# Research on the Path of Artisan Spirit to Party Ideological Education in Colleges and Universities Based on Image Processing Technology

Authors: Bo Wang; Yu Li; Muhammad Talha
Journal: Journal of Advanced Transportation
 (2022)

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## Abstract

This research study aims to measure the study analysis on the path of artisan spirit related to party education related to the ideological in colleges and universities. The image processing technology research study describes that primary data related to the artisan spirit performance were gathered using different questions related to the image processing technology. The party ideological education is the dependent variable, and image processing technology includes segmentation quality factors and performance related to the image processing technology. These are considered independent variables. For measuring, the data used AMOS software and run different results related to the party ideological education in college and universities. The character design major has more significant commercial benefits and chances for growth. The investigation and analysis can confirm that the main is appropriately orientated. It maintains continual communication with companies, scheduling, increasing students’ practical competence, and also offers students internship opportunities. The overall results found that the artisan path to party ideological education significantly relates to college and universities based on the image processing technology.


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## Body

## 1. Introduction

Attributing significance to education means assigning a future value and devoting significance to education means securing the future. Undergraduates at universities and colleges are a valuable human capital for developing a country and the foundation for constructing a socialist efficient society [1]. Although the abilities of young people are quite significant, in a contemporary global development environment, it is especially crucial to encourage the spirit of artisanship to the best transition from a large population country to a significant population state. There is need to understand the transformation of manufacturing process of China toward the reinvention of Chinese system. It adheres to the current trend and acts as a healthy medication for societal advancement. With the arrival of the Industry 4.0 age, conventional manufacturing models and processes have been rendered obsolete, innovation has become associated with progress and development, and the innovation and artisanship spirit are linked by source and origin. As a result, the artisan spirit advances the requirements of the development of the current era [2].Apart from this, education of professional ethics, considered one of the components of political and ideological education in universities and colleges, is very significant for improving students’ personal and professional ethics levels. Artisanship spirit plays a significant role in encouraging students to create strong professional ethics practices. The recent inner soul’s supplies and orientation of the (HE) higher education is known as “moral education.” Simultaneously, the development of artisan spirit is a new challenge that technical and higher vocational education is confronting [3]. Whereas, in the 1950s, the image processing technology began in the US. China’s image processing technology began later than that of other countries. People working on the image processing technology have emerged in China since the 1980s; image processing technology is the fastest growing technology. We can enhance the quality of the image, such as resolution, clarity, and design. For the development of image processing, artisan spirit is necessary [4]. Today, image processing technology is used in every field of life, such as to diagnose a medical condition; art design, engineering, and science also have a vast application in image processing technology [5]. China is the fastest developing country and has a lot of facilities for individuals; according to the recent developing talent demand in the image processing technology, the universities and colleges of China should establish a comprehensive, shared. Moreover, open professional artisan spirit training foundation combines scale and diversity in the market of China and develops teaching quality and training of artisanship spirit, and professional and technical skill identification [6].Apart from this, students at universities and colleges must have a good talent in marketing because it is considered the essential element of the inventive party in developing “artisan spirit,”, and it is the critical trait that separates it from the other practical activities. Furthermore, universities and college students must complete the task of image design and do it in a high-quality manner [7]. One of the most significant factors for adapting to the current development condition is the inauguration of the artisanship spirit. Unfortunately, many universities and colleges today are plagued by a lack of perseverance, poor professional quality, sloppy work, a lack of creativity, and a lack of artisan spirit. To that end, universities and colleges of China should intensely encourage the artisan spirit, cultivate innovative talents, improve innovative industries, and promote transformation toward a smart power from manufacturing in China [8]. Furthermore, throughout the education process, the “artisan spirit” is quietly reinforced. The basis for understanding “Made in China 2025” was set in the student’s professional learning.To cultivate the artisan spirit in higher-level education in universities and vocational colleges, we must first take a leading position in higher education, ensuring that students value the artisan spirit. In addition, to improve skill and quality training of image processing, students must be guided to pay significant attention to the artisan spirit in their emotions and thoughts as part of the growth of great country artisans [9]. Apart from this, in short, China is an industrialized country, and in the new era of image processing technology, China has transferred its manufacturing power toward a smart power. Excellent technical workers and young talents are considered as important factors for the development in this era [10]. Artisan spirit is a desirable professional conduct that interpreters must exhibit. Therefore, higher universities and colleges should improve teaching strategies, combine the artisan spirit to workout goals of training of different disciplines, increase the staff of teachers, and make a practical teaching system. The atmosphere of artisan spirit should be formulated in the campus education as the primary location for technical personnel training. Furthermore, in short, it is investigated that there is an urgent need to develop the artisan spirit to ideological education in universities and colleges, so that students can meet the requirements of enterprises and which in turn seem helpful for the development of the economy in the country [11].


## 2. Research Objective

The article focuses on researching the path of artisan spirit to ideological education in universities and colleges that rely on the image processing technology. The research findings will be helpful for universities and colleges to improve their theoretical systems of political and ideological teaching. Political and ideological education in universities and colleges has the vital role of promoting ideological quality in the students at universities and colleges. It also supports them in developing the correct worldview. It is noted that in the economic domain, opening and reform have taken off, and simultaneously, they have gradually altered people’s ideas. As a result, the human nature is more impulsive, lucrative, and uncaring [12]. Therefore, cultivating the artisan spirit will assist the students at universities and colleges in forming correct values. Furthermore, it will help to perform and understand a socialist theoretical system intensely; besides, knowledge, a demanding work style and appropriate behavior may help students at universities and colleges develop a noble personality and healthy character. In addition, the growth of artisan spirit serves the demands of universities and colleges in developing advanced talents and presenting theoretical substructure for cultural and spiritual education at colleges.


## 3. Literature Review

### 3.1. Path of Artisan Spirit and Ideological Education in Universities and Colleges

In the context of image processing technology and artificial intelligence, Luo et al. focus on the development strategy of the artisan spirit of the students at universities and colleges in China [13]. It was explored that the growth of the artisan spirit satisfies the demands of universities and colleges in terms of providing theoretical support and developing new talents for cultural and spiritual education at universities and colleges. Liu and Wang claimed that professional ethics education is an essential component of universities and college education [13]. It was analyzed that with the fast development in image processing technology, the implementation of socialist principles and values into professional, ethical education and emerging development were the essential requirements for developing artisan spirit in universities and college students.Furthermore, after the opening and reforms, China has diligently extended its doors to everyone globally, absorbing successful experience and sophisticated knowledge from across the world and affiliating into the globalization trend. Hui investigated that China’s economic transformation has quickened, demand for high-quality composite specialists has surged, industry restructuring has been substantially reinforced [14]. As a result, the excellence’s artisan spirit has become increasingly vital, especially since entering an advanced age of image processing technology. Incorporating “artisan spirit” into universities and colleges’ political and ideological education is consistent with China’s current development trend, favorable to improving the professional quality of college and university students in China, thus promoting China’s great transformation toward “intellectual creation” from manufacturing and promoting social stability. Zeyang said that the importance of the artisan spirit in the development of talent in universities could not be overstated [15]. This research investigates the growing path of artisan spirit in universities and colleges using an examination of the features of applied colleges and the association of artisan spirit. After examination, the path of artisan spirit explored (a) bolstering top-level design and preserving the spirit of artisans; (b) prioritizing teacher development and raising educational standards; (c) depending on the integration of teaching and production to boost education; and practice (d) regular cultivation should be strengthened and the educational environment should be improved.Whereas, Xu claimed that the behavior performance and value orientation of applied skills while pursuing, refining, and carving perfection of the production is referred to as the artisan spirit [16]. It has a more profound development connotation with time, and the inventive modern connotation is more substantial than any other era. To adapt to economic growth, high-quality image processing talents with “artisan spirit” have been considered essential for training artisan spirit in universities and colleges. Tao studied that the artisan spirit is a type of innovation and cultural heritage [17]. The importance of nurturing the artisan spirit in college students is critical to their future development and growth. As a result, combining the requirements of teaching political and ideological education of college students with educational purposes has a remarkable role in the artisan spirit on political and ideological education and diligently extends the productive path of artisan spirit into college students’ political and ideological education.Production operations are considered more flexible; Fei said that businesses are urged to aim for craftsmanship excellence, enrich product style, foster an “artisan spirit, [18]” to increase quality, and develop a brand [19]. The debate over the “artisan spirit” has sparked a significant concern among researchers, specialists, and the public. At the same time, Lin and Dong claimed that developing the artisan spirit in the students at colleges and universities was a necessity for the training staff of artisan spirit in universities and colleges to accommodate the economic growth, particularly for the students of a medical group who have responsibilities for the health of people [20]. Jing et al. analyzed that with the fast development in the technology of image processing, there was not only necessity for the students to have a lot of computer experience, practice, and innovative abilities but also requirement for perfect personality, noble ethics, positive attitude, and artisan spirit to survive in the employment market [21]. Developing the computer talent’s artisan spirit in universities and colleges was essential for economic growth development. It was especially very significant for establishing the firms’ artisan spirit for computer majors’ development path in the future. It was also crucial for the student to enhance personal quality, improve professional ethics, etc. [21].In higher education, integrating political and ideological theory with engineering and science courses was a tough task. Yang et al. emphasizes the integration of artisan spirit into engineering and science courses by analyzing the features of engineering and science courses [22]. This study included a practical execution path plan and practical proposals for the broad promotion and growth of political and ideological education in engineering and science courses. In addition, cultivating exceptional inventive e-commerce skills was a tangible reflection of enhancing the “artisan spirit.” Based on the point of view of exceptional talent development, Pan examines the inadequacy of college e-commerce entrepreneurship and innovation instruction [23]. Therefore, forming the artisan spirit should become a significant aim of people training in universities and college education. Still, higher technical and vocational institutions have faced several challenges, including misunderstanding, a lack of social culture, and social image humiliation [24]. Peng claimed that universities and colleges should be devoted to growing spirit and inventiveness, beginning with the professional curriculum, personal values, and achievement or other elements of keen instructions, to spark a revolutionary ideological transformation [8]. Simultaneously, this represents a significant step forward in China’s cultivation of high-level art specialists and the fast growth of the cultural industry at the national level.


## 3.1. Path of Artisan Spirit and Ideological Education in Universities and Colleges

In the context of image processing technology and artificial intelligence, Luo et al. focus on the development strategy of the artisan spirit of the students at universities and colleges in China [13]. It was explored that the growth of the artisan spirit satisfies the demands of universities and colleges in terms of providing theoretical support and developing new talents for cultural and spiritual education at universities and colleges. Liu and Wang claimed that professional ethics education is an essential component of universities and college education [13]. It was analyzed that with the fast development in image processing technology, the implementation of socialist principles and values into professional, ethical education and emerging development were the essential requirements for developing artisan spirit in universities and college students.Furthermore, after the opening and reforms, China has diligently extended its doors to everyone globally, absorbing successful experience and sophisticated knowledge from across the world and affiliating into the globalization trend. Hui investigated that China’s economic transformation has quickened, demand for high-quality composite specialists has surged, industry restructuring has been substantially reinforced [14]. As a result, the excellence’s artisan spirit has become increasingly vital, especially since entering an advanced age of image processing technology. Incorporating “artisan spirit” into universities and colleges’ political and ideological education is consistent with China’s current development trend, favorable to improving the professional quality of college and university students in China, thus promoting China’s great transformation toward “intellectual creation” from manufacturing and promoting social stability. Zeyang said that the importance of the artisan spirit in the development of talent in universities could not be overstated [15]. This research investigates the growing path of artisan spirit in universities and colleges using an examination of the features of applied colleges and the association of artisan spirit. After examination, the path of artisan spirit explored (a) bolstering top-level design and preserving the spirit of artisans; (b) prioritizing teacher development and raising educational standards; (c) depending on the integration of teaching and production to boost education; and practice (d) regular cultivation should be strengthened and the educational environment should be improved.Whereas, Xu claimed that the behavior performance and value orientation of applied skills while pursuing, refining, and carving perfection of the production is referred to as the artisan spirit [16]. It has a more profound development connotation with time, and the inventive modern connotation is more substantial than any other era. To adapt to economic growth, high-quality image processing talents with “artisan spirit” have been considered essential for training artisan spirit in universities and colleges. Tao studied that the artisan spirit is a type of innovation and cultural heritage [17]. The importance of nurturing the artisan spirit in college students is critical to their future development and growth. As a result, combining the requirements of teaching political and ideological education of college students with educational purposes has a remarkable role in the artisan spirit on political and ideological education and diligently extends the productive path of artisan spirit into college students’ political and ideological education.Production operations are considered more flexible; Fei said that businesses are urged to aim for craftsmanship excellence, enrich product style, foster an “artisan spirit, [18]” to increase quality, and develop a brand [19]. The debate over the “artisan spirit” has sparked a significant concern among researchers, specialists, and the public. At the same time, Lin and Dong claimed that developing the artisan spirit in the students at colleges and universities was a necessity for the training staff of artisan spirit in universities and colleges to accommodate the economic growth, particularly for the students of a medical group who have responsibilities for the health of people [20]. Jing et al. analyzed that with the fast development in the technology of image processing, there was not only necessity for the students to have a lot of computer experience, practice, and innovative abilities but also requirement for perfect personality, noble ethics, positive attitude, and artisan spirit to survive in the employment market [21]. Developing the computer talent’s artisan spirit in universities and colleges was essential for economic growth development. It was especially very significant for establishing the firms’ artisan spirit for computer majors’ development path in the future. It was also crucial for the student to enhance personal quality, improve professional ethics, etc. [21].In higher education, integrating political and ideological theory with engineering and science courses was a tough task. Yang et al. emphasizes the integration of artisan spirit into engineering and science courses by analyzing the features of engineering and science courses [22]. This study included a practical execution path plan and practical proposals for the broad promotion and growth of political and ideological education in engineering and science courses. In addition, cultivating exceptional inventive e-commerce skills was a tangible reflection of enhancing the “artisan spirit.” Based on the point of view of exceptional talent development, Pan examines the inadequacy of college e-commerce entrepreneurship and innovation instruction [23]. Therefore, forming the artisan spirit should become a significant aim of people training in universities and college education. Still, higher technical and vocational institutions have faced several challenges, including misunderstanding, a lack of social culture, and social image humiliation [24]. Peng claimed that universities and colleges should be devoted to growing spirit and inventiveness, beginning with the professional curriculum, personal values, and achievement or other elements of keen instructions, to spark a revolutionary ideological transformation [8]. Simultaneously, this represents a significant step forward in China’s cultivation of high-level art specialists and the fast growth of the cultural industry at the national level.


## 4. Hypothesis Development

Following are the hypothesis statements of the paper; H1 = There is a significant relation between party ideological education based on the image processing technology. H2 = There is a positive relation between party ideological education based on the image processing technology.


### 4.1. Variables

Table1 shows the variables and notations.Table 1
Variables and notations.
Sr. NoDescriptionsNotations1Party ideological educationPIE2Image processing technologyIPT3Segmentation quality factorSQF4Performance of image processingPIP


#### 4.1.1. Part Ideological Education

Ideology in education refers to the ideas, practices, culture, and values governing economics, politics, morality, religion, knowledge, truth, and the creative arts. The educational system was decentralized, meaning a new set of ideological governing norms affected teachers’ actions, particularly TE. During this transition period, school privatization increased.


#### 4.1.2. Image Processing Technology

Image processing is the process of executing operations on an image to enhance it or extract useful information from it. It is a type of signal processing in which the input is an image, and the output is either an image or image characteristics/features. Image processing is one of today’s most rapidly evolving technologies.


#### 4.1.3. Segmentation Quality Factors Related to Image Processing

Image segmentation is a way of breaking down a digital image into several subgroups called image segments, which reduce the complexity of the image and make further processing or analysis of the image easier. In simpler words, segmentation is the process of assigning labels to pixels.


#### 4.1.4. Performance of Image Processing

Image processing is a method of improving or extracting critical information from an image by executing its operations. However, photos must be processed after capture in a post-processing phase to optimize workflow and prevent losing time. Thus, it was designed for people to boost their visual impact. Image processing takes a low-quality image as input and produces a higher-quality image as output. Image enhancement, restoration, encoding, and compression are all common image processing techniques. The manipulation of digital images with a computer is known as digital image processing. It is a branch of signals and systems that focuses specifically on visuals. The system’s input is a digital image and the system processes that image using efficient algorithms to produce an image as an output.


### 4.2. Methodology

This research study describes the path of artisan spirit to party ideological education in colleges and universities based on image processing technology. The research study based on primary data analysis for measuring the data used different questions related to the path artisan party ideological education and image processing technology. The data are collected with the help of questions from more than 100 respondents.


### 4.3. Methods and Techniques

This research study is based on primary data analysis by measuring AMOS software’s data to run different results. It also includes minimization history, covariance analysis as well as correlation coefficient, and model summary description. The results first describe that the path AMOS model in between variables included dependent and independent variables.


## 4.1. Variables

Table1 shows the variables and notations.Table 1
Variables and notations.
Sr. NoDescriptionsNotations1Party ideological educationPIE2Image processing technologyIPT3Segmentation quality factorSQF4Performance of image processingPIP


### 4.1.1. Part Ideological Education

Ideology in education refers to the ideas, practices, culture, and values governing economics, politics, morality, religion, knowledge, truth, and the creative arts. The educational system was decentralized, meaning a new set of ideological governing norms affected teachers’ actions, particularly TE. During this transition period, school privatization increased.


### 4.1.2. Image Processing Technology

Image processing is the process of executing operations on an image to enhance it or extract useful information from it. It is a type of signal processing in which the input is an image, and the output is either an image or image characteristics/features. Image processing is one of today’s most rapidly evolving technologies.


### 4.1.3. Segmentation Quality Factors Related to Image Processing

Image segmentation is a way of breaking down a digital image into several subgroups called image segments, which reduce the complexity of the image and make further processing or analysis of the image easier. In simpler words, segmentation is the process of assigning labels to pixels.


### 4.1.4. Performance of Image Processing

Image processing is a method of improving or extracting critical information from an image by executing its operations. However, photos must be processed after capture in a post-processing phase to optimize workflow and prevent losing time. Thus, it was designed for people to boost their visual impact. Image processing takes a low-quality image as input and produces a higher-quality image as output. Image enhancement, restoration, encoding, and compression are all common image processing techniques. The manipulation of digital images with a computer is known as digital image processing. It is a branch of signals and systems that focuses specifically on visuals. The system’s input is a digital image and the system processes that image using efficient algorithms to produce an image as an output.


## 4.1.1. Part Ideological Education

Ideology in education refers to the ideas, practices, culture, and values governing economics, politics, morality, religion, knowledge, truth, and the creative arts. The educational system was decentralized, meaning a new set of ideological governing norms affected teachers’ actions, particularly TE. During this transition period, school privatization increased.


## 4.1.2. Image Processing Technology

Image processing is the process of executing operations on an image to enhance it or extract useful information from it. It is a type of signal processing in which the input is an image, and the output is either an image or image characteristics/features. Image processing is one of today’s most rapidly evolving technologies.


## 4.1.3. Segmentation Quality Factors Related to Image Processing

Image segmentation is a way of breaking down a digital image into several subgroups called image segments, which reduce the complexity of the image and make further processing or analysis of the image easier. In simpler words, segmentation is the process of assigning labels to pixels.


## 4.1.4. Performance of Image Processing

Image processing is a method of improving or extracting critical information from an image by executing its operations. However, photos must be processed after capture in a post-processing phase to optimize workflow and prevent losing time. Thus, it was designed for people to boost their visual impact. Image processing takes a low-quality image as input and produces a higher-quality image as output. Image enhancement, restoration, encoding, and compression are all common image processing techniques. The manipulation of digital images with a computer is known as digital image processing. It is a branch of signals and systems that focuses specifically on visuals. The system’s input is a digital image and the system processes that image using efficient algorithms to produce an image as an output.


## 4.2. Methodology

This research study describes the path of artisan spirit to party ideological education in colleges and universities based on image processing technology. The research study based on primary data analysis for measuring the data used different questions related to the path artisan party ideological education and image processing technology. The data are collected with the help of questions from more than 100 respondents.


## 4.3. Methods and Techniques

This research study is based on primary data analysis by measuring AMOS software’s data to run different results. It also includes minimization history, covariance analysis as well as correlation coefficient, and model summary description. The results first describe that the path AMOS model in between variables included dependent and independent variables.


## 5. Results and Discussion

### 5.1. Growth Curve Model

The Figure1 growth curve model represents relation and significant level of variables with the slope and ICEP. The model shows a 1.00 significant relation between party ideology education and image processing technology.Figure 1
Growth curve model.The segmentation quality factor and its slope value of 0.33 and performance image processing show 1.000 significant relationships with each other.


### 5.2. Assessment of Normality

Table2 result presents the normality test analysis of each variable with the help values minimum, maximum, and rate present that skew values also describe the kurtosis value and c.r values. The party ideological education considers a dependent variable; its minimum value is 1.000, and the maximum value is 5.00. The skew value of party ideological education is 1.299. According to the result, the c.r value is 5.277 and 3.099, respectively. The image processing technology shows that the sew value is 1.572. Its c.r value is 6.386; its kurtosis value is 3.339. The result presents that the segmentation quality factor is part of the independent variable; its skew value is 1.019, its c.r value is 4.138, the kurtosis value is 1.799, and the c.r value is 3.653, respectively. The performance of image processing explains that minimum value of variable is one and maximum value is five, whereas the skew value is 1.065, respectively. The kurtosis value of performing image processing is 0.852, and its c.r value is 1.730, respectively. All the values present positive rates related to measuring the path of artisan spirit to party ideological education in colleges and universities based on the image processing technology.Table 2
Assessment of normality.
VariableMinMaxSkewc.r.Kurtosisc.r.Party ideological education1.0005.0001.2995.2771.5263.099Image processing technology1.0005.0001.5726.3863.3396.781Segmentation quality factor1.0004.0001.0194.1381.7993.653Performance of image processing1.0005.0001.0654.3270.8521.730Multivariate4.8393.475


### 5.3. Covariance

Table3 presents that covariance analysis among all variables included independent and dependent variables. The party ideological education present that 1.070 rate with each other; the image processing technology shows that 0.014 means 1% significant covariance analysis with party ideological education and 0.700 with segmentation quality factors. Image processing performance shows that negative covariance with party ideological education, the segmentation quality factors, and image processing technology rates are −0.045, −0.009, and −0.045, respectively. Therefore, the performance of image processing shows positive covariance with party ideological education. The condition number according to the result is 2.845, and its eigenvalues are 1.100, 0.782, 0.699, and 0.387, respectively. The determinant of sample covariance matrix presents that 0.232 shows a 23% significant level.Table 3
Covariance.
PIPSQFIPTPIEParty ideological education1.070Image processing technology0.0140.700Segmentation quality factor−0.129−0.0090.418Performance of image processing−0.045−0.009−0.0450.779Condition number = 2.845. Eigenvalues 1.100, 0.782, 0.699, and 0.387. Determinant of sample covariance matrix = 0.232.


### 5.4. Standardized Regression Weights

The result from Table4 describes that standardized regression weight with the estimate values the PIE and ICEPT shows that 0.063 estimate values in between them. The PIE and SLOPE correspond to 0.000 estimated values with each other, the IPT corresponds to the0.065 estimated value with IVEPT, and 0.267 corresponds to SLOPE. The PIP presents that 0.057 estimated values with ICEPT and PIP show that the SLOPE value rate is 0.704, respectively.Table 4
Standardized regression weights.
EstimatePIE<---ICEPT0.063PIE<---SLOPE0.000IPT<---ICEPT0.065IPT<---SLOPE0.267SQF<---ICEPT0.062SQF<---SLOPE0.519PIP<---ICEPT0.057PIP<---SLOPE0.704


### 5.5. Implied (For All Variables) Correlations

The result from Table5 represents that implied correlation between each variable included dependent and independent variables with the help of significant values. The results describe that party ideological education shows positive relationships with the slope and negative relation with the ICEPT rate level are −2.610 and 0.490, respectively. The image processing technology shows a positive relationship with the performance of the image processing rate level is 0.092, respectively. The segmentation quality factors that negatively correlated with each variable included SLOPE, PIP, SQF, IPT, and PIE. Image processing performance shows that adverse effects with other rate levels are −0.238, 0.063, and −0.164.Table 5
Implied (for all variables) correlations.
SLOPEICEPTPIPSQFIPTPIESLOPE1.000ICEPT−3.7861.000Party ideological education0.490−2.6101.000Image processing technology0.284−1.9040.0921.000Segmentation quality factor0.021−0.945−0.038−0.0481.000Performance of image processing−0.2380.063−0.164−0.120−0.0601.000


### 5.6. AIC

The Table6 result presents that the AIC model related to the default and saturated models also explain that independence model. The AIC model describes the 37.088 value of the default model and that AIC values present the saturated model is 28.000, the independence model presents that 20.803 values of AIC. According to the result, the BCC shows significant values of each model included 37.733, 29.505, and 21.663, respectively.Table 6
AIC.
ModelAICBCCBICCAICDefault model37.08837.733Saturated model28.00029.505Independence model20.80321.663


### 5.7. ECVI

The Table7 result presents ECVI analysis with the default model, the saturated model, and the independence model. The ECVI shows 0.378, 0.286, and 0.212, respectively. Furthermore, the result presents LO90 values, which show 0.261, 0.286, and 0.224 values of results. The result shows significant relations between party ideology education and image processing technology level are 0.03, respectively.Table 7
ECVI.
ModelECVILO 90HI 90MECVIDefault model0.3780.2610.5730.385Saturated model0.2860.2860.2860.301Independence model0.2120.2240.3050.221


### 5.8. Residual Covariance

The Table8 presents that residual covariance value relation between party ideological education and image processing technology party ideological education shows that 0.180 rates with each other. The image processing technology shows that negative residual covariance with segmentation quality factor and image processing technology rate are −0.061 and −0.035, respectively. Image processing performance shows that a segmentation quality factor shows that positive residual covariance with party ideology education at the rate level is 0.086 which shows a 8% significant level. The image processing performance shows that positive residual covariance with party ideology education rate level is 0.062 and that positive relationships with segmentation quality factors rate level are 0.078, respectively.Table 8
Residual covariance.
PIPSQFIPTPIEParty ideological education0.180Image processing technology−0.061−0.035Segmentation quality factor−0.0990.025−0.258Performance of image processing0.0860.078−0.0030.062


### 5.9. Minimization History

Table9 results present minimization history values with negative rates, the smallest values, and the ratios of all iterations. The negative eigenvalues show that the condition value of 2, 1, 0, 0, 0, and 0 present that of each iteration is 1604.890, 256.708, 242.931, respectively. The diameter rates of each iteration are 9999.00, 0.926, 0.209, and 1.130, respectively. The results present that rations of each iteration are 0.880, 0.773, 0.000, 1.172, 1.124, 1.039, 1.003, and 1.000, respectively.Table 9
Minimization history.
IterationNegative eigenvaluesCondition #Smallest eigenvalueDiameterFEntriesRatio0E2−0.3239999.000243.97709999.0001e∗1−0.8400.92685.703180.8802E01604.8900.20947.73260.7733E0256.7081.13034.92830.0004E0242.9310.18026.27511.1725E0255.5790.13625.14211.1246E0258.2840.04125.08811.0397E0263.7710.00325.08811.0038E0263.8340.00025.08811.000


### 5.10. Critical Ratios for Differences between Parameters

The above Table10 presents the critical ratio for differences between parameters with the help of covariance, variance, and mean values. The covariance ratio shows that 0.000, which means a 100% significant level. The I variance presents a 0.618 rate of covariance, and that S variance shows the 1.407 rates of covariance and 2.016 rates of variance, respectively. The overall results present the performance of mean, variance, and covariance of independent and dependent variables.Table 10
Critical ratios for differences between parameters.
CovarianceI VarianceS VarianceVarI MeanS MeanCovariance0.000I Variance0.6180.000S Variance1.4072.0160.000Var6.9305.0120.8570.000I Mean11.55214.6904.2599.3490.000S Mean1.7591.258−0.776−3.389−7.4480.000


## 5.1. Growth Curve Model

The Figure1 growth curve model represents relation and significant level of variables with the slope and ICEP. The model shows a 1.00 significant relation between party ideology education and image processing technology.Figure 1
Growth curve model.The segmentation quality factor and its slope value of 0.33 and performance image processing show 1.000 significant relationships with each other.


## 5.2. Assessment of Normality

Table2 result presents the normality test analysis of each variable with the help values minimum, maximum, and rate present that skew values also describe the kurtosis value and c.r values. The party ideological education considers a dependent variable; its minimum value is 1.000, and the maximum value is 5.00. The skew value of party ideological education is 1.299. According to the result, the c.r value is 5.277 and 3.099, respectively. The image processing technology shows that the sew value is 1.572. Its c.r value is 6.386; its kurtosis value is 3.339. The result presents that the segmentation quality factor is part of the independent variable; its skew value is 1.019, its c.r value is 4.138, the kurtosis value is 1.799, and the c.r value is 3.653, respectively. The performance of image processing explains that minimum value of variable is one and maximum value is five, whereas the skew value is 1.065, respectively. The kurtosis value of performing image processing is 0.852, and its c.r value is 1.730, respectively. All the values present positive rates related to measuring the path of artisan spirit to party ideological education in colleges and universities based on the image processing technology.Table 2
Assessment of normality.
VariableMinMaxSkewc.r.Kurtosisc.r.Party ideological education1.0005.0001.2995.2771.5263.099Image processing technology1.0005.0001.5726.3863.3396.781Segmentation quality factor1.0004.0001.0194.1381.7993.653Performance of image processing1.0005.0001.0654.3270.8521.730Multivariate4.8393.475


## 5.3. Covariance

Table3 presents that covariance analysis among all variables included independent and dependent variables. The party ideological education present that 1.070 rate with each other; the image processing technology shows that 0.014 means 1% significant covariance analysis with party ideological education and 0.700 with segmentation quality factors. Image processing performance shows that negative covariance with party ideological education, the segmentation quality factors, and image processing technology rates are −0.045, −0.009, and −0.045, respectively. Therefore, the performance of image processing shows positive covariance with party ideological education. The condition number according to the result is 2.845, and its eigenvalues are 1.100, 0.782, 0.699, and 0.387, respectively. The determinant of sample covariance matrix presents that 0.232 shows a 23% significant level.Table 3
Covariance.
PIPSQFIPTPIEParty ideological education1.070Image processing technology0.0140.700Segmentation quality factor−0.129−0.0090.418Performance of image processing−0.045−0.009−0.0450.779Condition number = 2.845. Eigenvalues 1.100, 0.782, 0.699, and 0.387. Determinant of sample covariance matrix = 0.232.


## 5.4. Standardized Regression Weights

The result from Table4 describes that standardized regression weight with the estimate values the PIE and ICEPT shows that 0.063 estimate values in between them. The PIE and SLOPE correspond to 0.000 estimated values with each other, the IPT corresponds to the0.065 estimated value with IVEPT, and 0.267 corresponds to SLOPE. The PIP presents that 0.057 estimated values with ICEPT and PIP show that the SLOPE value rate is 0.704, respectively.Table 4
Standardized regression weights.
EstimatePIE<---ICEPT0.063PIE<---SLOPE0.000IPT<---ICEPT0.065IPT<---SLOPE0.267SQF<---ICEPT0.062SQF<---SLOPE0.519PIP<---ICEPT0.057PIP<---SLOPE0.704


## 5.5. Implied (For All Variables) Correlations

The result from Table5 represents that implied correlation between each variable included dependent and independent variables with the help of significant values. The results describe that party ideological education shows positive relationships with the slope and negative relation with the ICEPT rate level are −2.610 and 0.490, respectively. The image processing technology shows a positive relationship with the performance of the image processing rate level is 0.092, respectively. The segmentation quality factors that negatively correlated with each variable included SLOPE, PIP, SQF, IPT, and PIE. Image processing performance shows that adverse effects with other rate levels are −0.238, 0.063, and −0.164.Table 5
Implied (for all variables) correlations.
SLOPEICEPTPIPSQFIPTPIESLOPE1.000ICEPT−3.7861.000Party ideological education0.490−2.6101.000Image processing technology0.284−1.9040.0921.000Segmentation quality factor0.021−0.945−0.038−0.0481.000Performance of image processing−0.2380.063−0.164−0.120−0.0601.000


## 5.6. AIC

The Table6 result presents that the AIC model related to the default and saturated models also explain that independence model. The AIC model describes the 37.088 value of the default model and that AIC values present the saturated model is 28.000, the independence model presents that 20.803 values of AIC. According to the result, the BCC shows significant values of each model included 37.733, 29.505, and 21.663, respectively.Table 6
AIC.
ModelAICBCCBICCAICDefault model37.08837.733Saturated model28.00029.505Independence model20.80321.663


## 5.7. ECVI

The Table7 result presents ECVI analysis with the default model, the saturated model, and the independence model. The ECVI shows 0.378, 0.286, and 0.212, respectively. Furthermore, the result presents LO90 values, which show 0.261, 0.286, and 0.224 values of results. The result shows significant relations between party ideology education and image processing technology level are 0.03, respectively.Table 7
ECVI.
ModelECVILO 90HI 90MECVIDefault model0.3780.2610.5730.385Saturated model0.2860.2860.2860.301Independence model0.2120.2240.3050.221


## 5.8. Residual Covariance

The Table8 presents that residual covariance value relation between party ideological education and image processing technology party ideological education shows that 0.180 rates with each other. The image processing technology shows that negative residual covariance with segmentation quality factor and image processing technology rate are −0.061 and −0.035, respectively. Image processing performance shows that a segmentation quality factor shows that positive residual covariance with party ideology education at the rate level is 0.086 which shows a 8% significant level. The image processing performance shows that positive residual covariance with party ideology education rate level is 0.062 and that positive relationships with segmentation quality factors rate level are 0.078, respectively.Table 8
Residual covariance.
PIPSQFIPTPIEParty ideological education0.180Image processing technology−0.061−0.035Segmentation quality factor−0.0990.025−0.258Performance of image processing0.0860.078−0.0030.062


## 5.9. Minimization History

Table9 results present minimization history values with negative rates, the smallest values, and the ratios of all iterations. The negative eigenvalues show that the condition value of 2, 1, 0, 0, 0, and 0 present that of each iteration is 1604.890, 256.708, 242.931, respectively. The diameter rates of each iteration are 9999.00, 0.926, 0.209, and 1.130, respectively. The results present that rations of each iteration are 0.880, 0.773, 0.000, 1.172, 1.124, 1.039, 1.003, and 1.000, respectively.Table 9
Minimization history.
IterationNegative eigenvaluesCondition #Smallest eigenvalueDiameterFEntriesRatio0E2−0.3239999.000243.97709999.0001e∗1−0.8400.92685.703180.8802E01604.8900.20947.73260.7733E0256.7081.13034.92830.0004E0242.9310.18026.27511.1725E0255.5790.13625.14211.1246E0258.2840.04125.08811.0397E0263.7710.00325.08811.0038E0263.8340.00025.08811.000


## 5.10. Critical Ratios for Differences between Parameters

The above Table10 presents the critical ratio for differences between parameters with the help of covariance, variance, and mean values. The covariance ratio shows that 0.000, which means a 100% significant level. The I variance presents a 0.618 rate of covariance, and that S variance shows the 1.407 rates of covariance and 2.016 rates of variance, respectively. The overall results present the performance of mean, variance, and covariance of independent and dependent variables.Table 10
Critical ratios for differences between parameters.
CovarianceI VarianceS VarianceVarI MeanS MeanCovariance0.000I Variance0.6180.000S Variance1.4072.0160.000Var6.9305.0120.8570.000I Mean11.55214.6904.2599.3490.000S Mean1.7591.258−0.776−3.389−7.4480.000


## 6. Model Fit Summary

### 6.1. CMIN

Table11 presents that model fit summary with the help of the default model, saturated model, and independence model. The NPAR shows 6, 14, and 8; the CMIN values show 25.088, 0.000, and 4.803, respectively. The DF value presents 8, 0, and 6 and also that CMIN/DF shows the 3.136 default model, and 0.800 shows the independence model values in CMIN rates.Table 11
CMIN.
ModelNPARCMINDFPCMIN/DFDefault model625.08880.0023.136Saturated model140.0000Independence model84.80360.5690.800


### 6.2. Baseline Comparisons

Table12 presents that the baseline comparison model fits the summary with the help of the default model, saturated model, and independence model. For example, the values of NFI is 1.000, −4.224, and 0.000; the RFI shows that −2.918 and 0.000; the IFI shows that 6.344 and also that 1.000, respectively.Table 12
Baseline comparisons.
ModelNFI Delta1RFI rho1IFI Delta2TLI rho2CFIDefault model−4.224−2.9186.34411.7040.000Saturated model1.0001.000Independence model0.0000.0000.0000.000


### 6.3. Parsimony-Adjusted Measures

Table13 shows that parsimony-adjusted measures of fit summary related to the party ideological education and image processing models. The PRATIO shows the 1.333 rates of the default model, the saturated model value is 0.000, and the independence model shows 1.000, respectively. The PNFI presents that −5.632 is considered the default model and that the saturated model shows 0.000, respectively, presents that adjusted measure between them.Table 13
Parsimony-adjusted measures.
ModelPRATIOPNFIPCFIDefault model1.333−5.6320.000Saturated model0.0000.000Independence model1.0000.000


### 6.4. RMSEA

Table14 describe that RMSEA values of the default model and independence model rates are 0.148, 0.000, 0.085, 0.000, 0.215, 0.116, 0.008, and 0.702, respectively. The results show each variable’s RMSEA, LO90, H190, and PCLOSE values of the default and independence models.Table 14
RMSEA.
ModelRMSEALO 90HI 90PCLOSEDefault model0.1480.0850.2150.008Independence model0.0000.0000.1160.702


## 6.1. CMIN

Table11 presents that model fit summary with the help of the default model, saturated model, and independence model. The NPAR shows 6, 14, and 8; the CMIN values show 25.088, 0.000, and 4.803, respectively. The DF value presents 8, 0, and 6 and also that CMIN/DF shows the 3.136 default model, and 0.800 shows the independence model values in CMIN rates.Table 11
CMIN.
ModelNPARCMINDFPCMIN/DFDefault model625.08880.0023.136Saturated model140.0000Independence model84.80360.5690.800


## 6.2. Baseline Comparisons

Table12 presents that the baseline comparison model fits the summary with the help of the default model, saturated model, and independence model. For example, the values of NFI is 1.000, −4.224, and 0.000; the RFI shows that −2.918 and 0.000; the IFI shows that 6.344 and also that 1.000, respectively.Table 12
Baseline comparisons.
ModelNFI Delta1RFI rho1IFI Delta2TLI rho2CFIDefault model−4.224−2.9186.34411.7040.000Saturated model1.0001.000Independence model0.0000.0000.0000.000


## 6.3. Parsimony-Adjusted Measures

Table13 shows that parsimony-adjusted measures of fit summary related to the party ideological education and image processing models. The PRATIO shows the 1.333 rates of the default model, the saturated model value is 0.000, and the independence model shows 1.000, respectively. The PNFI presents that −5.632 is considered the default model and that the saturated model shows 0.000, respectively, presents that adjusted measure between them.Table 13
Parsimony-adjusted measures.
ModelPRATIOPNFIPCFIDefault model1.333−5.6320.000Saturated model0.0000.000Independence model1.0000.000


## 6.4. RMSEA

Table14 describe that RMSEA values of the default model and independence model rates are 0.148, 0.000, 0.085, 0.000, 0.215, 0.116, 0.008, and 0.702, respectively. The results show each variable’s RMSEA, LO90, H190, and PCLOSE values of the default and independence models.Table 14
RMSEA.
ModelRMSEALO 90HI 90PCLOSEDefault model0.1480.0850.2150.008Independence model0.0000.0000.1160.702


## 7. Discussion

The research describes the path of artisan spirit to party ideological education in colleges and universities based on the image processing technology. The research describes artisan spirit performance in colleges and universities; these data are based on the primary form and run through specific AMOS software. The minimization history, correlation, covariance, and estimated values related to the research are present by measuring the path of artisan spirit to party ideological education in colleges and universities based on the image processing technology. Results found a direct and significant effect inb between party ideology education and image processing technology in colleges and universities [21]. Based on a review of pertinent information from local and international sources, the author argues that the artisan spirit has transitioned into modern society, expanding its relevance [10]. The term “artisan” does not apply to ancient artisans—professionals who are devoted, serious, and determined. Typically based on the artisan spirit, which includes excellent abilities and fantastic skills, rigorous and thorough work attitude, the concept of excellence, and the identity of the art, a spirit of devotion, were all formed as a result of a focused and responsible work attitude. It is an essential metric for identifying competent employees in a business [21]. In conclusion, I believe that the spirit of artisans is a thorough representation of professional abilities, professionalism, and professional mindset, encompassing commitment, excellence, responsibility, and creativity, among other things [25]. True artisans like crafting their items and trying their best products to make them great. In today’s culture, however, there are several examples of pleasure and impracticality, with many people chasing urgent short-term objectives while neglecting product quality and long-term sustainable development benefits. Only by spiritual living can society impetuosity be curbed and the best in goods and services be obtained. Today’s rapid economic expansion in China and people’s yearning for quality contrast with the country’s current state of social instability, impetuousness, and superficiality. It motivates people to appreciate and spread the maker’s spirit.


## 8. Conclusion

This research study measures artisan spirit’s path to party ideological education in colleges and universities based on the image processing technology. The research study describes artisan spirit ideology education research into the primary form and its data collected through specific questions. The image processing technology is divided into two sub-variables: the segmentation process and performance related to the image processing technology. Results concluded that there is a significant relationship between party ideology education and image processing technology in colleges and universities. Therefore, it is recommended that the teaching reform be deepened and improve the quality of teaching.To increase the quality and specification of talent training, it must change teaching materials, course teaching modes, assessment methods, and evaluation standards and stay current. Furthermore, it is recommended that valuable teaching materials for this significance be compiled using teaching materials that correspond with the characteristics of higher vocational training at home and abroad, that advanced teaching methods be used, that experts and technicians be hired to teach and give lectures, and that students’ innovation consciousness and practice ability be cultivated. Then, in the domain of vocational training, a competitive mechanism must be introduced, existing teaching resources must be used to support local economic growth, and vast amounts of high-quality compound technical skills must be trained. The research presents that party ideological education in college and universities is based on the image processing technology; this variable is divided into two other factors, including segmentation factors and performance related to the image processing technology. Thus, processing technology plays a vital role in colleges and universities’ party performance. Furthermore, it is necessary to learn from the experience and management mechanisms of excellent higher vocational colleges, to strengthen the horizontal connection with relevant colleges, to conduct more exchanges and cooperation, to facilitate the construction and teaching reform of character design that vocational education can adapt to the demand of the socialist market economy and to follow the development trend of higher vocational education. Finally, enhancing the character image design major and training a large number of “practical” technical skills of high quality fulfill the demands of the company’s orderly and quick development and are also the purpose of technical education and training.



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*Source: 2006133-2022-03-28.xml*