Conducting complete energy audit (both process and utility) of a sponge iron unit is challenging as there is no laid down procedure to audit the process side. Further, the average heat to power ratio (kWth/kWe) of spo...Conducting complete energy audit (both process and utility) of a sponge iron unit is challenging as there is no laid down procedure to audit the process side. Further, the average heat to power ratio (kWth/kWe) of sponge iron plants ranges from (25:1) to (31:1). This shows that the manufacturing process mostly uses thermal energy and application of electrical energy is insignificant. The main & only source of thermal energy is coal and the entire coal is fed to the rotary kiln. Therefore we find that “Kiln” is the “Black-Box” of this industry and the success of energy efficiency is hidden in the kiln process chemistry. This article tries to establish detailed energy audit methodology of sponge iron manufacturing process or kiln operation with a view to finding out major energy saving potential of the unit. In the research work we find that it is the incomplete reaction of coal that causes the major energy inefficiency in the process. Substantial amount of un-reacted carbon comes out with the char (by-product) which has virtually zero commercial value. The article also puts a question mark on the justification of using high-grade imported coal in such energy inefficient industries.展开更多
This paper mainly studies big data-related position portrait construction based on recruitment data crawled from the 51job website.We first use text mining technique to classify job information and accurately obtain t...This paper mainly studies big data-related position portrait construction based on recruitment data crawled from the 51job website.We first use text mining technique to classify job information and accurately obtain the texts of two important aspects:work content and job requirements.We then apply the information extraction technique to extract labels describing different aspects of positions from structured and unstructured text data,and also adopt the Kano model to obtain more labels.Finally,we construct a multi-aspect and multi-dimensional position portrait through the sunburst chart.The position portrait constructed in this paper provides multi-dimensional analysis of the requirements of big data-related jobs and can help job seekers,enterprises,universities,and even third-party training institutions know the demand for talents and quickly determine the pertinence of a candidate's resume.展开更多
文摘Conducting complete energy audit (both process and utility) of a sponge iron unit is challenging as there is no laid down procedure to audit the process side. Further, the average heat to power ratio (kWth/kWe) of sponge iron plants ranges from (25:1) to (31:1). This shows that the manufacturing process mostly uses thermal energy and application of electrical energy is insignificant. The main & only source of thermal energy is coal and the entire coal is fed to the rotary kiln. Therefore we find that “Kiln” is the “Black-Box” of this industry and the success of energy efficiency is hidden in the kiln process chemistry. This article tries to establish detailed energy audit methodology of sponge iron manufacturing process or kiln operation with a view to finding out major energy saving potential of the unit. In the research work we find that it is the incomplete reaction of coal that causes the major energy inefficiency in the process. Substantial amount of un-reacted carbon comes out with the char (by-product) which has virtually zero commercial value. The article also puts a question mark on the justification of using high-grade imported coal in such energy inefficient industries.
文摘This paper mainly studies big data-related position portrait construction based on recruitment data crawled from the 51job website.We first use text mining technique to classify job information and accurately obtain the texts of two important aspects:work content and job requirements.We then apply the information extraction technique to extract labels describing different aspects of positions from structured and unstructured text data,and also adopt the Kano model to obtain more labels.Finally,we construct a multi-aspect and multi-dimensional position portrait through the sunburst chart.The position portrait constructed in this paper provides multi-dimensional analysis of the requirements of big data-related jobs and can help job seekers,enterprises,universities,and even third-party training institutions know the demand for talents and quickly determine the pertinence of a candidate's resume.
