Search Results - (( java application optimisation algorithm ) OR ( changes detection means algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Weighting method for modal parameter based damage detection algorithms by Fayyadh, M.M., Abdul Razak, H.

“…This study proposes weighting method for damage detection algorithms based on the bending mode shapes for beam structures. …”
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Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment by Al-Doski, Jwan M. Mohammed

“…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
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Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

“…Hence, there must be substantial improvement in network intrusion detection techniques and systems. Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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Detection of muscle activities in the sEMG signal by using frequency features and adaptive decision threshold by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

“…In this paper, an amplitude-independent algorithm had been developed with an adaptive decision threshold; the algorithm employed only frequency features of the sEMG signal to detect muscle activities. …”
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Detection of muscle activities in the sEMG signal by using frequency features and adaptive decision threshold by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

“…In this paper, an amplitude-independent algorithm had been developed with an adaptive decision threshold; the algorithm employed only frequency features of the sEMG signal to detect muscle activities. …”
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Comparative analysis of segmented correlation trimmed mean algorithm for locating random and static partial discharges in power cables by Asfarina Abu Bakar, Chai Chang Yii, Chin Kui Fern, Yoong Hou Pin, Muhammad Nur Afnan Uda, Liau Chung Fan, Teddy Goh Khian Teck, Markus Diantoro

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Detection and Measurement System for Button Mushrooms Using Convolutional Neural Network by Yong, Lio Wei, Ambar, Radzi, Abd Wahab, Mohd Helmy, Abd Jamil, Muhammad Mahadi, Choon, Chew Chang

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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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A comparison of double-end partial discharge localization algorithms in power cables by Asfarina Abu Bakar, Chai, Chang Yii, Chin, Kui Fern, Yoong, Hou Pin, Herwansyah Lago, Mohamad Nur Khairul Hafizi Rohani

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Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri by Nik Mohd Asri, Nik Asyraniasna

“…Through the analysis of various customer data sets, such as people, products, promotion, place, the K-means algorithm can detect clusters that correspond to consistent client groups. …”
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Detection of Likurai Dance Movement Types in Malaka Regency Using Yolov8 Based on Video by Da Costa, Zania Abuk, Rahman, Aviv Yuniar, Putra, Rangga Pahlevi

“…The detection model is the YOLOv8 algorithm, known for detecting objects quickly and accurately. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Detecting cyber-security attacks is still a challenging task. …”
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Lane detection system for autonomous vehicle using image processing techniques by Mohd Kiblee, Shahizul Eza

“…A Radon peak detection algorithm was developed based on two values, Rand O. …”
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Blotch removal using multi-level scanning, shape analysis, and meta heuristic techniques by Khammar, Mohammad Reza

“…Therefore, error in detection can cause some unnecessary changes in the uncorrupted pixels. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB) by Hashim, Nurul Akmal

“…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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Portable Stress Detection System for Autistic Children Using Fuzzy Logic by Melinda Melinda, Verdy Setiawan, Yunidar Yunidar, Gopal Sakarkar, Nurlida Basir

Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon by Lim , Pooi Khoon

“…In this study, an automated artifact detection algorithm was developed for Blood Pressure and PPG signals. …”
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