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Zaeri Mohammad Reza,Esmaeilzadeh Feridun 한국화학공학회 2024 Korean Journal of Chemical Engineering Vol.41 No.3
This paper evaluated ZnO, SiO 2 and zeolite 13X for removing CO 2 from normal heptane (nC 7 ) as synthetic gas condensates in batch mode. Based on the results of CO 2 adsorption isotherms, zeolite 13X had the highest CO 2 uptake in 1400–3700 ppm at atmospheric pressure. Due to the higher specifi c surface area of granular zeolite 13X, its CO 2 uptake was more than that of zeolite 13X powder. Also, the CO 2 adsorption equilibrium time was less than 30 min for zeolite 13X powder. The selectivity of zeolite 13X powder (i.e., H 2 S/CO 2 ) was 2.36–4.08 for 2001–3930 ppm H 2 S with 1668 ppm CO 2 . Besides, the CO 2 breakthrough time for zeolite 13X powder was 50–4 min for WHSV (weight hourly space velocity) = 5–20 h −1 at 30 bar in continuous mode. Additionally, for the increased CO 2 concentration from 1000 to 3000 ppm, the CO 2 breakthrough time decreased from 30 to 11 min with WHSV = 10 h −1 . The CO 2 breakthrough time diminished by 2.5-fold as the pressure was reduced from 30 bar to atmosphere for the initial CO 2 concentration of 1000 ppm in nC 7 and WHSV = 10 h −1 . Subsequently, the regeneration of zeolite 13X by stagnant hot air was investigated for the CO 2 concentration range of 1000–3000 ppm, air-adsorbent contact time range of 30–180 min and temperature range of 100–300 °C using Box–Behnken design. Its regeneration effi ciency was more than 95% for the CO 2 concentration below 1000 ppm.
A Framework for Semantic Interpretation of Noun Compounds Using Tratz Model and Binary Features
Ahmad Zaeri,Mohammad Ali Nematbakhsh 한국전자통신연구원 2012 ETRI Journal Vol.34 No.5
Semantic interpretation of the relationship between noun compound (NC) elements has been a challenging issue due to the lack of contextual information, the unbounded number of combinations, and the absence of a universally accepted system for the categorization. The current models require a huge corpus of data to extract contextual information, which limits their usage in many situations. In this paper, a new semantic relations interpreter for NCs based on novel lightweight binary features is proposed. Some of the binary features used are novel. In addition, the interpreter uses a new feature selection method. By developing these new features and techniques, the proposed method removes the need for any huge corpuses. Implementing this method using a modular and plugin-based framework, and by training it using the largest and the most current fine-grained data set, shows that the accuracy is better than that of previously reported upon methods that utilize large corpuses. This improvement in accuracy and the provision of superior efficiency is achieved not only by improving the old features with such techniques as semantic scattering and sense collocation, but also by using various novel features and classifier max entropy. That the accuracy of the max entropy classifier is higher compared to that of other classifiers, such as a support vector machine, a Naïve Bayes, and a decision tree, is also shown.
Ontology-lexicon-based question answering over linked data
Jabalameli, Mehdi,Nematbakhsh, Mohammadali,Zaeri, Ahmad Electronics and Telecommunications Research Instit 2020 ETRI Journal Vol.42 No.2
Recently, Linked Open Data has become a large set of knowledge bases. Therefore, the need to query Linked Data using question answering (QA) techniques has attracted the attention of many researchers. A QA system translates natural language questions into structured queries, such as SPARQL queries, to be executed over Linked Data. The two main challenges in such systems are lexical and semantic gaps. A lexical gap refers to the difference between the vocabularies used in an input question and those used in the knowledge base. A semantic gap refers to the difference between expressed information needs and the representation of the knowledge base. In this paper, we present a novel method using an ontology lexicon and dependency parse trees to overcome lexical and semantic gaps. The proposed technique is evaluated on the QALD-5 benchmark and exhibits promising results.