The Detection of Dysarthria Severity Levels Using AI Models: A Review حسب Afnan Al-Ali (16888695)

Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

"…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …"
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Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis حسب 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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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis حسب 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. …"

AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques حسب Khalid, Naji

"…The results of this study demonstrated the effectiveness of the proposed defect detection and localization algorithm as it managed to read all barcodes, localize defective columns, and binary classify the condition of the concrete covers against their surrounding objects. …"
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VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems حسب Hisham A. Kholidy (18891802)

"…The Nonnested Generalized Exemplars (NNGE) algorithm is one of the most accurate classification techniques that can work with such data of CPPS. …"

Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm حسب Abu Zitar, Raed

"…Moreover, the image pixels in different and more similar areas of the image are located next to one another in a group and classified using the specified thresholds. As a result, the embedding capacity in each class can increase by reducing the value of the difference between two consecutive pixels, and the distortion of the marked image can decrease after inserting the personal data using the DE method. …"
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data حسب Rajesh Kumar Dhanaraj (19646269)

"…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …"

Joint Inversion of Direct Current Resistivity and Seismic Refraction Data, using Local and Global Optimization Algorithms with Synthetic and Real Data Examples حسب unknown

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A machine learning model for early detection of diabetic foot using thermogram images حسب Amith Khandakar (14151981)

"…Several studies have reported that thermogram images may help to detect an increase in plantar temperature prior to DFU. …"

Deep and transfer learning for building occupancy detection: A review and comparative analysis حسب Aya Nabil Sayed (17317006)

"…Occupancy data might be collected using a variety of devices. …"

Chlorophyll-a concentrations in the Arabian Gulf waters of arid region: A case study from the northern coast of Qatar حسب Sankaran, Rajendran

"…The performance of the algorithms was studied using WorldView-3 data, which provided the R2 values of 60% and the best suitability of the NDCI algorithm and MSI data to map the concentration of Chl-a. …"
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Anomaly Detection Based Framework for Profile Monitoring حسب Al-Rahim, Nour Al-Huda Z. Al-Abed

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Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review حسب Avneet Kaur (712349)

"…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. …"

Four-dimensional representation and collision detection for movingobjects حسب Aliyu, M.D.S.

"…We consider the collision detection problem for general objects. A four-dimensional approach is proposed for this problem which detects exactly and in one-step when and where the earliest collision will occur between the objects. …"
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Deepfakes Signatures Detection in the Handcrafted Features Space حسب Hamadene, Assia

"…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …"
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Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression حسب Alaa Abd-Alrazaq (17430900)

"…Wearable AI is a promising tool for depression detection and prediction although it is in its infancy and not ready for use in clinical practice. …"

Using Machine Learning Algorithms to Forecast Solar Energy Power Output حسب Ali Jassim Lari (22597940)

"…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …"

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval حسب Mohammed Tahar Habib Kaib (21633176)

"…One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA). …"

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms حسب Usman Ali (6586886)

"…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …"