Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1,781)
  • Open Access

    ARTICLE

    Multifactorial Disease Detection Using Regressive Multi-Array Deep Neural Classifier

    D. Venugopal1, T. Jayasankar2,*, N. Krishnaraj3, S. Venkatraman4, N. B. Prakash5, G. R. Hemalakshmi5

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 27-38, 2021, DOI:10.32604/iasc.2021.015205

    Abstract Comprehensive evaluation of common complex diseases associated with common gene mutations is currently a hot area of human genome research into causative new developments. A multi-fractal analysis of the genome is performed by placing the entire DNA sequence into smaller fragments and using the chaotic game representation and systematic methods to calculate the general dimensional spectrum of each fragment. This is a time consuming process as it uses floating point to represent large data sets and requires processing time. The proposed Regressive Multi-Array Deep Neural Classifier (RMDNC) system is implemented to reduce the computation time, it is called a polymorphic… More >

  • Open Access

    ARTICLE

    Building Information Modeling Based Automated Building Regulation Compliance Checking Asp.net Web Software

    Murat Aydın*

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 11-25, 2021, DOI:10.32604/iasc.2021.015065

    Abstract Building regulations used in the architecture, engineering, and construction sectors are legal documents prepared under the control of local authorities for use by individuals. These regulations determine the conditions for ensuring performance and quality throughout the entire construction process. The building regulation inspection process conducted with the traditional manual method is time-consuming and error-prone for architects, engineers, and local authorities. It is known that most of these inspections are carried out with municipalities by local authorities. The mutual interview study and literature review shows that there is no standard rule for the legal auditing process and the same services are… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Language Translation Platform

    Manjur Kolhar*, Abdalla Alameen

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 1-9, 2021, DOI:10.32604/iasc.2021.014995

    Abstract The use of computer-based technologies by non-native Arabic-speaking teachers for teaching native Arabic-speaking students can result in higher learner engagement. In this study, a machine translation (MT) system is developed as a learning technology. The proposed system can be linked to a digital podium and projector to reduce multitasking. A total of 25 students from Prince Sattam Bin Abdulaziz University, Saudi Arabia participated in our experiment and survey related to the use of the proposed technology-enhanced MT system. An important reason for using this framework is to exploit the high service bandwidth (up to several bandwidths) made available for interactive… More >

  • Open Access

    ARTICLE

    Soil Moisture Prediction in Peri-urban Beijing, China: Gene Expression Programming Algorithm

    Hongfei Niu1,2, Fanyu Meng3, Huanfang Yue3, Lihong Yang4, Jing Dong2,5, Xin Zhang2,5,*

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 93-106, 2021, DOI:10.32604/iasc.2021.010131

    Abstract Soil moisture is an important indicator for agricultural planting and agricultural water management. People have been trying to guide crop cultivation, formulate irrigation systems, and develop intelligent agriculture by knowing exactly what the soil moisture is in real time. This paper considers the impact of meteorological parameters on soil-moisture change and proposes a soil-moisture prediction method based on the Gene Expression Programming (GEP) algorithm. The prediction model is tested on datasets from Shunyi, Yanqing and Daxing agricultural farms, Beijing. The results show that the GEP model can predict soil moisture with a maximum correlation coefficient of 0.98, and the root-mean-square… More >

  • Open Access

    ARTICLE

    A Learning-based Static Malware Detection System with Integrated Feature

    Zhiguo Chen1,*, Xiaorui Zhang1,2, Sungryul Kim3

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 891-908, 2021, DOI:10.32604/iasc.2021.016933

    Abstract The rapid growth of malware poses a significant threat to the security of computer systems. Analysts now need to examine thousands of malware samples daily. It has become a challenging task to determine whether a program is a benign program or malware. Making accurate decisions about the program is crucial for anti-malware products. Precise malware detection techniques have become a popular issue in computer security. Traditional malware detection uses signature-based strategies, which are the most widespread method used in commercial anti-malware software. This method works well against known malware but cannot detect new malware. To overcome the deficiency of the… More >

  • Open Access

    ARTICLE

    Multi-Model Fuzzy Formation Control of UAV Quadrotors

    Abdul-Wahid A. Saif1, Mohammad Ataur-Rahman1, Sami Elferik1, Muhammad F. Mysorewala1, Mujahed Al-Dhaifallah1,*, Fouad Yacef2

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 817-834, 2021, DOI:10.32604/iasc.2021.015932

    Abstract In this paper, the formation control problem of a group of unmanned air vehicle (UAV) quadrotors is solved using the Takagi–Sugeno (T–S) multi-model approach to linearize the nonlinear model of UAVs. The nonlinear model sof the quadrotor is linearized first around a set of operating points using Taylor series to get a set of local models. Our approach’s novelty is in considering the difference between the nonlinear model and the linearized ones as disturbance. Then, these linear models are interpolated using the fuzzy T–S approach to approximate the entire nonlinear model. Comparison of the nonlinear and the T–S model shows… More >

  • Open Access

    ARTICLE

    Impact of COVID-19 Pandemic: A Cybersecurity Perspective

    Mohammed Baz1, Hosam Alhakami2, Alka Agrawal3, Abdullah Baz4, Raees Ahmad Khan3,*

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 641-652, 2021, DOI:10.32604/iasc.2021.015845

    Abstract Inspite of the world being at a complete standstill in the wake of unprecedented health emergency of COVID-19 pandemic, people have managed to retain their digital interactions through Information Technology. Cloud networks, departmental servers, data centres, and the digital devices have ensured that businesses and industries as well as workers across the world remain associated with each other and are connected to the organizations’ data. In such a scenario, the requirements placed on digital frames have increased rapidly. While this has proved to be a boon in the combat against the spread of Coronavirus, alarming increase in the instances of… More >

  • Open Access

    ARTICLE

    PTS-PAPR Reduction Technique for 5G Advanced Waveforms Using BFO Algorithm

    Arun Kumar1, Manoj Gupta1, Dac-Nhuong Le2,3,*, Ayman A. Aly4

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 713-722, 2021, DOI:10.32604/iasc.2021.015793

    Abstract Non-orthogonal multiple access (NOMA) will play an imperative part in an advanced 5G radio arrangement, owing to its numerous benefits such as improved spectrum adeptness, fast data rate, truncated spectrum leakage, and, so on. So far, NOMA undergoes from peak to average power ratio (PAPR) problem, which shrinks the throughput of the scheme. In this article, we propose a hybrid method, centered on the combination of advanced Partial transmission sequence (PTS), Selective mapping (SLM), and bacteria foraging optimization (BFO), known as PTS-BFO and SLM-PTS. PTS and SLM are utilized at the sender side and divide the NOMA into several sub-blocks.… More >

  • Open Access

    ARTICLE

    Analyzing the Implications of COVID-19 Pandemic: Saudi Arabian Perspective

    Shakeel Ahmed*, Abdulaziz Alhumam

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 835-851, 2021, DOI:10.32604/iasc.2021.015789

    Abstract Most of the patients diagnosed with COVID-19 pandemic usually suffer from mild-to-serious respiratory illness and become stable without any specific care. In fact, in some countries like India the mortality rate is as low. Those who are amongst the most vulnerable groups are the elderly and the ones with chronic ailments like diabetes, heart ailments, and respiratory ailments. However, apart from the impact on the physical health of the patients, this disease has had a more debilitating affect on the mental as well as emotional well-being of the people. Due to continuous watching and protection programs to fight the pandemic,… More >

  • Open Access

    ARTICLE

    Economic Shocks of Covid-19: Can Big Data Analytics Help Connect the Dots

    Hakimah Yaacob, Qaisar Ali*, Nur Anissa Sarbini, Abdul Nasir Rani, Zaki Zaini, Nurul Nabilah Ali, Norliza Mahalle

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 653-668, 2021, DOI:10.32604/iasc.2021.015442

    Abstract Since the beginning of the Covid-19 pandemic, big data analytics (BDA) remains a signatory medium in the battle against it. Governments and policymakers alike are yet to leverage on this scalable technology in an attempt to curb the economic effects of Covid-19. The primary objective of this study is to leverage on BDA to identify economic shocks, and propose a strategic solution for economic recovery in ASEAN member states (AMS). The findings of this study suggest that BDA techniques, frameworks, and architectures are effective tools in predicting and tracking economic shocks, as well as in designing and implementing an effective… More >

Displaying 1411-1420 on page 142 of 1781. Per Page