Search Results - (( java segmentation using algorithm ) OR ( machine loading process algorithm ))

Cloud computing load balancing technique with virtual machine migration / Rabiatul Addawiyah Mat Razali by Mat Razali, Rabiatul Addawiyah

“…Based on this idea, an algorithm in activating and deciding on the virtual machine migration operation is proposed, in which the overall load balancing process could be improved. …”
Get full text
Get full text

Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…Finally, the algorithm found, which would solve the image segmentation problem.…”
Get full text
Get full text
Get full text
Get full text

Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

“…Results show that during the part-routing process in a normal manufacturing circumstance, nearer set of required machines for producing a product are employed more than other parallel machines.This phenomenon can cause increasing machine-loads in such cells and may lead to machine-load variation in set of closer machines while other machines are allocated less (or even left idle). …”
Get full text
Get full text

Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

“…Then the optimal criterion for exchanging tasks between two machines is proposed and exploited to speed up the improving process towards load balance. …”
Get full text

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”

Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
Get full text
Get full text
Get full text

An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

“…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
Get full text
Get full text
Get full text
Get full text

Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

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

Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele B.V., Mustapa S.I., Kanthasamy R., Mohammad N., AlTurki A., Babu T.S.

Cyberbullying detection: a machine learning approach by Yeong, Su Yen

“…Bag of Words model was used to convert text into numerical inputs. The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
Get full text
Get full text

Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

“…In response to the unprecedented challenges posed by the COVID-19 pandemic, this research project presents a systematic approach to outbreak prediction, specifically advocating for the implementation of Support Vector Machine (SVM) algorithms. The methodology integrates a thorough literature review, meticulous data collection from reliable sources, and rigorous data pre-processing to ensure the dataset's quality and relevance. …”
Get full text
Get full text

Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

“…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
Get full text
Get full text

Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”

Capacity planning for mixed-load tester under demand and testing time uncertainty by Asih, Hayati Mukti

“…Capacity planning is an important decision in production planning as it determines the capacity to install in order to satisfy customer demands and also to allocate products to those capacities.This research is based on mixed-load machine problem which is categorized by multiple products that can be processed simultaneously with different processing time.The problem is further complicated with high product varieties and high demand variabilities.This research was conducted based on a case company from a multinational manufacturing company in Malaysia that produces hard disk drives.The study focused on the automated testing process characterized by long lead time and high product variability.Each testing machine with 2880 slots is a mixed load tester with the ability to load and test multiple product families simultaneously.In addition,the uncertain demand and testing time makes the problem more challenging. …”
Get full text
Get full text
Get full text

Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

“…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
Get full text
Get full text

A new method for decreasing cell-load variation in dynamic cellular manufacturing systems by Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol, Baharudin, Btht Hang Tuah, Leman, Zulkiflle

“…An in-depth analysis is conducted on the results in consideration of various factors, and control charts are used on machine-load variation. Our findings indicate that the dynamic condition of product demands affects the routing of product parts and may induce machine-load variations that yield to cell-load diversity. …”
Get full text
Get full text

Development of CAD/CAM System for Cold Working Closed Die Forging Process by Abdulmawlla, Mohamed A.

“…In the third stage, a machining code for the optimised die was developed and implemented using CAD/CAM software called UniGraphics and CNC machine. …”
Get full text
Get full text

The development of integrated planning and scheduling framework for dynamic and reactive environment of complex manufacturing problem by Zakaria, Zalmiyah, Deris, Safaai, Mat Yatim, Safie, Othman, Muhamad Razib

“…Secondly, in Chapter 2 we described the modeling of the real world manufacturing processes using Petri Nets. We present two models of manufacturing process, namely machine model and process model. …”
Get full text
Get full text
Get full text

Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

“…However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
Get full text
Get full text
Get full text

A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty by Delgoshaei, Aidin, Ali, Ahad, Ariffin, Mohd Khairol Anuar, Gomes, Chandima

“…Our findings show that the condition of dynamic costs affects the routing of materials in process and may induce machine-load variation that yield to cell-load diversity. …”
Get full text
Get full text