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A protocol for developing a classification system of mosquitoes using transfer learning by Pradeep Isawasan, Zetty Ilham Abdullah, Ong, Song Quan, Khairulliza Ahmad Salleh

“…Transfer learning is a type of machine learning that is viable and durable in image classification with limited training images. This protocol aims to develop step-by-step procedure in developing a classification system with transfer learning algorithm for mosquito, we demonstrate the protocol to classify two species of Aedes mosquito - Aedes aegypti L. and Aedes albopitus L, but user can adopt the protocol for higher number of species classification. …”
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Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

“…A text extraction prototype is built using Visual C# 2008 to validate the algorithm. It is a windows application mixed with web connection protocol. …”
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Modelling of the anti-collision algorithm in RFID system: article / Shafinaz Ismail by Ismail, Shafinaz

“…To avoid these collisions, there are several anti-collision algorithms used in the RFID system. The major classifications of the algorithms are Aloha based protocols and tree based protocols. …”
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Modelling of the anti-collision algorithm in RFID system / Shafinaz Ismail by Ismail, Shafinaz

“…To avoid these collisions, there are several anti-collision algorithms used in the RFID system. The major classifications of the algorithms are Aloha based protocols and tree based protocols. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…This is achieved by using a new design algorithm by separating marker TCP and UDP protocols and extended the marking probability for injecting more green and yellow traffic into the network. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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Clustering network traffic utilization by Mohd Khairudin, Nazli, Muda, Zaiton, Mustapha, Aida, Nagarathinam, Yogeswaran, Salleh, Mohd. Sidek

“…Classification of network traffic using distinctive characteristic application is not ideal for P2P and HTTP protocols. …”
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Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review by Goh, Choon-Hian, Ferdowsi, Mahbuba, Gan, Ming Hong, Kwan, Ban-How, Lim, Wei Yin, Tee, Yee Kai, Rosli, Roshaslina, Tan, Maw Pin *

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A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features by Keshkeh, Kinan

“…This study also investigates TLSMalDetect detection performance using seven ML classification algorithms and identifies the one with the highest accuracy.…”
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Energy-efficient intrusion detection in wireless sensor network by Salehian, Solmaz, Masoumiyan, Farzaneh, Udzir, Nur Izura

“…Attacks can occur from any direction and any node in WSNs, so one crucial security challenge is to detect networks' intrusion. There are several algorithms for building Intrusion Detection Systems (IDS) based on different WSN routing protocol classifications with respect to energy-efficient manner. …”
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Fuzzy logic based link status classification for efficient multipath routing in multi-hop wireless mesh networks by Shah, P.A., Hasbullah, H.B., Rafique, S., Rehman, S.U., Jung, L.T.

“…This problem can best be modelled through fuzzy logic based classification that is based on continuous values. This paper presents a new fuzzy logic based link status classification mechanism for use with multipath routing protocols in multi-hop wireless networks like WMNs. …”
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Mitigating Slow Hypertext Transfer Protocol Distributed Denial of Service Attacks in Software Defined Networks by Akanji, Oluwatobi Shadrach, Abisoye, Opeyemi Aderiike, Iliyasu, Mohammed Awwal

“…This study contributes to the ongoing research in detecting and mitigating slow HTTP DDoS attacks with emphasis on the use of machine learning classification and meta-heuristic algorithms.…”
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General purpose search and classification algorithms for distributed information access by Siraj, Fadzilah, Wan Ishak, Wan Hussain

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Detection algorithm for internet worms scanning that used user datagram protocol by Rasheed M.M., Norwawi N.M., Ghazali O., Faaeq M.K.

Human emotion classifications for automotive driver using skin conductance response signal by Minhad, Khairun Nisa', Md. Ali, Sawal Hamid, Ooi, Jonathan Shi Khai, Ahmad, Siti Anom

“…The main goal of this study is to recognize human emotions by using a nonintrusive sensor and low-design-complexity protocols. …”
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Brain Machine Interface Controlled Robot Chair by Hema Chengalvarayan, Radhakrishnamurthy

“…Classification of the four hand motor imagery signals is presented using static and dynamic neural networks. …”
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Machine learning-based enhanced deep packet inspection for IP packet priority classification with differentiated services code point for advance network management by Khan, Fazeel Ahmed, Abubakar, Adamu

“…This study presents an approach to enhance intelligent packet forwarding priority classification on Differentiated Services Code Point (DSCP), leveraging classifiers from machine learning algorithms for Deep Packet Inspection (DPI). …”
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Compression Header Analyzer Intrusion Detection System (CHA - IDS) for 6LoWPAN Communication Protocol by Napiah, Mohamad Nazrin, Idris, Mohd Yamani Idna, Ramli, Roziana, Ahmedy, Ismail

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A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features by Keshkeh, Kinan, Jantan, Aman, Alieyan, Kamal

“…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. …”
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Routing protocols strategies for flying Ad-Hoc network (FANET): Review, taxonomy, and open research issues by Almansor M.J., Din N.M., Baharuddin M.Z., Ma M., Alsayednoor H.M., Al-Shareeda M.A., Al-asadi A.J.