Three-phase induction motors are the main elements for converting electrical energy into mechanical energy and are extensively used in industry. Reducing maintenance costs becomes an incentive for developing systems c...
详细信息
Three-phase induction motors are the main elements for converting electrical energy into mechanical energy and are extensively used in industry. Reducing maintenance costs becomes an incentive for developing systems capable of identifying defects. This research proposes a framework for recommending machine learning algorithms that diagnose and detect broken bar defects in three-phase induction motors under transient operation based on artificial intelligence. Employing experimental data, features were extracted and selected based on current, voltage, and vibration. A protocol of insertion of white noise showed that the proposed framework admitted 80% of noise without losing the predictive capacity based on a multicriteria performance measure.
Purpose: The purpose of this study was to create an air movement operations planning model to rapidly generate air mission request (AMR) assignment and routing courses of action (COA) in order to minimize unsupported ...
详细信息
Control Performance Assessment (CPA) is a critical endeavor in industrial processes, ensuring optimal functioning of control systems. Traditionally, CPA has been addressed through solutions using some control performa...
详细信息
Control Performance Assessment (CPA) is a critical endeavor in industrial processes, ensuring optimal functioning of control systems. Traditionally, CPA has been addressed through solutions using some control performance indicators. Nowadays, the integration of data science and machine learning has emerged as a viable alternative, particularly in classification tasks related to CPA. That is, in a binary classification scheme, the goal is to predict whether incoming data from the control loop belongs to class 0 or 1, representing the absence or presence of an anomaly (performance degradation). In such a case, a trade-of between false positives and false negatives should be obtained, via the training phase of a given supervised machine learning structure for example. Usually, this is a conflicting trade-of, where multi-objective optimization techniques in the training phase of such learners could bring interesting results. In this paper, we explore the usability of multi-objective optimization training in machine learning, for control performance assessment classification. A database describing 30 control performance indicators (features) in a PID control loop is used. The obtained results indicate that the proposed approach could bring interesting applications to improve the performance of CPA classification systems.
Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is...
详细信息
ISBN:
(数字)9798350353952
ISBN:
(纸本)9798350353969
Forest fires have a significant impact on ecosystems and human life, especially in northern Thailand, where Chiang Mai is severely affected. Traditional methods for detecting forest fires have limitations, so there is a need for advanced simulation models. This research uses Agent-Based Modeling (ABM) to develop a forest fire simulation for Chiang Mai. The methodology involves collecting historical data, performing Multiple Regression Analysis, designing the simulation, and testing it. Data from 1998 to 2021, including temperature, relative humidity, wind speed/direction, burn area, and slope, were collected from various sources. Multiple regression analysis identified wind speed as the most significant factor affecting burn area. The forest fire simulation, designed using ZF Wang's spread model and tested with AnyLogic, showed that wind direction and speed are crucial in fire spread. The simulation accurately predicted high-risk areas, helping in proactive planning and response. This study confirms that wind is a critical factor in forest fire spread, providing a valuable tool for fire districts to improve preparedness and management. Future research should focus on refining the model with localized data and integrating real-time detection to improve its accuracy and applicability.
Online games display a unique market with a promising economy; hence many developer companies are exploring and have been utilizing this technology because of good possibility in recent years. This study aimed to dete...
详细信息
ISBN:
(纸本)9798400700095
Online games display a unique market with a promising economy; hence many developer companies are exploring and have been utilizing this technology because of good possibility in recent years. This study aimed to determine the composition of online game attribute that is most preferred by customers using a Conjoint Analysis Approach. This study utilized different attributes such as graphics, player-to-player interaction, character creation freedom, game accessibility, monetization, storyline, and business model. An orthogonal design of conjoint analysis was utilized to assess customer preference for online games. A survey was proposed to a community of online game players and segmented among their gender, age, and income. The results showed that business model was the most considered attribute while accessibility and monetization were the least preferred. The findings of this study could be beneficial to both technology corporations developing products that fit their target customers and customers making most of their investment.
Internet has evolved from a basic communication medium into wide networks of communication networks where it has become integrated in people's daily lives. Not only that, because of the recent pandemic, the demand...
详细信息
ISBN:
(纸本)9798400700095
Internet has evolved from a basic communication medium into wide networks of communication networks where it has become integrated in people's daily lives. Not only that, because of the recent pandemic, the demand for internet has been rapidly increasing. With the integration of internet to our day to day interactions, choosing a provider that is inclined with consumers preference and usage should be the basis. This study aims to determine the Filipino consumer preference on choosing Fixed line internet service providers using Conjoint analysis. The method uses survey questionnaires that is disseminated across the regions of the Philippines. The data gathered from the survey are analyzed using SPSS. The result shows that out of all the attributes considered internet speed is the top priority of the consumers followed by pricing and brand. Overall, this study is beneficial in developing market strategies for companies in the telecommunications industry.
Welding is both as art and science and its common use is the jointing of points. Some of the welding procedures used for jointing metal pipes are Tungsten Inert Gas and Gas Metal Arc welding and in common practice pla...
详细信息
ISBN:
(数字)9798350386097
ISBN:
(纸本)9798350386103
Welding is both as art and science and its common use is the jointing of points. Some of the welding procedures used for jointing metal pipes are Tungsten Inert Gas and Gas Metal Arc welding and in common practice plastic pipes are bonded with the use of butt-fusion welding procedure. Since 1970’s conjoint analysis was used as a way of finding out what the preference of consumers. The objective of this study is to determine the combination welding attributes that were most preferred using a conjoint analysis approach. With conjoint analysis, together with, the orthogonal design the preference for welding materials and procedures were analyzed. It showed that pipe material with 29.24% was the most preferred attribute and Non-destructive test as the least preferred with $\mathbf{2. 6 6 \%}$. The result of this study may be utilized in future related reviews and could be applicable in other related Mechanical systems requiring welding works.
This study aimed to examine the factors influencing the acceptance of eLearning platforms in medical education during the COVID-19 pandemic in the Philippines, using the latent variables from the Unified Theory of Acc...
详细信息
ISBN:
(数字)9798350386097
ISBN:
(纸本)9798350386103
This study aimed to examine the factors influencing the acceptance of eLearning platforms in medical education during the COVID-19 pandemic in the Philippines, using the latent variables from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and two additional variables derived from relevant literature. A total of $\mathbf{3 6 0}$ medical students participated by completing an online survey comprising 40 questions. The analysis, conducted using stepwise multiple linear regression, revealed that Performance Expectancy (PE), Habit (HB), and Instructor Characteristics (IC) were significant predictors of Actual Use (AU) with an accuracy of 54.22%. Higher levels of PE, HB, and IC were found to positively influence the acceptance and utilization of medical eLearning platforms. The findings from this study can provide valuable insights for the Commission on Higher Education in the Philippines, aiding in the enhancement of eLearning platforms for medical education. Although this research primarily focused on UTAUT2 and two additional variables-Learning Value and Instructor Characteristicsthe results offer substantial implications for the broader development f eLearning platforms in the medical field.
The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This prelimi...
详细信息
ISBN:
(数字)9798350353952
ISBN:
(纸本)9798350353969
The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness.
Multi-channel speech separation has been successfully applied in a complex real-world environment such as the far-field condition. The common solution to deal with the far-field condition is using a multi-channel sign...
详细信息
暂无评论