Abdul Ghapar Ahmad
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Preferred name
Abdul Ghapar Ahmad
Official Name
Ahmad, Abdul Ghapar
Alternative Name
Ahmad, Abdul Ghapar
Ahmad, A.G.
Main Affiliation
Scopus Author ID
57192914392
Researcher ID
ENF-7604-2022

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  • Publication
    Potential of pretreated palm kernel shell on pyrolysis
    ( 2023-01-01)
    Razi Ahmad
    ;
    Ragunathan Al Santiagoo
    ;
    Abdul Ghapar Ahmad
    ;
    Syakirah Afiza Mohammed
    ;
    Wan Ahmad W.A.M.
    ;
    Vikneswaran Vijean
    ;
    Ibrahim N.R.
    The impact of pretreatment on palm kernel shell (PKS) with torrefaction for the possibility of pyrolysis is discussed in this study. PKS samples were torrefied at different holding times of 30 and 60 minutes at temperatures of 200, 225, 250, 275, and 300 °C. In a fixed-bed reactor with a constant nitrogen flow rate of 500 ml/min, torrefaction pretreatment was carried out. The elemental composition, mass, and energy yield, as well as proximate analysis, were all performed on the pretreated PKS. The optimised pretreated PKS was pyrolyzed next at a temperature of 400 to 550 °C in a fixed-bed reactor. The outcomes demonstrated that the pretreated PKS had a significant mass and energy yield at a temperature of 250 °C and a holding time of 30 min. PKS's calorific value and carbon content both rose after pretreatment. However, the oxygen and moisture content decreased for pretreated PKS. The maximum bio-oil production of 58% was achieved during the pyrolysis of pretreated PKS at a temperature of 500 °C. At higher temperature of 550 ℃, the bio-oil decreased due to secondary cracking reaction. Consequently, the pretreated PKS has greater potential as effective feedstock for successive proses particularly pyrolysis for bio-oil production.
  • Publication
    Cloud-based System for University Laboratories Air Monitoring
    ( 2020-09-21)
    Abu Hassan Abdullah
    ;
    Sukhairi Sudin
    ;
    Mustafa M.H.
    ;
    Fathinul Syahir Ahmad Sa'ad
    ;
    Khairul Azwan Ismail
    ;
    Muhammad Aizat Abu Bakar
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Abdul Ghapar Ahmad
    ;
    Zahari Awang Ahmad
    ;
    Sara Yasina Yusuf
    Indoor air such as house, shopping complex, hospital, university, office and hotel should be monitor for human safety and wellbeing. These closed areas are prone to harmful air pollutants i.e. allergens, smoke, mold, particles radon and hazardous gas. Laboratories in university are special room in which workers (student, technician, teaching/research assistants, researcher and lecturer) conduct their works and experiment. The activities and the environment will generate specific air pollutant which concentration depending to their parameters. Anyone in the environment that exposure to these pollutants may affect safety and health issue. This paper proposes a study of development of a cloud-based electronic nose system for university laboratories air monitoring. The system consists of DSP33-based electronic nose (e-nose) as nodes which measure main indoor air pollutant along with two thermal comfort variables, temperature and relative humidity. The e-noses are placed at five different laboratories for acquiring data in real time. The data will be sent to a web server and the cloud-based system will process, analyse using Neuro-Fuzzy classifier and display on a website in real time. The system will monitor the laboratories air pollutants and thermal comfort by predict the pollutant concentration and dispersion in the area i.e. Air Pollution Index (API). In case of air hazard safety (e.g., gas spills detection and pollution monitoring), the system will alert the security by activate an alarm and through e-mail. The website will display the API of the area in real-time. Results show that the system performance is good and can be used to monitor the air pollutant in the university laboratories.
      38  2
  • 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.
      2  34
  • 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.
      35  1
  • Publication
    Identification of habitual smokers through speech signal
    ( 2024-02-08)
    Vikneswaran Vijean
    ;
    Ragunathan Al Santiagoo
    ;
    Abdul Ghapar Ahmad
    ;
    Syakirah Afiza Mohammed
    ;
    Razi Ahmad
    ;
    Wan Amiza Amneera Wan Ahmad
    Smoking is an addictive behavior and can result major health complications. Nowadays, many young adults tend to pick up this unhealthy habits which could potentially harm their health and affects the future workforce of the nation. Most of the habitual smokers have difficulties in ceasing this habit and require external assistance in the form of group therapy, medical interventions to quit smoking. Therefore, the main aim of this study is to investigate the speech signals of the subjects in an effort to identify the habitual smokers non-invasively. Through this detection, young smokers could be identified. Voice samples from VOice ICar fEDerico II from PhysioNet database were used for this study. Wavelet Packet Transform was used to extract non-linear features from the signals. Due to uneven data, ADASYN algorithm was used to produce a balanced dataset through synthetic data sampling. Subspace KNN and SVM classifiers were used for the investigations and classification accuracies up to 83.7% and 94% of AUC curve were observed from the analysis. The results suggests that the proposed method is effective in detecting habitual smokers, and can be considered as an early screening for smoking habits in young adults for targeted rehabilitation strategies.
      23  1
  • Publication
    Influence of Torrefaction on Sewage Sludge
    ( 2023-01-01)
    Razi Ahmad
    ;
    Abdul Ghapar Ahmad
    ;
    Mohammed S.A.
    ;
    Wan Ahmad W.A.M.
    ;
    Vikneswaran Vijean
    ;
    Ragunathan Al Santiagoo
    ;
    Ibrahim N.R.
    ;
    Udin N.
    Sewage sludge (SS) from sewage treatment plants has been seen as a waste for decades and little attention to investigate the potential and its beneficial product. SS contain a large amount of recoverable energy; however, it has high moisture, ash, heavy metals, and organic contents. Thus, the goal of this research is to use torrefaction to produce upgraded or torrefied SS. The proximate and ultimate analysis was used to determine the physical and chemical characteristic of raw SS. Torrefaction was performed through inert atmosphere in fixed bed reactor. According to the findings, at torrefaction temperature of 300 °C, torrefaction had improved the quality of raw SS, increasing its fixed carbon content by 47.8%, and its moisture content by 61.3%. The optimum temperature for torrefaction was at 300 ℃ with holding time of 60 minutes. This study improved the quality of sewage sludge to be utilised in subsequent thermochemical conversion.
      5  27
  • 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.
      36  2
  • 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.
      3  28
  • Publication
    Carbon footprint hotspots of prefabricated sandwich panels for hostel construction in Perlis
    ( 2017-10-16)
    Norashikin Razali
    ;
    Afizah Ayob
    ;
    Muhammad Erwan Shah Chandra
    ;
    Mohd Faiz Mohammad Zaki
    ;
    Abdul Ghapar Ahmad
    Sustainable design and construction have gained increasing research interest, and reduction of carbon from building construction has become the main focus of environmental strategies in Malaysia. This study uses life cycle assessment and life cycle inventory analysis frameworks to estimate the amount of carbon footprint expressed in carbon dioxide equivalent tons (CO2e) produced by manufacturing prefabricated Industrialized Building System sandwich panels and its installation for a five-story hostel in Perlis, Malaysia. Results show that the carbon footprint hotspots were centered on boiler machine operation and cement with 4.52 and 369.04 tons CO2e, respectively. This finding is due to the extensive energy used for steam heating and high engine rating for the boiler. However, for cement, the carbon footprint hotspots are caused by the large quantity of cement applied in shotcrete mixture and its high extraction and production CO2 emission values. The overall onsite materials generated 96.36% of the total carbon footprint. These carbon footprint hotspot results constitute a necessary base for the Malaysian government in accomplishing an adequate dimensioning of carbon emissions in the building sector.
      3  20