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- PublicationOptimization Of Surface Soil Moisture Extraction Using Sentinel-1a Sar And Machine Learning In Northwest Shandong Plain, China(2025-08)In semi-humid regions, soil moisture (SM) plays a crucial role in influencing hydrological cycle processes and energy balance. While machine learning (ML) and Synthetic Aperture Radar (SAR) offer potential for SM information retrieval, their performance and applicability are limited by challenges such as feature selection and sensitivity to environmental variations across different seasons. This challenge is exacerbated by the lack of comprehensive frameworks that effectively integrate multiple polarimetric parameters with traditional backscatter coefficients, which could improve the accuracy of SAR-based SM retrieval. Hence, this research aims to develop an innovative method that combines advanced polarimetric decomposition techniques with ML algorithms for robust SM retrieval in the Northwest Shandong Plain, China.
- PublicationThe Effect Of Cognitive Behavioral Therapy Psychoeducation Module In Reducing Body Image Dissatisfaction Among College Students In China(2025-08)Body image dissatisfaction refers to negative cognition and attitudes toward one`s body shape and physical characteristics, as well as the negative emotions and feelings arise on that basis. It has been recognized as a public health issue; however, there is a lack of relevant research in China, particularly in the college population. Body image dissatisfaction has a negative impact on mental health and is often linked to self-esteem, depression and anxiety. This study aimed to investigate the levels of body image dissatisfaction, self-esteem, depression, and anxiety among Chinese college students; to analyze gender differences in these variables and their relationships in groups with body image dissatisfaction; and to develop a psychoeducational module based on cognitive-behavioral therapy combined with other learning theories (Behaviorist Learning Theory, Cognitive Learning Theory and Humanistic Learning Theory) to reduce body image dissatisfaction among Chinese college students.
- PublicationErich Fromm’s Conception Of Man: An Analysis From A Phenomenological Perspective(2025-07)Erich Fromm, a renowned psychoanalyst and ethicist of the 20th century, introduced sociology and historical materialism into the domain of psychology, establishing a humanistic psychoanalysis aimed at improving human creativity and achieving freedom. His conception of the “whole and universal man” represents the fundamental nature of humanity and has profound implications for his ethical thought. Despite numerous studies on Fromm’s psychoanalysis and philosophy, there is a lack of in-depth research on his conception of man from a phenomenological perspective. This thesis aims to address this gap by exploring Fromm’s ideas through an analysis from phenomenological perspectives. The primary objectives are to provide a comprehensive examination of Fromm’s conception of man, explore major viewpoints on the conception of man in phenomenology, and analyze Fromm’s ideas through phenomenological perspectives.
- PublicationPaddy Farmers’ Intention To Fully Adopt Smart Farming Technologies: Examining The Role Of Overall Perceived Value And Technology Readiness(2025-08)Smart Farming Technologies (SFTs) hold significant potential for enhancing productivity, optimizing resource utilization, and promoting sustainability in agriculture. Modern farming faces a complex array of interconnected challenges, from soil health and water management to pest control and yield optimization, that a single technology cannot adequately address. However, adoption rates remain low in developing countries like Malaysia, where many farmers still rely on traditional practices despite government initiatives. This highlights a gap between policy and practice, necessitating evidence-based research to address the underlying factors influencing SFTs adoption. While recent studies emphasize the role of farmers' value perceptions in SFTs adoption, this notion remains underexplored, especially concerning the value complexity and the factors that shape it.
- PublicationConditional And Anonymous Payment Protocol With Local Dispute Resolution Mechanism In Payment Channel Networks(2025-08)This research proposes a conditional and anonymous payment protocol with a local dispute resolution mechanism, addressing three key issues. First, a lightweight and Lightning Network-compatible Onion Style Symmetric Commitment (OSSC) that ensures a secure and efficient locking and unlocking scheme. Second, the Efficient Multi-party Conditional Payment Flow (EMCPF) protocol relies on a Hybrid Encryption Mechanism (HEM). It extends a refined OSSC version by avoiding the ideal anonymous communication assumption, preserving privacy, security, and preventing long collateral durations and Wormhole attacks. Finally, a Local Dispute Mechanism (LDM) is extended with EMCPF to resolve disputes and unresponsiveness cases between channel parties locally and synchronously, avoiding costly blockchain lifecycle.
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- ItemSynthesis And Evaluation Of Silica Particles From Rice Husk For Fabrication Of Dental Nanohybrid Composites(Universiti Sains Malaysia, 2015-10)The objective of this study was to synthesize silica particles from rice husk with ideal characteristics, like spherical shape, low surface area and wide particle size distribution, for use as fillers in dental composites. The silica was leached in to a solution of NaOH to form sodium silicate. The silica was synthesized from sodium silicate solution using a simple acid precipitation technique. Several parameters were tested to obtain silica particles with ideal characteristics for use as fillers in dental composites. These included the effect of various precipitating acids and solvents, effect of dilution of sodium silicate solution, mixing speed, feed rate and various concentrations of solvents. It was possible to obtain spherical silica particles with a BET surface area of 30 m2/g and a mean diameter of 261nm. The silica particles were modified using a coupling agent, 3--(Trimethoxysilyl) propyl methacrylate. The silica surface was successfully modified using a very simple technique and was characterized using FTIR and NMR studies. Dental composites with two different filler/matrix ratios (EC1: 40/60 and EC2: 50/50) were fabricated from the surface modified nanohybrid silica, followed by mechanical properties testing, which included flexural strength, flexural modulus, compressive strength, Vickers’ hardness and surface roughness tests. Although both experimental dental composites showed promising results, EC2 exhibited better test values. EC2 showed a flexural strength of 106.6 MPa, flexural modulus of 6.2 GPA, compressive strength of 190.6 MPa, Vickers’ hardness of 38.66 HV1 and surface roughness of 0.057 Ra which are comparable with a commercial dental composite. Biocompatibility of the silica particles and EC2 were tested using cytotoxicity studies on human periodontal ligament fibroblast cells using the MTT assay. The silica particles were non-cytotoxic at all the concentrations tested. The results for experimental dental composite showed that it was moderately cytotoxic only at the highest tested concentrations, which is in agreement with several other studies. The results indicate that rice husk, which is an agricultural waste, is a good and inexpensive source of silica for potential use as fillers in dental composites.
- ItemA cross sectional study of the proximal femur morphology of the normal malay population using computed tomography images (scanogram) at HUSM(Pusat Pengajian Sains Perubatan Universiti Sains Malaysia, 2008)A cross sectional study on the morphometry of proximal femur in Malay patients who were treated in Hospital Universiti Sains Malaysia. Objectives To quantify the proximal femur dimensions in Malay patients, to compare the parameters between male and female patients and to determine the correlation between the parameters. Summary of the Background Data Previous studies have shown a significantly smaller proximal femur parameters in the Asian population compared to Caucasian population. Currently used proximal femur implants size were based on Caucasian studies. However, due to the smaller size of proximal femur in Asian population, improvement in the design of implant are required to optimize component fixation and to restore the normal biomechanics of the hip joint. Methods Proximal femoral bones were studied in 140 patients ( 70 male and 70 female ) who had undergone computerized tomographic scan for various pelvic pathology but with normal proximal femur morphology. The age range was between 18 to 80 years old. The VII following parameters were studied : 1) Femoral neck shaft angle, 2) Femoral head diameter, 3) Femoral neck isthmus diameter, 4) Vertical offset of femur, 5) Horizontal offset of femur. The data obtained were statistically analyzed using independent T -test to determine the differences between male and female patients. The mean of all the parameters of current study were compared with published Western and Asian studies using one sample T -test. Significant differences for all the statistical test were set at p < 0.05. Results There were significant differences between male and female patients in femoral head diameter, femoral neck isthmus diameter, vertical offset and horizontal offset. However, there was no significant difference in neck shaft angle. Female patients have significantly smaller dimensions in all the parameters measured except for neck shaft angle which was larger. When the observations in the current study was compared to radiographic study by Sugano et al and Noble et al, significant differences were found in head diameter, neck isthmus diameter, vertical offset and neck shaft angle. The head diameter, neck isthmus diameter and vertical offset of the current study were significantly smaller compared to their study. However the neck shaft angle of the current study was significantly larger than their study. Vlll Conclusions The current study have shown that the proximal femur morphometry of Malay population was smaller compared to Caucasian and Thai population.
- PublicationCoenzyme Q10 supplementation for prophylaxis in adult patients with migraine : A meta-analysis(2022)Objective To determine the effects of coenzyme Q10 (CoQ10) for reduction the severity, frequency of migraine attacks and duration of headache in adult patients with migraine. Design Systematic review and meta- analysis. Data sources Cochrane Central Register of Controlled Trials, CENTRAL, MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Psychological Information Database (PsycINFO) from inception till December 2019. Study selection All randomized control trials (RCTs) comparing CoQ10 with placebo or used as an adjunct treatment included in this meta-analysis. Crossover designs and controlled clinical trials (CCT) were excluded. Data synthesis Heterogeneity at face value by comparing populations, settings, interventions and outcomes were measured and statistical heterogeneity was assessed by means of the I2 statistic. The treatment effect for dichotomous outcomes were using risk ratios (RRs) and risk difference (RD), and for continuous outcomes, mean differences (MDs) or standardized mean difference (SMD); both with 95% confidence intervals (CIs) were used. Subgroup analyses were carried out for dosage of CoQ10 and if CoQ10 combined with another supplementation. Sensitivity analysis was used to investigate the impact risk of bias for sequence generation and allocation concealment of included studies. Results Six studies with a total of 371 participants were included in meta-analysis. There is no statistically significant reduction in severity of migraine headache with CoQ10 supplementation. CoQ10 supplementation reduced the duration of headache attacks compared to the control group (mean difference -0.19, 95% CI -0.27 to -0.11; random effects; I2 statistic = 0%; P < 0.00001). CoQ10 usage reduced the frequency of migraine headache compared to the control group (MD -1.52, 95% CI -2.40 to -0.65; random effects; I2 statistic = 0%; P = <0.001). Conclusion CoQ10 appears to have beneficial effects in reducing duration and frequency of migraine attack.
- PublicationEmotion recognition in children with autism spectrum disorder, attention-deficit/hyperactivity disorder and typical development with exploratory observation on comorbid case(2025-08)Children with Autism Spectrum Disorder (ASD), Attention Deficit/Hyperactivity Disorder (ADHD), and comorbid ASD + ADHD often exhibit challenges in emotion recognition, which can impact social functioning. This study aimed to investigate the unique and shared emotion recognition profiles of children with ASD, ADHD, ASD + ADHD, and typically developing (TD) peers. A total of 17 children (15 males, 2 females; mean age = 9 years) participated, including 5 with ASD, 6 with ADHD, 1 with comorbid ASD + ADHD, and 5 TD children. Using a two-phase methodology, Phase 1 involved translation, cultural adaptation, and pilot testing of a screening questionnaire - selected modules from the Autism-Tics, ADHD, and other Comorbidities Inventory (A-TAC) used in phase 2 to categorize participants into diagnostic groups. Phase 2 utilized computerized experimental tasks, including a Facial Emotion Recognition (FER) task and Affective Prosody (AP) task, to assess and compare visual and auditory emotion recognition abilities across the groups. Given recruitment constraints, the initial 4 × 2 factorial design was adapted, and analyses were conducted using ANOVA, ANCOVA, and regression to examine group and modality effects while accounting for age and FSIQ. Findings revealed no significant group-level differences in overall emotion recognition accuracy. However, across conditions, children performed significantly better in visual than in auditory emotion recognition, highlighting a consistent modality effect. This suggests that visual cues, particularly facial expressions, may represent a relative strength, whereas auditory prosody presents greater challenges across groups. These results imply that interventions may be more effective when they build on visual strengths while providing targeted support for auditory processing difficulties. The absence of strong diagnostic or cognitive predictors further underscores the potential value of shared, transdiagnostic approaches to intervention, rather than disorder-specific models. Future research should prioritize larger and more balanced samples to clarify the impact of comorbidity and individual variability on emotion recognition profiles.
- ItemWhite-Matter Lesion Segmentation In Brain Mri Using Adaptive Trimmed Mean Approach(Universiti Sains Malaysia, 2011-06)White Matter (WM) lesions are diffuse white matter abnormalities, that appear as hyperintense (bright) regions in cranial Magnetic Resonance Imaging (MRI). WM lesions are often observed in older population and are important indicators of stroke, multiple sclerosis, dementia and other brain-related disorders. Manual detection of WM lesions is laborious and the currently adopted visual scoring approaches for lesion grading is very subjective. In this thesis, a new approach for automated WM Lesions Segmentation is presented. In the proposed approach, the presence of WM lesions is detected as outliers in the intensity distribution of the Fluid Attenuated Inversion Recovery (FLAIR) MR images using an Adaptive Outlier Detection technique. Outliers are detected using a novel adaptive Trimmed Mean and Box-Whisker Plots. In addition, the approach includes pre and post-processing steps to reduce False Positives attributed to MRI artefacts commonly observed in FLAIR sequences. The proposed approach is validated using the cranial MRI sequences of 38 subjects. A significant correlation (R=0:8506;P=3:94x106) is observed between automated approach and manual visual scoring (Age-related White Matter Changes Scale). The accuracy of the proposed approach was further validated by comparing the lesion volumes computes using the automated approach and lesions manually segmented by an expert radiologist. The proposed approach is also compared against leading lesion segmentation algorithms using a benchmark dataset.