Vikneswaran Vijean
Thumbnail Image
Preferred name
Vikneswaran Vijean
Official Name
Vijean, Vikneswaran
Alternative Name
Vikneswaran
Vikneswaran, V.
Vijean, V.
Main Affiliation
Scopus Author ID
54785424700
Researcher ID
D-2539-2015

Research Output

Filters

32
32
Reset filters

Settings
Now showing 1 - 10 of 32
  • Publication
    Early Detection of Diabetic Foot Ulcers through Wearable Shoe Design
    ( 2022-01-01)
    Vikneswaran Vijean
    ;
    Syakirah Afiza Mohammed
    ;
    Razi Ahmad
    ;
    Wan Amiza Amneera Wan Ahmad
    ;
    Ragunathan Al Santiagoo
    ;
    Abdul Ghapar Ahmad
    ;
    Palaniappan R.
    Diabetes Mellitus is categorized as a chronic metabolic disease where blood glucose levels are abnormal. Diabetic foot ulcer is a complication often associated with this disease. Diabetes foot ulcer is also commonly known as diabetes foot pain. It is a type of foot damage medical condition that progresses from diabetes mellitus. According to scientific data, almost 15% of diabetes patients may develop diabetes foot ulcer in their lifetime [1]. A foot ulcer is an open wound that commonly found under the feet, it can be a shallow open wound on the surface of the skin (less severe) or it can be a deep wound which exposes bones, tendons and joints [2]. However, if early prevention is carried out, diabetes patients might be able to avoid problems from diabetes foot ulcer. Thus, in this study, a wearable shoe prototype for early detection of foot ulcers is proposed to be used in home. The developed device will be associated with temperature sensor, vibration motor and pressure sensor. This device enables diabetes patients to carry out evaluation on their foot in daily life. With this device, early symptoms of foot ulcer can be detected and the seriousness of foot ulcer can be monitored.
  • Publication
    DT-CWPT based Tsallis Entropy for Vocal Fold Pathology Detection
    ( 2020-10-26)
    Farah Nazlia Che Kassim
    ;
    Vikneswaran Vijean
    ;
    Muthusamy H.
    ;
    Abdullah Z.
    ;
    Rokiah Abdullah
    ;
    Palaniappan R.
    The study of voice pathology has become one of the valuable methods of vocal fold pathology detection, as the procedure is non-invasive, affordable and can minimise the time needed for the diagnosis. This paper investigates the Dual-Tree Complex Wavelet Packet Transform (DT-CWPT) based Tsallis entropy for vocal fold pathology detection. The proposed method is tested with healthy and pathological voice samples from Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database and Saarbruecken Voice Database (SVD). A pairwise classification using k-Nearest Neighbors (k-NN) classifier gave 91.59% and 85.09% accuracy for MEEI and SVD database respectively. Higher classification accuracy of 93.32% for MEEI and 85.16% for SVD database achieved using Support Vector Machine (SVM) classifier.
  • Publication
    Simulation of PLC Ladder Logic Programming for an Automated Glass Bottle Molding and Refilling Plant
    ( 2021-01-01)
    Khan M.M.
    ;
    Shawareb O.M.A.
    ;
    Palaniappan R.
    ;
    Vikneswaran Vijean
    ;
    Nabi F.G.
    ;
    Shawareb A.H.A.
    ;
    Khan N.K.
    Automation has been gaining interest in every branch today. The reason for the popularity of automation in industries today is due to its capability to reduce labour cost, reduce material wastage, increase the production quantity, to improve the quality of the product and to reduce idle time in manufacturing industry. In this work, an industrial process of glass molding and filling operation is simulated using the Fiddle PLC simulator. GRAFCET based modelling of discrete event is used in developing the PLC ladder logic program for the industrial process. The proposed method reduces labour cost by 40%, Increases production value by 55%, and reduces material wastage by 20% compared to manual operation. The proposed GRAFCET based model was found to be reliable, efficient, and accurate in performing the control sequence of the glass molding and filling operation. In future, it is proposed to develop the HMI (human machine interface) and the corresponding hardware will be developed for the same application.
  • Publication
    Data Acquisition System for Web-based Multi-modal Data Repository
    ( 2021-03-25)
    Rushambwa M.C.
    ;
    Mukherjee A.
    ;
    Maity M.
    ;
    Palaniappan R.
    ;
    Vikneswaran Vijean
    ;
    Ghulam Nabi F.
    The multimodal medical data with annotation helps to build different automated algorithms. Each reported work has used a specific disease database and developed a CAD based on the considered database. Therefore, the availability and quality of medical database play the most crucial role in developing any CAD. However, it has been observed that most of the reported studies used public database (created by foreign universities/centers) or private database. Unfortunately, the availability of a national medical database in India is negligible. However, development of such medical database is possible. Such medical database can encourage new research activity and help a large research community. The proposed study focuses on developing an online public medical multimodal database platform. Here, the data acquisition software is build for collecting various information.
  • Publication
    Recognition of plant diseases by leaf image classification using deep learning approach
    ( 2023-02-21)
    Goy S.Y.
    ;
    Chong Y.F.
    ;
    Teoh T.K.K.
    ;
    Lim Chee Chin
    ;
    Vikneswaran Vijean
    Plant health is important in maintaining the sustainability of the foods crop. The key to prevent the loss of yield of plant crops is the identification of plant diseases. The process of monitor plant health manually is challenging as it required expert knowledge which is expensive and time-consuming. Hence, the image processing techniques can be useful for the detection and classification of plant leaf disease. In this project, the leaf images of 5 plant types in the PlantVillage dataset are used for plant type and plant disease classification. The original images are resized to the required input sized and the proposed background removal methods (improved HSV and GrabCut segmentation) are performed to reduce the background noise. The segmented images are then given to proposed models (AlexNet and DenseNet121) for training and classification. For plant type classification, DenseNet121 got a better validation accuracy of 99% compared to AlexNet with 91.2%. After that, the leaf image is given to plant disease models according to their species. All the plant disease models training with DenseNet121 can achieve high validation accuracy of 99%, 99%, 100%, 100% and 97% for apple, grape, potato, strawberry and tomato. Lastly, a user-friendly graphical user interface (GUI) is developed.
  • Publication
    Optimization of dual-tree complex wavelet packet based entropy features for voice pathologies detection
    ( 2020-07-01)
    Farah Nazlia Che Kassim
    ;
    Vikneswaran Vijean
    ;
    Abdullah Z.
    ;
    Muthusamy H.
    ;
    Rokiah Abdullah
    The Dual-Tree Complex Wavelet Packet Transform (DT-CWPT) has been successfully implemented in numerous field because it introduces limited redundancy, provides approximately shift-invariance and geometrically oriented signal in multiple dimensions where these properties are lacking in traditional wavelet transform. This paper investigates the performance of features extracted using DT-CWPT algorithms which are quantified using k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM) classifiers for detecting voice pathologies. Decomposition is done on the voice signals using Shannon and Approximate entropy (ApEn) to signify the complexity of voice signals in time and frequency domain. Feature selection methods using the ReliefF algorithm and Genetic algorithm (GA) are applied to obtain the optimum features for multiclass classification. It is observed that the best accuracies obtained using DT-CWPT with ApEn entropy are 91.15 % for k-NN and 93.90 % for SVM classifiers. The proposed work provides a promising detection rate for multiple voice disorders and is useful for the development of computer-based diagnostic tools for voice pathology screening in health care facilities.
  • Publication
    Investigation on Medicated Drugs in ECG of Healthy Subjects
    ( 2022-01-01)
    Vikneswaran Vijean
    ;
    Abdul Ghapar Ahmad
    ;
    Syakirah Afiza Mohammed
    ;
    Razi Ahmad
    ;
    Wan Amiza Amneera Wan Ahmad
    ;
    Ragunathan Al Santiagoo
    ;
    Lim Chee Chin
    Heart diseases are now the leading cause of death worldwide, it is estimated that around 7 million patients who are living in developed countries, lost their lives due to diseases related to their cardiovascular system. In Malaysia, cardiovascular diseases represents one fifth of total deaths in the country in the past three decades. Currently patients need some sort of drugs that help them to stabilize and restore the regular patterns of their heart beat because if the patients cannot manage to restore the normal heart beat pattern, the undesired heart condition could lead life threatening situations. Advancement of biotechnology has enabled the creation of new medicated drugs to provide better treatment options. However, when this treatment option fails and there is a need to provide emergency intervention to the patients in hospitals, the medical experts often need to know about the patients' intake of any medications prior to hospital admittance for providing suitable treatments. Sometimes, this would be a difficult task as the patient might be admitted in semi-conscious or unconscious state. Therefore, this study focusses on identification of different medicated drugs usage through analysis of ECG data of the users. The data for the experiment was obtained from physionet library, which provides ECG data of subjects administered with a combination of Dofetilide, Mexiletine, lidocaine, Moxifloxacin and Diltiazem medicated drugs. The use of morphological and non-linear features derived from the ECG signals were able to provide prediction accuracy of 77.26% using SVM classifier.
  • Publication
    Optimum Binder Content of Asphaltic Concrete (ACW14) Mixture Incorporating Limestone
    ( 2023-01-01)
    Syakirah Afiza Mohammed
    ;
    Abdul Ghapar Ahmad
    ;
    Ragunathan Al Santiagoo
    ;
    Vikneswaran Vijean
    ;
    Wan Amiza Amneera Wan Ahmad
    ;
    Razi Ahmad
    ;
    Kai L.S.
    Due to the high demand for natural aggregates in pavement construction, researchers have been looking for alternative materials to replace natural aggregate. In this research, the optimum binder content of asphalt mixture incorporate limestones was investigated. The optimum binder content of asphalt mixture was tested according to Marshall method. About 20 % of limestone was used as aggregate replacement in asphaltic concrete mixture. To determine the stability, volumetric properties, and bitumen binder content, three percentage of asphalt binder content, namely 4.0%, 5.0% and 6.0% was prepared. From analysis, it indicated that stability and volumetric properties of asphalt mixture incorporate limestone meet the requirement set by JKR. From the result obtained, the optimum binder content of the control sample is 5.0% and optimum binder content of limestone mixture is 5.2%. The slightly different in optimum binder content value indicate that the optimum binder content of limestone mixture was comparable with control mixture.
  • Publication
    Compatibilizers Effect on Recycled Acrylonitrile Butadiene Rubber with Polypropylene and Sugarcane Bagasse Composite for Mechanical Properties
    ( 2023-10-16)
    Zainal M.
    ;
    Ragunathan Al Santiagoo
    ;
    Razi Ahmad
    ;
    Mohammed S.A.
    ;
    Abdul Ghapar Ahmad
    ;
    Vikneswaran Vijean
    ;
    Wan Amiza Amneera Wan Ahmad
    ;
    Allan Melvin Andrew
    Compatibilizers effect on recycled acrylonitrile butadiene rubber (NBRr) with polypropylene (PP) and sugarcane bagasse (SCB) composite for mechanical properties is evaluated. Trans-Polyoctylene Rubber (TOR) and Bisphenol a Diglycidyl Ether (DGEBA) are used as compatibilizers in this study. Three (3) different composites (80/20/15, 60/40/15, and 40/60/15), with fixed filler (15 phr) and compatibilizers (10 phr) content, were carried out. These composites were arranged via melt mixing technique utilizing a heated two-roll mill at a temperature of 180 C for 9 minutes employing a 15-rpm rotor speed. Tensile and morphological properties were evaluated. The result shown average tensile strength dropped by 48.50% as the recycle NBR content rises 20 phr. Nevertheless, subsequent compatibilization reveals that the compositesâ tensile properties were all greater than control composites. The morphology discovered validates the tensile properties, indicating a stronger interaction between the PP/SCB and recycle NBR composites with the addition of compatibilizer DGEBA.
  • Publication
    Predictive Maintenance System Design for Infant Intensive Phototherapy Lamp
    ( 2022-01-01)
    Vikneswaran Vijean
    ;
    Razi Ahmad
    ;
    Wan Amiza Amneera Wan Ahmad
    ;
    Ragunathan Al Santiagoo
    ;
    Abdul Ghapar Ahmad
    ;
    Syakirah Afiza Mohammed
    Planned-Preventive maintenance (PPM) is an essential part of clinical engineering to ensure correct functionality of the medial equipment. PPM involves the extension of equipment's life and reducing failure by performing selective substitution of its components in contrast to the "fix it when it fails"concept. However, this strategy often leads to un-necessary downtime and increased costs, especially in hospital environment. Therefore, a maintenance system for predictive preventive maintenance that can monitor the usage of medical equipment is much preferred option. In this regards, a predictive maintenance system design is proposed that focuses on the LED Infant Intensive Phototherapy Lamp. In order to improve the weakness arise from the schedule Planned-Preventive Maintenance (PPM), the predictive maintenance system will be real time performance based in which the performance of the LED Infant Intensive Phototherapy Lamp will be monitored. The purpose of this monitoring system is to ensure that the light intensity, which is measured in irradiance level, can be delivered in sufficient amount for the baby with jaundice. In order to monitor the performances of LED infant intensive phototherapy lamp, a cloud based webpage has been implemented for real time monitoring of LED infant intensive phototherapy lamp which can be accessed by authorized personals.