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Fulltext Establishing a hyperacute stroke service during the COVID-19 pandemic: our institution's one year experience

Abdul Rashid AM, Md Noh MSF, Yusof Khan AHK, Loh WC, Baharin J, Ibrahim A, et al.

BMC Neurol, 2023 Feb 15;23(1):72.
PMID: 36792988 DOI: 10.1186/s12883-023-03102-z

BACKGROUND AND AIMS: The corononavirus 2019 (COVID-19) pandemic resulted in modifications in the workflow and redistribution of human resources, causing challenges in setting up of an acute stroke service. We would like to share our preliminary outcome amid this pandemic, to determine if the implementation of COVID-19 standard operating procedures (SOPs) affected the delivery of our hyperacute stroke service.
METHODS: We retrospectively analyzed one-year data from our stroke registry that began with the establishment of our hyperacute stroke service at Universiti Putra Malaysia Teaching Hospital from April 2020 until May 2021.
RESULTS: Setting up acute stroke services during the pandemic with constrained manpower and implementation of COVID-19 SOPs, was challenging. There was a significant dip of stroke admission from April to June 2020 due to the Movement Control Order (MCO) implemented by the government to curb the spread of COVID-19. However, the numbers of stroke admission steadily rose approaching 2021, after the implementation of recovery MCO. We managed to treat 75 patients with hyperacute stroke interventions i.e. intravenous thrombolysis (IVT), mechanical thrombectomy (MT) or both. Despite implementing COVID-19 SOPs and using magnetic resonance imaging (MRI) as our first line acute stroke imaging modality, clinical outcomes in our cohort were encouraging; almost 40% of patients who underwent hyperacute stroke treatment had early neurological recovery (ENR), and only 33% of patients had early neurological stability (ENS). In addition, we were able to maintain our door-to-imaging (DTI) and door-to-needle (DTN) time in line with international recommendations.
CONCLUSIONS: Our data reflects that COVID-19 SOPs did not deter successful delivery of hyperacute stroke services in our center. However, bigger and multi center studies are required to support our findings.
Fulltext Call to Action: SARS-CoV-2 and CerebrovAscular DisordErs (CASCADE)

Abootalebi S, Aertker BM, Andalibi MS, Asdaghi N, Aykac O, Azarpazhooh MR, et al.

J Stroke Cerebrovasc Dis, 2020 Sep;29(9):104938.
PMID: 32807412 DOI: 10.1016/j.jstrokecerebrovasdis.2020.104938

BACKGROUND AND PURPOSE: The novel severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), now named coronavirus disease 2019 (COVID-19), may change the risk of stroke through an enhanced systemic inflammatory response, hypercoagulable state, and endothelial damage in the cerebrovascular system. Moreover, due to the current pandemic, some countries have prioritized health resources towards COVID-19 management, making it more challenging to appropriately care for other potentially disabling and fatal diseases such as stroke. The aim of this study is to identify and describe changes in stroke epidemiological trends before, during, and after the COVID-19 pandemic.
METHODS: This is an international, multicenter, hospital-based study on stroke incidence and outcomes during the COVID-19 pandemic. We will describe patterns in stroke management, stroke hospitalization rate, and stroke severity, subtype (ischemic/hemorrhagic), and outcomes (including in-hospital mortality) in 2020 during COVID-19 pandemic, comparing them with the corresponding data from 2018 and 2019, and subsequently 2021. We will also use an interrupted time series (ITS) analysis to assess the change in stroke hospitalization rates before, during, and after COVID-19, in each participating center.
CONCLUSION: The proposed study will potentially enable us to better understand the changes in stroke care protocols, differential hospitalization rate, and severity of stroke, as it pertains to the COVID-19 pandemic. Ultimately, this will help guide clinical-based policies surrounding COVID-19 and other similar global pandemics to ensure that management of cerebrovascular comorbidity is appropriately prioritized during the global crisis. It will also guide public health guidelines for at-risk populations to reduce risks of complications from such comorbidities.
Empirical gas emission and oxidation measurement at cover soil of dumping site: example from Malaysia

Abushammala MF, Basri NE, Basri H, Kadhum AA, El-Shafie AH

Environ Monit Assess, 2013 Jun;185(6):4919-32.
PMID: 23054277 DOI: 10.1007/s10661-012-2913-5

Methane (CH₄) is one of the most relevant greenhouse gases and it has a global warming potential 25 times greater than that of carbon dioxide (CO₂), risking human health and the environment. Microbial CH₄ oxidation in landfill cover soils may constitute a means of controlling CH₄ emissions. The study was intended to quantify CH₄ and CO₂ emissions rates at the Sungai Sedu open dumping landfill during the dry season, characterize their spatial and temporal variations, and measure the CH₄ oxidation associated with the landfill cover soil using a homemade static flux chamber. Concentrations of the gases were analyzed by a Micro-GC CP-4900. Two methods, kriging values and inverse distance weighting (IDW), were found almost identical. The findings of the proposed method show that the ratio of CH₄ to CO₂ emissions was 25.4 %, indicating higher CO₂ emissions than CH₄ emissions. Also, the average CH₄ oxidation in the landfill cover soil was 52.5 %. The CH₄ and CO₂ emissions did not show fixed-pattern temporal variation based on daytime measurements. Statistically, a negative relationship was found between CH₄ emissions and oxidation (R(2) = 0.46). It can be concluded that the variation in the CH₄ oxidation was mainly attributed to the properties of the landfill cover soil.
Regional landfills methane emission inventory in Malaysia

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.
Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization

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.
Fulltext Hydrological Analysis of Batu Dam, Malaysia in the Urban Area: Flood and Failure Analysis Preparing for Climate Change

Allias Omar SM, Wan Ariffin WNH, Mohd Sidek L, Basri H, Moh Khambali MH, Ahmed AN

Int J Environ Res Public Health, 2022 Dec 09;19(24).
PMID: 36554413 DOI: 10.3390/ijerph192416530

Extensive hydrological analysis is carried out to estimate floods for the Batu Dam, a hydropower dam located in the urban area upstream of Kuala Lumpur, Malaysia. The study demonstrates the operational state and reliability of the dam structure based on hydrologic assessment of the dam. The surrounding area is affected by heavy rainfall and climate change every year, which increases the probability of flooding and threatens a dense population downstream of the dam. This study evaluates the adequacy of dam spillways by considering the latest Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) values of the concerned dams. In this study, the PMP estimations are applied using comparison of both statistical method by Hershfield and National Hydraulic Research Institute of Malaysia (NAHRIM) Envelope Curve as input for PMF establishments. Since the PMF is derived from the PMP values, the highest design flood standard can be applied to any dam, ensuring inflow into the reservoirs and limiting the risk of dam structural failure. Hydrologic modeling using HEC-HMS provides PMF values for the Batu dam. Based on the results, Batu Dam is found to have 200.6 m3/s spillway discharge capacities. Under PMF conditions, the Batu dam will not face overtopping since the peak outflow of the reservoir level is still below the crest level of the dam.
Solid waste bin level detection using gray level co-occurrence matrix feature extraction approach

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.
Integrated technologies for solid waste bin monitoring system

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.
In Vitro Blood-Brain Barrier Models for Neuroinfectious Diseases: A Narrative Review

Badawi AH, Mohamad NA, Stanslas J, Kirby BP, Neela VK, Ramasamy R, et al.

Curr Neuropharmacol, 2023 Dec 08.
PMID: 38073104 DOI: 10.2174/1570159X22666231207114346

The blood-brain barrier (BBB) is a complex, dynamic, and adaptable barrier between the peripheral blood system and the central nervous system. While this barrier protects the brain and spinal cord from inflammation and infection, it prevents most drugs from reaching the brain tissue. With the expanding interest in the pathophysiology of BBB, the development of in vitro BBB models has dramatically evolved. However, due to the lack of a standard model, a range of experimental protocols, BBB-phenotype markers, and permeability flux markers was utilized to construct in vitro BBB models. Several neuroinfectious diseases are associated with BBB dysfunction. To conduct neuroinfectious disease research effectively, there stems a need to design representative in vitro human BBB models that mimic the BBB's functional and molecular properties. The highest necessity is for an in vitro standardised BBB model that accurately represents all the complexities of an intact brain barrier. Thus, this in-depth review aims to describe the optimization and validation parameters for building BBB models and to discuss previous research on neuroinfectious diseases that have utilized in vitro BBB models. The findings in this review may serve as a basis for more efficient optimisation, validation, and maintenance of a structurally- and functionally intact BBB model, particularly for future studies on neuroinfectious diseases.
Fulltext Factors influencing consumers’ preferences towards meat and meat products with traceability systems in Malaysia

Basri, H. N., Kamarulzaman, N. H., Shamsudin, M. N., Nolila Mohd Nawi

International Food Research Journal, 2018;25(102):157-164.
MyJurnal

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.
Fulltext Guillain-Barré syndrome complicating dengue fever: Two case reports

Boo YL, Aris MAM, Chin PW, Sulaiman WAW, Basri H, Hoo FK

Ci Ji Yi Xue Za Zhi, 2015 11 17;28(4):157-159.
PMID: 28757747 DOI: 10.1016/j.tcmj.2015.09.007

Guillain-Barré syndrome is a rare neurological manifestation associated with dengue infection. More common antecedent infections include Campylobacter jejuni and Cytomegalovirus infection. Here, we report two cases of Guillain-Barré syndrome complicating dengue infection.
Fulltext Effect of Edible Bird's Nest Extract on Lipopolysaccharide-Induced Impairment of Learning and Memory in Wistar Rats

Careena S, Sani D, Tan SN, Lim CW, Hassan S, Norhafizah M, et al.

Evid Based Complement Alternat Med, 2018;2018:9318789.
PMID: 30186358 DOI: 10.1155/2018/9318789

Cognitive disability is a common feature associated with a variety of neurological conditions including Alzheimer's Disease (AD), Parkinson's Disease (PD), brain injury, and stroke. Emerging evidence has demonstrated that neuroinflammation plays an important role in the development of cognitive impairment. Current available therapies are relatively ineffective in treating or preventing cognitive disabilities, thus representing an important, unfulfilled medical need. Hence, developing potential treatment is one of the major areas of research interest. Edible bird's nests (EBN) are nests formed by swiftlet's saliva containing sialic acid, which is believed to improve brain function. This present study was embarked upon to evaluate the learning and memory enhancing potential effect of EBN by using Morris water maze test in a Wistar rat model of LPS-induced neuroinflammation. LPS elicited cognitive impairment in the rats by significantly increasing the escape latency while decreasing the number of entries in the probe trial, which are coupled with increased production of proinflammatory cytokines (TNF-α, IL-1β, and IL-6) and oxidative markers (ROS and TBARS) in the hippocampus. Treatment with EBN (125 mg/kg, 250 mg/kg, and 500 mg/kg; p.o.) effectively reversed the effect of LPS on escape latency and probe trial and, in addition, inhibited the LPS-induced upregulation of proinflammatory cytokines and oxidative markers. These findings are suggestive that there is existence of neuroprotective effect contained inside the edible bird's nest.
Fulltext Effects of a Multi-Component Training Program on Healthy Older Adults' Prospective Memory Performance: Assessing Change Over Time

Farzin A, Ibrahim R, Madon Z, Basri H, Farzin S, Motalebizadeh A

Front Public Health, 2021;9:594953.
PMID: 33968872 DOI: 10.3389/fpubh.2021.594953

Prospective Memory (PM) is a cognitive function affected by aging. PM is the memory of future intentions and is significantly involved in everyday life, especially among older adults. Nevertheless, there are a few studies focused on PM training among healthy older adults and these studies did not report the optimal duration of training regarding improving PM performance among older adults. The present study aimed to determine the effective duration for training PM performance among healthy older adults. The current study was a randomized, controlled, single-blind, within-participants crossover trial including a training program with a duration of 12 h. The sample of 25 older adults aged 55 to 74 years recruited from the active members of the University of the Third Age (U3A), Kuala Lumpur/Selangor, their family members, and friends. The study design ensured some participants would receive the training after baseline while others would wait for 6 weeks after the baseline before receiving the training. All participants were evaluated five times: at baseline, 6, 12, 16, and at 24 weeks post-baseline. Moreover, the training program ensured all participants were assessed after each training session. The minimum number of hours to achieve training effects for this multi-component training program was eight. Results supported the efficacy of the training program in improving PM performance among healthy older adults. Also, the optimal duration for the multicomponent training program on PM performance among healthy older adults was obtained. This trial is registered at isrctn.com (#ISRCTN57600070).
The Efficiency of a Multicomponent Training for Prospective Memory Among Healthy Older Adults: A Single-Blind, Randomized Controlled Within-Participants Cross-Over Trial

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.
Fulltext Challenges faced and lessons learned A multi-component prospective memory training program for Malaysian older adults

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.
Religious coping and psychological well-being among Iranian stroke caregivers

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
Feature extraction using Hough transform for solid waste bin level detection and classification

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.
An automated solid waste bin level detection system using a gray level aura matrix

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.
Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system

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.
Content-based image retrieval system for solid waste bin level detection and performance evaluation

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.

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