Results (1696)
Search Parameters:
Keyword: FFDigitalization Review for American SMEs
SME big data maturity models will be reviewed in this study to identify systematic publications related to the subject. For SMEs to remain competitive, digitalization is essential. Due to limited resources, SMEs need to be more proactive in digitalization. Still, the benefits, such as operational efficiency, cost reduction, quality improvement, and innovative culture, make digitalization…
Read MoreIoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring
Gas leakage caused by various causes poses significant risks to public safety. To address this problem, an intelligent model is proposed for the accurate monitoring of Liquefied Petroleum Gas (LPG) distribution based on the integration of Internet of Things (IoT) and Business Intelli- gence (BI) technologies. Through the use of sensors and actuators, it seeks…
Read MoreEarly Detection of SMPS Electromagnetic Interference Failures Using Fuzzy Multi-Task Functional Fusion Prediction
This study addresses the need for improved prognostics in switch-mode power supplies (SMPS) that incorporate electromagnetic interference (EMI) filters, with a focus on aluminum electrolytic capacitors, which are critical for the reliability of these systems. The primary aim is to develop a robust model-based approach that can accurately predict the degradation and operational lifetime of…
Read MoreGPT-Enhanced Hierarchical Deep Learning Model for Automated ICD Coding
In healthcare, accurate communication is critical, and medical coding, especially coding using the ICD (International Classification of Diseases) standards, plays a vital role in achieving this accuracy. Traditionally, ICD coding has been a time-consuming manual process performed by trained professionals, involving the assignment of codes to patient records, such as doctor’s notes. In this paper,…
Read MoreHybrid Optical Scanning Holography for Automatic Three-Dimensional Reconstruction of Brain Tumors from MRI using Active Contours
This paper presents a method for automatic 3D segmentation of brain tumors in MRI using optical scanning holography. Automatic segmentation of tumors from 2D slices (coronal, sagittal and axial) enables efficient 3D reconstruction of the region of interest, eliminating the human errors of manual methods. The method uses enhanced optical scanning holography with a cylindrical…
Read MoreFrom Sensors to Data: Model and Architecture of an IoT Public Network
RetePAIoT of Emilia-Romagna region is an IoT Public Network, financed by Emilia-Romagna Region and developed by Lepida Scpa, where citizens, private companies and Public Administrations can integrate free of charge their own sensors of any type and anywhere in the region. The main objective of the project is to provide a facility to implement the…
Read MoreDeploying Trusted and Immutable Predictive Models on a Public Blockchain Network
Machine learning-based predictive models often face challenges, particularly biases and a lack of trust in their predictions when deployed by individual agents. Establishing a robust deployment methodology that supports validating the accuracy and fairness of these models is a critical endeavor. In this paper, we introduce a novel approach to deploying predictive models, such as…
Read MoreLeveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity
Polyfluoroalkyl substances (PFAS) are persistent chemicals that accumulate in the body and environment. Although recent studies have indicated that PFAS may disrupt kidney function, the underlying mechanisms and overall effects on the organ remain unclear. Therefore, this study aims to elucidate the impact of PFAS on kidney health using machine learning techniques. Utilizing a dataset…
Read MoreSolar Photovoltaic Power Output Forecasting using Deep Learning Models: A Case Study of Zagtouli PV Power Plant
Forecasting solar PV power output holds significant importance in the realm of energy management, particularly due to the intermittent nature of solar irradiation. Currently, most forecasting studies employ statistical methods. However, deep learning models have the potential for better forecasting. This study utilises Long Short-Term Memory (LSTM), Gate Recurrent Unit (GRU) and hybrid LSTM-GRU deep…
Read MoreEvaluation of Various Deep Learning Models for Short-Term Solar Forecasting in the Arctic using a Distributed Sensor Network
The solar photovoltaic (PV) power generation industry has experienced substantial, ongoing growth over the past decades as a clean, cost-effective energy source. As electric grids use ever-larger proportions of solar PV, the technology’s inherent variability—primarily due to clouds—poses a challenge to maintaining grid stability. This is especially true for geographically dense, electrically isolated grids common…
Read MoreAn Adaptive Heterogeneous Ensemble Learning Model for Credit Card Fraud Detection
The proliferation of internet economies has given the corporate world manifold advantages to businesses, as they can now incorporate the latest innovations into their operations, thereby enhancing ease of doing business. For instance, financial institutions have leveraged credit card usage on the aforesaid proliferation. However, this exposes clients to cybercrime, as fraudsters always find ways…
Read MoreMalaysia’s Renewable Energy Policy and its Impact on ASEAN Countries
As the global community increasingly shifts its focus towards sustainable development and combating climate change, renewable energy policies have become pivotal in shaping national and regional energy landscapes. Malaysia, as a developing nation with a rapidly growing economy, has recognized the importance of renewable energy sources in achieving its socio-economic goals while addressing environmental concerns.…
Read MoreButon Rock Asphalt Paving Block Innovation using Waste Engine Oil and Recycled Concrete Aggregate
Road surface coating using concrete paving block cement has been used for a long time. As an aggregate binding agent, asphalt can be made into paving blocks. Utilizing waste in the recycling process is an activity to control the sustainability of natural resources. Waste Engine Oil and Recycled Concrete Aggregate can be used as road…
Read MoreSpatial Distribution Patterns of the Royal Development Projects Initiated by King Rama 9th of Thailand
The study aimed to create a chronological overview of the royal development projects initiated by King Rama IX and to analyze their spatial distribution patterns. The research used a mixed-methods approach, combining quantitative and qualitative data collection methods such as obtaining data from relevant offices, internet research, and field observations. Data analysis involved descriptive statistics…
Read MoreDouble-Enhanced Convolutional Neural Network for Multi-Stage Classification of Alzheimer’s Disease
Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…
Read MoreOptimal Engagement of Residential Battery Storage to Alleviate Grid Upgrades Caused by EVs and Solar Systems
The integration of distributed energy resources has ushered in a host of complex challenges, significantly impacting power quality in distribution networks. This work studies these challenges, exploring issues such as voltage fluctuations and escalating power losses caused by the integration of solar systems and electric vehicle (EV) chargers. We present a robust methodology focused on…
Read MoreDevelopment of a GSM-RC Automated Device for Measuring Mobile Communication Signal Strength and Meteorological Parameters
The automated Global System for Mobile Communication Signal Strength and Radio Climatological (GSM-RC) measuring device is an integration of different electronic sensors in a box for an in-situ measuring system. The sensor, data logging, and communication subsystems are integrated for transmitting information on meteorological parameters (MPs) and GSM signal strength level (SSL). The goal is…
Read MoreInvestigating Heart Rate Variability Index Classification in Macaca fascicularis and Humans: Exploring Applications for Personal Identification and Anonymization Studies
In this paper, we determine the feasibility of differentiating between the heart rate patterns of Macaca fascicularis and human infants by comparing pertinent hyperparameters. This verification process was undertaken to ascertain the suitability of Macaca fascicularis heart rate data as a testbed for evaluating heart rate parameter privacy safeguarding methodologies. The biological characteristics of Macaca…
Read MoreA Novel Metric for Evaluating the Stability of XAI Explanations
Automated systems are increasingly exerting influence on our lives, evident in scenarios like AI-driven candidate screening for jobs or loan applications. These scenarios often rely on eXplainable Artificial Intelligence (XAI) algorithms to meet legal requirements and provide understandable insights into critical processes. However, a significant challenge arises when some XAI methods lack determinism, resulting in…
Read MoreSmart Agent-Based Direct Load Control of Air Conditioner Populations in Demand Side Management
The integration of fluctuating renewable resources such as wind and solar into existing power systems poses challenges to grid reliability and the seamless incorporation of these resources. To address the inherent variability in renewable generation, direct load control emerges as a promising method for demand-side management. Thermostatically controlled appliances, like air conditioners, hold a significant…
Read MoreBridging Culture and Care: A Mobile App for Diabetes Self-Care Honoring Native American Cultural Practices
Diabetes presents a significant public health issue for Native Americans, exacerbated by cultural nuances often ignored by conventional healthcare. To address this, we introduce a mobile app designed with the cultural context of Native American populations in mind. The app’s development followed participatory design principles, with direct input from Native American stakeholders through focus groups…
Read MoreDevelopment and Usability Evaluation of Mobile Augmented Reality Contents for Railway Vehicle Maintenance Training: Air Compressor Case
The air compressor of a railroad vehicle is an important equipment that produces compressed air used in braking systems. New visual interaction techniques were proposed and evaluated to develop effective augmented reality content for maintenance support and training of this device. To this end, modeling techniques capable of fast animation, storyboard production to support light…
Read MoreTracing the Evolution of Machine Translation: A Journey through the Myanmar (Burmese)-Wa (sub-group of the Austro-Asiatic language) Corpus
Machine Translation (MT) has come a long way toward reducing linguistic gaps. However, its progress in efficiently handling low-resource languages—such as the Wa language in the Myanmar-Wa corpus—has not received enough attention. This study begins with a thorough investigation of the historical development of MT systems, painstakingly following their development against the complex background of…
Read MoreEnhancing Compressive Strength of Pervious Concrete for Use as Pavement Layer in Urban Roads Aper
South African Drainage and Stormwater Systems in urban roads has been of great concern, more so with recent flash floods in Gauteng and KwaZulu Natal Province in South Africa. Pervious concrete can be used to mitigate these challenges for urban roads. Pervious concrete is a concrete that contains no fines or only a small amount…
Read MoreAnalysis of Emotions and Movements of Asian and European Facial Expressions
The aim of this study is to develop an advanced framework that not only recognize the dominant facial emotion, but also contains modules for gesture recognition and text-to-speech recognition. Each module is meticulously designed and integrated into unified system. The implemented models have been revised, with the results presented through graphical representations, providing prevalent emotions…
Read More
