Sumit Kumar^1,*, S. Indu², Gurjit Singh Walia¹

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1035-1051, 2023, DOI:10.32604/iasc.2023.024469 - 06 June 2022

Abstract Android Smartphones are proliferating extensively in the digital world due to their widespread applications in a myriad of fields. The increased popularity of the android platform entices malware developers to design malicious apps to achieve their malevolent intents. Also, static analysis approaches fail to detect run-time behaviors of malicious apps. To address these issues, an optimal unification of static and dynamic features for smartphone security analysis is proposed. The proposed solution exploits both static and dynamic features for generating a highly distinct unified feature vector using graph based cross-diffusion strategy. Further, a unified feature is More >

R. S. Aashmi¹, T. Jaya^2,*

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 79-95, 2023, DOI:10.32604/iasc.2023.024291 - 06 June 2022

Abstract

Cloud computing is the technology that is currently used to provide users with infrastructure, platform, and software services effectively. Under this system, Platform as a Service (PaaS) offers a medium headed for a web development platform that uniformly distributes the requests and resources. Hackers using Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks abruptly interrupt these requests. Even though several existing methods like signature-based, statistical anomaly-based, and stateful protocol analysis are available, they are not sufficient enough to get rid of Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks

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V. Kavitha^1,*, K. Subramanian²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 231-241, 2023, DOI:10.32604/iasc.2023.024257 - 06 June 2022

Abstract Induction motor drives (IMDs) can achieve high performance levels comparable to dc motor drives. A major problem in getting high dynamic performance in an IMD is the coupling between the flux and torque producing components of stator current. This is successfully overcome in FOC (Field-Oriented Control) IM, making it to the industry standard control. The performance of an IMD with an improved power quality converter at the front end is presented in this study. In the IMD, boost converter is employed to reduce power quality difficulties at the utility interface. As the boost converter contains… More >

P. Srinivasan^1,*, P. Jagatheeswari²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 381-397, 2023, DOI:10.32604/iasc.2023.024179 - 06 June 2022

Abstract Renewable energy production plays a major role in satisfying electricity demand. Wind power conversion is one of the most popular renewable energy sources compared to other sources. Wind energy conversion has two major types of generators such as the Permanent Magnet Synchronous Generator (PMSG) and the Doubly Fed Induction Generator (DFIG). The maximum power tracking algorithm is a crucial controller, a wind energy conversion system for generating maximum power in different wind speed conditions. In this article, the DFIG wind energy conversion system was developed in Matrix Laboratory (MATLAB) and designed a machine learning (ML) More >

S. Leo Pauline^1,*, T. R. GaneshBabu²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 465-473, 2023, DOI:10.32604/iasc.2023.024030 - 06 June 2022

Abstract In this paper Substrate Integrated Waveguide-based filtenna operating at Ku band is proposed. The model is designed on a low loss dielectric substrate having a thickness of 0.508 mm and comprises of shorting vias along two edges of the substrate walls. To realize a bandpass filter, secondary shorting vias are placed close to primary shorting vias. The dimension and position of the vias are carefully analyzed for Ku band frequencies. The model is fabricated on Roger RT/duroid 5880 and the performance characteristics are measured. The proposed model achieves significant impedance characteristics with wider bandwidth in the More >

S. Sathishkumar^1,*, R. Devi Priya²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 129-148, 2023, DOI:10.32604/iasc.2023.023817 - 06 June 2022

Abstract Electrocardiogram (ECG) is a diagnostic method that helps to assess and record the electrical impulses of heart. The traditional methods in the extraction of ECG features is inneffective for avoiding the computational abstractions in the ECG signal. The cardiologist and medical specialist find numerous difficulties in the process of traditional approaches. The specified restrictions are eliminated in the proposed classifier. The fundamental aim of this work is to find the R-R interval. To analyze the blockage, different approaches are implemented, which make the computation as facile with high accuracy. The information are recovered from the… More >

Sagar Mekala^1,*, K. Shahu Chatrapati²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 581-593, 2023, DOI:10.32604/iasc.2023.023539 - 06 June 2022

Abstract In the contemporary era of unprecedented innovations such as Internet of Things (IoT), modern applications cannot be imagined without the presence of Wireless Sensor Network (WSN). Nodes in WSN use neighbour discovery (ND) protocols to have necessary communication among the nodes. Neighbour discovery process is crucial as it is to be done with energy efficiency and minimize discovery latency and maximize percentage of neighbours discovered. The current ND approaches that are indirect in nature are categorized into methods of removal of active slots from wake-up schedules and intelligent addition of new slots. The two methods… More >

Venkata Sunil Srikanth^*, S. Krithiga

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 63-78, 2023, DOI:10.32604/iasc.2023.023474 - 06 June 2022

Abstract Deep neural network (DNN) based computer-aided breast tumor diagnosis (CABTD) method plays a vital role in the early detection and diagnosis of breast tumors. However, a Brightness mode (B-mode) ultrasound image derives training feature samples that make closer isolation toward the infection part. Hence, it is expensive due to a meta-heuristic search of features occupying the global region of interest (ROI) structures of input images. Thus, it may lead to the high computational complexity of the pre-trained DNN-based CABTD method. This paper proposes a novel ensemble pre-trained DNN-based CABTD method using global- and local-ROI-structures of… More >

Hafsa Naveed¹, Abid Sohail², Jasni Mohamad Zain^3,*, Noman Saleem⁴, Rao Faizan Ali⁵, Shahid Anwar⁶

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 15-30, 2023, DOI:10.32604/iasc.2023.023277 - 06 June 2022

Abstract Question and answer websites such as Quora, Stack Overflow, Yahoo Answers and Answer Bag are used by professionals. Multiple users post questions on these websites to get the answers from domain specific professionals. These websites are multilingual meaning they are available in many different languages. Current problem for these types of websites is to handle meaningless and irrelevant content. In this paper we have worked on the Quora insincere questions (questions which are based on false assumptions or questions which are trying to make a statement rather than seeking for helpful answers) dataset in order More >

Huiyu Sun^*, Ralph Grishman

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1415-1423, 2022, DOI:10.32604/iasc.2022.030794 - 25 May 2022

Abstract Active learning methods which present selected examples from the corpus for annotation provide more efficient learning of supervised relation extraction models, but they leave the developer in the unenviable role of a passive informant. To restore the developer’s proper role as a partner with the system, we must give the developer an ability to inspect the extraction model during development. We propose to make this possible through a representation based on lexicalized dependency paths (LDPs) coupled with an active learner for LDPs. We apply LDPs to both simulated and real active learning with ACE as evaluation More >