Abstract: A system selecting a process key factor in a commercial chemical process, includes: a data extraction unit that extracts tag data in units of a set period; an outlier discrimination unit that discriminates and aggregates outliers by tag by using an outlier extraction reference master; an outlier processing unit that generates an input mart draft excluding the outliers; a derived variable generation unit that generates derived variables for each tag, and generates an advanced input mart having the derived variable added thereto; a yield calculation unit that backs up the result of calculation of a yield by realizing a target value via exclusion and correction of the outliers; and a key factor extraction unit that extracts a yield key factor by calculating importance of each tag, and backs up importance data for each tag.

Abstract: A system for predicting process changes by using key factors in a commercial chemical process, includes: a key factor extraction and individual tag importance backup unit that extracts yield key factors by calculating the importance of each tag, and backs up importance data for each tag; and a yield prediction model training and yield prediction performing unit that performs yield prediction model training by using the importance of each tag accumulated in the key factor extraction and individual tag importance backup unit, and performs yield prediction so as to output a yield prediction result, evaluates performance, and selects an optimal prediction model.

Abstract: There is provided a dehydrogenation catalyst for producing olefins from alkane gases, in which a metal active component is supported on an alumina carrier containing boron. There is provided a method for preparing a dehydrogenation catalyst for producing olefins from alkane gases. The method includes impregnating alumina in a boron-containing solution and calcining it to provide a boron-alumina carrier; providing a solution containing the metal active component; impregnating the boron-alumina solution in the solution containing the metal active component and drying it; and calcining the boron-alumina carrier on which the metal active component is supported at 700° C. to 900° C.

Abstract: Disclosed are an apparatus and a method for detecting whether an anomalous sentence having a context different from that of other sentences exists in a document. The apparatus for detecting a contextually-anomalous sentence in a document according to the present invention includes: a sentence encoder for encoding individual sentences constituting document data by means of a predetermined rule (function) to generate encoding vectors; a context embedder neural network for converting the generated encoding vector into embedding vectors corresponding thereto; and a context anomaly detector neural network for detecting whether an anomalous sentence exists in the converted document data.

Abstract: The present disclosure is to provide a catalyst for olefin production which is eco-friendly and has excellent conversion rates and selectivity and a preparation method thereof, and the catalyst for olefin production according to the present disclosure is one in which cobalt and zinc are supported with alumina. Particularly, the catalyst according to the present disclosure uses an amount of platinum that is about 400 times smaller than that of the conventional catalysts, and has high conversion rates and selectivity under conditions in which continuous reaction-regeneration process is possible without an additional hydrogen reduction process.

Abstract: A dehydrogenation catalyst for producing olefins from alkane gases, in which cobalt and zinc are supported on alumina. A method for preparing the dehydrogenation catalyst for producing olefins from alkane gases, includes: preparing a mixed solution by mixing cobalt and zinc precursors with water; preparing a supported catalyst by impregnating alumina with the mixed solution; drying the supported catalyst; and calcining the dried supported catalyst at 500° C. to 900° C.

Abstract: Disclosed are an apparatus and a method for detecting whether an anomalous sentence having a context different from that of other sentences exists in a document. The apparatus for detecting a contextually-anomalous sentence in a document according to the present invention includes: a sentence encoder for encoding individual sentences constituting document data by means of a predetermined rule (function) to generate encoding vectors; a context embedder neural network for converting the generated encoding vector into embedding vectors corresponding thereto; and a context anomaly detector neural network for detecting whether an anomalous sentence exists in the converted document data.