Search Results - (( developing negative detection algorithm ) OR ( java application stemming algorithm ))

Missing tags detection algorithm for radio frequency identification (RFID) data stream by Zainudin, Nur 'Aifaa

“…Thus in this research, an AC complement algorithm with hashing algorithm and Detect False Negative Read algorithm (DFR) is used to developed the Missing Tags Detection Algorithm (MTDA). …”
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Melanoma skin cancer recognition using negative selection algorithm / Muhammad Rushamir Hakimi Ruslan by Ruslan, Muhammad Rushamir Hakimi

“…This project presents a novel intelligence that inspired by immune system or specifically the Artificial Immune System. The Negative Selection Algorithm has been successfully applied in several application areas such as fault detection, virus detection and data integrity protection. …”
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

“…Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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A study on the performances of danger theory and negative selection algorithms for mobile spam detection by Sulaiman N.F., Jali M.Z., Abdullah Z.H., Ismail S.

Extended development of a Computer Aided Detection (CAD) system for brain bleed in CT / Muhammad Illyas Abdul Muhji by Muhammad Illyas, Abdul Muhji

“…Computer aided detection Computer aided detection (CAD) is a tool developed to assist radiologist interpretations from diagnostic modalities to decrease observational oversights or false negative rates. …”
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Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

“…IP-PBX face challenges in detecting and mitigating malicious traffic. In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. …”
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Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

“…Then, the percentage of detection accuracy was used to compare the detection performance of all five algorithms. …”
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Haar cascade algorithm for microsleep detection by Awang, Norkhushaini, Azhar, Ahmad Mirza

“…During the development phase, the system was built in Python using OpenCV and dlib for real-time facial analysis and the Haar Cascade algorithm for efficient facial feature detection. …”
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Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

“…Negative selection algorithm has been successfully used in several purposes such as in fault detection, data integrity protection, virus detection and etc.due to the unique ability in self-recognition by classifying self or non-self’s detectors. …”
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Automated negative lightning return strokes characterization using brute-force search algorithm by Abdul Haris, Faranadia, Ab. Kadir, Mohd Zainal Abidin, Sudin, Sukhairi, Jasni, Jasronita, Johari, Dalina, Zaini, Nur Hazirah

“…Moreover, the characterization mainly on the negative return strokes also significantly contributed to the development of the lightning detection system. …”
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Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki by Mohd Zaki, Sofea Najihah

“…A user-friendly desktop prototype was developed, and users may upload handwritten samples and get immediate results for the dyslexia handwriting type (normal or reversal) and status of handwriting (detect or not detect). …”
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Automated negative lightning return strokes characterization using brute-force search algorithm by Abdul Haris, Faranadia, Ab. Kadir, Mohd Zainal Abidin, Sudin, Sukhairi, Jasni, Jasronita, Johari, Dalina, Zaini, Nur Hazirah

“…Moreover, the characterization mainly on the negative return strokes also significantly contributed to the development of the lightning detection system. …”
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Automated Negative Lightning Return Strokes Characterization Using Brute-Force Search Algorithm by Faranadia Abdul Haris, Mohd Zainal Abidin Ab. Kadir, Sukhairi Sudin, Jasronita Jasni, Dalina Johari, Nur Hazirah Zaini

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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat by Selamat, Nur Syuhada

“…It also caused many protections are developed to fight the malware. The most common method of detecting malware relies on signature-based detection. …”
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A Bio-Inspired Behavior-Based Hybrid Framework for Ransomware Detection by Mohammed A. F. Salah, Mohd Fadzli Marhusin, Rossilawati Sulaiman

Remote to Local Attack Detection Using Supervised Neural Network by Iftikhar, Ahmad, Azween, Abdullah, Abdullah , S. Alghamdi

“…The developed system is applied to R2L attacks. Moreover, experiment indicates this technique has comparatively low false positive rate and false negative rate, consequently it effectively resolves the deficiency of existing intrusion detection approaches…”
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Image recognition using Artificial Immune systems approach by Hasnah, Ahmad, Puteh, Saad

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Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

“…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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An Evolutionary Stream Clustering Technique for Outlier Detection by Supardi, N.A., Abdulkadir, S.J., Aziz, N.

“…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
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A new intrusion detection system based on fast learning network and particle swarm optimization by Ali, Mohammed Hasan, Mohamad Fadli, Zolkipli, Al Mohammed, B.A.D., Alyani, Ismail

“…Our developed model has been compared against a wide range of meta-heuristic algorithms for training ELM, and FLN classifier. …”
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