AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients by Azar, Danielle

“…The performance of the three algorithms is evaluated on a data set found in the public UCMI repository.…”
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A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications by Sharafeddine, Sanaa

“…The proposed scheme monitors the signal strength level during the file transfer process and compresses data blocks on-the-fly only whenever energy reduction gain is expected. …”
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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

“…The proposed StackDPPred method improves the overall accuracy by 13.41% and 7.62% compared to existing DPs predictors iDPF-PseRAAC and iDEF-PseRAAC, respectively on validation test. Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …”

Barriers of Adopting Artificial Intelligence Tools in Engineering Construction Projects by ALKAABI, ABDULLA

“…The situation may cause concern and trepidation about integrating AI technologies and lack understanding of their optimal deployment and operation. Construction data management and integration are difficult. AI algorithms depend on data for training and analysis. …”
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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…As part of this work, two deep learning models are compared according to their performance. …”
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Combined cycle gas turbine system optimization for extended range electric vehicles by Barakat, Aya A.

“…Second, a series-hybrid extended range vehicle model is developed, to assess the consumption savings of the prioritized combined cycle on the Worldwide Harmonized Light Vehicle Test Cycle. …”
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Growing hierarchical self-organizing map for filtering intrusion detection alarms by Mansour, Nashat

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Dynamic single node failure recovery in distributed storage systems by Itani, M.

“…We selected fractional repetition coding due to its simple repair mechanism that minimizes the repair and disk access bandwidths together with the property of un-coded repair process. To minimize the system repair cost, we formulate our problem using incidence matrices and solve it heuristically using genetic algorithms for all possible cases of single node failures. …”
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Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning by Mohamed Elhadary (16329082)

“…With the significant advancements in machine learning (ML) and artificial intelligence (AI) in recent years, numerous models and algorithms have been proposed to support the diagnosis and classification of CLL. …”

ISSP by Zouein, P.P.

“…Many decision-support tools were developed to assist planners in space scheduling but these were limited to providing the user with a platform that ties spatial and temporal data in the project and left it up to the user to decide on positions of resources and schedule adjustments to solve spatial conflicts that may arise in the process of constructing site layouts over time.The ISSP system, presented here, provides a graphical user-interactive interface with underlying layout and scheduling algorithms that construct feasible layout and schedule solutions under 2-dimensional spatial constraints between resources. …”
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The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation by Getahun, Fekade

“…We particularly discuss multimedia primary horizontal fragmentation and focus on semantic-based textual predicates implication required as a pre-process in current fragmentation algorithms in order to partition multimedia data efficiently. …”
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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) by Bitar, Mandy

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Design and Analysis of Secure Digital Twin Architecture by Shaikh, Eman

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Creating and detecting fake reviews of online products by Joni Salminen (7434770)

“…We show that a machine classifier can accomplish this goal near-perfectly, whereas human raters exhibit significantly lower accuracy and agreement than the tested algorithms. The model was also effective on detected human generated fake reviews. …”

Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features by Mariam Bahameish (19255789)

“…However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”

Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

“…The results demonstrate that the suggested RF-ANN-based technique can predict the optimal composite design with high accuracy (precision, recall, and f1-score for test and train dataset were 1). Furthermore, the confusion matrix validates the random forest classification model's accuracy. …”

Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose by Atiq Ur Rehman (8843024)

“…These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performance of ML algorithms and the models those are trained on drift free data fail to perform on the drifted data. …”

Identity and Aggregate Signature-Based Authentication Protocol for IoD Deployment Military Drone by Saeed Ullah Jan (9079260)

“…Both GPS and UAVN/FANET use open network channels for data broadcasting, which are exposed to several threats, thus making security risky and challenging. …”

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”

Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

“…While artificial intelligence (AI) smooths the path of computers to think like humans, machine learning (ML) and deep learning (DL) pave the way more, even by adding training and learning components. DL algorithms require data labeling and high-performance computers to effectively analyze and understand surveillance data recorded from fixed or mobile cameras installed in indoor or outdoor environments. …”