This paper investigates the applications of Chat-GPT, a state-of-the-art language model, in the field of applied software project management. Chat-GPT, developed by OpenAI, is a generative AI model that has demonstrated remarkable advancements in natural language processing and generation of text-based output. This paper aims to highlight the potential uses of Chat-GPT in project management, including communication, risk management, resource allocation, and decision-making. By leveraging the capabilities of generative AI in language models, Chat-GPT offers innovative solutions for project management challenges. This paper also discusses the benefits and challenges associated with integrating Chat-GPT into project management workflows. Through this exploration, we shed light on how Chat-GPT can enhance project management practices, streamline communication processes, and improve overall project throughput and outcomes. The research findings provide valuable insights for practitioners and organizations seeking to harness the power of generative AI in applied project management.
In this paper, we present a performance evaluation of PID controller gains for angle control of drones. The primary objective is to optimize the PID gains to enhance the performance of the drone. The proposed solution is named Adaptive PID flight controller for controlling the altitude dynamics of a UAV. This approach is based on three comparisons: Firstly, we compare the use of a single PID controller for all three angles. Secondly, we explore the option of using two PID controllers for the three angles, where the first controller is designed to con-trol the Pitch and Roll angles, while the second controller is dedicated to the Yaw angle. Finally, we use three PID controllers for each angle (Pitch, Roll and Yaw). Our ultimate aim is to identify the most effective PID controller configuration that optimizes drone angle control, leading to improved sta-bility, responsiveness, and accuracy during flight.
Scientific research is increasingly reliant on computational methods, posing challenges for ensuring research reproducibility. This study focuses on the field of artificial intelligence (AI) and introduces a new framework for evaluating AI platforms for reproducibility from a cyber security standpoint to address the security challenges associated with AI research. Using this framework, five popular AI reproducibility platforms—Floydhub, BEAT, Codalab, Kaggle, and OpenML—were assessed. The analysis revealed that none of these platforms fully incorporates the necessary cyber security measures essential for robust reproducibility. Kaggle and Codalab, however, performed better in terms of implementing cyber security measures covering aspects like security, privacy, usability, and trust. Consequently, the study provides tailored recommendations for different user scenarios, including individual researchers, small laboratories, and large corporations. It emphasizes the importance of integrating specific cyber security features into AI platforms to address the challenges associated with AI reproducibility, ultimately advancing reproducibility in this field. Moreover, the proposed framework can be applied beyond AI platforms, serving as a versatile tool for evaluating a wide range of systems and applications from a cyber security perspective.
This study evaluates the Modified Firefly Algorithm (MFA), an advanced optimization technique that integrates processes like Constraint Satisfaction, Hamming Distance, objective function filtering, and positional adjustment. The MFAs were assessed based on solution quality, computational efficiency, and performance in complex optimization problems. A meta-optimization process fine-tuned its parameters, improving solution quality. Despite longer computation times, the MFA outperformed other Firefly Algorithm variants in solution quality and adaptability. The study demonstrated the MFA's effectiveness in a real-world staff scheduling scenario, making it promising for similar problems in various domains. Despite challenges in computation time, the study underscores the trade-off for enhanced solution quality and the potential for further refinement highlights the benefits of enhanced solution quality, and recommends exploring varying n values and comparing them with other advanced optimization algorithms for future research.
This study aimed to determine whether the pre-laboratory discussion video enhances and determines possible indicators of the enhancement of laboratory performance among the actual 27 participants in one Grade 9 class of Xavier University Junior High School. Moreover, the study aims to know how were the experiences of students and teachers with the integration of the EdPuzzle discussion video, and learning how the results of the study help the community to further improve the laboratory procedures enhancement of Grade 9 students in a hybrid mode of learning. This study employed the mixed method design which is the combination of qualitative and quantitative approach to collect and analyze data. As for the sampling procedure, this study uses a purposive sampling, where the respondents of this study were selected on a specific grade level and section. Based on the results, there was an increase in test score results from pretest in which there are those who failed and to the post-test in which all passed. Moreover, there was a “significant difference “ between the pretest and posttest data through the T-test results and the FGD responses through thematic analysis. Through the utilization of the EdPuzzle discussion, students' interests increased in conducting more experiments in order to understand in depth the world around us. In addition to this, students’ test scores have a congruence to the performance rubric results. Prior to performing the experiment, students can be prepared by watching the EdPuzzle pre-laboratory discussion video and learning technical terms, equipment, and laboratory procedures. Hence, pretest and post-test scores improvement, good performance rubric results, rejection of the null hypothesis, and no groups required for experiment repetition, indicates conceptual and procedural knowledge retention of the students. It is recommended that the EdPuzzle pre-laboratory discussion be used in laboratory experiments in Xavier University Junior High School.
This study examines the effects of changing Young's modulus on mode shapes and natural frequencies in an airplane model, with an emphasis on Carbon fiber reinforced polymer (CFRP) for airplane fuselage and Aluminum alloy 7075-T6 (Al 7075-T6) for airplane wings. The study examines the effects of changed Young's Modulus while maintaining other parameters constant using NX Nastran simulation. Taguchi analysis is used to find the best material configurations for increasing Signal-to-Noise Ratios (SNRs) in a variety of aerodynamic modes. The study uses one-way Analysis of Variance (ANOVA) to statistically assess Young's Modulus's impact on mode values. The results show that Young's Modulus modifications cause different differences in mode shapes and natural frequencies. Notably, Mode 2 is highly responsive to Young's Modulus changes in both materials, emphasizing its importance in design optimization. These findings highlight the possibility of precisely influencing dynamic behavior through tailored material selection, providing valuable insights for aerospace design. Such insights are important for optimizing mode shapes and frequencies, which will ultimately improve aircraft performance and reliability.
Pulse Width Modulation (PWM), as it applies to Electric Motor Control, is a way of delivering energy through a succession of pulses rather than a continuously varying (analogue) signal. By increasing or decreasing the pulse width, the microcontroller regulates the energy flow into the motor shaft. The motor’s own inductance acts like a filter, storing energy during the “on” cycle while releasing it at a rate corresponding to the input or reference signal. In this project, Pulse Width Modulation (PWM) technique was used for controlling the speed of the Single Phase Induction Motor. This was achieved by programming a microcontroller AT89C52, using embedded C language to produce PWM pulses according to the switching of buttons, achieved wirelessly, using 433.92MHz Transmitter and Receiver.
Textbooks are almost the only learning materials for many reasons in Afghanistan and Iran that are have been using by both teachers and students during learning and teaching process. Consequently, when girls and boys enter the school environment, the portrayal of females and males in textbooks, shape their identity of gender roles and influence their attitudes. Furthermore, textbooks have great importance for the formation of the world perception of the child thorough education. Therefore, this research compares gender representation in current social studies textbooks that are designed by Ministry of Education and are teaching as an obligatory subject in both countries; Iran and Afghanistan primary schools. In the present study, two methods of analysis performed. First, quantitative method to measure the frequency of male and female portrayal in both text and illustration. Second, qualitative method, to analyze the values, and messages that text and illustration transmit to the users. Findings shows that there are significant gender biases in both countries’ social studies textbooks of primary school. As a result, the findings would help the stockholders and teachers to take the gender balance and equality in account, and might help the textbooks’ contributors to consider gender equality in the next revisions of textbooks.
Manual folding of t-shirts has long been recognized as a time-consuming task. In recent years, the rise of automation in systems and machinery has significantly contributed to increased productivity, reduced manual labor, and improved overall efficiency. With this, automated folding machines have emerged. The aim of this paper is to design and develop an Arduino-based automated T-Shirt folder that incorporates sensor integration and motor control. This study used ultrasonic sensors, servo motors, and the Arduino Uno microcontroller to fold t-shirts of various sizes. To complete the folding task successfully, the developed machine incorporates a feedback and control mechanism. The performance of developed T-Shirt folder was evaluated, assessing its folding speed. The results revealed that the machine can adeptly fold t-shirts of different sizes at an average speed of 8.16 seconds per shirt, reducing the time it takes for a human to perform the same task. This project exhibits promising potential for further refinement and potential application in the clothing industry.
First principle based, full potential linearized augmented plane-wave plus local-orbitals (FPLAPW+LO) density functional theory calculations are used to examine the thermodynamic and structural properties of Li3OI. The phase diagram of Li3OI is calculated via thermodynamic potentials that offered crucial information about stable synthesis of material. The obtained restriction of chemical atomic potential values of Li, I and O provides information about stable synthesis of Li3OI. Our calculated results clarify the background of experimentally for the synthesis of Li3OI and related binary phases.