The study of the performance of high-efficiency heat pump systems has been a hot issue of general interest in the field of heat pump air conditioning. For the designed and developed two-stage casing tandem heat exchanger of heat pump system, the 3D finite volume method and the realizable k-ε model are used to numerically analyze the influence law of inlet fluid temperature and flow velocity on the overall heat transfer coefficient as well as the Nussle number of inner and outer tubes. The results show that decreasing the inlet water temperature or increasing the inlet refrigerant temperature can improve the overall heat transfer performance; Nu_in increases with the increase of water and refrigerant flow rates, while Nu_out increases with the increase of water flow rate but decreases with the increase of refrigerant flow rate; Nu_in and Nu_out both increase with the decrease of water temperature or refrigerant temperature increases.

Inequity in infrastructure distribution and social injustice’s effects on Ethiopia’s efforts to build a democratic society are examined in this essay. By ensuring fair access to infrastructure, justice, and economic opportunity, those who strive for social justice aim to redistribute resources in order to increase the well-being of individuals, communities, and the nine regional states. The effects that social inequity and injustice of access to infrastructure have on Ethiopia’s efforts to develop a democratic society were the focus of the study. Time series analysis using principal component analysis (PCA) and composite infrastructure index (CII), as well as structural equation modeling–partial least squares (SEM-PLS), were necessary to investigate this issue scientifically. This study also used in-depth interviews and focus group discussions to support the quantitative approach. The research study finds that public infrastructure investments have failed or have been disrupted, negatively impacting state- and nation-building processes of Ethiopia. The findings of this research also offer theories of coordination, equity, and infrastructure equity that would enable equitable infrastructure access as a just and significant component of nation-building processes using democratic federalism. Furthermore, this contributes to both knowledge and methodology. As a result, indigenous state capability is required to assure infrastructure equity and social justice, as well as to implement the state-nation nested set of policies that should almost always be a precondition for effective state- and nation-building processes across Ethiopia’s regional states.

Shore line change is considered as one of the most dynamic processes, which were mapped along the coast of Tiruvallur district by using topographic maps of 1976 and multi-temporal satellite images. The satellite images pertaining to 1988, 1991, 2006, 2010, 2013 and 2016 were used to extract the shorelines. It is important to map and monitor the HTL (High Tide Line) at frequent time intervals as the shoreline was demarcated by using visual interpretation technique from satellite images and topographic maps. Followed by this, an overlay analysis was performed to calculate areas of erosion and accretion in the study area. The results revealed that the coast of Tiruvallur district lost 603 ha and gained 630 ha due to erosion and accretion respectively. It was confirmed after the ground truth survey carried out in the study area. The high accretion of 178 ha was found nearby Pulicat Lake and low accretion of 19 ha was seen between Pulicat Lake and Kattupali Port. The high erosion area was found along the Pulicat Lake, Kattupali and Ennore ports, and Ennore creek mouth and southern Ennore such as Periya Kuppam, Chinna Kuppam, Kasi Koil Kuppam, and Thyagarajapuram. It may be concluded that the coastal erosion and accretion in the study area were mainly caused by anthropogenic and natural factors, which altered the coastal environment.

The objective of the present study is to observe the surface morphology, structure and elemental composition of the ash particles produced from some thermal power stations of India using scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDXA). This information is useful to better understand the ash particles before deciding its utility in varied areas.

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.