A Secure and Decentralized Blockchain Based EV Energy Trading Model Using Smart Contract in V2G Network by Atif Iqbal (5504636)

Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

“…Our study aimed to use data mining classification techniques, in order to classify the individual into two categories: user or non-user. …”
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UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks by Ebrahimi, Dariush

“…Among the emerging markets, Internet of Things (IoT) use cases are standing out with the proliferation of a wide range of sensors that can be configured to continuously monitor and transmit data for intelligent processing and decision making. …”
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I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams by Raun, Kristo

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Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

“…We searched Embase, PubMed, Scopus, and Google Scholar to retrieve relevant studies. After pre-processing and screening, we extracted data from 34 studies that fulfilled the inclusion criteria. …”

Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic by AL MANSOORI, MOUZA

“…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. In this study, we used twitter as our data source. …”
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Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection by HAMDALLAH, KHALID WAJIH TURKI

“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates by Andrianarison, O.

“…The whole piezoelectric multilayered plate’s dynamic stiffness is then built, from which its circular frequencies are computed with the help of the Wittrick-Williams algorithm. A detailed discussion is provided on the implementation aspects, followed by some numerical examples to assess the robustness, accuracy and effectiveness of the proposed method. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

“…We present the new framework for the detection of cyberattacks, which makes use of AI and ML. We begin a process to cleaning up the data in the CPS database by applying normalization to eliminate errors and duplication. …”
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Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks by Yaacoub, Elias

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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

“…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption by Azadeh, Ali

“…Design/methodology/approach In the proposed approach, the parameter tuning process is performed on all parameters of genetic algorithm (GA), and the finest coefficients with minimum errors are identified. …”
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A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities by Muhammad Mazhar Rathore (17051745)

“…To efficiently process the incoming big data streams, the proposed architecture uses the Apache GraphX tool with several parallel processing nodes, along with Spark and Hadoop that ultimately provide better performance against various state-of-the-art solutions. …”

Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”

A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011) by Kozhaya, David Elias

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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

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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Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare by Haraty, Ramzi A.

“…With all the preventive methods, malicious users still find new methods that overcome the system security, and access and modify the sensitive information. To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. …”
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KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …”