A
PROFILE
Laman Web Staf UPM
PROF. MADYA TS. DR. MASNIDA BINTI HUSSIN
TIMBALAN PENGARAH (INOVASI PENGAJARAN DAN PEMBELAJARAN)
PUSAT PEMBANGUNAN DAN KECEMERLANGAN KEPEMIMPINAN AKADEMIK
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EN
PROFESIONAL
NAMA :
(Prof. Madya Ts. Dr.) Masnida Binti Hussin
JAWATAN :
Timbalan Pengarah (inovasi Pengajaran Dan Pembelajaran)
ENTITI :
Pusat Pembangunan Dan Kecemerlangan Kepemimpinan Akademik
PENERBITAN
2021:
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
2021:
Generic Costing Scheme Using General Equilibrium Theory for Fair Cloud Service Charging
2021:
A Fault-Intrusion-Tolerant System and Deadline-Aware Algorithm for Scheduling Scientific Workflow in the Cloud
2021:
Conflict Aspects between French and Malay Verbal Systems
2021:
Cloud-based Secure Healthcare Framework by using Enhanced Ciphertext Policy Attribute-Based Encryption Scheme
2021:
EFFECT OF TEAM COHESION ON EMPLOYEE ENGAGEMENT AMONG THE MILLENNIALS IN MALAYSIA
2020:
CONZONE CONGESTION CONTROL IN MOBILE AD-HOC NETWORK FOR RELIABLE CROWDSOURCING
2020:
TOWARDS CLASIFICATION EXPLORATION IN SPATIAL CROWDSOURCING DOMAIN: A SYSTEMATIC LITERATURE REVIEW
2020:
InCell VR: A Virtual Reality-based Application on Human Cell Division for Mobile Learning
2020:
ENHANCING THE TRANSPARENCY OF STUDENT MERIT SYSTEM USING QR CODE TECHNOLOGY: A SMART CAMPUS INITIATIVE
2020:
AWARENESS OF ENERGY CONSUMPTION IN CLOUD DATA CENTERS: A SURVEY ON EMPLOYEE ENGAGEMENT IN ENERGY MANAGEMENT
2020:
Scheduling Scientific Workflow using Multiobjective Algorithm with Fuzzy Resource Utilization in Multi-cloud Environment
2020:
A Survey on QoS requirement based on Particle Swarm Optimization Scheduling Techniques for Workflow Scheduling in Cloud Computing
2020:
Performance Evaluation of Machine Learning Classification Techniques in Intrusion Detection
2020:
COMPARATIVE ANALYSIS OF PSO-DERIVED WORKFLOW SCHEDULING ALGORITHMS IN CLOUD COMPUTING BASED ON QOS REQUIREMENTS
2020:
Grain Recognition based on Colour and Shape Analysis
2020:
OUTFIT CLASSIFICATION AND RECOMMENDATION BASED ON INTEGRATED FEATURES AND BAGGED DECISION TREE