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Sampath Suranjan Salins,Shiva Kumar,S. V. Kota Reddy 대한설비공학회 2020 International Journal Of Air-Conditioning and Refr Vol.28 No.1
Desiccant cooling mechanism is one of the alternate methods to control the humidity of air and temperature, compared to the conventional vapor compression method of air conditioning. Desiccant cooling doesn’t use harmful chemicals which effect the ozone layer and it saves lots of energy. Summer air condition system can use this technology since it removes the latent heat load from the room effectively and this process is economical. Selection of the appropriate liquid desiccant and packing material is very vital to obtain maximum dehumidification. This paper focuses on the different desiccants and packings used by different researchers to enhance the dehumidification. Simple and hybrid systems are also reviewed, and their comparison are presented based on the construction and dehumidification performance.
Salins Sampath Suranjan,Kumar Shiva,Reddy S. V. Kota,Kuniyil Avin Vivek,kumar Sreejith Sanal 대한설비공학회 2021 International Journal Of Air-Conditioning and Refr Vol.29 No.3
Heating ventilation air conditioning (HVAC) design mainly deals with moisture and its control. The moisture may be present inside ducts, conditioned spaces, or outdoors. The process of humidification and dehumidification requires equipment for mass and heat transfer, where the transfer of energy and mass takes place at varying concentrations and temperatures. The exchange of mass or heat depends on the type of flow and is conceivably in the form of gas to liquid or liquid–vapor. This paper aims to review the effect of moisture in the buildings and modulate its effect with several humidifying and dehumidifying techniques as sustainable techniques depending upon the external weather conditions to maintain thermal comfort. Various humidification and dehumidification techniques have been discussed with both their merits, limitations, applications and future scope to meet sustainable energy demands.
Sarkar, Kamal,Nasipuri, Mita,Ghose, Suranjan Korea Information Processing Society 2012 Journal of information processing systems Vol.8 No.4
The paper presents three machine learning based keyphrase extraction methods that respectively use Decision Trees, Na$\ddot{i}$ve Bayes, and Artificial Neural Networks for keyphrase extraction. We consider keyphrases as being phrases that consist of one or more words and as representing the important concepts in a text document. The three machine learning based keyphrase extraction methods that we use for experimentation have been compared with a publicly available keyphrase extraction system called KEA. The experimental results show that the Neural Network based keyphrase extraction method outperforms two other keyphrase extraction methods that use the Decision Tree and Na$\ddot{i}$ve Bayes. The results also show that the Neural Network based method performs better than KEA.