Titlebook: Artificial Intelligence and Digitalization for Sustainable Development; 10th EAI Internation Bereket H. Woldegiorgis,Kibret Mequanint,Abdul

灰姑娘

Amharic Text Complexity Classification Using Supervised Machine Learning,riment, 5126 sentences are used. TFIDF and BOW with bigram language modeling are applied for vectorizing the text document and, Support Vector Machine (SVM), Random forest (RF), and Na?ve Bayes (NB) algorithms are used for the experiment. SVM has better classification accuracy with a result of 87.1%

外科醫(yī)生

Process Parameter Optimization of Single Lap-Adhesive Joint Date Palm Fiber Reinforced Polyester Cod to relate input and output parameters. The best parameter combinations were found using a genetic algorithm (GA) optimization technique. Using this technique, the optimum parameters of single lap adhesive joint DPFRPC were, 56?mm overlapping length, 36?mm width, and 0.95?mm adhesive thickness, wit

預(yù)測

Process Parameter Optimization of Single Lap-Bolt Joint Date Palm Fiber Reinforced Polyester Compos.5), W/D (2.5, 3.5, and 4.5), and fiber orientation (0/0°, 45/?45°, and 0/90°) was studied using L. orthogonal array experimental design. Artificial neural network (ANN) was used to model the experimental results. Genetic algorithm (GA) optimization technique was used to determine the optimum proces

inhumane

Formidable

Finite Time Trajectory Tracking of a Mobile Robot Using Cascaded Terminal Sliding Mode Control Undeontrol input for the inner loop angular velocity control of each wheel. An angular and linear velocity control input is designed in order to make angular and posture error to converge to zero in a finite time based on global fast terminal sliding mode?control (GFTSMC). Then, the inner loop GFTSMC of

vasospasm

OPINE

Numerical Simulation and Optimization of a Locally Built Midibus Structure in Quasi-static and Rollus structure failed the standard requirement and has unacceptable strength in both quasi-static and rollover simulation. Moreover, related to the baseline model, the structure’s weight of the reinforced Model was effectively reduced by 5.2%. However, an optimized model (using the Successive Response

不遵守

Veneer

Nomadic

Amharic Character Recognition Using Deep Convolutional Neural Network,nd a close resemblance in the shapes of the different characters available in the language, a relatively complex convolutional Neural Network is utilized to capture those features and categorize them into the correct characters. Dropout layers are utilized to avoid overfitting. The character recogni