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Improved Boosting Algorithms by Pre-Pruning and Associative Rule Mining on Decision Trees for predicting Obstructive Sleep Apnea by Doreen Ying Ying, Sim, Chee Siong, Teh, Ahmad Izuanuddin, Ismail

“…The improved algorithms were implemented in OSA dataset and UCI online databases for comparisons. …”
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An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

“…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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Enhancement of parallel thinning algorithm for handwritten characters using neural network by Engkamat, Adeline

“…Thus, this project presents a framework for the implementation of a multilayer perceptron neural network with backpropagation algorithm, in the Parker thinning algorithm in order to produce a fast fully parallel thinning algorithm. …”
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Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

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Car dealership web application by Yap, Jheng Khin

“…Hence, two transfer learning algorithms were proposed and implemented to provide initial performance boost to the River adaptive random forest regressor and classifier, respectively. …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…Initially, the Particle Swarm Optimization was implemented to establish the optimal sizes of DGs and the performance of the implemented algorithm was analyzed and quantified. …”

Embedded car plate image recognition system by Moo Wui Hung

“…Usually, a general framework is: Pre-processing, Bounding, Character Segmentation, and Character Recognition. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Security framework based multi agent system architecture to facilitate data fetching from cloud data storage by Mohamed, Amir Mohamed Talib

“…In order to evaluate our proposed security framework based on MAS architecture, a pre-survey is conducted using a questionnaire survey. …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…For the abnormal eye, the images has been examined and confirmed by a doctor who checks the images for verified that the images are the cases of CA. The framework consists of three stages of implementation such as pre-processing, features extraction and classification. …”
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A concept paper on readiness in artificial intelligence (AI) mastery and its impact on 21st century pedagogy among pre-service history teachers by Arzizul Bin Antin, Dg Norizah binti Ag Kiflee Dzulkifli

“…Anchored in Vygotsky’s Constructivist Theory and the Technological Pedagogical Content Knowledge (TPACK) framework, the study aims to explore the gap between teachers’ awareness of AI and their practical and ethical preparedness to implement AI tools in the 21st century pedagogy classroom. …”
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Analysis characteristic and performance of passive Radio Frequency Identification (RFID) for 13.56MHz system / Mohd Faizul Azmy Amat by Amat, Mohd Faizul Azmy

“…Scopes of work include the algorithm for RFID flow in which frequency band will be continually implemented considering pre-determined constraints. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

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A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

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User interface and interactivity design guidelines of algorithm visualization on mobile platform by Supli, Ahmad Affandi

“…Algorithm Visualization (AV) is a pedagogical tool that can help learners to see the animation of the step-by-step process of an algorithm. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

An Approach to Automatic Garbage Detection Framework Designing using CNN by Kumar Sharma, Akhilesh, Jain, Antima, Chaudhary, Deevesh, Tiwari, Shamik, Mahdin, Hairulnizam, Baharum, Zirawani, Shaharudin, Shazlyn Milleana, Maskat, Ruhaila, Arshad, Mohammad Syafwan

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An Approach to Automatic Garbage Detection Framework Designing using CNN by Sharma, Akhilesh Kumar, Jain, Antima, Deevesh Chaudhary, Deevesh Chaudhary, Tiwari, Shamik, Mahdin, Hairulnizam, Baharum, Zirawani, Shaharudin, Shazlyn Milleana, Maskat, Ruhaila, Arshad, Mohammad Syafwan

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An Approach to Automatic Garbage Detection Framework Designing using CNN by Akhilesh Kumar Sharma, Akhilesh Kumar Sharma, Jain, Antima, Deevesh Chaudhary, Deevesh Chaudhary, Shamik Tiwari, Shamik Tiwari, Mahdin, Hairulnizam, Baharum, Zirawani, Shaharudin, Shazlyn Milleana, Maskat, Ruhaila, Arshad, Mohammad Syafwan

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Passive client-centric rogue access point detection framework for WiFi hotspots by Ahmad, Nazrul Muhaimin

“…The proliferation of Wi-Fi hotspots in public places provides seamless Internet connectivity anywhere at any time to the wireless clients.Although many hotspots are often unprotected,unmanaged and unencrypted,this does not prevent the clients from actively connecting to the network.The underlying problem is that the network Access Point (AP) is always trusted.The adversary can impersonate a legitimate AP by setting up a rogue AP to commit espionage and to launch evil-twin attack,session hijacking,and eavesdropping.To aggravate the threats, existing detection solutions are ill-equipped to safeguard the client against rogue AP.Infrastructure- centric solutions are heavily relied on the deployment of sensors or centralized server for rogue AP detection, which are limited,expensive and rarely to be implemented in hotspots.Even though client-centric solutions offer threat-aware protection for the client,but the dependency of the existing solutions on the spoofable contextual network information and the necessity to be associated with the network makes those solutions are not viable for the hotspot’s client.Hence,this work proposes a framework of passive client-centric rogue AP detection for hotspots.Unlike existing solutions,the key idea is to piggyback AP-specific and network-specific information in IEEE 802.11 beacon frame that enables the client to perform the detection without authentication and association to any AP.Based on the spatial fingerprints included in the broadcasted information from the APs in the vicinity of the client,this work discloses a novel concept that enables the rogue AP detection via the client’s ability to self-colocalize and self-validate its own position in the hotspot.The legitimacy of the APs in the hotspot,in this view,lies in the fact that the correct matching between the Received Signal Strength Indicator (RSSI) measurements at the client and pre-recorded fingerprints is attainable when the beacons are transmitted only from the legitimate APs.Hence,any anomalousness in AP’s beacon frame or any attempt to replay the legitimate AP’s beacon frame from different location can be detected and classified as rogue AP threats.Through experiments in real environment,the results demonstrate that with proper algorithm selection and parameters tuning,the rogue AP detection framework can achieve over 90% detection accuracy in classifying the absence and presence of rogue AP threats in the hotspot.…”
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