Siti Yuhaniz

Siti Yuhaniz
Universiti Teknologi Malaysia | UTM · Razak Faculty of Technology and Informatics

Bachelor of Science (Computer Science) Universiti Teknologi Malaysia, PhD, University of Surrey

About

49
Publications
40,342
Reads
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986
Citations
Additional affiliations
July 2014 - February 2016
Universiti Teknologi Malaysia
Position
  • Professor (Associate)
July 2014 - February 2016
Universiti Teknologi Malaysia
Position
  • Professor (Associate)
March 2001 - July 2014
Universiti Teknologi Malaysia
Position
  • Professor (Associate)

Publications

Publications (49)
Article
Full-text available
In late December 2019, an epidemic of the novel coronavirus (COVID-19) was informed, and because of the quick diffusion of the infection in various regins of the world, the World Health Organization proclaimed an emergency. In this context, researchers are urged and encouraged to research in various fields, to stop the spread of this deadly virus....
Conference Paper
This paper studies the method used in orbit propagation in order to enhance the Simplified General Perturbations-4 (SGP4) model which is the common orbit propagation model used by the satellite operator. The orbit propagation is used to determine and predict the position and velocity of a satellite. The capability of making an accurate orbital pred...
Article
Full-text available
Credit card based online payments has grown intensely, compelling the financial organisations to implement and continuously improve their fraud detection system. However, credit card fraud dataset is heavily imbalanced and different types of misclassification errors may have different costs and it is essential to control them, to a certain degree,...
Conference Paper
Full-text available
To date, many developing countries and Muslim nations those existing in poverty are incapable of contributing in local and international markets due to the lack of digitalisation knowledge, entrepreneurial skills and complete absence of supportive from Government institutions. For digitalisation enhancing innovations in developing countries and pov...
Chapter
Deep Learning or also known as deep structured learning or hierarchical learning is a part of a broader family of Machine Learning methods based on learning data representations (Bengio et al. 2013). Giving that Hordri et al. (2017) have systematically reviewed that the features of the Deep Learning are a hierarchical layer, high-level abstraction,...
Article
As there are increasing numbers of mobile subscriber and the market demands of reaching customer personally, Short Message Service (SMS) has become a target of unsolicited text message known as Spam that resulting waste in time, money, and privacy. Many text classification methods using traditional machine learning algorithm has been proposed to pr...
Conference Paper
Aiming effective information extraction from textual documents, an important task is the Cross-document Coreference Resolution (CCR) in which co-referring entity mentions are resolved across multiple documents. The task of CCR, consists of multiple processing stages in which each stage plays a critical role in the whole process. In this paper, an o...
Article
Manual medical diagnosis which depends on physicians’ knowledge to diagnose the presence of the symptoms of the disease is impracticable. Therefore, automatic and intelligent medical diagnosis has become very useful to the physicians when dealing with huge amount and high dimensional medical database. In this paper, we have proposed hybridization m...
Article
Biometric cryptosystem is a template protection used to secure the cryptographic key using the biometric features. However, the major issues in biometric is irreplaceable, which the compromise biometric template database poses a serious threat to the biometric-cryptosystem. Fuzzy vault is used to protect the biometric templates and secret key simul...
Article
Full-text available
Context: Deep Learning (DL) is a division of machine learning techniques that based on algorithms for learning multiples level of representations. Big Data Analytics (BDA) is the process of examining large scale of data and variety of data types. Objectives: The aims of this study are to identify the existing features of DL approaches for using in...
Conference Paper
Full-text available
In the past few years, Deep Learning has becoming a trend. Since deep learning attempts to make a better analysis and can learn massive amounts of unlabeled data, deep learning has been applied to several of fields. Hence, this paper presents a review on deep learning and its applications over the years, with a goal of providing useful references t...
Article
Full-text available
CubeSats enable low-cost experiment and missions to be performed by universities and research institution in space. CubeSats for research use UHF and VHF communication for its tracking and telemetry applications. The current practice of a CubeSat communication is to modify radio amateur's Terminal Node Controller (TNC) to enable data to be received...
Article
Textile Artificial Magnetic Conductor (AMC) with wire dipole is presented. The AMCs are made of fleece and Shieldit fabrics and were designed to have in-phase reflections at 2.45GHz and 5.8GHz. Thorough parametric studies based on AMC unit cell have been performed to obtain the optimized design. Performance comparison between different types of env...
Article
Commercial CubeSat kit is widely used to simplify CubeSat design process and shortened development schedule by providing standard and reliable hardware architecture. However, project team still needs to coordinate subsystems integration. It becomes more difficult for undergraduate students because they may not familiar with the components used in t...
Conference Paper
This paper discusses the development process of a mission control station software for TiGA-U, a CubeSat bus. The software development process follows an iterative model whereby each phase in the cycle is repeated and modified according to the requirements from the stakeholders. The requirements, software architecture and design, and software testi...
Article
MapReduce programming model allows the processing of massive amount of data in parallel through clustering across a distributed system. The tasks for MapReduce have been categorized into areas which are data management and storage, data analytics, on line processing and security and privacy protection. For sensitive data uploaded by users, it must...
Article
The Data Warehousing Institute (TDWI) estimates that data quality problems cost U.S. businesses more than $600 billion a year. The problem with data is that its quality quickly degenerates over time. Experts say 2 percent of records in a customer file become obsolete in one month because customers die, divorce, marry, and move. In addition, data en...
Article
The strength of the adaptive neuro-fuzzy system (ANFIS) involves two contradictory requirements in a common fuzzy modeling problem, i.e. interpretability and accuracy. It is known that simultaneous optimization of accuracy and interpretability will improve performance of the system and avoid over-fitting of data. The objective of this study is the...
Article
Full-text available
This paper presents a chain codes extraction of Thinned Binary Image (TBI) using Meta-Heuristic approach. There are four methods in Meta-heuristic approach that called Differential Evolution (DE), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Ant-Colony Optimization (ACO). In the feature extraction, Freeman Chain Code (FCC) was used...
Article
Full-text available
Isolated characters usually contain many branches on their characters' nodes that causes difficulties to decide which direction would a traverse continues. Furthermore, a revisit to previous nodes is often required in order to visit all the nodes in one continuous route. Handwritten Character Recognition (HCR) consists of three stages which are pre...
Article
Full-text available
In recent decades, artificial neural networks (ANNs) have been extensively applied in different areas such as engineering, medicine, business, education, manufacturing and so on. Nowadays, ANNs are as a hot research in medicine especially in the fields of medical disease diagnosis. To have a high efficiency in ANN, selection of an appropriate archi...
Article
Full-text available
The majority of Combinatorial Optimization Problems (COPs) are defined in the discrete space. Hence, proposing an efficient algorithm to solve the problems has become an attractive subject in recent years. In this paper, a meta-heuristic algorithm based on Binary Particle Swarm Algorithm (BPSO) and the governing Newtonian motion laws, so-called Bin...
Article
Full-text available
Improving the approximation accuracy and interpretability of fuzzy systems is an important issue either in fuzzy systems theory or in its applications. It is known that simultaneous optimization both issues was the trade-offs problem, but it will improve performance of the system and avoid overtraining of data. Particle swarm optimization (PSO) is...
Article
Full-text available
Most optimization problems have constraints. The solutions of the problem are obtained from the final results of the search space that have satisfied the given constraints. In such cases, heuristic algorithms are capable to find the estimated solutions, but sometimes they have some limitations. This paper investigates the performance of three heuri...
Article
Full-text available
The fusion of different forensic modalities for arriving at a decision of whether the evidence can be attributed to a known individual is considered. Since close similarity and high dimensionality can adversely affect the process, a method of score fusion based on discretization is proposed. It is evaluated considering the signatures and fingerprin...
Conference Paper
Full-text available
In change detection analysis, it is important to reduce the influence of image misalignment in order to produce image changes that are relevant to the user. The accuracy of change detection solely depends on the image registration accuracy yet image misalignment is still a major challenge in change detection analysis. In change detection analysis,...
Conference Paper
A framework for solving tailing and necking problem in thinned binary image (TBI) is proposed. Tailing and necking are some of the classical problems occurred in thinned binary image. Artificial Neural Network (ANN) approach has been selected to be implemented in this study for obtaining a better thinned binary image. The identified TBI with tailin...
Article
This paper presents the results of a feasibility study on intelligent image processing for flood monitoring on board satellites. The ability to detect temporal changes in images is one of the most important functions in intelligent image processing systems for hazard and disaster monitoring applications. An automatic change detection system is prop...
Article
Full-text available
Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the o...
Conference Paper
Full-text available
Crowd is a unique group of individual or something involves community or society. The phenomena of the crowd are very familiar in a variety of research discipline such as sociology, civil and physic. Nowadays, it becomes the most active-oriented research and trendy topic in computer vision. Traditionally, three processing steps involve in crowd ana...
Article
Full-text available
It has been more than 30 years that statistical learning theory (SLT) has been introduced in the field of machine learning. Its objective is to provide a framework for studying the problem of inference that is of gaining knowledge, making predictions, making decisions or constructing models from a set of data. Support Vector Machine, a method based...
Article
Full-text available
This paper proposes a recognition model for English handwritten (lowercase, uppercase and letter) character recognition that uses Freeman chain code (FCC) as the representation technique of an image character. Chain code representation gives the boundary of a character image in which the codes represent the direction of where is the location of the...
Article
Full-text available
In a handwriting recognition problem, characters can be represented using chain codes. The main problem in representing characters using chain code is optimizing the length of the chain code. This paper proposes to use randomized algorithm to minimize the length of Freeman Chain Codes (FCC) generated from isolated handwritten characters. Feedforwar...
Article
This paper presents a new approach to disaster monitoring using an automatic change detection system onboard small satellites that features image tiling and fuzzy inference. Unlike other onboard change detection systems for satellites, the proposed system performs change detection on an image tile level rather than on a pixel-by-pixel basis. This i...
Conference Paper
This paper presents the results of a feasibility study on intelligent image processing and decision-making for flood monitoring on board satellites. The ability to detect temporal changes in images is one of the most important functions in intelligent image processing systems for hazard and disaster monitoring applications. An automatic change dete...
Conference Paper
Full-text available
Disaster monitoring from space can provide a powerful tool for advanced warning, assessment of the affected areas and coordination of relief measures. In this context the almost instantaneous availability of information is one of the key factors for success. However, most current Earth observation missions do not offer such a quick response due to...
Conference Paper
Current commercial Earth Observation satellites have very restricted image processing capabilities on-board. They mostly operate according to a ‘store-and forward’ mechanism, where the images are stored on-board after being acquired from the sensors and are downlinked when contact with a ground station occurs. However, in order for disaster monitor...
Article
Full-text available
The Disaster Monitoring Constellation (DMC) is a constellation of Earth observing small satellites developed by the Surrey Satellite Technology Limited (SSTL) and jointly owned by several countries. The DMC offers a novel approach to disaster monitoring by providing daily coverage of any place of the Earth using medium spatial resolution multispect...
Article
Full-text available
In change detection analysi s, the accuracy of matching techniques depend solely on the accuracy of correction methods (such as geometric correction method, intensity variation methods) used before the actual alignment is performed. When the poor cor rection methods are used during image processing, errors such as matching errors, localisation erro...

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