Deep learning-based prediction model for crude palm oil prices using news sentiment analysis with sliding window

Crude palm oil (CPO) price prediction plays an important role in agricultural economic development. Various economics and agricultural-related factors have been used to predict CPO prices. Nevertheless, understanding news sentiment features will also be important in CPO price prediction. This paper proposes a CPO price prediction model to help the plantation organizations in the palm oil sector to successfully anticipate CPO price fluctuations and manage the resources more effectively. The CPO price behavior is nonlinear in nature, and thus prediction is very difficult. In this paper, an improved version of recurrent network, long short-term memory (LSTM)-based CPO price prediction model with news sentiment, is used to produce an enhanced prediction model. The findings of this study show that the LSTM-based forecasting model with news headline sentiment using a six-month sliding window produced the best result in forecasting the CPO price movement compared to other sliding window sizes

Optimization of perovskite solar cell with MoS2-based HTM layer using hybrid L27 Taguchi-GRA based genetic algorithm

This article proposes an optimization method to predictively model the perovskite solar cell with molybdenum disulfide (MoS2) based inorganic hole transport material (HTM) for improved fill factor (FF) and power conversion efficiency (PCE) by finding the most optimum thickness and donor/acceptor concentration for each layer via a hybrid L27 Taguchi grey relational analysis (GRA) based genetic algorithm (GA). Numerical simulation of the device is carried out by employing one-dimensional solar cell capacitance simulator (SCAPS-1D) while the optimization procedures are developed based on combination of multiple methods; L27 Taguchi orthogonal array, GRA, multiple linear regression (MLR), and GA. The results of post-optimization reveal that the most optimum layer parameters for improved FF and PCE are predicted as follows; SnO2F thickness (0.855 μm), SnO2F donor concentration (9.206×1018 cm-3), TiO2 thickness (0.011 μm), TiO2 donor concentration (9.306×1016 cm3),CH3NH3PbI3 thickness (0.897 μm), CH3NH3PbI3 donor concentration (0.906×1013 cm-3), MoS2 thickness (0.154 μm), and MoS2 acceptor concentration (9.373×1017 cm-3). Both FF and PCE of the device are improved by ~1.1% and ~12.6% compared to the pre-optimization

Visualizing anthocyanins: Colorimertic analysis of blue maize

Anthocyanin, vibrant pigments found in a wide range of plants, including maize, contribute to the red, blue, and purple hues observed in fruits, vegetables, and grains. The inherent color variations in maize, including natural shades of purple, red, blue, and even rainbow colors, pose a significant challenge in accurately assessing maize maturity. This study recognizes the importance of visualizing the distinct blue purplish anthocyanin coloration to determine the optimal harvest time for blue maize, particularly among small-scale producers. To address this crucial need, this research project presents the development of the MaizeMeter, an advanced colorimeter specifically designed to analyze maize color based on anthocyanin pigmentation. Leveraging the power of Internet of Things (IoT) implementation, the MaizeMeter provides real-time monitoring and interpretation of anthocyanin color values. The proposed methodology encompasses the calibration of the color sensor and the prototyping of the MaizeMeter, culminating in the establishment of a comprehensive database of anthocyanin color profiles in blue maize. The generated anthocyanin color database by the MaizeMeter will serve as a vital tool for small-scale farmers and researchers, enabling more efficient and accurate assessment of maize maturity in the future

A regression model of hip flexion force of the dominant leg among Malaysian adults in standing posture

Introduction: The disregard for hip flexion force when designing foot-operated equipment poses a potential threat to non-compliance with ergonomics principles, ultimately impacting occupational health. Nevertheless, there is a noticeable lack of studies focusing on the hip flexion strength of Malaysian adults in a standing position. This paper aimed to measure the maximum force of hip flexion strength and formulate a regression model for Malaysian young adults in a standing posture. Materials and methods: The experiment invited sixty Malaysian adults aged 20 to 26 years old. A digital force gauge (Mark-10, USA) was used to measure the hip flexion force. A regression model was developed to determine the influence of gender, body mass, body height, thigh length, and thigh circumference on the hip flexion force. Results: The results of this study found that the means of hip flexion force for the male and female participants were 192.8 N and 126.0 N, respectively. The regression model concluded that gender is the most significant factor influencing hip flexion force (p0.05). Conclusion: This study concluded that the relationship between anthropometric parameters and hip flexion force is not always straightforward and can be influenced by various factors. To gain a more comprehensive picture of hip flexion, it is essential to consider other potential factors such as muscle mass, neuromuscular control, and joint mechanics

Interphase investigation of modified McLachlan model and the 3D finite element method for electrical conductivity

This paper explores the electrical conductivity interphase of Ag/Epoxy composite using modified McLachlan theory and 3D finite element composite model through experimental verification. The model characteristic presents conductivity as a dynamic function influenced by particle content, particle electrical properties, electrical properties transition, and an exponent. This model was meticulously crafted, considering the intricate interplay between the polymer matrix and silver particles, the tunnelling distance between adjacent silver particles, and the interphase regions around particles. This model has proven its mettle through rigorous analysis of experimental results and the impact of various parameters on conductivity. The predictions have shown impressive alignment with the experimental data, highlighting the crucial roles played by the parameters in the conductivity of silver composites where the percolation threshold reached 6 vol % of filler loading. The experimental study demonstrated that the electrical conductivity was 3.84 × 10−1 S/cm for micro-sized particles and 1.32 × 10−2 S/cm for nano-sized particles. Notably, a large tunnelling distance drastically reduces conductivity, while higher and slighter surface energies of the polymer matrix and filler enhance conductivity. Furthermore, a thin interphase yields minimal conductivity, whereas a thick interphase and low waviness improve conductivity. The McLachlan-modified model falls slightly short in accuracy compared to the 3D finite element method models. Adjustments to the equations can enhance its alignment with experimental data

Design and optimization of a linear fiber-reinforced soft actuator for improved linear motion performance

The demand for safe and flexible actuators has increased as traditional actuators pose safety risks due to their rigid materials, especially in applications requiring human-machine interaction. This study focuses on designing and optimizing a linear fiber-reinforced soft actuator to enhance linear motion performance while maintaining safety and flexibility. Finite element method (FEM) analysis was used to evaluate the effects of varying key design parameters, including core radius, actuator length, and core wall thickness. The analysis revealed that increasing the core radius leads to greater linear extension, while increasing the actuator’s length and wall thickness reduces extension. Among the tested designs, the R10 design exhibited the highest linear extension, with a 44.41% increase in length compared to the original design. However, the R10 design also showed undesirable bulging at the free end under pressure, which necessitated further optimization. By increasing the thickness of the sheath wall, the bulging was reduced, and the optimized design achieved a 34.53% increase in extension. This study highlights the significance of parameter optimization in fiber-reinforced soft actuators to achieve superior linear motion performance. Future work will explore further improvements in structural stability, sensor integration for precise control, and advanced fabrication techniques for better customization and durability

Integrating water quality model and aeration with IoT technology in water quality management: A conceptual framework

Eutrophication poses a significant threat to both human population growth and aquatic life. It gives rise to a range of issues, including algae blooms, loss of habitat, reduced self-purification capacity, and changes in the biodiversity system. In order to restore the ecosystem, it is imperative to implement water quality management measures to combat eutrophication. Common methods for mitigating eutrophication include the use of water quality models, aeration, and IoT technology. Water quality model simulations have been demonstrated to accurately predict future water quality. Aeration, on the other hand, increases oxygen concentration in water through dispersion. Furthermore, the utilization of IoT in water quality monitoring provides users with precise and real-time data. Despite research findings that suggest the effectiveness of water quality models, aeration, and IoT technologies in addressing eutrophication, their current integration is inadequate. Therefore, the aim of this paper is to develop a conceptual framework that incorporates water quality models, aeration, and IoT technology to regulate water quality, with a specific focus on preventing the eutrophication issue. The conceptual framework was created by studying existing research on frameworks for water treatment, water quality modelling, aerators, and IoT technologies. Several adjustments were made to tailor the general framework to the specific requirements of this study. The discussion emphasizes the advantages of conceptual framework development in managing water quality, which integrates water quality models, aerators, and IoT technologies. This framework is expected to serve as an effective tool for managing eutrophication in water, while also promoting sustainable measures to address water contamination

Application of the trait-Factor theory-Based vocational preference inventory on the government school counsellors in Malaysia

The study aimed to develop a reliable module of career counselling based on the trait-factor theory for government school counsellors in Malaysia. Known as the Modul Kaunseling Kerjaya Tret dan Faktor (MKKKTF), this module was adapted from the Model Pembinaan Modul Sidek (MPMS) and integrated with the trait-factor theorem guidelines. To determine the module’s validity, the content and the module’s appropriateness and significance were evaluated and reviewed by a group of panel experts who were selected using a specific list of criteria. Using the Fuzzy Delphi Technique, the experts’ responses and evaluation of MKKKTF were analysed, and the findings revealed that the MKKKTF was significantly variable to be used as a guideline for government school counsellors, including those who are not registered with the Kaunselor Berdaftar Perakuan Amalan (KBPA) in Malaysia

Performance analysis of a rectangular nested fractal antenna for multiband applications

This paper presents the design, fabrication, and measurement of a novel rectangular nested fractal antenna tailored for multiband applications in diverse communication systems. The proposed antenna introduces a unique nested fractal geometry that optimizes resonant frequency allocation and enhances gain, a significant improvement over traditional fractal designs. With compact dimensions of 40×50×0.8 mm³, the antenna is fabricated using FR4 glass epoxy, a widely adopted dielectric material with a relative permittivity of 4.7 and a low loss tangent of 0.0197. Unlike conventional designs, this antenna achieves seven distinct resonant frequency bands at 1.99, 3.68, 4.91, 6.11, 7.60, 8.06, and 9.39 GHz, with corresponding bandwidths of 90, 80, 90, 100, 70, 22, and 210 MHz. Moreover, it demonstrates superior gains of 0.88, 2.18, 18.86, 8.89, 13.22, 12.24, and 4.01 dBi, surpassing prior designs in terms of performance consistency across multiple bands. The innovative nested fractal structure enhances multiband capabilities while maintaining a compact footprint, ensuring compatibility with emerging communication standards. Rigorous laboratory testing of the fabricated prototype confirmed the accuracy of simulated results, validating the antenna's high reliability and precision. These advancements make the proposed antenna a cutting-edge solution for applications including mobile communications, Wi-Fi, 5G, satellite communications, radar systems, and microwave communications

Influence of aluminium and tungsten impurities on reduced graphene oxide/zinc oxide nanocomposites humidity sensing performance

In this work, impurities-induced ZnO nanostructured powders were prepared via a benign, ultrasonicated low-temperature solution immersion method. The humidity sensor was constructed utilizing the nanocomposite consisting of the synthesized impurities-induced ZnO nanostructured powders with reduced graphene oxide by a facile brush printing procedure. This work intended to evaluate the effect of impurities on the formation of nanocomposite heterostructures for optimal humidity sensing properties and investigate their correlation with morphological, chemical, optical, and electrical characteristics. The characterization for morphological, chemical, and optical changes induced by Al and W impurities in the nanocomposites was conducted through XRD, HRTEM, EDS, Raman spectroscopy, XPS and DRS. The fabricated humidity sensors have been evaluated at room temperature to assess their sensor resistance ratio, sensitivity, sensing response, and other related humidity sensing performance at relative humidity levels ranging from 40 to 90%. The humidity sensor utilizing rGO/W:ZnO nanocomposite exhibited better resistance changes compared to rGO/ZnO. Corresponding to the nanocomposite formation between W:ZnO and rGO, the sensor resistance ratio and sensitivity improved significantly to 249.61 ± 0.97 and 12.67 ± 0.06 MΩ/%RH, respectively with the sensor establishing a maximum sensing response of 99.61 ± 0.02. Furthermore, the rGO/W:ZnO heterostructure-based humidity sensor demonstrated improved and lowest hysteresis error, long-term stability over 30 days, and reliable repeatability compared to other tested samples within the tested relative humidity range. The utilization of W:ZnO with rGO as sensing material provides a novel direction for designing a cost-effective and highly sensitive humidity monitoring sensor