Performance analysis of yolo and ssd-based deep learning models for detection of oil palm trees in drone images

This study explores the use of advanced deep learning models for detecting and counting oil palm plants in precision agriculture using drone-based high-resolution images. The motivation stems from the limitations of manual monitoring methods, which are time-consuming, error-prone, and not feasible for large-scale plantations. Given Malaysia’s significant role in global palm oil production, efficient and automated detection systems are essential to support sustainable plantation management. The primary challenge is to accurately identifying oil palm trees in complex conditions, such as overlapping canopies, dense vegetation, varying lighting, and similar surrounding plants. These factors limit traditional image processing techniques, prompting the use of robust deep learning frameworks. This study evaluates four state-of-the-art object detection models: YOLOv5x, YOLOv7, YOLOv8, and SSDv2FPN, selected for their real-time detection capabilities and accuracy in agricultural environments. Two datasets were used: a smaller set of 10 drone images containing 79 annotated palm trees, and a larger dataset of 482 images with 5,233 trees. Evaluation metrics included True Positives, False Positives, False Negatives, Precision, Recall, F1-Score, and Detection Time. SSDv2FPN achieved perfect precision at 100% with an F1-Score of 89.49%, but required 83 seconds per image, which limits its suitability for real-time applications. In contrast, YOLOv5x, YOLOv7x, and YOLOv8x detected palm trees in relatively lower execution time of 16, 12, and 14 seconds respectively, with YOLOv5x achieving an F1-Score of 97.36%. These results demonstrate the clear advantage of YOLO models with regard to high speed execution. On the larger dataset, YOLOv8 models outperformed other frameworks, thereby achieving F1-Scores between 97.36% and 99.31%, precision values ranging from 99.27% to 99.70%, and recall rates between 95.89% and 99.36%. Among the YOLOv8 variants, YOLOv8s and YOLOv8n demonstrated the fastest detection times of 28 and 33 seconds, respectively, effectively balancing rapid inference and detection performance. This makes them ideal for deployment in practical agricultural monitoring systems

Sociodemographic, dietary pattern, serum biomarkers (insulin-like growth factor 1 (igf-1) and insulin-like growth factor binding protein 3 (igfbp-3)) and genetic polymorphisms in breast cancer among palestinian women: a case control study

Breast cancer (BC) remains a global public health challenge. This case-control study explores the relationships between serum insulin-like growth factor binding protein 3 (IGFBP-3), insulin-like growth factor 1 (IGF-1), genetic polymorphisms, dietary patterns, and BC risk in Palestinian women. The study involved 112 newly diagnosed BC confirmed by histopathology and 222 age-matched, cancer-free controls. Data collection included face-to-face interviews, biochemical, genetic, and immunohistochemical analyses, and bioinformatics. Tumour tissue samples from BC cases were analysed for ER, PR, and HER-2 status. SPSS program version 28 was used for all data analysis. Multivariate analysis revealed that elevated serum IGF-1 levels were associated with increased BC risk (OR=1.013; 95%CI 1.007, 1.019), as well as ER(+)/PR(+) status (rs= 0.232, p ≤ 0.001) and advanced disease stages (III and IV) (rs= 0.191, p ≤ 0.001; rs= 0.119, p = 0.029) respectively. Higher BC odds were linked to never being pregnant (OR=2.122; 95%CI 1.022, 4.408), first delivery at ≤18 years (OR=6.033; 95%CI 2.217, 16.413), and low-intensity exercise (OR=9.609; 95%CI 1.009, 91.471). Conversely, women aged 35–40 years had a reduced BC risk compared to those <35 years (OR=0.427; 95%CI 0.188, 0.971). The IGFBP-3 A-202C polymorphism showed significant associations with BC risk. The homozygous CC allele was more frequent in cases (70.5%) compared to controls (20.7%) and linked to elevated IGFBP-3 (rs = 0.164; p = 0.003) and IGF-1 levels (rs = 0.175; p ≤ 0.001), and an increased risk of BC (OR=16.237; 95%CI 7.904, 33.356, p ≤ 0.001). Moreover, the IGFBP-3 A-202C genotype was significantly associated with PR status and double positive hormone receptor ER/PR (p = 0.020). Furthermore, bioinformatics analysis identified IGF-1 variants (rs1520220, rs6214, rs7136446, rs6220) significantly associated with breast carcinoma and malignant neoplasm of the breast (p-value = 6.29E−0.6 and 2.84E−0.6) respectively. Additionally, the dietary analysis revealed that eight of the 14 food groups studied were linked to a decreased risk of BC, including fresh fruits and their juices (OR= 0.966; 95%CI 0.947, 0.985), meat products (OR= 0.963; 95%CI 0.934, 0.993), grains (OR=0.944; 95%CI 0.912, 0.977), low-fat dairy (OR=0.970; 95%CI 0.945, 0.995), nuts (OR=0.835; 95%CI 0.745, 0.936), snacks and sweets (OR=0.967, 95%CI 0.937, 0.998), and soups and sauces (OR=0.945; 95%CI 0.911, 0.979), were associated with a reduction in BC risk, while eggs were associated with increased risk (OR=1.125; 95%CI 1.019,1.243) with p-values < 0.05. Drinks and beverages was positively correlated with IGF-1 levels (rp = 0.121, p = 0.027). These findings underscore the importance of IGF-1 and IGFBP-3 as potential biomarkers for BC risk. Integrating genetic, biochemical, dietary, and lifestyle factors provides novel insights for personalized prevention and treatment strategies, particularly in resource-limited settings such as the Gaza Stri

Pusat Kajian Kelestarian Global (Centre for Global Sustainability Studies (CGSS),(2025) Kampus Sejahtera @ USM Town Hall TNCJIM Induk v2.0

Kampus Sejahtera ialah satu inisiatif yang diperkenalkan oleh Universiti Sains Malaysia (USM) pada tahun 2001. Ianya adalah inovasi unik USM dalam menerajui pembangunan lestari di dalam kampus. Kampus Sejahtera merupakan komitmen universiti terhadap kelestarian, kesejahteraan, dan pembangunan holistik komuniti USM. Konsep "Sejahtera" merangkumi kesejahteraan fizikal, emosi, rohani, intelektual, alam sekitar dan sosial. Kampus Sejahtera bertanggungjawab menyelaras pelaksanaan agenda kelestarian universiti dan strategi Matlamat Pembangunan Lestari (SDG) universiti. Ia selaras dengan visi USM ‘Mentransformasikan Pendidikan Tinggi Untuk Kelestarian Hari Esok’

Buletin Majlis Penghuni Desasiswa Tekun Sidang Akademik 2024/2025 Semester 1

The 2030 Agenda for Sustainable Development, 17 Sustainable Development Goals (SDGs), Reduced inequalities (SDG 10), Peace, justice, and strong institutions (SDG 16), Climate action (SDG 13), Quality education (SDG 4), Good health and well-being (SDG 3), Partnerships for the goals (SDG 17)

Fatigue failure analysis of cfrp composite laminates using modified stiffness degradation method

Carbon fibre reinforced polymer (CFRP) composite laminates have been extensively utilised in various industrial applications due to their outstanding mechanical properties. In this study, the stiffness degradation behaviour of CFRP laminates subjected to cyclic loading conditions was analysed using two analytical models: the Modified Stage I model and the modified Stage I to Stage III model. Both models were developed based on the original model proposed by Lurie and Minhat, and subsequently enhanced through the introduction of several specific parameters to improve the predictive accuracy between analytical results and experimental data. The application of a linear elastic model facilitated the determination of the mechanical properties of the CFRP materials, which served as input parameters for the modified models. The modified Stage I model was employed to evaluate stiffness degradation during the initial damage phase, particularly matrix cracking. The resulting analytical stiffness degradation curves were compared with the experimental curves. Subsequently, the modified Stage I to Stage III model was applied to assess the full spectrum of stiffness degradation, encompassing damage evolution from the initial stage to the final stage, including fibre breakage. To evaluate the accuracy of both models, the percentage difference between the analytical model and experimental data was calculated for all three CFRP laminate configurations investigated in this study, namely [0,±45]s, [0,902]s, and [0,90,±45]s. Overall, the findings indicate that the Modified Stage I model offers the highest predictive accuracy when directly compared with experimental data, particularly for early-stage damage. The simplicity of its formulation and its strong agreement with empirical results render it highly effective and reliable for predicting fatigue-induced damage in the initial service life of the structure. However, to provide a more comprehensive representation of the material’s stiffness degradation behaviour throughout its service life, the modified Stage I to Stage III model presents a balanced compromise between predictive accuracy and the ability to capture the complete damage progression. Therefore, the selection of the most appropriate model should be guided by the intended application. For short-term assessments or early-stage damage monitoring, the Stage I model is the most suitable. Conversely, for long-term durability predictions involving comprehensive structural integrity evaluation, the Stage I to Stage III model is more appropriate, as it demonstrates a high level of accuracy and inclusiveness that closely aligns with experimental observations

Low-cost condition monitoring for unbalanced motor systems using tuned dynamic vibration absorber

Unbalanced motor is referred to the situation of a rotating system where there is an uneven distribution of mass, resulting the significant vibration or imbalance problems. Poor management of unbalanced motor can lead to various issues, such as increased vibration, decreased efficiency, and potential damage of both motor and the integrated system. This study investigates the performance of reduction vibration for an integrated unbalanced motor-beam structure using a Tuned Dynamic Vibration Absorbers (TDVA), with different types of TDVA stiffness (stainless steel, aluminium, brass and titanium). To gain a better understanding of the system dynamic behavior, the natural frequencies of the beam were determined using an Experimental Modal Analysis prior to implementing the TDVA. The Operational Deflection Shapes (ODS) experiment was conducted in the z-axis direction with three different motor speeds; 880 RPM (14.8 Hz), 2100 RPM (35 Hz) and 2800 RPM (46.5 Hz) to observe the most significant vibration of the beam during operation. Later, the TDVA which consisted of two secondary masses, was employed to modify the structural dynamic response of the beam. The lengths of the TDVA masses were adjusted based on the motor speed to optimize vibration reduction of the beam. The selection of TDVA stiffness materials was driven by their varying densities, moduli of elasticity and damping capacities, providing insight into their suitability for specific operating frequencies and conditions. Various TDVA stiffness materials were applied to determine the most effective vibration attenuation and it was found that aluminium xxi material has produced the highest attenuation of 93.18 % at motor speed of 2880 RPM. Furthermore, a low-cost condition-based monitoring (CBM) system was developed using an Arduino Uno microcontroller connected to a Raspberry Pi. This system utilized an MPU9250 sensor which is cost-effective and appropriate for vibration measurement. The CBM system dashboard was hosted using the cloud, allowing real-time access to the vibration data. The system employed four programmable conditions to continuously assess the vibration activities. This affordable approach offers an accessible solution for small-scale industries, reducing reliance on expensive industrial-grade analyzers. In the event of abnormal vibration, the CBM system can trigger a notification alert, serving as a preventive measure against structure failures. The findings contribute to broader applications, including the improvement of maintenance strategies across various industries, emphasizing the transformative impact of combining effective vibration control and low-cost monitoring systems. It is also contributes to the understanding of the effect of different TDVA stiffness materials on the vibration control of beam structures with the additional of practical approach for real-time condition monitoring to improve system reliability

Confirmatory factor analysis of the Malaysia medication adherence assessment tool (MYMAAT) among patients with chronic medications

The MyMAAT was developed using Exploratory Factor Analysis and the current study intends to confirm the measurement model, dimensionality and ensure the factor structure by Confirmatory Factor Analysis (CFA). A cross-sectional study was conducted using a self-report questionnaire at six health facilities in the Federal Territories Kuala Lumpur and Putrajaya Health Department between May to November 2023. Participants with age≥18 years old, prescribed with one or more chronic medications for at least six months and understand English or Malay language were selected using quota sampling. There were two constructs in the MyMAAT, namely the Specific Medication-Taking Behaviour (Factor 1) with eight items and the Social-Cognitive Theory of Self-Efficacy and Social Support (Factor 2) with four items. There were 470 participants which comprised of Malay (62.7%), Chinese (24.0%) dan Indian (12.2%). Most participants had five drugs or less (81.3%). The final model for the Malay version of the MyMAAT retained the two constructs and 12 items with good fit: CFI=0.978, TLI=0.973, RMSEA=0.036(90%CI 0.001,0.067) and with good composite reliability CR=0.790 for Factor 1 and CR=0.787 for Factor 2. The factor loadings ranged from 0.413 to 0.832 with p-value<0.001 The AVE for Factor 1 was 0.664 and for Factor 2 was 0.491. There was a strong correlation (ρ=0.507, p < 0.001) between the Malay version of the MyMAAT with the Malay version of the MMAS-8 by adherence category from the data of 191 participants. The final measurement model of the English version did not achieve the minimum level of good fit to the data: CFI=0.933, TLI=0.917, RMSEA=0.073(90%CI 0.052,0.094) but had good composite reliability CR=0.802 for Factor 1 and CR=0.852 for Factor 2. The factor loadings ranged from 0.347 to 0.845. The AVE was 0.630 for Factor 1 and 0.392 for Factor 2. Fifty-two participants completed the test-retest after five to ten days from the first administration. The Malay version had moderate to excellent reliability based on ICC=0.932(95%CI:0.661,0.986) for Factor 1 whereas Factor 2 had poor to excellent reliability based on ICC=0.956(95%CI:0.325,0.997) by using the Two-Way Mixed Model and Consistency type. The English version had moderate to excellent reliability based on ICC=0.911(95%CI:0.554,0.982) for Factor 1 whereas Factor 2 had poor to excellent reliability based on ICC=0.941(95%CI:0.092,0.996). It can be concluded that the Malay version of the MyMAAT is valid and reliable in measuring medication adherence among participants with chronic medication(s), but the English version needs to be improved and then re-teste

Knowledge, attitude and practice toward epilepsy among mother with epilepsy children in pediatric clinic, Hospital Universiti Sains Malaysia

Epilepsy is a chronic non-communicable disease of the brain that affects around 50 million people worldwide (WHO, 2023). The knowledge, attitude, and practice of mothers regarding epilepsy are crucial for the effective management of the condition, reducing stigma, providing emotional support, and ensuring the overall well-being of children with epilepsy. Objective of this study aims to determine the knowledge, attitude and practice toward epilepsy among mothers with epilepsy children in pediatric clinic, Hospital Universiti Sains Malaysia. Besides that, this study also investigates the association between knowledge and sociodemographic factors (education level) toward epilepsy among mothers with epilepsy children in pediatric clinic, Hospital Universiti Sains Malaysia. A cross-sectional study design was used, and 135 mothers participated in this research. The data was collected using a hard copy questionnaire distributed to the respondents. Descriptive statistics were used to describe the respondent and identify the level of knowledge, attitude, and practice toward epilepsy among mothers with epilepsy children in pediatric clinic, Hospital Universiti Sains Malaysia. Pearson Chi-square were used to test association between knowledge and sociodemographic factors (education level) toward epilepsy among mothers with epilepsy children in pediatric clinic, Hospital Universiti Sains Malaysia. The findings of the study revealed that most mothers (56.5%) have good knowledge about epilepsy, their overall attitude (84.4%) was neutral, and their practices (60.0%) during the last seizure were good. The results also showed no association between knowledge and educational level among mothers of children with epilepsy at the pediatric clinic, Hospital Universiti Sains Malaysia , where (p > 0.05). Although most of the mother has good knowledge and practice, however, their attitude toward epilepsy needs to be improved to enhance the care and support of their children

Association between breakfast consumption pattern with body mass index (bmi) and physical activity among undergraduate students in Universiti Sains Malaysia, Health Campus, Kubang Kerian, Kelantan.

Breakfast is widely acknowledged as the most important meal of the day because it provides energy throughout the day and offers many benefits, including physical, mental, and cognitive functions. However, the practice of healthy eating habits, such as consuming breakfast, is still reported to be low among young adults, especially university students. Therefore, this study aimed to determine the association between breakfast consumption pattern with body mass index (BMI) and physical activity among undergraduate students at the USM Health Campus, Kubang Kerian, Kelantan. This cross-sectional study involved 116 undergraduate students selected through a convenience sampling method. The self-administered questionnaire consisted of four sections: socio-demographic characteristics, anthropometric measurements, the International Physical Activity Questionnaire (IPAQ), and questions related to breakfast consumption patterns. The majority of respondents were female (81.0%), aged between 19 and 23 years (90.5%) with a mean age of 21.90 ± 1.40 years. Most respondents were third-year students (32.8%), PPSK students (87.1%), and of Malay ethnicity (64.7%). More than half of respondents, 58.6%, spent between RM10 to RM15 on their daily food budget, with a mean of RM14.66 ± 6.03 and received between RM500 to RM1000 for their monthly allowance, with mean of RM553.73 ± 261.78. A total of 38.8% received loans as sponsorship throughout their studies and 97.4% of the respondents stayed in campus hostel. Based on BMI classification, 11.2% were underweight, 43.9% were normal weight, 29.3% were overweight, and 16.4% were obese. Regarding physical activity levels, 45.7% had moderate physical activity levels, and 55.2% of respondents were classified as breakfast skippers. However, there was no significant association between breakfast consumption patterns and BMI (p= 0.267). The findings also revealed that there was no significant association between breakfast consumption patterns and physical activity reported in this study (p= 0.279)