Lu Wu, Quan Liu, Ping Lou

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 249-257, 2019, DOI:10.31209/2018.100000010

Abstract The scheme of spatial pyramid matching (SPM) causes feature ambiguity near dividing lines because it divides an image into different scales in a fixed manner. A new method called soft SPM (sSPM) is proposed in this paper to reduce feature ambiguity. First, an auxiliary area rotating around a dividing line in four orientations is used to correlate the feature relativity. Second, sSPM is performed to combine these four orientations to describe the image. Finally, an optimized multiple kernel learning (MKL) algorithm with three basic kernels for the support vector machine is applied. Specifically, for each More >

Nour EL Yakine Kouba^a, Mohamed Menaa^a, Kambiz Tehrani^b, Mohamed Boudour^a

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 279-294, 2019, DOI:10.31209/2018.100000007

Abstract This paper presents the use of a novel nature inspired meta-heuristic algorithm namely Ant Lion Optimizer (ALO), which is inspired from the ant lions hunting mechanism to enhance the frequency regulation and optimize the load frequency control (LFC) loop parameters. The frequency regulation issue was formulated as an optimal load frequency control problem (OLFC). The proposed ALO algorithm was applied to reach the best combination of the PID controller parameters in each control area to achieve both frequency and tie-line power flow exchange deviations minimization. The control strategy has been tested firstly with the standard More >

Jun Ye

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 15-23, 2019, DOI:10.31209/2018.100000067

Abstract Because existing proportional-integral-derivative (PID) tuning method using similarity measures of single-valued neutrosophic sets (SVNSs) and an increasing step algorithm shows its complexity and inconvenience, this paper proposes a PID tuning method using a cosine similarity measure of SVNSs and genetic algorithm (GA) to improve the existing PID tuning method. In the tuning process, the step response characteristic values (rising time, settling time, overshoot ratio, undershoot ratio, peak time, and steady-state error) of the control system are converted into the single-valued neutrosophic set (SVNS) by the neutrosophic membership functions (Neutrosophication). Then the values of three appropriate More >

Hsing‐Chung Chen^1,2, Shyi‐Shiun Kuo^1,3

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 217-228, 2019, DOI:10.31209/2018.100000057

Abstract Nowadays, more and more smartphones communicate to each other’s by using some popular Next Generation Instant Messaging (NGIM) applications (Apps) which are based on the blockchain (BC) technologies, such as XChat, via IPv4/IPv6 dual stack network environments. Owing to XChat addresses are soon to be implemented as stealth addresses, any DoS attack activated form malicious XChat node will be treated as a kind of DDoS attack. Therefore, the huge NGIM usages with stealth addresses in IPv4/IPv6 dual stack mobile networks, mobile devices will suffer the Distributed Denial of Service (DDoS) attack from Internet. The probing More >

Yong‐Hwan Lee, Hyochang Ahn, Hyo‐Beom Ahn, Sun‐Young Lee

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 205-215, 2019, DOI:10.31209/2018.100000056

Abstract Object tracking plays an important role in many vision applications. This paper proposes a novel and robust object detection and tracking method to localize and track a visual object in video stream. The proposed method is consisted of three modules; object detection, tracking and learning. Detection module finds and localizes all apparent objects, corrects the tracker if necessary. Tracking module follows the interest object by every frame of sequences. Learning module estimates a detecting error, and updates its value of credibility level. With a validity level where the tracking is failed on tracing the learned More >

Tien‐Ho Chang¹, Chia‐Mei Chen², Han‐Wei Hsiao³, Gu‐Hsin Lai⁴

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 183-192, 2019, DOI:10.31209/2018.100000054

Abstract Wi-Fi Protected Access (WPA) and Wi-Fi Protected Access II (WPA2) are two security protocols developed by the Wi-Fi Alliance to secure wireless computer networks. The prevailing usage of GPUs improves the brute force attacks and cryptanalysis on access points of the wireless networks. It is time-consuming for the cryptanalysis with the huge total combinations of 9563 max. Now, it is the turning point that the leap progress of GPUs makes the Wi-Fi cryptanalysis much more efficient than before. In this research, we proposed a rule-based password cracking scheme without dictionary files which improves the efficiency More >

Jianfeng Guan^*, Jiawei Li, Zhongbai Jiang

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 131-141, 2019, DOI:10.31209/2018.100000050

Abstract The traditional web anomaly detection systems face the challenges derived from the constantly evolving of the web malicious attacks, which therefore result in high false positive rate, poor adaptability, easy over-fitting, and high time complexity. Due to these limitations, we need a new anomaly detection system to satisfy the requirements of enterprise-level anomaly detection. There are lots of anomaly detection systems designed for different application domains. However, as for web anomaly detection, it has to describe the network accessing behaviours characters from as many dimensions as possible to improve the performance. In this paper we… More >

Zubair Baig¹, Sherali Zeadally²

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 121-129, 2019, DOI:10.31209/2018.100000049

Abstract A critical infrastructure provides essential services to a nation’s population. Interruptions in its smooth operations are highly undesirable because they will cause significant and devastating consequences on all stakeholders in the society. In order to provide sustained protection to a nation’s critical infrastructure, we must continually assess and evaluate the risks thereof. We propose a risk assessment framework that can evaluate the risks posed to the security of a critical infrastructure from threat agents, with a special emphasis on the smart grid communications infrastructure. The framework defines finegrained risk identification to help quantify and assess More >

Ilsun You, Chang Choi, Vishal Sharma, Isaac Woungang, Bharat K. Bhargava

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 117-119, 2019, DOI:10.31209/2018.100000048

Abstract This article has no abstract. More >

Belayat Hossain^a, Takatoshi Morooka^b, Makiko Okuno^b, Manabu Nii^a, Shinichi Yoshiya^b, Syoji Kobashi^a

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 105-115, 2019, DOI:10.31209/2018.100000034

Abstract This work aimed to predict postoperative knee functions of a new patient prior to total knee arthroplasty (TKA) surgery using machine learning, because such prediction is essential for surgical planning and for patients to better understand the TKA outcome. However, the main difficulty is to determine the relationships among individual varieties of preoperative and postoperative knee kinematics. The problem was solved by constructing predictive models from the knee kinematics data of 35 osteoarthritis patients, operated by posterior stabilized implant, based on generalized linear regression (GLR) analysis. Two prediction methods (without and with principal component analysis… More >