Extending CAM-based XAI methods for Remote Sensing Imagery Segmentation

Current AI-based methods do not provide comprehensible physical interpretations of the utilized data, extracted features, and predictions/inference operations. As a result, deep learning models trained using high-resolution satellite imagery lack transparency and explainability and can be merely seen as a black box, which limits their wide-level adoption. Experts need help understanding the complex behavior of AI models and the underlying decision-making process. The explainable artificial intelligence (XAI) field is an emerging field providing means for robust, practical, and trustworthy deployment of AI models. Several XAI techniques have been proposed for image classification tasks, whereas the interpretation of image segmentation remains largely unexplored. This paper offers to bridge this gap by adapting the recent XAI classification algorithms and making them usable for muti-class image segmentation, where we mainly focus on buildings' segmentation from high-resolution satellite images. To benchmark and compare the performance of the proposed approaches, we introduce a new XAI evaluation methodology and metric based on "Entropy" to measure the model uncertainty. Conventional XAI evaluation methods rely mainly on feeding area-of-interest regions from the image back to the pre-trained (utility) model and then calculating the average change in the probability of the target class. Those evaluation metrics lack the needed robustness, and we show that using Entropy to monitor the model uncertainty in segmenting the pixels within the target class is more suitable. We hope this work will pave the way for additional XAI research for image segmentation and applications in the remote sensing discipline

Interaction effect of nitrogen and potassium on growth and yield of carrot

The experiment was carried out to study the effects of three mulching practices viz., no mulch, water hyacinth mulch and polythene mulch, three levels of nitrogen viz., 0, 150 and 200 and three levels of potassium viz., 0, 200 and 250 kg/ha on the growth and yield of carrot. The yield and yield contributing characters of carrot were significantly influenced by the application of nitrogen and potassium fertilizers with mulching treated plot. The highest marketable yield (63.47 t/ha) was recorded from the treatment combination of black polythene mulch with 200 kg N/ha and 200 kg K/ha treated plot and the lowest (23.69 t/ha) from the control treatment (M0N0K0). But the benefit-cost ratio (BCR) was found maximum (5.60) in the treatment combination of water hyacinth mulch with 200 kg N/ha and 200 kg K/ha, and the lowest (2.54) in control treatment. Considering the above findings, water hyacinth mulch with the application of 200 kg N/ha and 200 kg K/ha appeared to be recommendable for carrot cultivation for the place where irrigation facility was not available

Effects of Eurycoma longifolia

Testosterone replacement is the choice of treatment in androgen-deficient osteoporosis. However, long-term use of testosterone is potentially carcinogenic. Eurycoma longifolia (EL) has been reported to enhance testosterone level and prevent bone calcium loss but there is a paucity of research regarding its effect on the bone structural parameters. This study was conducted to explore the bone structural changes following EL treatment in normal and androgen-deficient osteoporosis rat model. Thirty-six male Sprague-Dawley rats aged 12 months were divided into normal control, normal rat supplemented with EL, sham-operated, orchidectomised-control, orchidectomised with testosterone replacement, and orchidectomised with EL supplementation groups. Testosterone serum was measured both before and after the completion of the treatment. After 6 weeks of the treatment, the femora were processed for bone histomorphometry. Testosterone replacement was able to raise the testosterone level and restore the bone volume of orchidectomised rats. EL supplementation failed to emulate both these testosterone actions. The inability of EL to do so may be related to the absence of testes in the androgen deficient osteoporosis model for EL to stimulate testosterone production

Parametric Feature Selection for an Enhanced Random Linear Oracle Ensemble Method

Random Linear Oracle (RLO) utilized classifier fusion-selection approach by replacing each classifier with two mini-ensembles separated by an oracle. This research investigates the effect of t-test feature selection toward classification performance of RLO ensemble method. Naïve Bayes (NB) classifier has been chosen as the base classifier due to its elegant simplicity and computationally inexpensive. Experiments were carried out using 30 data sets from UCI Machine Learning Repository. The results showed that RLO ensemble could greatly improve the ability of NB classifier in dealing with more data with different properties. Moreover, RLO ensemble receives benefits from feature selection algorithm, with a properly selected number of features from ttest, the performance of ensemble can be improved

Long term studies on compressive strength of high volume nano palm oil fuel ash mortar mixes

© 2015 Penerbit UTM Press. All rights reserved. Palm oil fuel ash is a waste material that can be used as partial cement replacement. However, its reactivity as pozzolanic material depends on the size of the particle. This paper presents the effects of nano size palm oil fuel ash on the long term characteristics of mortar. The study covers basic properties of mortar including the morphology, porosity, compressive strength and microstructural with regards to the variations in the mix design of the mortar. The palm oil fuel ash used has gone through heat treatment and was ground to a nano size with the percentage replacement of cement used was 60%, 80% and 100%. The different types of mortar samples were cast in a 70x70x70mm cube for compressive strength test. All casting and testing of the samples were conducted in the laboratory at ambient temperature. The results show that the use of 80% nano size palm oil fuel ash has produced higher compressive strength at the age of 28 days by 32% compared to the control mortar. Grinding the palm oil fuel ash to a nano size particle has improved the reactivity of the ash and because of it is a waste material it reduces the cost of the mortar. The experimental result also show that the compressive strength of the 80% nano size palm oil fuel ash mortar at 365 days was 25% higher than its strength at 28 days. In addition, the porosity of the 80% nano palm oil fuel ash mortar was reduced by 51% at the age of 1 year. The overall results have revealed that the use of high volume nano palm oil fuel ash can enhances the mortar properties and due to the high percentage of replacement it can contribute to a more sustainable construction

Performance of epoxy resin as self-healing agent

© 2015 Penerbit UTM Press. All rights reserved. Formation of cracks due to the shrinkage effects during curing and mechanical loading can deteriorate the concrete performance especially in terms of durability aspect. Chemical and harsh solutions will easily penetrate into the concrete and cause damage to the concrete. In order to solve this problem, researchers have introduced a self-healing concrete; the mechanism of automatically repairing concrete cracks without external intervention. Nowadays, the self-healing concrete by using bacteria as a healing agent had gained interest among researchers. In contrast, this paper presents the study on performance of epoxy resin without hardener as a self-healing agent in concrete. Mortar specimens were prepared with mass ratio of 1:3 (cement: fine aggregates), water-cement ratio of 0.48 and 5 to 20% epoxy resin of cement content. All tested specimens were subjected to wet-dry curing; where compressive strength, apparent porosity and self-healing evaluation were measured. Result shows that, the compressive strength of mortar with addition of epoxy resin by 10% increased significantly compared to normal mortar. Epoxy resin as a healing agent was found to be functioned well as the compressive strength and ultrasonic pulse velocity regain the initial reading with prolonged curing time. These results together with microstructure test indicate that epoxy resin can be used as a self-healing agent

Incorporation of homogenous ceramic tile waste to enhance mechanical properties of mortar

© 2015 Penerbit UTM Press. All rights reserved. Reduction, reuse and recycle of industrial and agricultural waste materials are regarded as very important to provide sustainable construction. The by-products such as fly ash, silica fume, slag and palm oil fuel ash, etc., have been studied for the past few decades and the findings are very well accepted as new innovative materials in construction. Currently, ceramic materials are widely used in many parts of the world. Consequently a large quantities of wastes are produced simultaneously by brick and tile manufacturers and from construction industry. Most of these wastes are dumped in landfills that cause environmental problem. In the present research the effect of homogeneous ceramic tile waste as sand replacement was investigated on the harden properties of mortar. The tests conducted under laboratory ambient condition were compressive and splitting tensile strengths. The percentage replacement of sand by ceramic aggregate by weight was in the range of 0% to 100%. The size of ceramic aggregate used is modified in accordance to ASTM C33-13. All samples were cast in a 50mm cube and cured in water until the age of testing. The results showed that the compressive strength values of the control sample and 100% ceramic aggregate as sand replacement at the age of 7days were 41.9 MPa and 40.9 MPa, respectively; almost similar. In addition, the splitting tensile strength of the mortar sample with 100% ceramic aggregate was found to be 6% higher than the control sample. Thus, the homogenous ceramic tile waste can not only be used as sand replacement for normal application in mortar mix but also to enhance its hardened properties

Geochemical assessment of groundwater composition and evaluating its suitability of Saidpur Upazilla in Bangladesh

The chemical analysis of 44 groundwater samples in the northern Bangladesh has been evaluated to determine the hydrogeochemical processes and major ions, heavy and rare metal concentration for its suitability for agricultural and domestic purposes. The quality analysis is performed through the estimation of pH, EC, cations (Ca2+, Mg2+, Na+ , K+ , Zn2+, Cu2+, Mn2+, Fe3+ and As3+), anions (CO3 2-, HCO3 - , NO3 - , SO4 2-, PO4 3- and Cl- ) and TDS (total dissolved solids). We also computed several variables such as SAR (sodium adsorption ratio), SSP (soluble sodium percentage) RSC (residual sodium carbonate), potential salinity, permeability index, Kelly's ratio, Gibbs ratio and hardness to evaluate the suitability of groundwater supply for specific uses. From the geochemical results, it has been found that both the cations and anions varied in the groundwater. Among the chemical budget of ions, magnesium and chloride were found to be the most predominant ions. The intense agricultural activities may be an important factor for the higher concentration of nitrates in these aquifers. Based on the total hardness, most groundwaters are moderately hard. According to EC and SAR the most dominant class is C1-S1. The major ion concentrations are below the acceptable level for drinking water. The salinity hazard is low thus, there is less chances to increase of toxic salt concentrations. Gibbs diagram indicates that all the samples fall in the precipitation dominance field. Regarding cation and anion constituents, groundwater is suitable for irrigation and drinking purposes except of few wells