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. …”
Get full text

Growing hierarchical self-organizing map for filtering intrusion detection alarms by Mansour, Nashat

Get full text
Get full text
Get full text
Get full text

Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

“…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. …”

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. …”
Get full text
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text
Get full text

Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) by Bitar, Mandy

Get full text
Get full text

Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
Get full text

Towards Multimedia Fragmentation by Saad, Samir

“…Database fragmentation is a process for reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. …”
Get full text
Get full text
Get full text
Get full text

Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review by Arfan Ahmed (17541309)

“…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”

CAD TOOL FOR THE AUTOMATIC-GENERATION OF MICROPROGRAMS by Sait, Sadiq M.

“…Since the UAHPL model is directly related to hardware, this approach is better than those based on ordinary high-level languages or special microprogram languages. …”
Get full text

Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

“…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…”

A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT by Harun Surej Ilango (17545728)

“…LR DoS attacks are difficult to detect as their attack signature is similar to benign network traffic. The existing AI-based detection algorithms in the literature are signature-based, and their efficacy in detecting unknown LR DoS attacks was not explored. …”

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

“…Lung-EffNet is built based on the architecture of EfficientNet and further modified by adding top layers in the classification head of the model. …”

Combinatorial method for bandwidth selection in wind speed kernel density estimation by El Dakkak, Omar

“…This goal calls for devising probabilistic models with adaptive algorithms that accurately fit wind speed distributions. …”
Get full text

Fuzzy controllers design using space-filling curves by Elshafei-Ahmed, M.

“…We then propose a SFC fuzzy inference model based on clustering the object space. The SFC fuzzy model is then used to design a fuzzy controller. …”
Get full text
Get full text

Fuzzy Controllers Design Using Space-Filling Curves by Elshafei-Ahmed, M

“…We then propose a SFC fuzzy inference model based on clustering the object space. The SFC fuzzy model is then used to design a fuzzy controller. …”
Get full text

Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks by Javed Butt , Usman

Get full text
Get full text

A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks by Sakib Mahmud (15302404)

“…We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”

Single-channel speech denoising by masking the colored spectrograms by Sania Gul (18272227)

“…With a slightly reduced PESQ score (by 0.58 points), the proposed model offers an improvement of 2 % in STOI, and 4375 and 1135 times reduction respectively in the required number of training epochs and network parameters when compared to a GAN-based model augmented by WavLM; a large-scale self-supervised learning model. …”