In-Depth Chemical Analysis of Particulate Matter
Emitted by Agarwood:
Study of Environmental Impact

Kaleri, Arif Hussain; Dai, Hao; Song, Xiqiang; Mehmood, Adeel; Nawaz, Saqib Ali; Kaleri, Ghulam Sajjad; Nizamani, Mir Muhammad; Khokhar, Aamir Ali; Bhatti, Mughair Aslam; Kaleri, Abdul Rasheed

doi:10.15244/pjoes/138207

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Thus, as with the prior approach, limited dependability is predicted since it is based on the human nose, which cannot sustain many samples due to quick exhaustion [5], [6], [9], [10]. This technique is also performed based on the human's health and at the end of the day, it will affect the human's health due the hazardous work by smelling the essential oil continuously in a large number of samples [7], [9], [10], [28]. Kaleri et al [28], researchers concluded that the natural agarwood tree's smoke is damaging the health and artificial agarwood tree's smoke can cause poisonous damage to the health.…”

Section: Grading Techniques Of Essential Oilmentioning

confidence: 99%

“…This technique is also performed based on the human's health and at the end of the day, it will affect the human's health due the hazardous work by smelling the essential oil continuously in a large number of samples [7], [9], [10], [28]. Kaleri et al [28], researchers concluded that the natural agarwood tree's smoke is damaging the health and artificial agarwood tree's smoke can cause poisonous damage to the health. The traditional technique of grading essential oil based on its resin content [4].…”

Section: Grading Techniques Of Essential Oilmentioning

confidence: 99%

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Preliminary study on agarwood essential oil and its classification techniques using machine learning

Al-Hadi

Amidon²,

Huzir³

et al. 2023

IJEECS

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Using essential oils derived from trees for pharmaceutical purposes, incense, aromatherapy, and other areas has expanded its popularity on the international market. However, since human sensory evaluation is still the primary technique used to grade essential oils in Malaysia, the classification technique for determining their grade is still below standard. Nonetheless, prior studies established new approaches for classifying the grade of essential oils by studying their chemical compounds. Therefore, agarwood essential oil was selected for the suggested model due to the increasing demand and the high cost of the world's natural raw materials. The support vector machine (SVM) using one versus all (OVA) approach was selected as the classifier for agarwood essential oil. This study provides an overview of essential oils and their prior research techniques. In addition, a review of SVM is conducted to demonstrate that the technique is appropriate for future studies.

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Section: Grading Techniques Of Essential Oilmentioning

confidence: 99%

Section: Grading Techniques Of Essential Oilmentioning

confidence: 99%

Preliminary study on agarwood essential oil and its classification techniques using machine learning

Al-Hadi

Amidon²,

Huzir³

et al. 2023

IJEECS

View full text Add to dashboard Cite

show abstract

Spatial Predictive Modeling of the Burning of Sugarcane Plots in Northeast Thailand with Selection of Factor Sets Using a GWR Model and Machine Learning Based on an ANN-CA

2022

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The main purpose of the study is to apply symmetry principles to general mathematical modelling based on multi-criteria decision making (MCDM) approach for use in development in conjunction with geographic weighted regression (GWR) model and optimize the artificial neural network-cellular automaton (ANN-CA) model for forecasting the sugarcane plot burning area of Northeast Thailand. First, to calculate the service area boundaries of sugarcane transport that caused the burning of sugarcane with a fire radiative power (FRP) values using spatial correlation analysis approach. Second, the analysis of the spatial factors influencing sugarcane burning. The study uses the approach of symmetry in the design of algorithm for finding the optimal service boundary distance (called as cut-off) in the analysis of hot-spot clustering and uses calculations with the geographic information system (GIS) approach, and the final stage is the use of screened independent variable factors to predict the plots of burned sugarcane in 2031. The results showed that the positively related factors for the percentage of cane plot sintering in the sub-area units of each sugar plant's service were the distance to transport sugarcane plots index and percentage of sugarcane plantations in service areas, while the negative coefficients were FRP differences and density of sugarcane yield factors, according to the analysis with a total of seven spatial variables. The best GWR models display local R2 values at levels of 0.902 to 0.961 in the service zones of Khonburi and Saikaw. An influential set of independent variables can increase the accuracy of the ANN-CA model in forecasting with kappa statistical estimates in the range of 0.81 to 0.85 The results of the study can be applied to other regions of Thailand, including countries with similar sugarcane harvesting industries, to formulate policies to reduce the exposure of sugarcane harvested by burning methods and to support the transportation of sugarcane within the appropriate scope of service so that particulate matter less than 2.5 microns () can be reduced.

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Agarwood as incense- a review: Part II- Therapeutic uses and health effects

Jayaraj,

Ahmed,

Hazarika

2024

J. Non-Timber Forest Prod.

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Agarwood is a resinous heartwood of various species of Thymelaeaceae and, one of its common use is incense, wherein the resin-loaded chips and compressed dust are burnt over heated charcoal or glowing embers to release the smoke. The effect of this smoke on human health is discussed in the review. While the smoke has been found to benefit neurological issues, it has been found detrimental to the pulmonary and cardiovascular system, besides being carcinogenic. There is a need for study to mitigate the ill effects while harnessing the therapeutic benefits of agarwood incense.

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In-Depth Chemical Analysis of Particulate Matter Emitted by Agarwood: Study of Environmental Impact

Cited by 3 publications

References 8 publications

Preliminary study on agarwood essential oil and its classification techniques using machine learning

Preliminary study on agarwood essential oil and its classification techniques using machine learning

Spatial Predictive Modeling of the Burning of Sugarcane Plots in Northeast Thailand with Selection of Factor Sets Using a GWR Model and Machine Learning Based on an ANN-CA

Agarwood as incense- a review: Part II- Therapeutic uses and health effects

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