This research was done to study the effect of methods of making containers by hot air oven (H) and a hot press machine (C) and the ratio of banana stem fiber to binder on the properties of containers made from banana sheath fibers. The ratios between the dried banana sheath powder and the binder (banana starch solution 7.5%) were 60:40, 70:30, 80:20, and 90:10, respectively. It was found that method C had shown low amounts of oil and water absorption and a high resistance to deformation, which was due to compression and penetration. In terms of compression and penetration forces, no significant differences were found for the ratios of 80:20 and 90:10. However, the ratio of 90:10 showed lower fat and water absorption when compared to other ratios. Therefore, the ratio of 90:10 between the banana sheath fiber and the binder and the method C were found to be the best ratio to use when making containers, which are suitable to be applied for further use.
Precision agriculture is a concept of agricultural management, based on analyzing, measuring, and reacting to inter and intra-field variability in crops. One of the tools deployed for crop monitoring in precision agriculture is the use of an unmanned aerial vehicle, able to obtain high flexibility with fewer restrictions, and high spatial and spectral resolution in comparison to airborne and spaceborne system. In this paper, the assessment of various vegetation indices were performed for paddy stress monitoring using red edge band from multispectral imagery. The objective of the study was to create rice field maps with the use of aerial imagery and object-based image analysis technique to validate vegetative indices in rice field maps by using soil plant analysis development (SPAD) data. The result showed Normalized Difference Vegetation Index (R=0.957), Normalized Difference Red Edge (NDRE) (R=0.974), Soil Adjusted Vegetation Index (R=0.964), and Optimized Soil Adjusted Vegetation Index (R=0.966), all of which provided positive linear correlations with SPAD readings. NDRE showed higher correlation compared with other vegetation indices, exhibiting a better measure ment for farmers to make decisions. This paper has demonstrated how aerial imagery can be used to collect an accurate mapping in real time that can be analyzed to monitor conditions of crop and chlorophyll content by using SPAD to enable farmers to make informed decisions. Further investigations need to be carried out by validating the real chlorophyll content to improve existing correlations.
Multispectral imagery, object-based analysis, red edge band, vegetation index
This paper presents parameters analysis for the estimated modal damping ratio using a new version of the automated enhanced frequency domain decomposition (AEFDD). The purpose of this study is to provide a better choice of a maximum number of points of time segments and modal assurance criterion (MAC) index number regarding to the variable level of system damping (low and high damped structure) and degree of freedom of the system. According current literature, frequency domain (FD) methods seem to have the problem with providing a correct identification of the modal damping ratio, since the correct estimate of modal damping is still an open problem and often leads to biased estimates. This technique is capable of providing consistent modal parameters estimation, particularly for modal frequencies and mode shapes. As a necessary fundamental condition, the algorithm has been assessed first from computed numerical responses according to random white noise, acting on different shear-type frame structures and corrupted with noise. Results indicate that reducing the value of natural frequencies and modal damping ratios of the modes under analysis demands longer time segments and a high value of the maximum number of points for adequate information on the decaying correlation functions when computing a modal damping ratio. In addition, the results also prove that the MAC index does not significantly affect the results for the low damped system. However, the use of a high MAC index value for the high damped system significantly introduces large error bound and it becomes worse, particularly for the higher modes, as the standard deviation of percentage error increases gradually. Furthermore, the use of a MAC index for a high number of points of time segments significantly increases the standard deviation of the percentage error.
Automated OMA, automatization, frequency domain decomposition, operational modal analysis
One potential land in marginal areas able to be utilized for keeping the sustainability of agriculture in Indonesia is coastal areas. However it requires optimum treatment, especially in using the water for plants efficiently due to the factors of land characteristics and climate. This paper describes the use of simple and low-cost soil moisture probe for sandy land in the coastal area. The probe is a parallel plate which separated at a certain distance. The principle is based on soil electrical conductivity, which delivers the electrical current from one plate to another. Two designs (single and double) and two distances (3 mm and 5 mm) of probes were tested to measure the sandy soil at the moisture content of 0%, 5%, 10%, 15%, 20%, 25%, 30%, 35% and 40%. It was found that the resistance of probes was inversely proportional to water content, but not linear. The best fit of probe resistance (X) to the moisture of sandy soil (Y) was of the 5 mm double parallel probe, with the equation Y = -10.33 ln(X) + 128.13 (R2 is 0.9199) and non-linearity of 62.88%. The probes and a built soil moisture logger/ controller were applied for sandy soil of Shallot cultivation land at coastal area in Empurancak Beach, Jepara (located about 150 m from the foreshore).
Voice pathology analysis has been one of the useful tools in the diagnosis of the pathological voice, as the method is non-invasive, inexpensive, and can reduce the time required for the analysis. This paper investigates feature extraction based on the Dual-Tree Complex Wavelet Packet Transform (DT-CWPT) using energy and entropy measures tested with two classifiers, k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM). Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database and Saarbruecken Voice Database (SVD) were used. Five datasets of voice samples were used from these databases, including normal and abnormal samples, Cysts, Vocal Nodules, Polyp, and Paralysis vocal fold. To the best of the authors knowledge, very few studies were done on multiclass classifications using specific pathology database. File-based and frame-based investigation for two-class and multiclass were considered. In the two-class analysis using the DT-CWPT with entropies, the classification accuracy of 100% and 99.94% was achieved for MEEI and SVD database respectively. Meanwhile, the classification accuracy for multiclass analysis comprised of 99.48% for the MEEI database and 99.65% for SVD database. The experimental results using the proposed features provided promising accuracy to detect the presence of diseases in vocal fold.
Malaysia is the worlds third largest exporter of liquified natural gas and the second largest oil and natural gas producer in Southeast Asia, following Indonesia. The potential air pollutants released from the industry may affect the health of the population. The primary objective of this study was to determine the potential health risk among the population in the zone of impact. This was a comparative case study between controlled and uncontrolled emissions based on the air dispersion modelling. Hazard quotient (HQ) was used to assess non-carcinogenic risk, while lifetime cancer risk (LCR) was used to assess carcinogenic risk. All ambient air pollutant levels were within permissible levels and adhered to the standard. The HQ for hydrogen sulphide and benzene was less than one in all scenarios. The LCR for benzene was acceptable in all scenarios. Advanced pollution prevention equipment should be installed within the gas emission system to treat the final emission to meet prescribed permissible limits. Continuous ambient air monitoring and effective control measures should be practiced to ensure the sustainability of clean air. The health risk assessment showed no risk of developing malignancy and non-cancer disorder among the workers and general population living surround the petrochemical plants. This allows the development of the petroleum refinery plants to be continued.
Air modeling, health risk assessment, oil refinery, petrochemical plants, pollutants
Monitoring of land use change is crucial for sustainable resource management and development planning. Up-to-date land use change information is important to understand its pattern and identify the drivers. Remote sensing and geographic information system (GIS) have proven as a useful tool to measure and analyze land use changes. Recent advances in remote sensing technology with digital image processing provide unprecedented possibilities for detecting changes in land use over large areas, with less costs and processing time. Thus, the objective of this study was to assess the land use changes in upper Prek Thnot watershed in Cambodia from 2006 until 2018. Geospatial tools such as remote sensing and GIS were used to process and produce land use maps from Landsat 5 TM, Landsat 7 ETM+ and Landsat 8. The post-classification comparison was conducted for analysing the land use changes. Results show forest area was greatly decreased by 1,162.06 km2 (33.67%) which was converted to rubber plantation (10.55 km2), wood shrub (37.65 km2), agricultural land (1,099.71 km2), built-up area (17.76 km2), barren land (3.65 km2), and water body (14.69 km2). Agricultural land increased by 1,258.99 km2 (36.48%), while wood shrub declined by 161.88 km2 (4.69%). Rubber plantation, built-up area, barren land, and water bodies were increased by 10.55 km2 (0.31%), 33.64 km2 (0.97%), 4.87 km2 (0.14%) and 15.89 km2 (0.46%), respectively. The decrease of forest and wood shrub had resulted due to population growth (1.8% from 2008 to 2019) and land conversion for agricultural purposes. Hence, this study may provide vital information for wise sustainable watersheds land management, especially for further study on the effect of land use change on runoff in this area.
Cambodia, land use change, Prek Thnot watershed, remote sensing-GIS, sustainable management
Increased disposal of heavy metals, including lead (II) (Pb(II)) into the environment calls for a reliable and sustainable solution. In this study, nano-sized biochar from sago activated sludge was proposed for the removal of Pb(II). Sago activated sludge was pyrolysed in a tube furnace followed by a chemical activation to yield nano-sized particles ranging from 45 to 75 nm. The nano-sized biochar obtained was characterised and the influence of pH (2 − 10), initial Pb(II) concentration (1 − 5 mg/L), contact time (30 − 90 mins) and adsorbent dosage (0.1 − 0.5 g) was investigated in a batch adsorption study. Response surface methodology (RSM) approach with central composite design (CCD) was used as statistical tools to optimize the adsorption process by relating the mutual interactions among all studied variables. Characterisation of the prepared adsorbent showed that large surface area was observed on sludge activated carbon (78.863 m2/g) compared with sludge biochar (8.044 m2/g) and sludge biomass (1.303 m2/g). The batch adsorption best fitted the Langmuir isotherm (maximum adsorption capacity, Q0 = 3.202 × 10-3 mg/g, R-squared value = 0.9308). The RSM indicated that the optimum Pb(II) removal (99.87%) was at 0.5 g of adsorbent, 5 mg/L initial concentration and 30 min contact time. This study is significant because utilisation of sago effluent will reduce sago manufacturing waste by conversion into a value-added product as adsorbent to adsorb Pb(II) in wastewater.
Beranang, one of the rural areas of Selangor which still depends on the groundwater as a secondary source of water for drinking and other purposes apart from treated water. The main objective of this study was to evaluate the health risk assessment of arsenic ingestion through groundwater consumption among Beranang residents in Selangor. Five houses with a functioning electrical pump-assisted tube well were chosen for the sampling, which occurred in February 2019. The groundwater samples were taken at each sampling point and stored at room temperature during transport to the laboratory within 24 hours. The groundwater samples were analyzed using the ICP-MS method. Both hazard quotient (HQ) and lifetime cancer risk (LCR) were calculated based on the formula provided by the US EPA (United States Environment Protection Agency). Arsenic concentration in the groundwater samples was higher than the WHO Drinking Guideline and Malaysia Raw Water Standard in all houses. The mean concentration was 46.90 μg/L with maximum and minimum concentrations of 54.40 μg/L and 23.70 μg/L, respectively. The concentration was approximately 2- to 6- fold in all houses with 100% prevalence of contaminated tube wells. The health risk degree of children was higher than that of adults on the whole, indicating that children suffer much higher risks than adults. The health risk degree through oral exposure was higher than dermal exposure. Despite the fact that the groundwater is not suitable for drinking, however, there is no health risk through dermal exposure.
Arsenic, groundwater, hazard quotient, health risk assessment, lifetime cancer risk
In this paper work, three-dimensional terrain models were reconstructed from two-dimensional contour lines. Firstly, spatial curves were generated from contour lines using parameterized cubic B-spline curve interpolation. Then surfaces were constructed by using B-spline ruled surface. In the reconstruction process, some issues such as keyholes and branching may arise. Therefore, we propose a method that handles the branching object to construct a bilinear patch by following the proposed data points extraction algorithm. We also solved keyholes issues by retaining the same knot vector condition on B-spline ruled surface. Results are also demonstrated for models with branching and without branching.
This paper focuses on the construction of two-point and three-point implicit block methods for solving general second order Initial Value Problems. The proposed methods are formulated using Hermite Interpolating Polynomial. The block methods approximate the numerical solutions at more than one point at a time directly without reducing the equation into the first order system of ordinary differential equations. In the derivation of the method, the higher derivative of the problem is incorporated into the formula to enhance the efficiency of the proposed methods. The order and zero-stability of the methods are also presented. Numerical results presented show the efficiency of these methods compared to the existing block methods.
Block methods, extra derivative, second order IVPs
Analyzing commodity prices contributes greatly to traders, economists and analysts in ascertaining the most feasible investment strategies. Limited knowledge about the price trend of the commodities indeed will affect the economy because commodities like palm oil and gold contribute a huge source of income to Malaysia. Therefore, it is important to know the optimal price trend of the commodities before making any investments. Hence, this paper presents a logic mining technique to study the price trend of palm oil with other commodities. This technique employs 2-Satisfiability based Reverse Analysis Method (2-SATRA) consolidated with 2-Satisfiability logic in Discrete Hopfield Neural Network (DHNN2-SAT). All attributes in the data set are represented as a neuron in DHNN which will be programmed based on a 2-SAT logical rule. By utilizing 2-SATRA in DHNN2-SAT, the induced logic is generated from the commodity price data set that explains the trend of commodities price. Following that, the performance evaluation metric; error analysis and accuracy will be calculated based on the induced logic. In this case, the experimental result has shown that the best-induced logic identifies which trend will lead to an increase in the palm oil price with the highest accuracy rate.
Artificial neural networks (ANNs) are actively utilized by researchers due to their extensive capability during the training process of the networks. The intricate training stages of many ANNs provide a powerful mechanism in solving various optimization or classification tasks. The integration of an ANN with a robust training algorithm is the supreme model to outperform the existing framework. Therefore, this work presented the inclusion of three satisfiability Boolean logic in the Hopfield neural network (HNN) with a sturdy evolutionary algorithm inspired by the Imperialist Competitive Algorithm (ICA). In general, ICA stands out from other metaheuristics as it is inspired by the policy of extending the power and rule of a government/country beyond its own borders. Existing models that incorporate standalone HNN are projected as non-versatile frameworks as it fundamentally employs random search in its training stage. The main purpose of this work was to conduct a comprehensive comparison of the proposed model by using two real data sets with an elementary HNN with exhaustive search (ES) versus a HNN with a standard evolutionary algorithm, namely- the genetic algorithm (GA). The performance evaluation of the proposed model was analyzed by computing plausible errors, such as root mean square error (RMSE), mean absolute error (MAE), global minima ratio (Rm), computational time (CT) and accuracy (Q). The computational simulations were carried out by operating the different numbers of neurons in order to validate the efficiency of the proposed model in the training stage. Based on the simulations, the proposed model was found to execute the best performance in terms of attaining small errors and efficient computational time compared to other existing models.
Weather variability poses threats to rural crop producers in Tanzania. This research aimed to find the impact of weather variation on the growth stage and yield of rice in Tanzania. The analyses were done using rice yield data and weather variables from 1981-2017. The approaches used were; decomposing rice yields into yield tendency and yield weather, stepwise integral regression for identification of significant yield model, and applied Fishers meteorological regression and Chebyshev polynomial function to compute coefficients for weather factors. From the results, other than the non-natural factors, rainfall, maximum and minimum temperature, and sunshine significantly affect rice yield from sowing to harvest stage. The effect of rainfall, sunshine, maximum and minimum temperature coefficients on the rice yield differ by growth stage. An increase of 1 millimeter of rainfall at the sowing-seedling stage increased rice yield by 2.7 kg/ha. In the sowing-seedling stage, the temperature had a stronger positive influence on the rice yield as with every 1°C in average maximum temperature increased the rice yield by 674.1 kg/ha. The minimum temperature coefficient had stronger influences in the vegetative, tillering-booting stages, thus, with 1°C increase in average minimum temperature, the rice yield increased by 70.1 kg/ha and 420.7 kg/ ha respectively. In the flowering-grain formation stage, the maximum temperature had a greater influence on rice yield, that is, as 1°C increased, the rice yielded increased by 674.7 kg/ha. The sunshine duration had a higher influence on the harvesting stage. Increased 1-hour duration of sunshine increased rice yield by 495.95 kg/ha. Finally, a meteorological rice model, which could be used for rice yield forecasting in the region, was developed.
Meteorological factors, natural and non-natural factors, rice, weather, yield
Hydrological models are reliable tools that have been extensively used for hydrological studies. However, the complexity of some of these models has been a major setback, which affects their performance. This study compared Hydrologic Engineering Corps Hydrologic Modeling System (HEC-HMS) with most widely applied Soil Water Assessment Tool (ArcSWAT) model and used to assess impacts of climate change on streamflow at Bernam Basin, Malaysia for 2010-2039, 2040-2069 and 2070-2099 to the baseline period (1976- 2005) using an ensemble of ten GCMs under three RCP scenarios (RCPs 4.5, 6.0 and 8.5). The models performed satisfactorily. However, HEC-HMS performed better compared to ArcSWAT with 0.74, 0.71, 4.21 and 0.37; and 0.71, 0.69, 5.32 and 0.31 for R2, NSE, PBIAS and RSR, respectively, during the calibration and validation periods. Future periods suggest a decreasing pattern in streamflow, with a higher percentage (−5.94%) expected for the RCP 8.5 scenario in the late century (2080s) during dry season period. In the wet season, streamflow decreases in all future periods except for RCP4.5 where it is expected to increase (0.36%). Therefore, the Basin may likely experience tremendous pressure in the late century due to low streamflow, particularly in dry season months.
ArcSWAT, climate change, flow regime, HEC-HMS, hydrological model
In the course of recent decades, cloud computing has turned into a hot research point for the logical, scholastic and mechanical networks. It is a wide-ranging term used to depict an extra class of framework-based enrolling that occurs over the web. The distributed computing principally plans to give capable access to remote and geologically disseminated assets. The other important purpose of cloud service providers is to gain maximum profit and use resources efficiently. As cloud technology is evolving day by day and confronts numerous challenges, one of them being uncovered is scheduling. Scheduling refers to a set of policies to control the order of work to be performed by a system. Every task needs a scheduling strategy which is assigned by the system in order to get executed by the processor. Procedures are vigorous to plan the trades for accomplishment. Job scheduling procedures supposed to be the most assumed difficulties in the cloud computing domain. The survey of existing papers reveals the better makespan time but cannot guarantee the proper balancing of load. To overcome this issue, Enhanced Multi-Objective Load balancing Scheduling Algorithm (EMOLB_LB) is proposed which uses Bee Colony Optimization algorithm for the analysis and balancing of load with more objective functions to sort the tasks and improvise the performance in terms of cost and time. The existing scheduling technique, Enhanced Multi-Objective Scheduling Algorithm (EMOSA) uses only non-dominating strategy for sorting the tasks but load management is not taken into consideration which is further optimized by proposing EMOLB_LB technique. The experimental results were analysed and compared with various existing techniques like Multi Objective Scheduling algorithm (MOSA), EMOSA and showed that the EMOLBA_LB technique was better than the earlier techniques in term of each performance attribute like average waiting time by 2.934%, processing cost by 17.6% and processing time by 20.5%.
For reliable data transmission, 802.11ax standard employs various orders of modulation schemes with a forward error correction method performing different coding rates (CR). Higher-order modulation schemes can enhance the data rate, but at the same time increasing the possibility of data corruption and bit error occurrence. Moreover, in wireless communications, each modulation scheme can be used with different guard intervals and channel bandwidths. A shorter guard interval increases the data rate at the cost of increasing the interferences and data loss. A longer guard interval solves the issue but at the cost of the performance reduction due to wasting the useful bandwidth. With regards to channel bandwidth, although wider channels increase the data rate, they are subject to more signal interference. This can get even worse in the high-density deployment of 802.11ax where many users are placed in close distance and the signal interferences are strong. Thus, aside from the modulation orders and coding rates parameters, the efficiency of modulation schemes relies on the channel bandwidth and guard interval which demands the proper selection of these parameters. Consequently, this work proposes a simulation model to optimize the performance of the 802.11ax network regarding the modulation schemes under high-density conditions. The model includes all available modulation schemes and their corresponding coding rates along with the channel bandwidth and guard interval. The model is further implemented and the most efficient values for performance optimization are determined on the basis of bit error rate, throughput and its efficiency, end-to-end delay, loss ratio, and jitter.
Ketoconazole is one of high-dose treatment drugs with flowability issue so that it is commonly formulated using wet granulation technique. However, the technique impacts stability of ketoconazole which it changes in color upon solvent usage. This research was conducted to study tablet quality of ketoconazole as function of certain excipients in dry granulation technique. Combination of spray dried lactose (SDL) and Avicel® PH-102 as filler-binder excipients and sodium starch glycolate (SSG) as a disintegration agent were used for the purpose. Ketoconazole tablets were formulated based on 22 factorial design. Evaluation was performed on tablet properties, then statistically analyzed using Minitab® software. Tablet hardness and disintegration time increased in increasing level of filler combination and SSG concentration, but a decrease was observed for friability and % dissolved ketoconazole. Both filler combination and disintegration agent exhibited insignificant effect toward tablet properties evaluated. According to overlay contour plot, it is predicted that the optimum formulation of ketoconazole tablet can be set into SDL-Avicel® PH-102 ratio of at least 3:1 or higher and SSG concentration is higher than 3.5%.
Chewing Khat is considered as a major deep-rooted sociocultural habit in Yemen. This custom has been causing various health problems. Using Doppler ultrasonography, this study assessed the changes that occurred in bilateral carotid arteries flow velocities and Doppler indices in Yemenis who regularly chewed Khat for years. Convenient sampling was conducted from August 2017 to August 2018 for 384 participants of whom 179 were excluded and the sample size became 205 participants including 108 (52.7%) Khat chewers and 97 (47.3%) non-Khat chewers. The mean age of the sample was 28.29 ± 7.0 years. In all cases, the carotid Doppler ultrasound scanning protocol, based on the standards of American Institute of Ultrasound in Medicine, was performed to measure carotid Doppler velocities and indices, in addition to internal carotid flow volume. The Khat chewing information of participants was obtained by a standardized questionnaire, and SPSS was used for result analysis. There were differences in systolic velocities between Khat chewers and non-chewers with lower values for the chewers, and they were significant in the right common carotid artery and in the internal carotid artery. The carotid Doppler indices, except the right internal carotid artery, were significantly decreased, and the Right internal carotid artery blood flow volume was significantly increased among Khat chewers compared to that of non-chewers. Moreover among Khat chewers, Doppler indices and most of the peak systolic velocities had a significantly negative correlation with the Khat chewing period. Therefore, this study may provide an interpretation of the high prevalence of hemorrhagic stroke among Yemeni population in their middle age, and suggest the mechanism that may cause this type of stroke. More studies are recommended to confirm this finding using the transcranial Doppler technique.
Graphene oxide (GO) is a reliable additive used to improve the wax crystal inhibition performance of pour point depressant (PPD). In understanding the lateral size effect on wax crystal inhibition, PPD emulsions containing graphene oxide of different lateral sizes were prepared. The parameters of pour point reduction (PPR) and dissipated wax crystallisation enthalpy were considered in the assessment of wax inhibition performance. PPR was measured using a pour point tester in accordance to ASTM D-97, while the enthalpy dissipation was evaluated via differential scanning calorimetry (DSC) under cooling cycle. The study revealed that the addition of GO lowered the wax crystallisation enthalpy, as indicated by the lesser amount of precipitated wax present in the model oil. The enthalpy underwent a decrease from 25.04 to 23.97 Jg-1 with decreasing GO lateral size. It is evident from the pour point test that the use of different GO lateral sizes significantly affects the wax inhibition, as verified through the highest PPR of 10°C displayed by the EJGO5 sample (with addition of the smallest lateral size of 1 μm). In short, manipulating the GO lateral size in sonicated samples boosted the PPR up to 100% compared to the unsonicated sample (EJGO1). Furthermore, smaller lateral size provides more nucleation site for wax co-crystallisation, hence preventing the neighbouring wax crystals from attaching and forming a looser crystal structure. The thermal characteristics of the PPD emulsions were also examined through DSC technique, which revealed that the emulsions thermal properties were unaffected by the addition of GO.
Ethylene vinyl acetate, graphene oxide, lateral size, pour point depressant, wax crystallisation