Papers by Jasni Mohamad Zain
Communications in computer and information science, 2011
The use of general descriptive names, registered names, trademarks, etc. in this publication does... more The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
Journal of Building Engineering
2016 2nd International Conference on Science in Information Technology (ICSITech), 2016
Inside the sets of data, hidden knowledge can be acquired by using neural network. These knowledg... more Inside the sets of data, hidden knowledge can be acquired by using neural network. These knowledge are described within topology, using activation function and connection weight at hidden neurons and output neurons. Is hardly to be understanding since neural networks act as a black box. The black box problem can be solved by extracting knowledge (rule) from trained neural network. Thus, the aim of this paper is to extract valuable information from trained neural networks using decision. Further, the Levenberg Marquardt algorithm was applied to training 30 networks for each datasets, using learning parameters and basis weights differences. As the number of hidden neurons increase, mean squared error and mean absolute percentage error decrease, and more time they need to deal with the dataset, that is result of investigation from neural network architectures. Decision tree induction generally performs better in knowledge extraction result with accuracy and precision level from 84.07 to 93.17 percent. The extracted rule can be used to explaining the process of the neural network systems and also can be applied in other systems like expert systems.
Journal of Computational and Theoretical Nanoscience, 2015
Educational data mining has been studied extensively as it provides useful information for educat... more Educational data mining has been studied extensively as it provides useful information for educators to make more accurate decisions concerning their students, and to adapt their teaching strategies accordingly. Data clustering as one of data mining techniques can be considered as an alternative method for educational data mining. In this paper, a data clustering technique based on soft set theory is presented. The Maximum Degree of Domination in soft set theory (MDDS) is proposed and further applied to select the best attribute in educational data clustering. To find meaningful clusters from a dataset, clustering attribute selection is conducted so that attributes within the clusters made will have a high correlation or high interdependence to each other while the attributes in other clusters are less correlated or more independent. The datasets are taken from a survey from a number of courses at the Information Engineering and the Architecture Departments of the University Technology of Yogyakarta, Indonesia. The evaluation criteria uses score range from 0 to 100. Student name, age, race, and attendance are not required in this assessment. In the results, we show how to determine the dominant attributes of a set of attributes of an assessment list by using the proposed technique. The results obtained can potentially contribute to give a recommendation in awarding the final grade of a course more quickly and accurately.
Advanced Science Letters, 2015
2015 4th International Conference on Software Engineering and Computer Systems (ICSECS), 2015
International Journal of Basic and Applied Sciences, 2015
In recent years, it has been argued and experimentally shown that ion channel noise in neurons ca... more In recent years, it has been argued and experimentally shown that ion channel noise in neurons can have profound effects on the neuron's dynamical behavior. Most profoundly, ion channel noise was seen to be able to cause spontaneous firing and stochastic resonance. It has been recently found that a non-trivially persistent cross correlation takes place between the transmembrane voltage fluctuations and the component of open channel fluctuations attributed to gate multiplicity. This non-trivial phenomenon was found to play a major augmentative role for the elevation of excitability and spontaneous firing in the small size cell. In addition, the same phenomenon was found to significantly enhance the spike coherence. In this paper, statistics of the coefficient of variation, to be obtained from the colored stochastic Hodgkin-Huxley equations using voltage clamps techniqueswill be studied. The simulation result shows the coefficient of variation; enhance the agreement with the microscopeinthe case of the noisy currents.
2014 IEEE Student Conference on Research and Development, 2014
Ener gy efficiency of mobile devices is par amount after the tr emendous advancement in technolog... more Ener gy efficiency of mobile devices is par amount after the tr emendous advancement in technology while the explosion of smar t mobile applications such as, YouTube, Facebook, Twitter s and Google maps makes Smar t I nter net Devices (SI Ds) the fir st choice of communication. On the other hand, multiple sensor s and wir eless inter faces dr ain batter y swiftly, thus r educing the oper ational time of SI Ds. Ther efor e, extending batter y life pr oblem has become of cr ucial r esear ch impor tance, at har dwar e and softwar e levels, both alike. This paper fir stly, makes contr ibution by r eviewing differ ent techniques at softwar e level used to enhance batter y life of SI Ds in par ticular Smar tphones. At the end, suggestions and opinions r elated to ener gy efficiency of SI Ds ar e given, based on the compar ative studies.
2012 International Conference on Advanced Computer Science Applications and Technologies (ACSAT), 2012
Wujud dakwaan adanya penggunaan ilmu sihir bagi memporak-perandakan hubungan antara suami dan ist... more Wujud dakwaan adanya penggunaan ilmu sihir bagi memporak-perandakan hubungan antara suami dan isteri. Isu ini pernah dibangkitkan dalam beberapa kes perkahwinan dan perceraian di Mahkamah Syariah di Malaysia, namun tidak ada insiatif diambil bagi mengatasinya. Ketiadaan peruntukan undang-undang berkaitan amalan sihir menyukarkan para hakim untuk mempertimbang dan menilai kebenaran dakwaan tersebut. Hingga hari ini, isu tersebut tergantung tanpa penyelesaian. Kertas kerja ini bertujuan untuk menilai sejauh manakah dakwaan 'kena sihir' boleh dijadikan sebagai satu pembelaan dalam kes-kes perceraian di Mahkamah Syariah di Malaysia. Dengan merujuk beberapa kes yang relevan, kajian ini akan menganalisa pandangan Syara' berkaitan hukum perceraian akibat kena sihir; dan sejauh manakah ianya boleh diaplikasikan sebagai satu pembelaan dalam kes perceraian. Kajian ini amat penting bagi membantu institusi kehakiman untuk berlaku adil dan membela nasib pasangan yang menjadi mangsa kepada kejahatan amalan sihir.
10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010), 2010
Abstract Recently, Machine Learning techniques have become very popular because of its effectiven... more Abstract Recently, Machine Learning techniques have become very popular because of its effectiveness. This study, applies Kernel Logistic Regression (KLR) to the credit risk classification in an attempt to suggest a model with better classification accuracy. Credit risk classification is an interesting and important data mining problem in financial analysis domain. In this study, the optimal parameter values (regularization and kernel function) of KLR. are found by using a grid search technique with 5-fold cross-validation. Credit risk ...
2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006
Digital watermarking medical images provides security to the images. The purpose of this study wa... more Digital watermarking medical images provides security to the images. The purpose of this study was to see whether digitally watermarked images changed clinical diagnoses when assessed by radiologists. We embedded 256 bits watermark to various medical images in the region of non-interest (RONI) and 480K bits in both region of interest (ROI) and RONI. Our results showed that watermarking medical images did not alter clinical diagnoses. In addition, there was no difference in image quality when visually assessed by the medical radiologists. We therefore concluded that digital watermarking medical images were safe in terms of preserving image quality for clinical purposes.
International Conference on Electrical, Control and Computer Engineering 2011 (InECCE), 2011
The authenticity or originality of sport jersey cloth fabric in market nowadays is difficult to d... more The authenticity or originality of sport jersey cloth fabric in market nowadays is difficult to distinguish. This is a critical issue that leads to the difficulty for customer to know whether they are purchase the original fabric or the fake one. The purpose of this paper is to develop a prototype for Fabric Authenticity System to judge the originality of jersey cloth fabric based on its pattern structure. Besides this, this study aimed to identify the image processing technique which is Fourier analysis to differentiate the authentic and artificial fabric. As a result, the originality of the fabric can be detected based on the fabric pattern structure itself by looking on its Fourier spectrum.
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
We propose a watermarking scheme that can recover the original image from the watermarked one. Th... more We propose a watermarking scheme that can recover the original image from the watermarked one. The purpose is to verify the integrity and authenticity of DICOM images. We used 800x600x8 bits ultrasound (US) images in our experiment. SHA-256 of the whole image is embedded in the least significant bits of the RONI (Region of Non-Interest). If the image has not been altered, the watermark will be extracted and the original image will be recovered. SHA-256 of the recovered image will be compared with the extracted watermark for authentication.
Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007), 2007
Abstract The Road Transport Department of Malaysia has endorsed a specification for car plates th... more Abstract The Road Transport Department of Malaysia has endorsed a specification for car plates that includes the font and size of characters that must be followed by car owners. However, there are cases where this specification is not followed. This will cause problems in the recognition phase because the existing systems will find difficulty in recognizing characters in car plates. To ensure the recognition can be done correctly, the thinning and feature extraction phases should be done successfully by applying appropriate ...
2014 International Conference on Computer, Communications, and Control Technology (I4CT), 2014
Medical image is seen as one of crucial data that demand for authentication method as it is highl... more Medical image is seen as one of crucial data that demand for authentication method as it is highly confidential and used in insurance claim, evidence of jurisdiction and personal identification. Nowadays, Hospital Information System (HIS) is used widely at hospitals and clinical departments and it handles thousands of crucial electronic data in medical. We have introduced a fragile watermarking method using spiral manner numbering which showed a good numbering system and excellent embedding, but due to the technique, it only embedded in square shape. We enhanced the scheme to the Hilbert numbering scheme, which is more compatible with medical image modalities, which is not only specific to square shape of image but applicable to all kinds of image.
Journal of Computer Science, 2009
Problem statement: Research on Smooth Support Vector Machine (SSVM) is an active field in data mi... more Problem statement: Research on Smooth Support Vector Machine (SSVM) is an active field in data mining. Many researchers developed the method to improve accuracy of the result. This study proposed a new SSVM for classification problems. It is called Multiple Knot Spline SSVM (MKS-SSVM). To evaluate the effectiveness of our method, we carried out an experiment on Pima Indian diabetes dataset. The accuracy of previous results of this data still under 80% so far. Approach: First, theoretical of MKS-SSVM was presented. Then, application of MKS-SSVM and comparison with SSVM in diabetes disease diagnosis were given. Results: Compared to the SSVM, the proposed MKS-SSVM showed better performance in classifying diabetes disease diagnosis with accuracy 93.2%. Conclusion: The results of this study showed that the MKS-SSVM was effective to detect diabetes disease diagnosis and this is very promising compared to the previously reported results.
2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005
This paper will discuss the properties of watermarking medical images. We will also discuss the p... more This paper will discuss the properties of watermarking medical images. We will also discuss the possibility of such images being compressed by JPEG and give an overview of JPEG compression. We will then propose a watermarking scheme that is reversible and robust to JPEG compression. The purpose is to verify the integrity and authenticity of medical images. We used 800x600x8 bits ultrasound (US) images in our experiment. SHA-256 of the image is then embedded in the Least significant bits (LSB) of an 8x8 block in the Region of Non Interest (RONI). The image is then compressed using JPEG and decompressed using Photoshop 6.0. If the image has not been altered, the watermark extracted will match the hash (SHA256) of the original image. The result shown that the embedded watermark is robust to JPEG compression up to image quality 60 (~91% compressed).
Procedia Engineering, 2012
Considering two-class classification, this paper aims to perform further study on the success of ... more Considering two-class classification, this paper aims to perform further study on the success of Truncated Newton method in Truncated Regularized Kernel Logistic Regression (TR-KLR) and Iterative Re-weighted Least Square (TR-IRLS) on solving the numerical problem of KLR and RLR. The study was conducted by developing the Newton version of TR-KLR and TR-IRLS algorithm respectively. They are general classifiers which are termed respectively as proposed Newton TR-KLR (NTR-KLR) and proposed NTR Regularized Logistic Regression (NTR-LR). Instead of using IRLS procedure as used by TR-KLR and TR-IRLS, the proposed algorithms implement Newton-Raphson method as the outer algorithm of Truncated Newton for KLR and RLR respectively. Since, for KLR and RLR, IRLS is equivalent to Newton-Raphson method, both proposed algorithms can be expected to perform as well as TR-KLR and TR-IRLS. Moreover, both proposed algorithms are mathematically simpler, because they do not need to restate the Newton-Raphson method as the IRLS procedure before such as in TR-KLR and TR-IRLS. Hence, they simply can be applied as further explanation to the effectiveness of Truncated Newton method in TR-KLR and TR-IRLS respectively. Numerical experiment with Image Segmentation data set has demonstrated that proposed NTR-KLR performs effectively when exist the singularity and the training time problem in using Newton-Raphson method for KLR (KLR-NR). While proposed NTR-LR has performed better training time than RLR with Newton-Raphson (RLR-NR) method on Letter Image data set. Moreover, both proposed algorithms have showed consistency with the convergence theory and have promising results, i.e. accurate and stable classification, on image data sets respectively.
Knowledge-Based Systems, 2012
Clustering is one of the most useful tasks in data mining process for discovering groups and iden... more Clustering is one of the most useful tasks in data mining process for discovering groups and identifying interesting distributions and patterns in the underlying data. One of the techniques of data clustering was performed by introducing a clustering attribute. Soft set theory, initiated by Molodtsov in 1999, is a new general mathematical tool for dealing with uncertainties. In this paper, we define a soft set model on the equivalence classes of an information system, which can be easily applied in obtaining approximate sets of rough sets. Furthermore, we use it to select a clustering attribute for categorical datasets and a heuristic algorithm is presented. Experiment results on fifteen UCI benchmark datasets showed that the proposed approach provides a faster decision in selecting a clustering attribute as compared with maximum dependency attributes (MDAs) approach up to 14.84%. Furthermore, MDA and NSS have a good scalability i.e. the executing time of both algorithms tends to increase linearly as the number of instances and attributes are increased, respectively.
3rd International Conference: Science of Electronic, Technologies of Information and Telecommunications, 2005
Abstract: This paper opens a discussion about securing telemedicine by looking at attacks to the ... more Abstract: This paper opens a discussion about securing telemedicine by looking at attacks to the security by viewing the function of the computer system as provision of information. Categories of attacks are discussed and an overview of watermarking is introduced as one of the security tool, using the medical image as the channel for watermarking. The main objectives for medical image watermarking are that the watermarks are imperceptible and act as a mean of authentication and integrity control. The issues in watermarking medical ...
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Papers by Jasni Mohamad Zain