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Applied System Innovation, Volume 8, Issue 2

2025 April - 31 articles

Cover Story: Can artificial intelligence help predict deaths linked to metabolic and endocrine diseases? This study presents explainable machine learning models trained on geolocalized air pollution data across Italy. By linking environmental exposures to regional mortality outcomes, this study offers a transparent, data-driven approach to understanding how pollutants contribute to endocrine, nutritional, and metabolic conditions. The integration of explainability strengthens trust and interpretability, marking a key step toward actionable, AI-powered public health strategies. View this paper
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Articles (31)

  • Article
  • Open Access
1 Citations
2,760 Views
46 Pages

Design, Manufacturing, and Electroencephalography of the Chameleon-1 Helmet: Technological Innovation Applied for Diverse Neurological Therapies

  • Asaf J. Hernandez-Navarro,
  • Gerardo Ortiz-Torres,
  • Alan F. Pérez-Vidal,
  • José-Antonio Cervantes,
  • Felipe D. J. Sorcia-Vázquez,
  • Sonia López,
  • Moises Ramos-Martinez,
  • R. E. Lozoya-Ponce,
  • Néstor Fernando Delgadillo Jauregui and
  • Reyna I. Rumbo-Morales
  • + 1 author

Brain activity plays a fundamental role in science and technology, particularly in the advancement of cognitive process therapies. Gaining a deeper understanding of brain function can contribute to the development of more effective therapeutic strate...

  • Article
  • Open Access
5 Citations
6,925 Views
25 Pages

The protection of personally identifiable information (PII) is being increasingly demanded by customers and governments via data protection regulations. Private and public organizations store and exchange through the Internet a large amount of data t...

  • Article
  • Open Access
2 Citations
3,652 Views
30 Pages

Bike-sharing initiatives play a crucial role in sustainable urban transportation, addressing vehicular congestion, air quality issues, and sedentary lifestyles. However, the connection between bike-sharing facilities and the advantages perceived by u...

  • Article
  • Open Access
3 Citations
2,949 Views
23 Pages

New Framework for Human Activity Recognition for Wearable Gait Rehabilitation Systems

  • A. Moawad,
  • Mohamed A. El-Khoreby,
  • Shereen I. Fawaz,
  • Hanady H. Issa,
  • Mohammed I. Awad and
  • A. Abdellatif

This paper presents a novel Human Activity Recognition (HAR) framework using wearable sensors, specifically targeting applications in gait rehabilitation and assistive robots. The new methodology includes the usage of an open-source dataset. This dat...

  • Article
  • Open Access
5 Citations
7,304 Views
32 Pages

This research utilizes machine learning (ML), and especially deep learning (DL), techniques for efficient feature extraction of intrusion attacks. We use DL to provide better learning and utilize machine learning multilayer perceptron (MLP) as an int...

  • Article
  • Open Access
19 Citations
1,790 Views
18 Pages

In recent times, gas is becoming one of the most significant resources utilised worldwide. The continuous increase in demand requires an increase in the production and preparation of gas for further utilisation. Conventional sources cannot satisfy th...

  • Article
  • Open Access
1 Citations
2,089 Views
16 Pages

Distinction Between Interturn Short-Circuit Faults and Unbalanced Load in Transformers

  • Raul A. Ortiz-Medina,
  • David A. Aragon-Verduzco,
  • Victor A. Maldonado-Ruelas,
  • Juan C. Olivares-Galvan and
  • Rafael Escalera-Perez

Transformers are essential in electrical networks, and their failure can lead to the shutdown of a section or the entire grid. This study proposes a combination of techniques for early fault detection, distinguishing between small load imbalances and...

  • Article
  • Open Access
5 Citations
2,126 Views
16 Pages

In this study, we conducted experimental and numerical investigations of a Darrieus rotor with asymmetrical blades, which has two structural configurations—with and without horizontal parallel plates. Experimental tests were conducted in a wind...

  • Article
  • Open Access
1 Citations
1,527 Views
13 Pages

Predictive and Explainable Machine Learning Models for Endocrine, Nutritional, and Metabolic Mortality in Italy Using Geolocalized Pollution Data

  • Donato Romano,
  • Michele Magarelli,
  • Pierfrancesco Novielli,
  • Domenico Diacono,
  • Pierpaolo Di Bitonto,
  • Nicola Amoroso,
  • Alfonso Monaco,
  • Roberto Bellotti and
  • Sabina Tangaro

This study investigated the predictive performance of three regression models—Gradient Boosting (GB), Random Forest (RF), and XGBoost—in forecasting mortality due to endocrine, nutritional, and metabolic diseases across Italian provinces....

  • Review
  • Open Access
5 Citations
8,132 Views
22 Pages

Pixel Circuit Designs for Active Matrix Displays

  • Dan-Mei Wei,
  • Hua Zheng,
  • Chun-Hua Tan,
  • Shenghao Zhang,
  • Hua-Dan Li,
  • Lv Zhou,
  • Yuanrui Chen,
  • Chenchen Wei,
  • Miao Xu and
  • Baohua Jia
  • + 3 authors

Pixel circuits are key components of flat panel displays, including liquid crystal displays (LCDs), organic light-emitting diode displays (OLEDs), and micro light-emitting diode displays (micro-LEDs). Depending on the active layer material of the thi...

  • Article
  • Open Access
992 Views
21 Pages

This article considers the numerical solution of the direct and inverse problems of the gas lift process in oil production, described by a system of hyperbolic equations. The inverse problem is reduced to an optimal control problem, where the control...

  • Article
  • Open Access
3 Citations
3,626 Views
38 Pages

The increasing number and complexity of cyber–physical systems in vehicles necessitate a rigorous approach to identifying functional safety and cybersecurity hazards during the concept phase of product development. This study establishes a syst...

  • Article
  • Open Access
2 Citations
3,331 Views
24 Pages

Identification, Control, and Characterization of Peristaltic Pumps in Hemodialysis Machines

  • Cristian H. Sánchez-Saquín,
  • Jorge A. Soto-Cajiga,
  • Juan M. Barrera-Fernández,
  • Alejandro Gómez-Hernández and
  • Noé A. Rodríguez-Olivares

Peristaltic pumps represent a fundamental component of hemodialysis machines. They facilitate the transfer of fluids, particularly in the collection and treatment of blood. This study aims to improve pump precision and reliability by reducing steady-...

  • Article
  • Open Access
1 Citations
2,842 Views
19 Pages

SIFT-Based Depth Estimation for Accurate 3D Reconstruction in Cultural Heritage Preservation

  • Porawat Visutsak,
  • Xiabi Liu,
  • Chalothon Choothong and
  • Fuangfar Pensiri

This paper describes a proposed method for preserving tangible cultural heritage by reconstructing a 3D model of cultural heritage using 2D captured images. The input data represent a set of multiple 2D images captured using different views around th...

  • Article
  • Open Access
2 Citations
1,790 Views
32 Pages

The goal of this study was to construct a mathematical and computational model that accurately represents the complex, flexible movements and mechanics of an elephant’s trunk. Rather than serving as a biological study, the elephant trunk model...

  • Article
  • Open Access
2 Citations
8,970 Views
35 Pages

Data-driven organizations aim to control business decisions based on data. However, despite significant investments in digitalization, studies show that many organizations continue to face challenges in fully realizing the benefits of data. Existing...

  • Article
  • Open Access
3 Citations
2,666 Views
25 Pages

In the era of Industry 5.0, human-centric manufacturing necessitates deep integration between workers and intelligent workshop scheduling systems. However, the inherent variability in worker efficiency due to learning and forgetting effects poses cha...

  • Article
  • Open Access
6 Citations
5,052 Views
28 Pages

Multimodal AI and Large Language Models for Orthopantomography Radiology Report Generation and Q&A

  • Chirath Dasanayaka,
  • Kanishka Dandeniya,
  • Maheshi B. Dissanayake,
  • Chandira Gunasena and
  • Ruwan Jayasinghe

Access to high-quality dental healthcare remains a challenge in many countries due to limited resources, lack of trained professionals, and time-consuming report generation tasks. An intelligent clinical decision support system (ICDSS), which can mak...

  • Article
  • Open Access
10 Citations
4,012 Views
22 Pages

Integrating Artificial Intelligence (AI) and Extended Reality (XR) technologies into agriculture presents a transformative opportunity to modernize education and sustainable food production. Traditional agriculture training remains resource-intensive...

  • Article
  • Open Access
1 Citations
7,226 Views
24 Pages

Mood-Based Music Discovery: A System for Generating Personalized Thai Music Playlists Using Emotion Analysis

  • Porawat Visutsak,
  • Jirayut Loungna,
  • Siraphat Sopromrat,
  • Chanwit Jantip,
  • Parunyu Soponkittikunchai and
  • Xiabi Liu

This study enhances the music-listening experience and promotes Thai artists. It provides users easy access to Thai songs that match their current moods and situations, making their music journey more enjoyable. The system analyzes users’ emoti...

  • Article
  • Open Access
4 Citations
2,015 Views
18 Pages

Enhanced Grey Wolf Optimization for Efficient Transmission Power Optimization in Wireless Sensor Network

  • Mohamad Nurkamal Fauzan,
  • Rendy Munadi,
  • Sony Sumaryo and
  • Hilal Hudan Nuha

The Internet of Things (IoT) and Wireless Sensor Networks (WSNs) heavily rely on the lifetime of sensor nodes, which is inversely proportional to transmission power. Nodes with greater separation demand higher transmission power, while those closer t...

  • Article
  • Open Access
7 Citations
5,197 Views
20 Pages

Exploring Pre-Trained Models for Skin Cancer Classification

  • Abdelkader Alrabai,
  • Amira Echtioui and
  • Fathi Kallel

Accurate skin cancer classification is essential for early diagnosis and effective treatment planning, enabling timely interventions and improved patient outcomes. In this paper, the performance of four pre-trained models—two convolutional neur...

  • Article
  • Open Access
1 Citations
1,160 Views
20 Pages

We study the throughput and losses of a buffer with stochastically dependent service times. Such dependence occurs not only in packet buffers within TCP/IP networks but also in many other queuing systems. We conduct a comprehensive, time-dependent an...

  • Article
  • Open Access
2 Citations
4,408 Views
19 Pages

The adoption of Information Technologies in organizations is a crucial decision for growth, productivity, competitiveness, and even survival in an increasingly competitive market. It highlights the growing importance of automation solutions such as R...

  • Article
  • Open Access
2 Citations
2,896 Views
35 Pages

Split air conditioning units are crucial for ensuring the thermal comfort of buildings. Conventional scheduling or pre-timed system activities result in high consumption and wasted energy. This study proposes an intelligent control system for automat...

  • Article
  • Open Access
1 Citations
1,798 Views
17 Pages

This study adopted a socio-technical approach to optimizing key factors for implementing the ETHICS (Effective Technical and Human Implementation of Computer-based Systems) framework in long-term care. Accurate record-keeping by nurse aides is essent...

  • Article
  • Open Access
2,707 Views
33 Pages

Enhanced Hybrid Algorithms for Inverse Problem Solutions in Computed Tomography

  • Rafał Brociek,
  • Mariusz Pleszczyński,
  • Jakub Miarka and
  • Mateusz Goik

This article presents a method for solving the inverse problem of computed tomography using an incomplete dataset. The problem focuses on reconstructing spatial objects based on the data collected from transmitters and receivers (referred to as proje...

  • Article
  • Open Access
1,747 Views
15 Pages

Early Detection of Failing Lead-Acid Automotive Batteries Using the Detrended Cross-Correlation Analysis Coefficient

  • Thiago B. Murari,
  • Roberto C. da Costa,
  • Hernane B. de B. Pereira,
  • Roberto L. S. Monteiro and
  • Marcelo A. Moret

This work introduces a model for lead-acid battery health monitoring in automobiles, focusing on detecting degradation before complete failure. With the proliferation of electronic modules and increasing power demands in vehicles, along with enhanced...

  • Article
  • Open Access
5 Citations
2,574 Views
26 Pages

Fed-Hetero: A Self-Evaluating Federated Learning Framework for Data Heterogeneity

  • Aiswariya Milan Kummaya,
  • Amudha Joseph,
  • Kumar Rajamani and
  • George Ghinea

Federated learning (FL) enables deep learning models to be trained locally on devices without the need for data sharing, ensuring data privacy. However, when clients have uneven or imbalanced data distributions, it leads to data heterogeneity. Data h...

  • Article
  • Open Access
2 Citations
3,846 Views
18 Pages

Understanding Visual Attention to Button Design Utilizing Eye-Tracking: An Experimental Investigation

  • Katharina Gleichauf,
  • Verena Wagner-Hartl,
  • Gerald J. Ackner and
  • Stefan Pfeffer

As graphical user interfaces continue to become more complex; it is becoming increasingly important for user interface (UI) and user experience (UX) designers to understand how design elements influence user attention. This study investigates the imp...

  • Article
  • Open Access
1 Citations
1,226 Views
16 Pages

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under d...

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Appl. Syst. Innov. - ISSN 2571-5577