Search Results - (( java implementation level algorithm ) OR ( machine loading process algorithm ))

AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

“…The encryption algorithms are playing an important part in the protection level for data. …”
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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. …”
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

“…Internet communication has become more common in this modern world recently, and one of the important algorithms used is ABS algorithm. However, most of the users have inadequate knowledge and understanding regard to this algorithm implementation in the communication field, as well as the level of security and accuracy will be questioned by the users because of the necessary to maintain the confidentiality of particular data transferred. …”
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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). …”
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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. …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

“…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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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. …”

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. …”
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A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

“…Level one is the development of userID and password, level two involve the insertion of the testing parameter speed coding. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…Performance Testing is used to test the performance of algorithm implementations in applications. The test results show that the Boyer Moore and Knuth Morris Pratt algorithms have an accuracy rate of 100%, and the Horspool algorithm 85.3%. …”
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An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe by Yakub Kayode, Saheed, Kazeem Alagbe, Gbolagade

“…We use a parallel technique that divides RSA power process into seperate threads and employs the use of Chinese Remainder Theorem (CRT) to decrease the time required for both encryption and decryption operation. Java programming language is used to implement the algorithm. …”
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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. …”
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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. …”
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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. …”
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Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

“…Therefore, the AES encryption algorithm has been implemented in HDFS to ensure the security of data stored in HDFS. …”
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Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

“…Therefore, the AES encryption algorithm has been implemented in HDFS to ensure the security of data stored in HDFS. …”
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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. …”
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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. …”
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