Application of Heuristic Algorithms for Multiuser Detection by Morra, H.

“…In this paper we propose application of heuristic algorithms in multiuser detection (MUD). The proposed algorithm combines a tabu search heuristic algorithm with a local search heuristic algorithm. …”
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A novel linear time corner detection algorithm by Sarfraz, M.

“…The complexity of our algorithm is linear. It is very efficient and as well as accurate. …”
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On a neural network-based fault detection algorithm by Al-Ghumgham, Mufeed Ahmed Saleh

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Error detection in algorithm-based fault tolerant systems by Al-Mehdar, Omar Salem

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Android Malware Detection Using Machine Learning by Al Ali, Shaikha

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Application of particle swarm optimization algorithm to multiuser detection in CDMA by El-Mora, H.H.

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Efficient algorithm for collision detection and path planning for robotics application by Aliyu, Mohammad Dikko S.

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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

“…This study uses the above facility in developing algorithms for digitally determining the basic pulse parameters and tackling the problem of pulse pile-up in Gamma-ray spectroscopy. …”
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients by Tokajian, Sima

“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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Use of Data Mining Techniques to Detect Fraud in Procurement Sector by AL HAMMADI, SUMAYYA ABDULLA

“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

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EFFICIENT LOCALIZATION ALGORITHMS FOR WIRELESS GAS LEAKAGE DETECTION IN OIL/GAS INDUSTRY by unknown

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Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

“…In addition, the framework outperforms conventional detection algorithms in words of detection rate, the rate of the false positive, and calculation time, respectively.…”
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Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection by HAMDALLAH, KHALID WAJIH TURKI

Subjects: “…machine learning algorithms, money laundering, financial crime detection,…”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Semantic based navigation and lane keeping by Abdeen, Abdallah Adel

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HVAC system attack detection dataset by Mariam Elnour (14147790)

“…It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.…”

Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

“…Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. In order to detect the anomalies in a dataset in an unsupervised manner, some novel statistical techniques are proposed in this paper. …”