1936) presented the following formula, which indicates the interaction between an individual and his/her surround: B = f (P, Eastward), in which B represents behavior; P represents persons, including individuals and groups; and E represents the environment in which those persons alive. Based on this formula, both users' social characteristics and local surroundings must be considered in human behavior studies. Previous studies pointed out that recreational behavior can exist affected by users' cultural background, age, and different local areas (Floyd, 1998; Payne et al., 2002; Guéguen et al., 2008).

Many dissimilar aspects of oversupply behavior can exist examined to draw conclusions. These can include characteristics of behaviors, such as move and action (Wang, 2014); characteristics of move, for instance, characterized as motility or non-movement, with the quondam including passing by and walking around and the latter including sitting (Chen, 2009); and characteristics of deportment, such every bit sitting, standing, watching, and loitering (Lepore et al., 2016). The number of participants is besides an important factor, that is, whether the behavior involves 1 person, 2 people, or multiple people (Jia, 2012); the intrinsic backdrop of such behaviors can besides be examined, such as whether they are necessary, spontaneous, or social (Gehl, 1987). The frequency and location of the behavior are also important, such equally whether it is neighborhood or urban behavior (Chen, 2009). Additionally, factors such every bit crowd beliefs in the audio surround, participation behavior, tendency beliefs, avoiding behavior, and other behaviors which are not affected past the environment are all significant angles that reveal crucial data regarding crowd behaviors (Jia, 2012).

The sound environment tin touch on human perception, and human being perception can influence crowd beliefs in both indoor and outdoor spaces. For case, previous studies have demonstrated that environmental music affects the pace of shopping and corporeality of time spent in shopping malls (Milliman, 1982). Other studies have also shown that eating and talking beliefs can be affected by groundwork music in dining spaces (Fiegel et al., 2014; Meng et al., 2017a). In urban open spaces, studies take found that people who pass by will stop to stand and watch music-related activities, whereas the amount of exercising behavior volition be changed a little by music-related activities (Meng and Kang, 2016). Another report indicated that the presence of music tin prolong the elapsing of stay in a tunnel when compared with silence, and classical music caused the longest elapsing of stay (Aletta et al., 2016). It has also been institute that in the instance of sound stimulation in the sound–visual environment of the countryside, report participants' gazing range was demonstrated to be significantly more dispersed than when no sound stimulation was present (Ren and Kang, 2015). Previous studies accept mainly focused on the issue of the audio surroundings on one's action (Zakariya et al., 2014; Aletta et al., 2016; Lepore et al., 2016). However, studies on the effects of certain typical sound sources on crowd behaviors classified as move or non-movement take been limited.

Musical audio is a common audio source in urban open spaces (N et al., 2004; Styns et al., 2007). Studies have shown that when people listen to music, their emotions fluctuate, and the effect is to alter their behavior (Orr et al., 1998). Studies have shown that unlike languages, tempos, tones, and sound levels of music tin can cause different effects on emotions, mental activities, and physical reactions. Overall, languages and tempos are the two most important factors (Sakharov et al., 2005; Carpentier and Potter, 2007). Other studies have institute that fast music is associated with more activation than boring music (Gomez and Danuser, 2004; Natarajan et al., 2004). For example, a study researching participants with headphones found that fast music increases walking speed, while wearisome music causes slower walking speeds (Franěk et al., 2014).

The cited studies signal that the sound environment can affect crowd behaviors; building on this finding, the present research focuses on the effects of music, an of import soundscape chemical element, on specific crowd behaviors, classified every bit movement, including passing by and walking around, or not-movement, including sitting. Previous studies indicate that path and speed are significant characteristics that describe movement behavior, while crowd density is important in describing non-movement behavior (Ye et al., 2012; Lavia et al., 2016). Therefore, the aims of this study are to find out: (1) whether music can modify the path or speed of passing by or walking around beliefs; we hypothesize that the speed of passing by or walking around behavior will increase with music, the path of passing by behavior volition shift closer to the music, and the area or perimeter of walking around beliefs will decrease with the music, since some previous studies take pointed out that music-related activities can increase the speed of passing by or walking around beliefs in some urban open up spaces and (2) whether music can decrease or increase sitting behaviors in urban open spaces; we hypothesize that the sitting behavior will increase with decreasing altitude of music, since eating and talking behaviors can be afflicted by music. An urban leisure square was chosen equally the case site, and music was chosen. In addition, three typical behaviors were selected for farther assay at the case site, and on-site observations were used for data collection. To achieve the aim of the study, several different approaches were explored. Starting time, this study examined the effect of music on the path and speed of passing by behavior. 2nd, it determined the effect of music on the path and speed of walking around behavior. Third, it observed the effect of music on the location of sitting behavior.

Materials and Methods

Survey Site

Previous studies have indicated that an urban street is a kind of linear space, where people have little choice simply for their paths to be confined to the pavement by buildings or motor vehicles (Hwang et al., 2011). In contrast, an urban square is an "areal" type of space, where people are gratis to choose their direction and path of travel (Marcus and Francis, 1998; Zakariya et al., 2014). In this study, a typical urban leisure square named "LANDSCAPE" square, located in Harbin, in Northeast Red china, was selected as the instance site. Maps of the square and survey site can be found in Figure 1.

FIGURE i. The map of LANDSCAPE square and the instance site: (A) location of LANDSCAPE square, (B) map of LANDSCAPE square, and (C) the survey site.

This site was called for the following 3 reasons. First, information technology is located at the crossing of Changjiang Route and Hongxiang Road; roads are nowadays on three sides of the square, and vegetation is found on the fourth side. The foursquare'southward surrounding environment (determining its calibration and format) resembles that of squares encountered in Europe and Japan (Ashihara, 1985; Whitlock, 2004), and thus has typicality. Next, the urban leisure foursquare is nearly 100 m long and 70 m wide and covers an area of about 7000 m^two, which is typical for modern cities (Dai, 2014). Finally, the foursquare has various sports facilities and lush vegetation; thus, a large number of local residents visit the square and it is an important urban open up infinite in this area for people to relax and collaborate. Overall, the square provides convenient conditions and the opportunity to assemble a large number of samples to study crowd motion behaviors as well as non-movement behaviors.

Studies indicate that environmental changes, such every bit changes in temperature and humidity, influence subjective acoustic perception (Thwaites et al., 2005; dela Fuente de Val et al., 2006). To avoid the effects of these environmental factors, measurements were performed on workdays in May and September 2017. The mean monthly temperatures (18–26°C) and the relative humidities of these months are approximately the same. Other studies bespeak that illuminance, which may also affect the perception or behaviors of users, changes with the time of day (Liu et al., 2013; Meng et al., 2017b). Thus, in the present report, measurements were performed betwixt 9:00–11:00 a.one thousand. and fourteen:00–xvi:00 p.m. daily on workdays to avoid the effects of time of day on the low-cal environment (Meng et al., 2017a).

Sound Source

In previous music studies, musical audio can be classified by sound level, tempo, genre, context, familiarity, and and then on (Husain et al., 2002; Sakharov et al., 2005; Kang, 2017). Based on the method used in the experiment by Lavia et al. (2016), the music excerpts were designed to be "inclusive," "non-aversive," and audio expert in a highly reverberant environment. In this study, a typically familiar pop vocal with lyrics, named "Free to Fly," was selected as the stimulus for intervention in the acoustic environment of the foursquare; the tempo of this song is 120 bpm.

A loudspeaker was used as the audio source; its location is shown in Figure 1C (S means sound source). The loudspeaker location was chosen for the following iii reasons. First, the music played past the loudspeaker can exist clearly heard at any betoken in the square. 2nd, the altitude betwixt the loudspeaker and the walls and other major reflective surfaces was ensured to exist at least xx m (Zahorik, 2002). Finally, to avoid any influence caused past the visual presence of the loudspeaker, it was placed near the water feature argue to avoid identification. During the experiment, the musical excerpt and silence were reproduced cyclically (Husain et al., 2002; Carpentier and Potter, 2007). The sound level was 88–90 dBA, exceeding background sound level.

Measurement of Audio Environment

Previous studies indicate that acoustic perception of urban open up spaces can be affected past sound pressure level (Yu and Kang, 2010; Xie et al., 2012). Since the measurement time for the current study was ix:00–11:00 a.thousand. and xiv:00–16:00 p.m., its crowd density was less than 0.05/g²; thus, the influence of the number of people on the square on the acoustic surround could be ignored (Meng and Kang, 2015). Therefore, audio-visual environmental measurement was carried out signal past betoken, not simultaneously.

To measure the sound environment, the area was divided into 6 m × 6 k units (Li and Meng, 2015). The equivalent continuous A-weighted sound force per unit area (L _Aeq) was immediately recorded using an 801 audio-level meter after each observation was completed. During the measurement, the sound-level meter was adapted to the slow speed (Kang and Zhang, 2010). Additionally, the distance between the measurement location and walls and other major reflective surfaces was ensured to be at least 1 m, and the altitude between the measurement location and the ground was 1.two–1.v m (Barron and Foulkes, 1994; Zahorik, 2002). One measurement was performed every 10 south. The data for each location were recorded for 5 min. A mean value was calculated to obtain the corresponding 50 _Aeq (Zhang et al., 2016).

The sound field in the urban open up infinite can be seen in Figure 2 (S means sound source). When there was no music sound source in the foursquare, the background acoustic level was 56.7 dB. When music was present, the acoustic level at 2 thou away from the music sound source was 88.3, or 31.6 dB higher than that without music. With the effect of musical sound source considered, the equivalent A-weighted sound pressure level reduced constantly with increasing altitude in the square. From 2 to 12 m abroad from the sound source, the sound pressure level reduced at 18.3 dB; from 12 to 24 chiliad away from the sound source, the acoustic level reduced at 6.four dB; and from 24 to 36 thousand away from the sound source, the sound pressure level reduced at 3.4 dB. The attenuation degree of the equivalent A-weighted sound level was mainly determined by the degree of enclosure for the infinite.

FIGURE two. The distribution of sound pressure in the case site (Due south means sound source): (A) with music and (B) without music.

Observation of Crowd Behaviors

In previous soundscape research, the investigation methods were classified as questionnaires and observations (Meng and Kang, 2016; Meng et al., 2017a). The questionnaires mainly focused on subjective evaluation indexes such equally sound comfort, subjective loudness, and sound preference. This written report involves measurements of oversupply motility and non-movement behaviors, including path, speed, location of the end points, etc., which is difficult to assess by questionnaire interview; thus, observation was the method used. To avoid any biases in the observation process, this study used an unmanned aerial vehicle (UAV; Oakes and North, 2008); the UAV was flown at a elevation of 100 m, since at that height, people on the square could not hear the noise of the UAV (Sinibaldi and Marino, 2013). The observations were made under completely natural conditions, and since the subjects mostly did not know that they were being observed, their behaviors were 18-carat; thus, the results were more reliable.

Each video shot by the UAV lasted 20–25 min. Videos of 10–15 groups for every situation were shot to ensure stochastic behavior in the measurement (Meng and Kang, 2013). Meanwhile, one photograph was taken every 10 s. The behaviors of the subjects were then classified and analyzed statistically, based on the review of videos and photos in the laboratory.

Statistical Analysis of Oversupply Behaviors

In this study, different samples were used for different behaviors, to capture the different times of collection of the behaviors. For instance, the menstruum needed to collect two samples of passing by behaviors was the same as that for three samples of walking around behavior and of v samples for sitting beliefs. In all, 51 samples were collected for passing by behavior: 26 samples (12 males and 14 females) without music and 25 (13 males and 12 females) with music; 84 samples were nerveless for walking effectually behavior, of which 43 samples (20 males and 23 females) were without music and 41 samples (twenty males and 21 females) with music; and 123 samples were collected for sitting behavior, 63 without music and 60 with music. In preliminary study, it was found that proportions of males and females engaging in given behaviors at the instance site are more often than not equal (Meng et al., 2017a). In club to employ the T-test to compare the samples, therefore, 24 samples (12 males and 12 females) without music and 24 samples (12 males and 12 females) with music were randomly selected for passing by behavior, forty samples (20 males and twenty females) with music and 40 samples (20 males and xx females) without music for walking around beliefs, and 60 samples without music and 60 with music for sitting behavior.

In the present written report, the power analysis was used to examination sample sizes (Carpentier and Potter, 2007). The results showed that the ability of samples for passing past behavior is 0.lx, p = 0.04 with consequence size 0.6; for walking effectually behavior, power is 0.77, p = 0.03, with effect size 0.6; and for sitting behavior, power is 0.87, p = 0.01 with consequence size 0.6. This indicates that all samples were sufficient.

The Path and Speed of Passing by Behaviors

To study the effect of music on the path and speed of passing past behaviors in urban open spaces, 48 samples, including 24 without music and 24 with, were selected for ascertainment from the videos shot past the UAV. The locations of the entrances and exits are shown in Figure 3. In previous studies, the path was represented past a prepare of dots, and each dot was considered a relatively independent process (Ye et al., 2012). The unabridged process of passing past behavior was thus viewed as a collection of data flows between the many dots. As revealed in Effigy 3A using passing by beliefs as an instance, the path points were labeled with circular dots representing the field of study's position as observed every 10 southward in the photography taken past the UAV. Thus, every bit Figure 3B shows, the path was in turn conceived past connecting all of the points.

Effigy three. The calculation process of speed of passing by behavior: (A) path points of passing past behavior and (B) path of passing by behavior.

The calculation procedure of the mean speed was every bit follows (Marušić, 2011; Ye et al., 2012):

$$\mathit{5}\mathit{northward}\mathrm{}=\mathrm{}\mathrm{\Delta }\mathit{L}\mathit{n}/\mathrm{\Delta }\mathit{T}\mathit{n}$$

where ΔLn is the distance of dot Cn and dot Cn+1, ΔTn is the time of dot Cn and dot Cn+1, Vn is the hateful speed of distance of dot Cn and dot Cn+one, and mean speed: ΔV = (51 + Vtwo + V3…… + Vn)/north.

The mean speed was a superimposition of data from 24 samples (with or without music). The unit of measurement was m/s.

The Path and Speed of Walking Around Behaviors

To written report the effect of music on the path and speed of walking around behaviors in urban open up spaces, 80 samples, including 40 samples without music and forty samples with music, were selected for observation from the videos shot by the UAV. Based on the observations, the paths of walking around behavior were classified into four types. The data from each walking beliefs were calculated as the mean of 5 occurrences, since previous studies betoken that the mistake of the mean of more than or equal to five times could be ignored. The adding process for hateful speed of walking behavior was the same every bit with passing by behavior. The results were the superimposition of data from 10 samples for each kind of path. The units used included m² (area), m (perimeter), and m/s (speed).

The Crowd Density of Sitting Behaviors

To study the upshot of music on the crowd density of a non-movement beliefs in urban open spaces, oversupply location was measured using the aforementioned photography method. Using sitting beliefs as an instance, one photograph shot by the UAV was selected every 2 min (Westover, 1989; Meng and Kang, 2015). In the laboratory, the locations of the crowd in the moving picture were labeled with round dots, and a half dozen thou × 6 thou grid was used. The value obtained was divided by the measurement expanse to determine a hateful value of crowd density as the average number of persons per foursquare meter. The unit used for measurement was persons/thouⁱⁱ. A total of 60 samples with music and lx samples without music were used. The unit used for measurement was persons/m^two (Meng et al., 2017b).

Results

Effects of Music on Motion Beliefs: Passing by Beliefs

Path

This section addresses the furnishings of music on the path of passing past behavior, which is shown in Figure 4, both with and without background music; the squares with dissimilar colors in Figures 4A,B indicate the numbers of users passing past, from 0 to 24 persons.

Figure 4. Effect of music on path of passing by behavior in the example site: (A) path without music, (B) path with music, (C) number of persons per grid without music, and (D) number of persons per grid with music. The dotted line indicates the purlieus of passing by behaviors. The squares with unlike colors mean the numbers of passing by users, from 0 to 24 persons.

Without background music

As Figure 4A shows, 79.two% of people with passing by behavior selected a relatively curt walking path. One possible reason for this is that when moving with a articulate goal, passers-by frequently tended to choose the shortest path. This is unremarkably a direct line approximately toward the goal, unless there is an obstacle (Gehl, 1987; Chen, 2009). It was establish that 20.8% of people engaging in passing past behavior selected a relatively longer walking path, and fifty-fifty that 8.three% of them walked near the border of the square. The areas covered by passing by behaviors were approximately 1436 chiliad².

With groundwork music

As Figure 4B shows, 0% of people with passing by beliefs walked nigh the edge of the square, and 87.5% of them selected the relatively shorter path to walk; 12.five% of people with passing by behavior passed past the square while walking close to the sound source. The areas covered by passing past behaviors were approximately 876 grand².

The area of passing by beliefs, both with and without groundwork music, is marked in Figure 4C, for the number of persons per grid without music, and Effigy 4D, with music. Comparison these two group of numbers, it can be seen that the path boundaries, with and without background music, were generally significantly different, with contained-samples T-test t = 0.848, p = 0.018, and upshot size = 0.412. The number of observations of people with passing by behaviors with a relatively short path shut to the music sound source in the foursquare was viii.3% higher with background music than without. Passing past behaviors near the border of the square with groundwork music were cypher when compared to the square without background music. Passing by behaviors closer to the music audio with background music were 12.5% higher when compared to the foursquare without background music. The areas covered by passing by behaviors tin can as well be reduced with music. This means that the presence of music caused people to be more centralized and walk closer to the sound source when passing past.

Speed

In terms of the speed of the passing by behavior, the foursquare was considered both with and without groundwork music.

Without groundwork music

The hateful speed of the walking around behavior in the foursquare was 1.30 thousand/s. The minimum speed was 1.09 m/southward, and the maximum speed was i.57 m/southward.

With groundwork music

The mean speed of the walking around behavior in the square was one.30 yard/s. The minimum speed was one.06 one thousand/southward, and the maximum speed was ane.59 g/s.

The mean speed of the passing by behavior in the square with music was generally not significantly different from that of without music, with independent-samples T-test t = -0.208, p = 0.836, and effect size = 0.032.

Furthermore, exploring gender effects indicated that the path and speed of the passing by behavior for males and females, with and without background music, were mostly not significantly dissimilar, with T-exam t = 0.132, p = 0.732, and effect size = 0.051.

Furnishings of Music on Movement Behavior: Walking Effectually Beliefs

Path

This section addresses the effects of music on the path of walking around beliefs. Previous studies signal that the paths from move behavior are non random, just rather they are regular and directional. In this instance, the users' paths in the square were influenced by environmental factors. Thus, based on the observations, the paths of walking around behavior were classified into four categories co-ordinate to the location of boundaries and the h2o characteristic fence in the square. As Figure 5 shows, path "a" represents walking effectually the fountain; path "b" implies walking around the fountain and tree puddle A; path "c" represents walking around the purlieus of the square except tree pool B; and path "d" implies walking around the purlieus of the square including tree pool B. In that location were significant differences between the four paths, and therefore they were separated for a comparative analysis in which the square with and without background music was considered.

FIGURE v. Four kinds of paths of walking around behavior.

Without background music

As Figure 6A shows, the hateful areas of the paths from walking around behavior in the foursquare were 1535 (a), 3024 (b), 4668 (c), and 5259 one thousand² (d). Every bit Figure 6B shows, the mean perimeters of the paths from walking around behavior in the square was 137 (a), 181 (b), 252 (c), and 274 m (d).

Figure 6. Effect of music on path of walking around behavior with and without music in the case site: (A) area and (B) perimeter.

With background music

As Figure 6A shows, the hateful areas of the paths from walking around behavior in the foursquare were 1038 (a), 1973 (b), 4311 (c), and 5338 grand² (d). Every bit Figure 6B shows, the mean perimeters of the paths from walking effectually behavior in the square were 113 (a), 160 (b), 243 (c), and 278 thousand (d).

The results indicated that the mean areas of walking around behavior in the square with background music were 32.36 (a), thirty.74 (b), 7.66 (c), and 4.thirty% (d) smaller than that of the square without background music. Comparing the cases with and without groundwork music indicated that the mean perimeters of walking around behavior in the square with background music were 17.34 (a), fifteen.14 (b), three.68 (c), and 1.54% (d) smaller than that of the square without groundwork music.

The ANOVA test was used to analysis the significance amidst music, category, and characteristics of walking effectually behavior, every bit shown in Table 1.

Table ane. ANOVA test for music, category, path and speed of walking effectually beliefs.

Compared with walking around behavior, with music and without, there were pregnant differences in areas at categories a and b, with ANOVA p = 0.000 and outcome size = 0.592 (a) and 0.529 (b); and there were no significant differences in areas at categories c and d, with ANOVA p = 0.165 (c) and 0.489 (d) and effect size = 0.104 (c) and 0.027 (d). Similarly, at that place were significant differences in perimeters at categories a and b, with ANOVA p = 0.000 (a) and 0.006 (b), and effect size = 0.621 (a) and 0.355 (b), and no significant differences in perimeters at categories c and d, with ANOVA p = 0.296 (c) and 0.249 (d), and effect size = 0.060 (c) and 0.073 (d). A possible reason for these results in categories a and b is that the crowd may take tended to motion toward sound stimuli so walk around at a shorter altitude away from the music; this is then similar to the results found for passing by behavior. Compared with categories a and b, a possible reason for the results in categories c and d is that the crowd at categories c and d was relatively far abroad from the music sound source and therefore the effect of music was not significant in these situations.

Speed

The mean speed of the iv paths was analyzed get-go. The maximum difference of hateful speeds among the four paths was 0.26 m/south without background music and 0.nineteen thou/s with background music. It can be seen, from Table one, that the speed of the paths in walking around beliefs with background music was significantly slower than without groundwork music in the 4 categories, with ANOVA p = 0.010 (a), 0.000 (b), 0.002 (c), and 0.002 (d), and effect size = 0.317 (a), 0.539 (b), 0.425 (c), and 0.410 (d). There were no significant differences betwixt the 4 categories, with ANOVA p = 0.590 (without music) and 0.965 (with music), and consequence size = 0.051 (without music) and 0.007 (with music). Therefore, the paths were merged to analyze the speed of walking effectually behavior. Effigy 7 shows the speed of walking around behavior in squares with and without background music.

Effigy vii. Effect of music on speed of walking effectually behavior with and without music in the square.

Without background music

The mean speed of the paths for walking around behavior in the square was 1.43 m/s. The minimum speed was 1.15 m/s, and the maximum speed was 1.74 1000/s.

With background music

The hateful speed of the paths for walking around beliefs in the foursquare was 1.14 m/s. The minimum speed was 0.93 m/s, and the maximum speed was one.49 thou/south.

Furthermore, exploring gender effects indicated that the path and speed of walking around beliefs for males and females, with and without groundwork music, was by and large non significantly different with T-test t = 0.211, p = 0.932, and effect size = 0.005.

Effects of Music on Non-motion Behavior: Sitting Beliefs

This section addresses the furnishings of music of sitting behavior on crowd density. According to the statistical analyses, the number of those exhibiting sitting behavior ranged from 0 to xxx. The human relationship between crowd density and altitude away from the music sound source in the foursquare is shown in Effigy 8, where the solid line means 0–ten persons, the dotted line means 11–xx persons, and the chain line means 21–30 persons, forth with the linear regression and the coefficient of decision R ². Results for observations with and without background music are discussed.

FIGURE 8. Relationship between crowd density of those with sitting behavior and distances away from music sound source in the foursquare: (A) with music and (B) without music, where the solid line means 0–10 persons, the dotted line means 11–20 persons, and the chain line means 21–30 persons.

Without Groundwork Music

As Effigy 8A shows, at that place were no significant differences in sitting behavior by distance away from the music sound source, with linear regression R ² of 0.014 (0–ten persons), 0.012 (11–twenty persons), and 0.021 (21–30 persons) and p > 0.one. The results indicated that sitting beliefs remained randomly distributed over the case site with the increase of crowd density, and was generally not changed with different distance of sound sources. When the number of persons engaged in sitting behavior ranged from 0 to x, xi to 20, and 21 to 30, the crowd densities were respectively about 0.46, ane.27, and 1.96 persons/m² within 15–xx m of the music audio source, and generally the same at 25–30 and 35–twoscore m.

With Background Music

Information technology tin exist seen that sitting behavior increased with decreasing altitude abroad from the music sound source, with linear regression R ⁱⁱ of 0.404 (0–10 persons), 0.875 (xi–xx persons), and 0.785 (21–thirty persons) and p < 0.001. It can exist seen from Effigy 8B that the crowd of persons engaged in sitting behavior decreased with increasing distance of music sound source. When the number of those exhibiting sitting behavior ranged from 0 to 10, the oversupply densities were 0.89 persons/grand² within 15–20 m of the music sound source, 0.56 persons/thousand² within 25–30 1000, and 0.41 persons/one thousand² inside 35–40 m. When the number of those exhibiting sitting behavior ranged from 10 to 20, the crowd densities were virtually one.82 persons/m² within xv–20 one thousand of the music sound source. When the number of those exhibiting sitting behavior ranged from twenty to 30, the crowd densities were near two.95 persons/m² within 15–20 m of the music sound source. Ane possible reason for these results is that the frequency of the music heard is reduced as the distance from music sound source is increased. It is interesting to notation that when the numbers exhibiting increase in sitting behavior, the inclination of the three corresponding linear trend curves fell faster. For example, when the number of those with sitting behavior ranged from 0 to ten, crowd density in the square with background music was reduced past 0.12 persons/m² for every 5 chiliad away from the source; when that number ranged from xx to 30, crowd density was reduced by 0.28 person/m² every v chiliad.

The comparing reveals that the crowd density of those exhibiting sitting behavior in the foursquare with background music was higher than that without background music, when the distance to sound source was relatively shorter, while the crowd density of sitting beliefs in the square with background music was lower than that without background music, when the altitude was relatively long. For instance, when the number of those with sitting behaviors ranged from xx to 30, at 15–20 thousand away from the music sound source, crowd density was 0.99 persons/m² higher with groundwork music than without, while at 35–40 one thousand away from the music sound source, oversupply density of those with sitting behaviors with background music was 0.99 persons/m² lower than without.

Discussion

The purpose of the present study was to explore the effect of music on movement behaviors, such as passing by behavior and walking effectually behavior, and non-movement behaviors, such as sitting beliefs, in urban open spaces.

Regarding the effect of music on passing by behavior, as discussed in Section "Effects of Music on Movement Behavior: Passing by Beliefs," the speed of passing past behavior was generally non significantly afflicted past music, while the path of passing by behavior shifted closer to the music sound source. This is in contrast to Lavia et al. (2016), who found that when music was deployed, people's walking speed through the other open spaces was slower. Ane possible reason for this is that the aims of passing by behavior are different in the two studies. In Lavia et al.'southward (2016) study, the users are just intending to walk in the street. Some previous studies have pointed that when walkers do non have a clear purpose, their speed can exist inverse by landscape or environmental factors (Chen, 2009; Jia, 2012; Xie et al., 2013). In contrast, in the present study, the users are passing to go to work or school, and thus take a clear purpose, making information technology reasonable that the speed of their behavior was not affected by the background music. An investigation amidst students too pointed out that visual differences do not change the speed of going to school (Fiegel et al., 2014). Every bit for the effect of audio on path of passing past behavior, some previous studies accept indicated that some animals and people will change their path to be far away from traffic dissonance (Lambert et al., 1984; Lengagne, 2008), whereas in the present study, it tin be seen that the path of the crowd can be inverse to be nearer the music. These results reinforce that behaviors can exist finer changed using the urban soundscape (Husain et al., 2002; Kang and Zhang, 2010).

Regarding the effect of music on walking effectually beliefs, as discussed in Section "Furnishings of Music on Movement Beliefs: Walking Around Behavior," the area, perimeter, and speed of the walking effectually beliefs decrease with music. This issue was the same every bit some other report in which oversupply behavior tended to move toward music (Jia, 2012). It is also interesting to note that a 3rd study found that the children have unlike play behaviors with increasing altitude from music (Holmes and Willoughby, 2005). In addition, the difference by the presence or absence of background music decreased as the area and perimeter increased. This was different from the upshot of music on speed of passing past behavior, as the mean speed during walking around behavior with groundwork music in the foursquare was 0.29 one thousand/s slower than without background music. These results show over again that behaviors without aims can be changed by environmental and landscape factors (Chen, 2009; Jia, 2012; Xie et al., 2013). Therefore, information technology can be concluded that the music drew people closer to the sound source and slowed their speed of walking. These results were the same as those constitute by Lavia et al. (2016) for other urban open spaces. A possible reason for this is that when hearing groundwork music, users feel more comfortable; thus, their speed of walking around slows. Another reason may exist that the presence of background music improves the feeling of rubber in the environment; thus, background music contributes to building an urban slow space, which is more suitable for residents' health (Ye et al., 2012).

Third, regarding the effect of music on the crowd density of those exhibiting sitting behavior, every bit discussed in Section "Effects of Music on Not-movement Behavior: Sitting Behavior," when at that place was no music, in that location was no significant difference in density no matter how close to the audio source they were located. However, as the altitude from the sound source increased, crowd density of those with sitting behavior decreased appropriately. Some previous studies have pointed that when there is no music, there is no significant divergence in the crowd density of those with sitting behavior in indoor spaces such every bit railway stations and underground shopping streets (Debrezion et al., 2009; Meng et al., 2013). In urban open spaces, Meng and Kang (2016) also constitute that human being sound-related activities generally take little outcome on the sitting behaviors of pedestrians. On the effect of music, this result proves over again the finding that music-related activities increased the number of persons who passed by who stood and watched (Meng and Kang, 2016). As with music, users tin as well exist attracted to a location by some nature sounds, such as sounds of bird or water (Liu et al., 2013). Some previous studies take also pointed that the audio-visual perception of music is unremarkably more salient than that of nature sounds (Aletta et al., 2016); this may pb to the dissimilar changes in sitting behaviors.

There are a number of possible implications for the practical value of the present report. Certain soundscapes, such as some music, may lead pedestrians to different paths in urban open spaces; it volition exist useful in landscape design to farther investigate means to lead walkers to suitable paths in gardens, for instance. Moreover, in leisure spaces such as parks, music tin can be used to decrease the speed of users and assistance them bask the landscape carefully. Furthermore, in balance areas in squares, a public-address organization can be used to circulate music to increase non-motility behavior, which can effectively increment interactions of citizens.

As demonstrated in the literature review, in that location are many classifications of musical sounds; notwithstanding, merely typical musical sounds were used in this study. In future studies, unlike tempos, genres, contexts, and levels of familiarity of musical sounds could also be investigated for comparing. Besides, the location of the sound source was stock-still in the present study; information technology can exist seen from other studies that different locations of sound sources may lead to varying acoustic perceptions (Kang and Zhang, 2010). Therefore, in future studies by the nowadays authors, different locations of music sound sources volition be designed to discover out their different effects on behaviors. Regarding motion and non-movement behaviors, only their speed and path were investigated in this work, whereas some previous studies take also pointed that characteristics of these behaviors such every bit duration and location also have effects that volition exist of import for landscape pattern and urban planning (Lepore et al., 2016); therefore, in future studies, the present authors will further explore and explain these factors likewise.

Writer Contributions

All authors carried out the study, designed the experiments, and wrote and critically reviewed the newspaper. QM and JK carried out the experiments. TZ analyzed the results.

Funding

This study was supported by the National Natural Science Foundation of Cathay (51678180 and 51778169).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of whatever commercial or financial relationships that could be construed as a potential disharmonize of involvement.

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Is It Necesarily Have Music Background On Speed Painting,

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