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Intrusion Detection by Using Hybrid of Decision Tree And K-Nearest Neighbor
Bilal Ahmad,Wang Jian,Muhammad Shafiq 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.12
In the modern age of information technology security of valuable asset become much important issue. Intrusion detection system plays a most important role in this area. It protects the system by attacks or threats by unauthorized access or person. The previous study has identified the need for more enhancements in the research of intrusion detection. This study gives the outline for intrusion detection and proposed a hybrid classification based method based on Decision Tree and K-Nearest Neighbor. This experiment perform on the bases of cross-10 fold validation techniques on the basis of decision tree and KNN classifiers and proposed hybrid classifier by using KDD cup dataset. Experimental result shows that the proposed idea gives good result as compared to individual base algorithms
한국 기후 상에서 지열히트펌프와 공대공히트펌프의 성능계수 비교
Bilal Ahmad,Kim, Dong-Hwan,Bahk, Sae-Mahn,Choi, Eun-Soo 明知大學校 産業技術硏究所 2009 産業技術硏究所論文集 Vol.28 No.-
This paper discusses a Coefficient of Performance of geothermal heat pump and air-to-air heat pump in the climatic conditions of Republic of Korea in heating mode.A vertica IU-shaped geothermal heat exchangεr using water as the working fluid has been designed using the temperature gradient of Korean soil obtained from Korea Meteorological Administration (KMA). The analysis was carried out using finite volume software ‘Fluent’. The heated water from the geothermal heat exchanger was used as the heat source for the heat pump circui t. A Comparison of Coefficient of Performance of geothermal heat pump and air-to-air heat pump in the climatic conditions of Republic of Korea has been dis cussed in heating mode. And it has been shown that using geothermal heat pumps is more efficient than air-to-air heat pump in the climatic conditions of Republic of Korea for heating purpose..
Hybrid Intrusion Detection Method to Increase Anomaly Detection by Using Data Mining Techniques
Bilal Ahmad,Wang Jian,Bilal Hassan 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.12
An Intrusion Detection System is an application which observes movements or action happen on the network and determine it for any kind of harmful activity that can disturb computer security policy. With progress of increase the usage rate of the internet, there is a widely increase in the number of internet attacks as well, so contests arise towards the network security due to the arrival of new approaches of attacks. To classify these attacks, a new hybrid method with the help of data mining based on decision tree C4.5 and Meta algorithm is planned. This method gives a classifier which expands the whole accuracy of detection. Many data mining techniques have been settled for detecting intrusion. For recognition of anomalies a hybrid technique based on decision tree C4.5 with Meta algorithm is offered that provides better accuracy and reduces the problem of high false alarm ratio. The assessment of the given approach is made with other data mining techniques. With this given approach detection rate is improved significantly. KDD Cup 1999 dataset use for experimental work.
Muhammad Bilal,Iftikhar Ahmad,Saeid Jalali Asadabadi,Rashid Ahmad,Muhammad Maqbool 대한금속·재료학회 2015 ELECTRONIC MATERIALS LETTERS Vol.11 No.3
In this paper we communicate the thermoelectric properties of carbon and nitrogen based metallic antiperovskites ANCa3 (A=Ge, Sn, Pb), BCFe3 (B=Al, Zn, Ga) and SnCD3 (D=Co and Fe) using the ab-initio calculations to explore efficient metallic thermoelectric materials. The consistency of the calculated results of SnCCo3 and SnCFe3 with the experimental results confirms the reliability of our theoretical calculations for the other investigated metallic antiperovskites. The results indicate that the thermopower of these materials can be enhanced by changing the chemical potential. The dimensionless figure of merit for the three nitrides approaches 0.96 at room temperature, which proves the usefulness of these materials in thermoelectric generators. Furthermore, the thermal conductivity is minimum at room temperature for chemical potential values between −0.25 μ(eV) and 0.25 μ(eV), and provides the maximum values of dimensionless figure of merit in this range. The striking feature of these studies is identifying a metallic compound, SnNCa3, with the highest value of Seebeck coefficient at room temperature out of all metals. The results anticipate that these materials could be efficient in thermoelectric generators; however, this needs experimental verification.