Displaying publications 1 - 20 of 54 in total

  1. Basri, H. N., Kamarulzaman, N. H., Shamsudin, M. N., Nolila Mohd Nawi
    Majority consumers around the world have become increasingly concern and aware about their health and food safety. Recent food crisis and foodborne illness incidents showed the needs to assure the authenticity and traceability of foods in the market especially meat and meat products. These scandals have led to negative effect and perception to consumers, food companies and both supply and demand chain. Hence, the food industry needs an excellent and reliable traceability system to ensure that consumers are persistently well protected from unconscious consumption of unsafe foods. Therefore, traceability systems can support the claims by making it verifiable. However, the awareness among Malaysian consumers is still lacking due to the inadequate exposure towards concept and the importance of traceability systems particularly in meat and meat products. The aim of this study is to determine factors influencing consumers’ preferences towards traceability systems of meat and meat products in Malaysia. Primary data were collected using structured questionnaire via face to face interview with 503 respondents in Klang Valley, Malaysia. Data collected were analyzed using descriptive and factor analysis. The findings of descriptive analysis showed that most of the consumers preferred using traceability systems and aware of its importance when buying meat and meat products. Meanwhile, the factor analysis results discovered six factors that influenced consumers’ preferences towards meat and meat products with traceability systems namely Halal certificate, transparency, quality, confidence, food safety and knowledge. Therefore, implementation of traceability systems could raise standards of food safety throughout the meat production supply chain. Furthermore, the society will become more confident and they can benefit from the quality of purchase and consumption. The findings from this study are also able to contribute to the body of knowledge to the producers or marketers towards food safety issues and foodborne illness that recently happened in Malaysia.
  2. Sapuan S, Basri H
    Malays J Med Sci, 2007 Jan;14(1):71-4.
    PMID: 22593657 MyJurnal
    A 43-year old lady presented with progressive loss of vision in both eyes followed by rapid deterioration of consciousness within the next few days. This was preceded by a viral infection one week before her presentation. At presentation she had evidence of meningism and signs of bilateral upper motor neuron lesions and was managed initially as acute meningoencephalitis with antibiotics. The brain CT was within normal limits but subsequent MRI of the brain revealed multiple foci of hyperintense lesions on T2-weighted and FLAIR images. The cerebrospinal fluid examination revealed lymphocytosis, and normal protein and glucose levels. Cultures of the CSF were negative. She was managed as acute disseminated encephalomyelitis (ADEM) with high-dose of intravenous methlyprednisolone one gram/day for three consecutive days followed by oral prednisolone 60 mg/day. Despite the management she lapsed into coma and succumbed to her illness nine days after admission.
  3. Zain SM, Basri H, Suja F, Jaafar O
    Water Sci Technol, 2002;46(9):303-8.
    PMID: 12448482
    Some of the major concerns when applying sewage sludge to land include the potential effect on pH and cation exchange capacity; the mobility and the accumulation of heavy metals in sludge treated soil; the potential of applying too much nutrients and the problems associated with odors and insects. The main objective of this study is to identify the effects of sewage sludge application on the physical and chemical properties of sludge treated soil. Sewage sludge was applied to soil at various rates ranging from 0 L/m2 to 341 L/m2. In order to simulate the natural environment, the study was carried out at a pilot treatment site (5.2 m x 6.7 m) in an open area, covered with transparent roofing material to allow natural sunlight to pass through. Simulated rain was applied by means of a sprinkler system. Data obtained from sludge treated soil showed that the pH values decreased when the application rates were increased and the application period prolonged. The effect of sewage sludge on cation exchange capacity was not so clear; the values obtained for every application rate of sewage sludge did not indicate any consistent behaviour. The mobility of heavy metals in soils treated with sludge were described by observing the changes in the concentration of the heavy metals. The study showed that Cd has the highest mobility in sludge treated soil followed by Cu, Cr, Zn, Ni and Pb.
  4. Farzin A, Ibrahim R, Madon Z, Basri H
    Am J Phys Med Rehabil, 2018 09;97(9):628-635.
    PMID: 29595585 DOI: 10.1097/PHM.0000000000000931
    OBJECTIVE: The main objective of the present trial was to evaluate the efficiency of a preventative multicomponent prospective memory training among healthy older adults.

    DESIGN: This study was a two-arm within-participants trial with 4- and 12-wk follow-ups. Allocation ratio was 1:1, and pretraining and posttraining measurements were included. A total number of 25 healthy older adults were enrolled (mean = 63.32, SD = 4.44). Participants were randomly allocated into two conditions: (a) prospective memory training: participants underwent a multicomponent prospective memory training, and (b) control: participants were not contacted during the training phase. After the training phase was finished, participants crossed over to undergo the condition they did not experience before. The differences between pretraining and posttraining measures of prospective memory, activities of daily living, negative mood (depression), and anxiety were assessed. All changes in the measurements were analyzed using general linear method. This trial is registered at https://www.isrctn.com (#ISRCTN57600070).

    RESULTS: Multicomponent prospective memory training program was significantly effective on both subjective and objective prospective memory performances among healthy older adults. Moreover, the training had significant positive effects on activities of daily living (independence) among participants. In addition, negative mood and anxiety levels were reduced after the training was finished.

    CONCLUSIONS: This multicomponent prospective memory training improved prospective memory performance and activities of daily living and reduce negative mood (depression) and anxiety levels among healthy older adults.

  5. Farzin A, Ibrahim R, Madon Z, Basri H
    Dement Neuropsychol, 2018 7 11;12(2):189-195.
    PMID: 29988335 DOI: 10.1590/1980-57642018dn12-020012
    The surrounding circumstances and environments of Malaysian older adults could make conducting interventions (mainly in terms of clinical or randomized controlled trials) a challenge. Working with older adults and facing cultural issues could be challenging.

    Objective: This paper illustrates a significant perspective of some of the challenges faced while conducting a randomized controlled trial exploring the impact of a multi-component intervention that included strategy- and process-based prospective memory (PM) training among Malaysian older adults.

    Methods: The current study was a randomized controlled trial (RCT) and therefore the challenges were presented in accordance with the CONSORT statement style.

    Results: A discussion on how these issues were addressed is provided.

    Conclusion: Some suggestions were presented to help researchers plan and create interventions for similar studies and to support a practical method of addressing all related challenges.

  6. Rasli NI, Basri H, Harun Z
    Heliyon, 2020 Jan;6(1):e03156.
    PMID: 32042952 DOI: 10.1016/j.heliyon.2020.e03156
    Zinc oxide (ZnO) was biosynthesised from aloe vera plant extract. The aloe vera plant extract was used as a reducing agent in biosynthesis process. Green synthesis method was proposed because it is cost effective and environmentally friendly. ZnO was characterised using SEM, EDX, FTIR, and XRD analyses. The antibacterial property was tested against Escherichia coli. The effects of aloe vera volume (2-50) mL, precursor concentration (0.001-0.300) M, reaction time (20 min-48 h), and temperature of the reaction (26-200) °C on ZnO characteristics were investigated and screened using a two-level factorial method. Based on the observation and ANOVA analysis result, precursor concentration was the only significant parameter that affected the production of the ZnO nanoparticles (NPs). The EDX analysis proved the presence of ZnO while the SEM analysis confirmed the average size of ZnO particle size was in the range of (18-618) μm with a rod-shape appearance. The XRD analysis showed that the average crystallite size was 0.452 μm and it was in the hexagonal phase. It was also proven to have antibacterial property against E. coli.
  7. Gholamzadeh S, Hamid TA, Basri H, Sharif F, Ibrahim R
    Iran J Nurs Midwifery Res, 2014 Sep;19(5):478-84.
    PMID: 25400675
    BACKGROUND: This study aims to explore the relationship between religiosity and psychological well-being of caregivers of stroke survivors in Shiraz, Iran.
    MATERIALS AND METHODS: A purposive sample of 96 family members, which included 34 daughters-in-law and 62 daughters, who were caring for severe impaired stroke survivors were enrolled in the study.
    RESULTS: The results showed a significant correlation between positive religious coping and caregivers' psychological well-being. Positive religious coping accounted for 7.2% of the change in psychological well-being. There was no significant association between demographic factors and caregivers' psychological well-being.
    CONCLUSIONS: Our results indicated that religious and spiritual belief have a role in caregiver adaptations with the situation. Therefore, in future studies, it is suggested to concentrate on the effects of other characteristics than the demographic variables on psychological well-being.
    KEYWORDS:Aging; caregivers; mental health; religious coping; stroke
  8. Hannan MA, Zaila WA, Arebey M, Begum RA, Basri H
    Environ Monit Assess, 2014 Sep;186(9):5381-91.
    PMID: 24829160 DOI: 10.1007/s10661-014-3786-6
    This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image's gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.
  9. Hasan S, B Basri H, P Hin L, Stanslas J
    Pak J Med Sci, 2013 May;29(3):859-62.
    PMID: 24353644
    Encephalitis has been included in the causes of optic neuritis, but post encephalitic optic neuritis has been rarely reported. Majority of the cases of optic neuritis are either idiopathic or associated with multiple sclerosis, especially in western countries. This is very important in the Asian population where the incidence and prevalence of multiple sclerosis is not as high as in the Western countries. Although post infectious optic neuritis is more common in children, it can also be found in adults and is usually seen one to three weeks after a symptomatic infective prodrome. Here, we present a case of a 48 year-old-male who developed optic neuritis following viral encephalitis. His first presentation was with severe headache of two weeks duration. Viral encephalitis was diagnosed and treated. The patient presented again three weeks later with right eye pain and other features typical of optic neuritis. Corticosteroid therapy facilitated prompt recovery. Optic neuritis is an uncommon manifestation of encephalitis. It is important that both doctors and patients remain aware of post infectious cause of optic neuritis, which would enable a timely diagnosis and treatment of this reversible cause of vision loss.
  10. Islam MS, Hannan MA, Basri H, Hussain A, Arebey M
    Waste Manag, 2014 Feb;34(2):281-90.
    PMID: 24238802 DOI: 10.1016/j.wasman.2013.10.030
    The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.
  11. Tangahu BV, Abdullah SR, Basri H, Idris M, Anuar N, Mukhlisin M
    Int J Phytoremediation, 2013;15(8):814-26.
    PMID: 23819277
    Phytoremediation is an environment-friendly and cost-effective method to clean the environment of heavy metal contamination. A prolonged phytotoxicity test was conducted in a single exposure. Scirpus grossus plants were grown in sand to which the diluted Pb (NO3)2 was added, with the variation of concentration were 0, 100, 200, 400, 600, and 800 mg/L. It was found that Scirpus grossus plants can tolerate Pb at concentrations of up to 400 mg/L. The withering was observed on day-7 for Pb concentrations of 400 mg/L and above. 100% of the plants withered with a Pb concentration of 600 mg/L on day 65. The Pb concentration in water medium decreased while in plant tissues increased. Adsorption of Pb solution ranged between 2 to 6% for concentrations of 100 to 800 mg/L. The Bioaccumulation Coefficient and Translocation Factor of Scirpus grossus were found greater than 1, indicating that this species is a hyperaccumulator plant.
  12. Hannan MA, Arebey M, Begum RA, Basri H
    Waste Manag, 2012 Dec;32(12):2229-38.
    PMID: 22749722 DOI: 10.1016/j.wasman.2012.06.002
    An advanced image processing approach integrated with communication technologies and a camera for waste bin level detection has been presented. The proposed system is developed to address environmental concerns associated with waste bins and the variety of waste being disposed in them. A gray level aura matrix (GLAM) approach is proposed to extract the bin image texture. GLAM parameters, such as neighboring systems, are investigated to determine their optimal values. To evaluate the performance of the system, the extracted image is trained and tested using multi-layer perceptions (MLPs) and K-nearest neighbor (KNN) classifiers. The results have shown that the accuracy of bin level classification reach acceptable performance levels for class and grade classification with rates of 98.98% and 90.19% using the MLP classifier and 96.91% and 89.14% using the KNN classifier, respectively. The results demonstrated that the system performance is robust and can be applied to a variety of waste and waste bin level detection under various conditions.
  13. Salim N, Basri M, Rahman MB, Abdullah DK, Basri H
    Int J Nanomedicine, 2012;7:4739-47.
    PMID: 22973096 DOI: 10.2147/IJN.S34700
    During recent years, there has been growing interest in the use of nanoemulsion as a drug-carrier system for topical delivery. A nanoemulsion is a transparent mixture of oil, surfactant and water with a very low viscosity, usually the product of its high water content. The present study investigated the modification of nanoemulsions with different hydrocolloid gums, to enhanced drug delivery of ibuprofen. The in vitro characterization of the initial and modified nanoemulsions was also studied.
  14. Arebey M, Hannan MA, Begum RA, Basri H
    J Environ Manage, 2012 Aug 15;104:9-18.
    PMID: 22484654 DOI: 10.1016/j.jenvman.2012.03.035
    This paper presents solid waste bin level detection and classification using gray level co-occurrence matrix (GLCM) feature extraction methods. GLCM parameters, such as displacement, d, quantization, G, and the number of textural features, are investigated to determine the best parameter values of the bin images. The parameter values and number of texture features are used to form the GLCM database. The most appropriate features collected from the GLCM are then used as inputs to the multi-layer perceptron (MLP) and the K-nearest neighbor (KNN) classifiers for bin image classification and grading. The classification and grading performance for DB1, DB2 and DB3 features were selected with both MLP and KNN classifiers. The results demonstrated that the KNN classifier, at KNN = 3, d = 1 and maximum G values, performs better than using the MLP classifier with the same database. Based on the results, this method has the potential to be used in solid waste bin level classification and grading to provide a robust solution for solid waste bin level detection, monitoring and management.
  15. Hannan MA, Arebey M, Begum RA, Basri H
    Waste Manag, 2011 Dec;31(12):2406-13.
    PMID: 21871788 DOI: 10.1016/j.wasman.2011.07.022
    This paper deals with a system of integration of Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system. RFID, GPS, GPRS and GIS along with camera technologies have been integrated and developed the bin and truck intelligent monitoring system. A new kind of integrated theoretical framework, hardware architecture and interface algorithm has been introduced between the technologies for the successful implementation of the proposed system. In this system, bin and truck database have been developed such a way that the information of bin and truck ID, date and time of waste collection, bin status, amount of waste and bin and truck GPS coordinates etc. are complied and stored for monitoring and management activities. The results showed that the real-time image processing, histogram analysis, waste estimation and other bin information have been displayed in the GUI of the monitoring system. The real-time test and experimental results showed that the performance of the developed system was stable and satisfied the monitoring system with high practicability and validity.
  16. Abushammala MF, Noor Ezlin Ahmad Basri, Basri H, Ahmed Hussein El-Shafie, Kadhum AA
    Waste Manag Res, 2011 Aug;29(8):863-73.
    PMID: 20858637 DOI: 10.1177/0734242X10382064
    The decomposition of municipal solid waste (MSW) in landfills under anaerobic conditions produces landfill gas (LFG) containing approximately 50-60% methane (CH(4)) and 30-40% carbon dioxide (CO(2)) by volume. CH(4) has a global warming potential 21 times greater than CO(2); thus, it poses a serious environmental problem. As landfills are the main method for waste disposal in Malaysia, the major aim of this study was to estimate the total CH(4) emissions from landfills in all Malaysian regions and states for the year 2009 using the IPCC, 1996 first-order decay (FOD) model focusing on clean development mechanism (CDM) project applications to initiate emission reductions. Furthermore, the authors attempted to assess, in quantitative terms, the amount of CH(4) that would be emitted from landfills in the period from 1981-2024 using the IPCC 2006 FOD model. The total CH(4) emission using the IPCC 1996 model was estimated to be 318.8 Gg in 2009. The Northern region had the highest CH(4) emission inventory, with 128.8 Gg, whereas the Borneo region had the lowest, with 24.2 Gg. It was estimated that Pulau Penang state produced the highest CH(4) emission, 77.6 Gg, followed by the remaining states with emission values ranging from 38.5 to 1.5 Gg. Based on the IPCC 1996 FOD model, the total Malaysian CH( 4) emission was forecast to be 397.7 Gg by 2020. The IPCC 2006 FOD model estimated a 201 Gg CH(4) emission in 2009, and estimates ranged from 98 Gg in 1981 to 263 Gg in 2024.
  17. Arebey M, Hannan MA, Basri H, Begum RA, Abdullah H
    Environ Monit Assess, 2011 Jun;177(1-4):399-408.
    PMID: 20703798 DOI: 10.1007/s10661-010-1642-x
    The integration of communication technologies such as radio frequency identification (RFID), global positioning system (GPS), general packet radio system (GPRS), and geographic information system (GIS) with a camera are constructed for solid waste monitoring system. The aim is to improve the way of responding to customer's inquiry and emergency cases and estimate the solid waste amount without any involvement of the truck driver. The proposed system consists of RFID tag mounted on the bin, RFID reader as in truck, GPRS/GSM as web server, and GIS as map server, database server, and control server. The tracking devices mounted in the trucks collect location information in real time via the GPS. This information is transferred continuously through GPRS to a central database. The users are able to view the current location of each truck in the collection stage via a web-based application and thereby manage the fleet. The trucks positions and trash bin information are displayed on a digital map, which is made available by a map server. Thus, the solid waste of the bin and the truck are being monitored using the developed system.
  18. Hannan MA, Arebey M, Begum RA, Basri H, Al Mamun MA
    Waste Manag, 2016 Apr;50:10-9.
    PMID: 26868844 DOI: 10.1016/j.wasman.2016.01.046
    This paper presents a CBIR system to investigate the use of image retrieval with an extracted texture from the image of a bin to detect the bin level. Various similarity distances like Euclidean, Bhattacharyya, Chi-squared, Cosine, and EMD are used with the CBIR system for calculating and comparing the distance between a query image and the images in a database to obtain the highest performance. In this study, the performance metrics is based on two quantitative evaluation criteria. The first one is the average retrieval rate based on the precision-recall graph and the second is the use of F1 measure which is the weighted harmonic mean of precision and recall. In case of feature extraction, texture is used as an image feature for bin level detection system. Various experiments are conducted with different features extraction techniques like Gabor wavelet filter, gray level co-occurrence matrix (GLCM), and gray level aura matrix (GLAM) to identify the level of the bin and its surrounding area. Intensive tests are conducted among 250bin images to assess the accuracy of the proposed feature extraction techniques. The average retrieval rate is used to evaluate the performance of the retrieval system. The result shows that, the EMD distance achieved high accuracy and provides better performance than the other distances.
  19. Akhtar M, Hannan MA, Begum RA, Basri H, Scavino E
    Waste Manag, 2017 Mar;61:117-128.
    PMID: 28153405 DOI: 10.1016/j.wasman.2017.01.022
    Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts.
  20. Hannan MA, Akhtar M, Begum RA, Basri H, Hussain A, Scavino E
    Waste Manag, 2018 Jan;71:31-41.
    PMID: 29079284 DOI: 10.1016/j.wasman.2017.10.019
    Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts.
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