Search Results - solution ((selection techniques) OR (detection techniques))

IoT intrusion detection using auto-encoder and machine learning techniques by Khudhu, Ahmed Ridha, Samsudin, Khairulmizam

“…Yet, the featureselection techniques used in the literature were based on feature selectionrather than a reduction in which individual solutions are being selected. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

“…But the large number of available prevention techniques make the selection of the best solution a big challenge, because not every technique fit all types of web application, hence a one technique for all is another issue and a difficult task. …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

Detection of heavy metal ions in solution using surface plasmon resonance optical sensor by Yap, Wing Fen

“…The sensitive, selective and cost-effective method for detection of heavy metal ions in solution is very important in environmental application. …”
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Systematic review of intrusion detection system based on machine learning techniques for internet of things by Idris, Muhammad, Md Yasin, Sharifah, Audi, Giade Hamza

“…We highlighted the most efficient machine learning algorithms and feature selection techniques, along with strategies to address issues related to dataset imbalance in benchmarked datasets, with the goal of fostering the development of robust IDS solutions for IoT security.…”
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Study on crack detection using image processing techniques and deep learning – a survey by Saleem, Muhammad Asif, Senan, Norhalina, Ahmad, Rehan

“…The purpose of this writing is to study and understand the existing crack detection techniques using image processing. For this purpose, recent research articles have been selected for review. …”
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Enhancing phishing detection with advanced ensemble learning techniques by Nur Syakirin Mohd Shahiran, Mohammed Ahmed

“…This study introduces an advanced phishing detection model that leverages ensemble learning techniques to improve accuracy, robustness, and adaptability. …”
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Automatic microsleep detection based on KNN classifier utilizing selected and effective EEG channels by Hasan, Md Mahmudul, Hossain, Mirza Mahfuj, Norizam, Sulaiman, Islam, Md Nahidul, Khandaker, Sayma

“…Regrettably, the current solutions fail to match these specified criteria. Moreover, by utilizing sophisticated features and employing machine learning techniques, it is possible to process electroencephalogram (EEG) information in a highly efficient manner, enabling the rapid and successful detection of microsleep. …”
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Determination of polycyclic aromatic hydrocarbons in beverage by low density solvent based-dispersive liquid-liquid microextraction-high performance liquid chromatography-fluoresce... by Loh, Saw Hong, Chong, Yu Ting, Khairun Nisa Nor Afindi, Norshima Abdullah Kamaruddin

“…Under the optimized extraction conditions, the technique achieved trace detection limits in the range of 0.001 to 0.3 μgL-1 for the targeted analytes, namely phenanthrene, fluoranthene and benzo[a]pyrene. …”
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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

“…From the results, an accuracy of 99% is achieved using the voting ensemble technique with feature selection compared with 77.3% without feature selection. …”
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A new intelligent multilayer framework for insider threat detection by Ahmad, Rabiah, Al-Mhiqani, Mohammed Nasser Ahmed, Zainal Abidin, Zaheera, Abdulkareem, Karrar Hameed, Mohammed, Mazin Abed, Gupta, Deepak K., Shankar K.

“…Despite the prominence of ML in the domain of insider threat detection, none of the previous works have utilized ML techniques for building a hybrid solution that can take advantage of the misuse and anomaly insider threat detection. …”
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A selective mitigation technique of soft errors for DNN models used in healthcare applications: DenseNet201 case study by Adam, Khalid, Izzeldin, I. Mohd, Ibrahim, Younis

“…In this paper, we propose a selective mitigation technique that relies on in-depth analysis. …”
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Breast Cancer Detection by Hybrid Techniques based on Deep Learning Networks by Azlan, N.A.N., Elamvazuthi, I., Tang, T.B., Lu, C.-K.

“…A possible solution is to detect it early, which can be done by computer-aided diagnosis technologies. …”
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Detection of DDoS attacks in IoT networks using machine learning algorithms by Abdulrahman Alwan, Alwan Ahmed, Shah, Asadullah, Abdulrahman Alwan, Alwan Abdullah, Laghari, Shams Ul Arfeen

“…This paper presents a robust and efficient framework for detecting DDoS attacks in IoT networks using advanced machine learning techniques and effective feature selection methods. …”
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Breast Cancer Detection by Artificial Intelligence Technologies by Azlan, Nur Aainaa Nadirah

“…Possible solution for this cancer is to detect it early which can be done by Artificial Intelligence (AI). …”
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Multi-attribute decision-making for intrusion detection systems: a systematic review by Alamleh, Amneh, Albahri, O. S., Zaidan, A. A., Alamoodi, A. H., Albahri, A. S., Zaidan, B. B., Qahtan, Sarah, Ismail, Amelia Ritahani, Malik, R. Q., Baqer, M. J., Jasim, Ali Najm, Al-Samarraay, Mohammed S.

“…Intrusion detection systems (IDSs) employ sophisticated security techniques to detect malicious activities on hosts and/or networks. …”
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Hexagonal grid-based dynamic routing adjustment for optimising network lifetime in wireless sensor network by Jarallah, Zaid Fawaz

“…The major issues while utilising this technique is how to detect the sink while moving and this is still a challenge. …”
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An intelligent condition monitoring system for fault diagnosis of rotating machinery using expert systems with optimization techniques by Satyanarayana, M. R. S., Dr.

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Deep learning model for predicting and detecting overlapping symptoms of cardiovascular diseases in hospitals of UAE by Abbas Alhadeethy, Najwa Fadhil, Khedher, Akram M Z M, Shah, Asadullah

“…Hence, the best clinical applications of DL require considerate problem solving solution, selection of the most suitable DL algorithms and information, and defining balance of outcome. …”
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Examining the impact of feature selection techniques on machine and deep learning models for the prediction of COVID-19 / Hafiza Zoya Mojahid ... [et al.] by Mojahid, Hafiza Zoya, Mohamad Zain, Jasni, Yusoff, Marina, Basit, Abdul, Jumaat, Abdul Kadir, Ali, Mushtaq

“…This research aims to provide insights into the optimal integration of feature selection techniques with advanced machine learning models for accurate prediction of COVID-19 virus.…”
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