Association for Scientic Computing Electronics and Engineering (ASCEE): Open Journal Systems
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Smart Healthcare Framework: Real-Time Vital Monitoring and Personalized Diet and Fitness Recommendations Using IoT and Machine Learning
Full text linkAdopting a healthy lifestyle necessitates a well-balanced nutritional plan and personalized exercise routines aligned with an individual's health status. The healthcare system often lacks personalized care, leading to weak prevention and generic diets. This study presents an IoT-based framework for easy health monitoring without frequent doctor visits. The system integrates sensors to measure vital indicators like pulse rate, body temperature, SpO?, and BMI, with minimal assistance from healthcare personnel. Utilizing data gathered from individuals aged 16–25, ML algorithms like Logistic Regression, Random Forest, and KNN analyze the parameters to deliver personalized dietary and fitness recommendations. The dataset includes BMI, body temperature, pulse rate, and SpO2 measurements gathered via an integrated IoT unit. Before analysis, the data was refined and optimized through ML algorithms. This comprehensive approach moves beyond traditional diagnostic methods by incorporating personalized recommendations, including dietary plans and exercise routines, tailored based on the evaluated data. Among the evaluated algorithms, Random Forest demonstrated the highest accuracy (99%) in a 60:40 training-to-testing ratio. To improve accessibility, a user-friendly web platform is designed, facilitating seamless interaction and engagement. The framework unifies real-time monitoring, cardiovascular risk detection, and adaptive guidance, bridging fragmented digital health solutions for early intervention and better health outcomes
Millimeter-wave microstrip antenna with enhanced gain for dual-band 26 /29 GHz operation
Full text linkThis paper suggests a dual-band rectangular patch antenna design and presents analysis of the radiation performance metrics for its operation and application in the 26 and 29 GHz millimeter-wave 5G mobile communication. To achieve antenna’s hign gain and improved radiation performance, the design includes a rectangular loop and two L-sloted patch and defective ground structure (DSG). The antenna is excited using 50 Ω inset feed line and modeled in CST Studio Suite. The simulation results show that the designed small sized 22.5×18.5 mm2 antenna offers improved super high gain of 9 dB and 11.39 dB and directivity of 9.49 dBi and 12.06 dBi at 26 and 29 GHz mmWave bands. Moreover, the antenna offers minimum reflection coefficient, acceptable VSWR and very good efficiency of 94.83% at 26 GHz, whilst of 94.44% at 29GHz, respectively. These findings along with its compact design suggest that the projected patch antenna would be a be a good choice for the development of high gain dual-band antenna for 5G mmWave mobile system
Neural Network Architectures for UAV Path Planning: A Comparative Study with A* Algorithm as Benchmark
Full text linkAutonomous path planning for Unmanned Aerial Vehicles (UAVs) plays a critical role in applications ranging from disaster response to urban logistics. Traditional algorithms, such as A*, are widely recognized for their reliability in generating collision-free and efficient trajectories but often struggle with scalability in complex and dynamic environments. This study evaluates the performance of several neural network architectures, including MLP-LSTM, CNN-GRU, CNN-LSTM, CNN BILSTM, and others, as potential alternatives to classical methods. A dataset of trajectories generated by the A* algorithm was used to train and benchmark the models, enabling direct performance comparison across key metrics such as path length, smoothness, clearance, collisions, and waypoint density. The results demonstrate that the MLP-LSTM model outperforms other neural architectures, producing paths that closely resemble A* trajectories with high smoothness and waypoint granularity. While some models, such as CNN-GRU and CNN-BILSTM, show promise in generating feasible paths, their performance is inconsistent across different UAV scenarios. Models like Residual CNN and Hybrid CNN-MHA failed to generate meaningful trajectories, highlighting the critical importance of architectural choices. This study underscores the potential of neural network models for UAV path planning
Self-Motion Control Exoskeleton for Upper Limb Rehabilitation with Perceptron Neuron Motion Capture
Full text linkUpper limb rehabilitation robot can facilitate patients to regain their original impaired arm function and reduce therapist’ workload. However, the patient does not have a direct control over his/ her arm movement, which may lead to discomfort or even injury. This paper focuses on the development of a self-motion rehabilitation robot using Perception Neuron motion capture, where the movement of the impaired arm imitates the motion of the healthy limb. The Axis Neuron software receives the healthy upper limb’s motion data from Perception Neuron. Unity serves as the simulation engine software that provides a 3-dimensional animation. ARDUnity acts as the communication platform between Unity software with Arduino. Arduino code is generated using Wire Editor, which avoids the need of the programming to be written in C++ or C#. Finally, Arduino instructs the exoskeleton motors that are connected to the impaired arm to move, following the healthy joint’s motion. The forward kinematics analysis for the robotic exoskeleton has been carried out to identify its workspace. Hardware experimental tests on the elbow and wrist flexion/ extension have shown the root-mean-square errors (RMSE) between the healthy and impaired arms movement to be 1.5809○ and 12.1955○ respectively. The average time delay between the healthy and impaired elbow movement is 0.1 seconds. For the wrist motion, the time delay is 1 second. The experimental results verified the feasibility and effectiveness of the Perception Neuron in realizing the self-motion control robot for upper limb rehabilitation. The proposed system enables the patients to conduct the rehabilitation therapy in a safer and more comfortable way as they can directly adjust the speed or stop the movement of the affected limb whenever they feel pain or discomfort
Two-Flexible-Link Manipulator Vibration Reduction Through Fuzzy-Based Position
Full text linkThe increasing demand for robotic applications has emphasized the need for advanced control strategies, particularly for flexible manipulators with lightweight links. These manipulators offer advantages such as reduced energy consumption, increased payload capacity, and precise high-speed operation but face challenges due to oscillations and delays caused by their flexibility. This study evaluates the performance of Fuzzy Logic Control (FLC) and Linear Quadratic Regulator (LQR) techniques for a Quanser two-link flexible manipulator, using quantitative metrics to compare their effectiveness. The LQR controller was implemented using state-space modeling, with weighting matrices Q and R tuned to achieve minimal overshoot and fast settling times. The FLC system employed five triangular membership functions for inputs and outputs, covering normalized ranges of [-1, 1] for angular errors and [-2.75, 2.75] for error rates, with a heuristic rule base designed to optimize performance. Simulations were conducted under step input conditions at target angles of 30° and 60°, with performance evaluated using vibration amplitude, settling time, steady-state error, and overshoot. Quantitatively, the LQR controller reduced vibration amplitudes to 5 radians for a 30° input and achieved settling times of approximately 2 seconds. For the same conditions, the FLC system reduced vibrations further to 4 radians, though with slightly longer settling times of around 2.3 seconds. At a 60° input, LQR vibrations peaked at over 10 radians, while FLC maintained peak vibrations at approximately 4 radians. These results highlight the FLC’s superior vibration suppression, particularly at higher input angles, albeit with marginally slower response times. However, the study was limited to idealized simulation conditions and requires further experimental validation. This research underscores the trade-offs between LQR’s precision and FLC’s adaptability, emphasizing the importance of parameter tuning and system modeling in achieving optimal performance for flexible manipulators
Global Existence for Heat Equation with Nonlinear and Damping Piecewise Neumann Boundary Condition
Full text linkThe Columbia space shuttle catastrophe in 2003 served as the inspiration for this paper’s improved mathematical model, which includes a nonlinear damping Neumann boundary condition. By creating and examining a modified heat equation with piecewise nonlinear source terms and damping Neumann boundary conditions, the study seeks to investigate the incident’s heat transport dynamics. To ensure that the problem is well-posed, we provide strong mathematical arguments for the existence of solutions both locally and globally. In addition, we use numerical simulations to show how the nonlinear boundary conditions affect heat dissipation and to confirm the theoretical results. The findings advance our knowledge of thermal modeling in aircraft applications and offer greater insights into heat propagation under such conditions
Collision Avoidance in Mini Autonomous Electric Vehicles Using Artificial Potential Fields for Outdoor Environment
Full text linkThe rapid advancement of technology is driving the transition toward Society 5.0, where intelligent transportation systems enhance safety, efficiency, and sustainability. One of the biggest challenges in transportation is the high frequency of vehicle accidents, with approximately 80% attributed to driver error. To mitigate this, Advanced Driver Assistance Systems (ADAS) have been developed to improve vehicle autonomy and reduce accidents. This research proposes a potential field-based collision avoidance system for autonomous vehicle navigation, where the vehicle and obstacles act as positive poles, repelling each other, while the target destination serves as a negative pole, attracting the vehicle. Experimental results demonstrate a GPS positioning error of 1.55 m with a 66% success rate and LiDAR sensor accuracy of 96.4%, exceeding the required 95% threshold. Obstacle avoidance was tested with two safety thresholds (2 m and 2.5 m) across single- and two-obstacle scenarios. The 2 m threshold resulted in shorter travel distances (16.406 m vs. 16.535 m for 2.5 m) and faster completion times (19.036 s vs. 19.144 s), while the 2.5 m threshold provided greater clearance. GPS accuracy was significantly influenced by HDOP values and satellite count, with lower HDOP improving trajectory precision. The system successfully adjusted its trajectory in response to obstacles, ensuring effective real-time navigation
Illustration process in visual communication: a qualitative study on storybook product development
No full textThe illustration process in visual communication design plays a critical role in supporting product development; however, there remains a lack of systematic and empirical studies that examine its practical stages within the design research context, particularly in the field of storybook illustration. This study aims to identify and describe the stages of the illustration process specifically applied in the development of storybook products. A qualitative descriptive case study approach was used, with data collected through literature review, in-depth interviews with four professional illustrators, and document analysis. The data were analyzed using content analysis techniques to extract patterns of practice and define the illustration workflow. The findings reveal an integrated, eleven-stage illustration process that includes narrative exploration, concept development, sketching, refinement, visual enhancement, layout, validation, and final presentation. This process is shown to be iterative, reflective, and context-sensitive, rather than strictly linear. The study contributes a structured conceptual model of the illustration process in design practice, providing theoretical insights and a practical reference for researchers, educators, and practitioners in visual communication design
Political aestheticization in the representation of Balinese selonding gamelan: between cultural practices and identity strategies
Full text linkSelonding Gamelan in Tenganan Pegringsingan Village, Bali, plays an important role in the traditional Mekaré-kare ritual and represents the close relationship between art and the social structure of the local community. This study aims to reveal how the aesthetics of Selonding Gamelan are mobilized as a symbolic strategy in responding to external influences on the local cultural order. Using ethnographic and participatory observation methods, especially in the context of the Mekaré-kare ritual, this study finds that Selonding Gamelan not only functions as a musical instrument, but also as a cultural medium that dampens elements of violence, negotiates identity, and strengthens social cohesion. Gamelan aesthetics are used consciously as a mechanism for protecting customary values against external cultural intervention. The conclusion of this study shows that ritual art has a transformative power in shaping the collective identity and cultural sovereignty of traditional communities. These findings open up new space for studying the relationship between art, ritual, and politics in the study of Nusantara performing arts
Study and Analysis of PWM with DC-DC Converter for Inverting Buck-Boost Inverter Topology
Full text linkThe simulation aims to study and analyze the effect of the duty cycle on the output voltage and signal reflection. This type of simulation is important for many practical applications of inverter boost converters, such as renewable energy systems or portable electronics. A voltage converter is being developed to generate a negative voltage output, i.e., it has the ability to invert the output signal. The converter's input is connected to a DC voltage source, and is intended to generate a higher or lower voltage, depending on the application requirements, while maintaining the inverting output signal. This converter is used in many fields, most notably those powered by batteries, such as portable devices, where the required voltage varies depending on the load. Converters regulate and provide a stable and suitable voltage for the batteries. A study and analysis of these converters will address these challenges by building and designing a simulation model to generate a voltage suitable for covering the load or charging the batteries, operating efficiently and reliably under various operating conditions. Its effectiveness can be verified through proposed tests covering operating conditions suitable for real-time operation. The first contribution is to verify the possibility of changing the converter output signal to the same value as the converter output voltage during the pulse generator duty cycle (50%). The second contribution is to verify the possibility of increasing the value of the converter output voltage in the pulse generator duty cycle (70%) or decreasing the value of the converter output voltage in the pulse generator duty cycle (20%). The results demonstrated the effectiveness of the proposed model and the possibility of changing the output voltage value with changing the output signal