This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.

This article analyzes the use and limitations of nonmonetary contract incentives in managing third-party accountability in human services. In-depth case studies of residential care homes for the elderly and integrated family service centers, two contrasting contracting contexts, were conducted in Hong Kong. These two programs vary in service programmability and service interdependency. In-depth interviews with 17 managers of 48 Residential Care Homes for the Elderly (RCHEs) and 20 managers of 10 Integrated Family Service Centers (IFSCs) were conducted. Interviews with the managers show that when service programmability was high and service interdependency was low, nonmonetary contract incentives such as opportunities for self-actualization professionally or reputation were effective in improving service quality from nonprofit and for-profit contractors. When service programmability was low and service interdependency was high, despite that only nonprofit organizations were contracted, many frontline service managers reported that professional accountability was undermined by ambiguous service scope, performance emphasis on case turnover, risk shift from public service units and a lack of formal accountability relationships between service units in the service network. The findings shed light on the limitations of nonmonetary contract incentives.

Since my country entered the era of Internet economy, the scale of the software industry is gradually expanding, and programming language, as an important tool and idea for software development, is a necessary skill for every development practitioner. Among them, C language, as the basic language of computer software programming, is also an important basic course for cultivating students’ computer application ability in science and engineering majors in colleges and universities. This paper mainly studies the teaching reform of C language programming courses and proposes corresponding optimization measures, so as to lay a solid foundation for the continuous improvement of students’ learning quality of C language courses and the continuous strengthening of programming ability.

The present study assessed the potential of sediment loading in Beteni, Lauruk, Andheri, and Harpan sub-watersheds of Phewa Lake and estimated the sediment yield in the year 2020. Morphometry, land use/land cover, geology, climate, and human and development factors of the sub-watersheds were studied to assess the potential of sediment loading in the sub-watersheds. SRTM DEM was used for the computation of morphometric parameters and land use/land cover maps were prepared by using Landsat imagery. Geology, rainfall data, census data, and road maps were collected from various secondary sources. The sediment yields of the four sub-watersheds in the year 2020 were estimated by measuring the sediment volume deposited in the sediment retention ponds at the outlet of each sub-watershed. Results indicated that Beteni had the highest potential for sediment loading, while Harpan had the lowest. Likewise, the sediment yields for Beteni, Lauruk, Andheri, and Harpan sub-watersheds in 2020 were estimated at 1,420.67 m³/km²/year, 2,280.14 m³/km²/year, 1,666.77 m³/km²/year, and 766.42 m³/km²/year, respectively. To reduce sedimentation in Phewa Lake, it is recommended to regularly maintain siltation dams and construct check dams along the drainage slopes, alongside other soil conservation measures and appropriate land use practices in the upstream areas of the sub-watersheds.