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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.
( Bilal Şeker ),( Sevtap Sümer Eker ),( Bilal Çekiç ) 호남수학회 2022 호남수학학술지 Vol.44 No.4
The purpose of the present paper is to obtain some sufficient conditions for analytic functions, whose coefficients are probabilities of the Miller-Ross type-Poisson distribution series, to belong to classes G(λ, δ) and K(λ, δ).
Nexus Between Inventory Volatility and Capital Investment: Evidence from Selected Asian Economies
Bilal Haider SUBHANI,Khurram ASHFAQ,Muhammad Asif KHAN,Natanya MEYER,Umar FAROOQ 한국유통과학회 2022 The Journal of Asian Finance, Economics and Busine Vol.9 No.1
The uncertainty regarding inventory may impart dynamic impacts on corporate-level financial decisions. Among others, a decision about capital investment is a crucial decision that requires overall financial stability. Following these theoretical notions, the current study aims to identify possible consequences of inventory volatility relating to corporate capital investment decisions. We employed ten years of data (2010–2019) of non-financial sector firms to achieve the objective. The Driscoll-Kraay model was used to quantify the regression. The statistical results imply that inventory volatility negatively influences capital investment decisions due to information asymmetry about the current financial position. Additionally, more volatility brings discrepancies in managers’ investing decisions to fulfill the possible demand options of capital investment that require processing the inventory. However, based upon the statistical findings, it is suggested to corporate managers that they should consider the financial sensitivity of enterprises regarding inventory volatility. Thus, the current study introduces new thoughts regarding inventory volatility and its empirical role in determining capital investment.
Bilal Tayfur,Ayșe T. Daloglu 한국강구조학회 2023 International Journal of Steel Structures Vol.23 No.3
In this study, the nonlinear dynamic analysis of steel structures against progressive collapse was examined, and the adequacy and validity of the analysis duration defined in the regulation were investigated. In addition, the effects of the seismic resistance and design against progressive collapse constraints on the structure were investigated. An optimization algorithm was used in order to conduct the iterative process with appropriate sections. The frames were analyzed to perform one cycle as recommended in the UFC, and then the analysis duration was extended until at least five cycles had been completed. When the UFC was considered only, it was observed that while some of the designs were classified as safe within the duration specified in the UFC, the structural integrity was seen to get into danger in the subsequent cycles. When constraints related to seismic effect are also included in the process, it was seen that the threat disappeared for the frames examined. In addition, it was observed that the steel frame resisted progressive collapse scenarios by creating formations like Vierendeel beams.
Enhancing Depth maps from Microsoft Kinect using multiple Sensors
Bilal Ahmed,In Yeop Jang,Jae Doug Yoo,Kwan H. Lee (사)한국CDE학회 2013 한국CAD/CAM학회 국제학술발표 논문집 Vol.2010 No.8
During recent years a new type of depth sensors was made available in the market known as Microsoft Kinect Sensor. Its active sensing technology is well suited for applications that may require higher frame rates. However, it can totally fail in situations where the subject absorbs or reflects the infrared pattern casted by the sensor i.e. specular or transparent and near or far away objects. Kinect depth output contains holes in areas where these objects exist. In this paper we formulate a framework to overcome this shortcoming. We utilized two Kinect sensors placed to have a different viewing angle in coordination with two Kinect RGB cameras forming a stereo pair. As Kinect provides information about unreliable depths, therefore enhancements were performed selectively only in those areas where necessary. In this way, two separately placed depth sensors are able to offer some enhancements due to their different viewing angles. In addition, we first align depth images and look for the areas that still require enhancements. Thus, those areas can be improved using stereo matching. Using adaptive algorithms for stereo matching provides us with faster possibilities to come up with a better depth map.
Magnetic Characteristics of Biological Fluid in Nonlinear Thermally Radiated Blood Flow
Bilal Ahmed,Sami Ullah Khan,M. Ijaz Khan,Soumaya Gouadria,Abdul H. Hamid,Mehreen Yousaf,M. Y. Malik 한국자기학회 2022 Journal of Magnetics Vol.27 No.1
The numerical solution of the flow non-Newtonian fluid induced by stretching sheet in the region of oblique stagnation point flow under inducement of externally applied uniform magnetic field orthogonal to the flow is presented. The analysis is made under the assumption of boundary layer which arrives to the system of partial differential equations which are then transformed to ordinary differential equations by using appropriate similarity transformations. The numerical solution of the modeled system of equation is obtained by parallel shooting technique and presented for different variations of involved parameters. It is noted that enhancement in magnetic field results in decrease in horizontal velocity and boundary layer becomes thinner. The obtained results are compared with the available results in the literature and found in excellent agreement in the limiting cases.
bilal shaker,Myung-Sang Yu,Jingyu Lee,Yongmin Lee,Chanjin Jung,Dokyun Na 한국미생물학회 2020 The journal of microbiology Vol.58 No.3
Due to accumulating protein structure information and advances in computational methodologies, it has now become possible to predict protein-compound interactions. In biology, the classic strategy for drug discovery has been to manually screen multiple compounds (small scale) to identify potential drug compounds. Recent strategies have utilized computational drug discovery methods that involve predicting target protein structures, identifying active sites, and finding potential inhibitor compounds at large scale. In this protocol article, we introduce an in silico drug discovery protocol. Since multi-drug resistance of pathogenic bacteria remains a challenging problem to address, UDP-N-acetylmuramate- L-alanine ligase (murC) of Acinetobacter baumannii was used as an example, which causes nosocomial infection in hospital setups and is responsible for high mortality worldwide. This protocol should help microbiologists to expand their knowledge and research scope.