Journal Description
Applied System Innovation
Applied System Innovation
is an international, peer-reviewed, open access journal on integrated engineering and technology. The journal is owned by the International Institute of Knowledge Innovation and Invention (IIKII) and is published bimonthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), Inspec, and other databases.
- Journal Rank: CiteScore - Q1 (Applied Mathematics)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 24.7 days after submission; acceptance to publication is undertaken in 4.7 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.8 (2022);
5-Year Impact Factor:
3.0 (2022)
Latest Articles
A Global Overview of SVA—Spatial–Visual Ability
Appl. Syst. Innov. 2024, 7(3), 48; https://doi.org/10.3390/asi7030048 (registering DOI) - 3 Jun 2024
Abstract
This study examines the global literature that looks at spatial–visual abilities (SVA) while considering the numerous differential studies, methods of evaluation designed over a century, and multiple external influences on its development. The dataset was retrieved from Google Scholar and publisher databases such
[...] Read more.
This study examines the global literature that looks at spatial–visual abilities (SVA) while considering the numerous differential studies, methods of evaluation designed over a century, and multiple external influences on its development. The dataset was retrieved from Google Scholar and publisher databases such as Elsevier, Taylor & Francis, Springer, etc. Only factual reports and bibliographic reviews were included in an analysis of a total of 87 documents. Each study of SVA is classified based on information, country, year, and age groupings. SVA has been extensively studied in the areas of “STEM (Science, Technology, Engineering and Mathematics) fields”, “demographic factors” and “other activities”. “Spatial visualisation” or “visual ability” is the term employed to refer to the cognitive ability that allows one to comprehend, mentally process, and manipulate three-dimensional visuospatial shapes. One of the most crucial distinct abilities involved is spatial aptitude, which aids in understanding numerous aspects of everyday and academic life. It is especially vital for comprehending scientific concepts, and it has been extensively studied. Nearly all multiple-aptitude assessments include spatial ability. It is determined that over the past two decades, the study of SVA has gained momentum, most likely because of information being digitised. Within the vast reservoir of spatial-cognition research, the majority of the studies examined here originate from the United States of America, with less than a quarter of the studies based in the Asia–Pacific region and the Middle East. This paper presents a comprehensive review of the literature on the assessment of SVA with respect to sector, year, country, age and socio-economic factors. It also offers a detailed examination of the use of spatial interventions in educational environments to integrate spatial abilities with training in architecture and interior design.
Full article
Open AccessArticle
Coopetition with the Industrial IoT: A Service-Dominant Logic Approach
by
Agostinho da Silva and Antonio J. Marques Cardoso
Appl. Syst. Innov. 2024, 7(3), 47; https://doi.org/10.3390/asi7030047 - 31 May 2024
Abstract
Abstract: This research addresses the critical gap in enabling effective coopetition networks through technological innovation with the development of Cockpit4.0+, an Industrial Internet of Things (IIoT) artefact tailored for small- and medium-sized enterprises (SMEs). By employing the principles of Service-Dominant Logic (S-D Logic)
[...] Read more.
Abstract: This research addresses the critical gap in enabling effective coopetition networks through technological innovation with the development of Cockpit4.0+, an Industrial Internet of Things (IIoT) artefact tailored for small- and medium-sized enterprises (SMEs). By employing the principles of Service-Dominant Logic (S-D Logic) and leveraging the Design Science Research (DSR) methodology, Cockpit4.0+ represents a pioneering approach to incorporating the IIoT within ecosystems for value co-creation. This facilitates competition and cooperation among firms, enhancing the operational dynamics within SME networks. Evaluated by experts in the ornamental stone sector, a significant sector of the Portuguese economy, the system demonstrated a positive functional acceptance rate of 78.9%. An experimental test was conducted following the positive preliminary functional evaluation of Cockpit4.0+, especially among more digitally advanced companies. The findings revealed that the on-time delivery performance under current best practices (CB.Ps) was 67.1%. In contrast, implementing coopetition network practices (CN.Ps) increased on-time delivery to 77.5%. These positive evaluations of Cockpit4.0+ underscore the practical applicability of S-D Logic and provide fresh insights into the dynamics of coopetition, particularly beneficial for SMEs. Despite its promising results, the real-world efficacy of IIoT systems like Cockpit4.0+ requires further empirical studies to verify these findings. Future research should focus on examining the scalability of Cockpit4.0+ and its adaptability across various sectors and enhancing its cybersecurity measures to ensure its long-term success and broader adoption.
Full article
(This article belongs to the Special Issue New Challenges of Innovation, Sustainability, Resilience in X.0 Era)
►▼
Show Figures
Figure 1
Open AccessArticle
Estimation of Total Real and Reactive Power Losses in Electrical Power Systems via Artificial Neural Network
by
Giovana Gonçalves da Silva, Alexandre de Queiroz, Enio Garbelini, Wesley Prado Leão dos Santos, Carlos Roberto Minussi and Alfredo Bonini Neto
Appl. Syst. Innov. 2024, 7(3), 46; https://doi.org/10.3390/asi7030046 - 29 May 2024
Abstract
Total real and reactive power losses in electrical power systems are an inevitable phenomenon and occur due to several factors, such as conductor resistance, transformer impedance, line reactance, equipment losses, and phase unbalance. Minimizing them is crucial to the system’s efficiency. In this
[...] Read more.
Total real and reactive power losses in electrical power systems are an inevitable phenomenon and occur due to several factors, such as conductor resistance, transformer impedance, line reactance, equipment losses, and phase unbalance. Minimizing them is crucial to the system’s efficiency. In this study, an artificial neural network, specifically a Multi-layer Perceptron, was employed to predict total real and reactive power losses in electrical systems. The network is composed of three layers: an input layer consisting of the variables loading factor, real and reactive power generated on the slack bus, a hidden layer, and an output layer representing the total real and reactive power losses. The training method used was backpropagation, adjusting the weights based on the desired output. The results obtained, using datasets from IEEE systems with 14, 30, and 57 buses, showed satisfactory performance, with a mean squared error of around 10−4 and a coefficient of determination (R2) of 0.998. In validation with 20% of the data that was not part of the training, the network demonstrated effectiveness, with a mean squared error around 10−3. This indicates that the network was able to accurately predict total power losses based on loads, generating estimates close to the desired values.
Full article
(This article belongs to the Section Artificial Intelligence)
►▼
Show Figures
Figure 1
Open AccessReview
Recent Trends of Authentication Methods in Extended Reality: A Survey
by
Louisa Hallal, Jason Rhinelander and Ramesh Venkat
Appl. Syst. Innov. 2024, 7(3), 45; https://doi.org/10.3390/asi7030045 - 28 May 2024
Abstract
►▼
Show Figures
Extended Reality (XR) is increasingly gaining momentum in industries such as retail, health, and education. To protect users’ personal data, establishing a secure authentication system for XR devices becomes essential. Recently, the focus on authentication methods for XR devices has been limited. To
[...] Read more.
Extended Reality (XR) is increasingly gaining momentum in industries such as retail, health, and education. To protect users’ personal data, establishing a secure authentication system for XR devices becomes essential. Recently, the focus on authentication methods for XR devices has been limited. To further our understanding of this topic, we surveyed authentication schemes, particularly systems and methods deployed in XR settings. In this survey, we focused on reviewing and evaluating papers published during the last decade (between 2014 and 2023). We compared knowledge-based authentication, physical biometrics, behavioral biometrics, and multi-model methods in terms of accuracy, security, and usability. We also highlighted the benefits and drawbacks of those methods. These highlights will direct future Human–computer Interaction (HCI) and security research to develop secure, reliable, and practical authentication systems.
Full article
Figure 1
Open AccessArticle
A Road Behavior Pattern-Detection Model in Querétaro City Streets by the Use of Shape Descriptors
by
Antonio Trejo-Morales and Hugo Jimenez-Hernandez
Appl. Syst. Innov. 2024, 7(3), 44; https://doi.org/10.3390/asi7030044 - 27 May 2024
Abstract
In this research, a proposed model aims to automatically identify patterns of spatial and temporal behavior of moving objects in video sequences. The moving objects are analyzed and characterized based on their shape and observable attributes in displacement. To quantify the moving objects
[...] Read more.
In this research, a proposed model aims to automatically identify patterns of spatial and temporal behavior of moving objects in video sequences. The moving objects are analyzed and characterized based on their shape and observable attributes in displacement. To quantify the moving objects over time and form a homogeneous database, a set of shape descriptors is introduced. Geometric measurements of shape, contrast, and connectedness are used to represent each moving object. The proposal uses Granger’s theory to find causal relationships from the history of each moving object stored in a database. The model is tested in two scenarios; the first is a public database, and the second scenario uses a proprietary database from a real scenario. The results show an average accuracy value of 78% in the detection of atypical behaviors in positive and negative dependence relationships.
Full article
(This article belongs to the Special Issue New Challenges of Innovation, Sustainability, Resilience in X.0 Era)
►▼
Show Figures
Figure 1
Open AccessArticle
Numerical Simulation and Development of a Continuous Microwave-Assisted Pilot Plant for Shelled Almond Processing
by
Luciano Mescia, Alessandro Leone, Claudio Maria Lamacchia, Angela Ferraris, Domenico Caggiano, Antonio Berardi and Antonia Tamborrino
Appl. Syst. Innov. 2024, 7(3), 43; https://doi.org/10.3390/asi7030043 - 27 May 2024
Abstract
►▼
Show Figures
This paper outlines the numerical modeling procedure aimed at defining the guidelines for the development of a continuous microwave-assisted pilot plant for shelled almond disinfestation, as an alternative to the use of chemicals. To this end, a 3D Multiphysics numerical tool involving both
[...] Read more.
This paper outlines the numerical modeling procedure aimed at defining the guidelines for the development of a continuous microwave-assisted pilot plant for shelled almond disinfestation, as an alternative to the use of chemicals. To this end, a 3D Multiphysics numerical tool involving both electromagnetic and thermal models was developed to predict the temperature and electric field profiles inside the microwave treatment chamber. Three different microwave sources arrangements were simulated and the accuracy of the model was verified under different residence times of almonds in the treatment chamber using the developed prototype. The modeling results demonstrated that the arrangement having five microwave sources, each delivering a maximum power of 1.5 kW and frequency of 2.45 GHz, ensures good heating uniformity. The obtained results proved that the model enables the accurate prediction of the temperature trend (root-mean-square error/RMSE = 0.82). A strong linear regression was detected for the standard deviation between the simulated and experimental data (linear regression, R2 = 0.91). The very low COV value for the experimental temperature data demonstrated the heating uniformity as the treatment time changed. The developed model and the simulation strategy used may provide useful design guidance for microwave-assisted continuous plants for disinfestation, with a significant impact on the almond industry.
Full article
Figure 1
Open AccessArticle
Design and Implementation of Adam: A Humanoid Robotic Head with Social Interaction Capabilities
by
Sherif Said, Karim Youssef, Benrose Prasad, Ghaneemah Alasfour, Samer Alkork and Taha Beyrouthy
Appl. Syst. Innov. 2024, 7(3), 42; https://doi.org/10.3390/asi7030042 - 27 May 2024
Abstract
Social robots are being conceived with different characteristics and being used in different applications. The growth of social robotics benefits from advances in fabrication, sensing, and actuation technologies, as well as signal processing and artificial intelligence. This paper presents a design and implementation
[...] Read more.
Social robots are being conceived with different characteristics and being used in different applications. The growth of social robotics benefits from advances in fabrication, sensing, and actuation technologies, as well as signal processing and artificial intelligence. This paper presents a design and implementation of the humanoid robotic platform Adam, consisting of a motorized human-like head with precise movements of the eyes, jaw, and neck, together with capabilities of face tracking and vocal conversation using ChatGPT. Adam relies on 3D-printed parts together with a microphone, a camera, and proper servomotors, and it has high structural integrity and flexibility. Adam’s control framework consists of an adequate signal exploitation and motor command strategy that allows efficient social interactions. Adam is an innovative platform that combines manufacturability, user-friendliness, low costs, acceptability, and sustainability, offering advantages compared with other platforms. Indeed, the platform’s hardware and software components are adjustable and allow it to increase its abilities and adapt them to different applications in a variety of roles. Future work will entail the development of a body for Adam and the addition of skin-like materials to enhance its human-like appearance.
Full article
(This article belongs to the Section Human-Computer Interaction)
►▼
Show Figures
Figure 1
Open AccessArticle
Fault Detection and Normal Operating Condition in Power Transformers via Pattern Recognition Artificial Neural Network
by
André Gifalli, Alfredo Bonini Neto, André Nunes de Souza, Renan Pinal de Mello, Marco Akio Ikeshoji, Enio Garbelini and Floriano Torres Neto
Appl. Syst. Innov. 2024, 7(3), 41; https://doi.org/10.3390/asi7030041 - 24 May 2024
Abstract
Aging, degradation, or damage to internal insulation materials often contribute to transformer failures. Furthermore, combustible gases can be produced when these insulation materials experience thermal or electrical stresses. This paper presents an artificial neural network for pattern recognition (PRN) to classify the operating
[...] Read more.
Aging, degradation, or damage to internal insulation materials often contribute to transformer failures. Furthermore, combustible gases can be produced when these insulation materials experience thermal or electrical stresses. This paper presents an artificial neural network for pattern recognition (PRN) to classify the operating conditions of power transformers (normal, thermal faults, and electrical faults) depending on the combustible gases present in them. Two network configurations were presented, one with five and the other with ten neurons in the hidden layer. The main advantage of applying this model through artificial neural networks is its ability to capture the nonlinear characteristics of the samples under study, thus avoiding the need for iterative procedures. The effectiveness and applicability of the proposed methodology were evaluated on 815 real data samples. Based on the results, the PRN performed well in both training and validation (for samples that were not part of the training), with a mean squared error (MSE) close to expected (0.001). The network was able to classify the samples with a 98% accuracy rate of the 815 samples presented and with 100% accuracy in validation, showing that the methodology developed is capable of acting as a tool for diagnosing the operability of power transformers.
Full article
(This article belongs to the Section Artificial Intelligence)
►▼
Show Figures
Figure 1
Open AccessArticle
Online Prediction Method of Transmission Line Icing Based on Robust Seasonal Decomposition of Time Series and Bilinear Temporal–Spectral Fusion and Improved Beluga Whale Optimization Algorithm–Least Squares Support Vector Regression
by
Qiang Li, Xiao Liao, Wei Cui, Ying Wang, Hui Cao and Xianjing Zhong
Appl. Syst. Innov. 2024, 7(3), 40; https://doi.org/10.3390/asi7030040 - 16 May 2024
Abstract
Due to the prevalent challenges of inadequate accuracy, unstandardized parameters, and suboptimal efficiency with regard to icing prediction, this study introduces an innovative online method for icing prediction based on Robust STL–BTSF and IBWO–LSSVR. Firstly, this study adopts the Robust Seasonal Decomposition of
[...] Read more.
Due to the prevalent challenges of inadequate accuracy, unstandardized parameters, and suboptimal efficiency with regard to icing prediction, this study introduces an innovative online method for icing prediction based on Robust STL–BTSF and IBWO–LSSVR. Firstly, this study adopts the Robust Seasonal Decomposition of Time Series and Bilinear Temporal–Spectral Fusion (Robust STL–BTSF) approach, which is demonstrably effective for short-term and limited sample data preprocessing. Subsequently, injecting a multi-faceted enhancement approach to the Beluga Whale Optimization algorithm (BWO), which integrates a nonlinear balancing factor, a population optimization strategy, a whale fall mechanism, and an ascendant elite learning scheme. Then, using the Improved BWO (IBWO) above to optimize the key hyperparameters of Least Squares Support Vector Regression (LSSVR), a superior offline predictive part is constructed based on this approach. In addition, an Incremental Online Learning algorithm (IOL) is imported. Integrating the two parts, the advanced online icing prediction model for transmission lines is built. Finally, simulations based on actual icing data unequivocally demonstrate that the proposed method markedly enhances both the accuracy and speed of predictions, thereby presenting a sophisticated solution for the icing prediction on the transmission lines.
Full article
(This article belongs to the Special Issue The State of the Art in Generative AI: Innovations and Applications in Engineering and Technology)
►▼
Show Figures
Figure 1
Open AccessArticle
Soft Sensor Technology for the Determination of Mechanical Seal Friction Power Performance
by
Nils Reeh, Gerd Manthei and Peter J. Klar
Appl. Syst. Innov. 2024, 7(3), 39; https://doi.org/10.3390/asi7030039 - 4 May 2024
Abstract
Mechanical seals ensure the internal sealing of centrifugal pumps from the surrounding environment. They are one of the most critical components in a centrifugal pump. For this reason, the condition of mechanical seals should be monitored during operation. Mechanical seal friction power is
[...] Read more.
Mechanical seals ensure the internal sealing of centrifugal pumps from the surrounding environment. They are one of the most critical components in a centrifugal pump. For this reason, the condition of mechanical seals should be monitored during operation. Mechanical seal friction power is an important component of mechanical losses in centrifugal pumps and is used as an indicator of wear and therefore seal condition. The soft sensor described in this paper is based on temperature measurements at the seal and can be used for determining the frictional power performance. A major factor in determining frictional power performance is the heat transfer between the mechanical seal and the medium inside the pump. For calculating the heat transfer, the stationary temperature fields in the rings of the mechanical seal are described by transmission efficiencies. The root mean squared error was determined for steady-state operating conditions to assess the quality of the soft sensor calculation. The frictional power performance can be determined by recording the temperature at the mechanical seal mating ring and the medium. The algorithm detects when the steady-state operating conditions change but does not map the dynamic changes between the stationary operating conditions.
Full article
(This article belongs to the Section Industrial and Manufacturing Engineering)
►▼
Show Figures
Figure 1
Open AccessArticle
Data-Driven Adaptive Controller Based on Hyperbolic Cost Function for Non-Affine Discrete-Time Systems with Variant Control Direction
by
Miriam Flores-Padilla and Chidentree Treesatayapun
Appl. Syst. Innov. 2024, 7(3), 38; https://doi.org/10.3390/asi7030038 - 28 Apr 2024
Abstract
►▼
Show Figures
As technology evolves, more complex non-affine systems are created. These complex systems are hard to model, whereas most controllers require information on systems to be designed. This information is hard to obtain for systems with varying control directions. Therefore, this study introduces a
[...] Read more.
As technology evolves, more complex non-affine systems are created. These complex systems are hard to model, whereas most controllers require information on systems to be designed. This information is hard to obtain for systems with varying control directions. Therefore, this study introduces a novel data-driven estimator and controller tailored for single-input single-output non-affine discrete-time systems. This approach focuses on cases when the control direction varies over time and the mathematical model of the system is completely unknown. The estimator and controller are constructed using a Multiple-input Fuzzy Rules Emulated Network framework. The weight vectors are updated through the gradient descent optimization method, which employs a unique cost function that multiplies the error by a hyperbolic tangent. The stability analyses demonstrate that both the estimator and controller converge to uniformly ultimately bounded (UUB) functions of Lyapunov. To validate the results, we show experimental tests of force control that were executed on the z-axis of a drive-controlled 3D scanning robot. This system has a varying control direction, and we also provide comparison results with a state-of-the-art controller. The results show a mean absolute percentage tracking error smaller than one percent on the steady state and the expected variation in the system’s control direction.
Full article
Figure 1
Open AccessArticle
Pipe Organ Design Including the Passive Haptic Feedback Technology and Measurement Analysis of Key Displacement, Pressure Force and Sound Organ Pipe
by
Paweł Kowol, Pawel Nowak, Luca Di Nunzio, Gian Carlo Cardarilli, Giacomo Capizzi and Grazia Lo Sciuto
Appl. Syst. Innov. 2024, 7(3), 37; https://doi.org/10.3390/asi7030037 - 28 Apr 2024
Abstract
►▼
Show Figures
In this work, an organ pipe instrument with a mechatronic control system including the Passive Haptic Feedback technology is implemented. The test bed consists of a motorized positioning stage mounted to a brace that is attached to a bridge on a platform. A
[...] Read more.
In this work, an organ pipe instrument with a mechatronic control system including the Passive Haptic Feedback technology is implemented. The test bed consists of a motorized positioning stage mounted to a brace that is attached to a bridge on a platform. A simple pneumatic mechanism is designed and realized to achieve the same dynamics pressure for each measurement attempt on the keyboard. This system contain pipes, an air compressor, valves, and a piston connected to applied force pressure on the keyboard of the organ pipe. The pneumatic components, like valves and pressure regulators, mounted on the profile plate are connected to the main air supply line via flexible tubing or hoses to the air compressor and mechanical trucker. The pneumatic system has many types of valves that regulate the air speed, air flow, and power. The combination of valves and air compressor control the air flow and the mechanism of piston and pressure on the keyboard. The mechanical actuator presses the key to be tested, and a load cell detects the applied key force. A laser triangulation measurement system based on a Laser Displacement Sensor measures the displacement of the key during the key depression. The velocity of the key motion is controlled by the pneumatic actuator. A miniature-sized strain gauge load cell, which is mounted on a musical keyboard key, measures the contact force between the probe and the key. In addition, the quality of the audio signal generated by the organ instrument is estimated using the Hilbert transform.
Full article
Figure 1
Open AccessArticle
Usability Analysis of Smart Speakers from a Learnability Perspective for Novel Users
by
Toshihisa Doi and Yuki Nishikawa
Appl. Syst. Innov. 2024, 7(3), 36; https://doi.org/10.3390/asi7030036 - 25 Apr 2024
Abstract
Although commercial smart speakers are becoming increasingly popular, there is still much potential for investigation into their usability. In this study, we analyzed the usability of commercial smart speakers by focusing on the learnability of young users who are not yet familiar with
[...] Read more.
Although commercial smart speakers are becoming increasingly popular, there is still much potential for investigation into their usability. In this study, we analyzed the usability of commercial smart speakers by focusing on the learnability of young users who are not yet familiar with voice user interface (VUI) operation. In the experiment, we conducted a task in which users repeatedly operated a smart speaker 10 times under four conditions, combining two experimental factors: the presence or absence of a screen on the smart speaker and the operation method (voice control only or in conjunction with remote-control operation). The usability of the smart speaker was analyzed in terms of task-completion time, task-completion rate, number of errors, subjective evaluation, and retrospective protocol analysis. In particular, we confirmed and compared the learning curves for each condition in terms of the performance metrics. The experimental results showed that there were no substantial differences in the learning curves between the presence and absence of a screen. In addition, the “lack of feedback” and “system response error” were identified as usability problems, and it was suggested that these problems led to “distrust of the system”.
Full article
(This article belongs to the Section Human-Computer Interaction)
►▼
Show Figures
Figure 1
Open AccessArticle
An Application-Driven Method for Assembling Numerical Schemes for the Solution of Complex Multiphysics Problems
by
Patrick Zimbrod, Michael Fleck and Johannes Schilp
Appl. Syst. Innov. 2024, 7(3), 35; https://doi.org/10.3390/asi7030035 - 24 Apr 2024
Abstract
►▼
Show Figures
Within recent years, considerable progress has been made regarding high-performance solvers for partial differential equations (PDEs), yielding potential gains in efficiency compared to industry standard tools. However, the latter largely remains the status quo for scientists and engineers focusing on applying simulation tools
[...] Read more.
Within recent years, considerable progress has been made regarding high-performance solvers for partial differential equations (PDEs), yielding potential gains in efficiency compared to industry standard tools. However, the latter largely remains the status quo for scientists and engineers focusing on applying simulation tools to specific problems in practice. We attribute this growing technical gap to the increasing complexity and knowledge required to pick and assemble state-of-the-art methods. Thus, with this work, we initiate an effort to build a common taxonomy for the most popular grid-based approximation schemes to draw comparisons regarding accuracy and computational efficiency. We then build upon this foundation and introduce a method to systematically guide an application expert through classifying a given PDE problem setting and identifying a suitable numerical scheme. Great care is taken to ensure that making a choice this way is unambiguous, i.e., the goal is to obtain a clear and reproducible recommendation. Our method not only helps to identify and assemble suitable schemes but enables the unique combination of multiple methods on a per-field basis. We demonstrate this process and its effectiveness using different model problems, each comparing the resulting numerical scheme from our method with the next best choice. For both the Allen–Cahn and advection equations, we show that substantial computational gains can be attained for the recommended numerical methods regarding accuracy and efficiency. Lastly, we outline how one can systematically analyze and classify a coupled multiphysics problem of considerable complexity with six different unknown quantities, yielding an efficient, mixed discretization that in configuration compares well to high-performance implementations from the literature.
Full article
Figure 1
Open AccessArticle
Preliminary Estimation for Software Development Projects Empowered with a Method of Recommending Optimal Duration and Team Composition
by
Vasyl Teslyuk, Anatoliy Batyuk and Volodymyr Voityshyn
Appl. Syst. Innov. 2024, 7(3), 34; https://doi.org/10.3390/asi7030034 - 23 Apr 2024
Abstract
In the early software development stages, the aim of estimation is to obtain a rough understanding of the timeline and resources required to implement a potential project. The current study is devoted to a method of preliminary estimation applicable at the beginning of
[...] Read more.
In the early software development stages, the aim of estimation is to obtain a rough understanding of the timeline and resources required to implement a potential project. The current study is devoted to a method of preliminary estimation applicable at the beginning of the software development life cycle when the level of uncertainty is high. The authors’ concepts of the estimation life cycle, the estimable items breakdown structure, and a system of working-time balance equations in conjunction with an agile-fashioned sizing approach are used. To minimize the experts’ working time spent on preliminary estimation, the authors applied a decision support procedure based on integer programming and the analytic hierarchy process. The method’s outcomes are not definitive enough to make commitments; instead, they are supposed to be used for communication with project stakeholders or as inputs for the subsequent estimation stages. For practical usage of the preliminary estimation method, a semistructured business process is proposed.
Full article
(This article belongs to the Section Industrial and Manufacturing Engineering)
►▼
Show Figures
Figure 1
Open AccessArticle
Design and Development of Complex-Order PI-PD Controllers: Case Studies on Pressure and Flow Process Control
by
Muhammad Najmi Bin Roslan, Kishore Bingi, P. Arun Mozhi Devan and Rosdiazli Ibrahim
Appl. Syst. Innov. 2024, 7(3), 33; https://doi.org/10.3390/asi7030033 - 23 Apr 2024
Abstract
This article examines the performance of the proposed complex-order, conventional and fractional-order controllers for process automation and control in process plants. The controllers are compared regarding disturbance rejection and set-point tracking, considering variables such as response time, robustness to uncertainty, and steady-state error.
[...] Read more.
This article examines the performance of the proposed complex-order, conventional and fractional-order controllers for process automation and control in process plants. The controllers are compared regarding disturbance rejection and set-point tracking, considering variables such as response time, robustness to uncertainty, and steady-state error. The study shows that a complex PI-PD controller has better accuracy, faster response time, and better noise rejection. Still, implementation is challenging due to increased complexity and processing requirements. In contrast, a standard PI-PD controller is a known solution but may have problems with accuracy and robustness. Fractional-order controllers based on fractional computations have the potential to improve control accuracy and robustness of non-linear and time-varying systems. Experimental insights and real-world case studies are used to highlight the strengths and weaknesses of each controller. The findings provide valuable insights into the strengths and weaknesses of complex-order and fractional-order controllers and help to select the appropriate controller for specific process plant requirements. Future perspectives on controller design and performance optimization are detailed, identifying the potential benefits of using complex and fractional-order controllers in process plants.
Full article
(This article belongs to the Section Control and Systems Engineering)
►▼
Show Figures
Figure 1
Open AccessArticle
Technology Readiness Levels (TRLs) in the Era of Co-Creation
by
Sofia Yfanti and Nikos Sakkas
Appl. Syst. Innov. 2024, 7(2), 32; https://doi.org/10.3390/asi7020032 - 16 Apr 2024
Abstract
Technology readiness levels (TRLs) is a well-established and widely used approach for defining the readiness of new technology. It assesses technology maturity against specific benchmarks, ranging from level 1 (concept) to level 9 (market solution). Although this is a useful classification service that
[...] Read more.
Technology readiness levels (TRLs) is a well-established and widely used approach for defining the readiness of new technology. It assesses technology maturity against specific benchmarks, ranging from level 1 (concept) to level 9 (market solution). Although this is a useful classification service that allows us to establish a common language, there are cases where we find that this conceptual approach cannot adequately highlight the maturity of certain innovative endeavors and effectively steer their development to higher TRLs. We will present an empirical case where the TRL approach presented a critical shortcoming in highlighting the true and effective readiness of a specific technological development and could not suggest the next natural step in ascending the maturity ladder. We will seek to generalize for the case of co-creation at large, analyze why co-creation may be poorly serviced by the current TRL model, and suggest an amendment that would allow the observed shortcomings of the traditional TRL approach to be overcome and its use extended into such co-creative settings, thus allowing stakeholders to enhance the effectiveness and impact of their collaborative innovation efforts.
Full article
(This article belongs to the Section Artificial Intelligence)
►▼
Show Figures
Figure 1
Open AccessArticle
Identifying Strengths and Weaknesses in Mobile Education: A Gender-Informed Self-Assessment of Teachers’ Use of Mobile Devices
by
Judith Balanyà Rebollo and Janaina Minelli De Oliveira
Appl. Syst. Innov. 2024, 7(2), 31; https://doi.org/10.3390/asi7020031 - 16 Apr 2024
Abstract
Mobile devices have the potential to transform education and society. Promoting mobile learning and enhancing teachers’ digital and entrepreneurial skills are essential in achieving this goal. This study analyses the conditions under which the use of mobile technology can support teachers in the
[...] Read more.
Mobile devices have the potential to transform education and society. Promoting mobile learning and enhancing teachers’ digital and entrepreneurial skills are essential in achieving this goal. This study analyses the conditions under which the use of mobile technology can support teachers in the design, implementation, and evaluation of teaching and learning processes. Data were collected using a quantitative method based on a self-assessment instrument (Cronbach’s alpha = 1.0046). A total of 327 educators filled out the survey, which included 67 items scored on a Likert scale. The self-assessment tool provided participants with feedback on their mobile device use for educational purposes and suggestions for improvement. The results indicate that the median score of the teachers was 7, which is regarded as satisfactory, with a gender gap of 3.5 points. In addition, three out of seven improvement dimensions were identified: technology learning spaces (54.74%), assessment (57.65%), and design activities (59.26%). In conclusion, the study enabled us to stratify and analyse teachers’ pedagogical perceptions of mobile learning and the significance of inference in certain training areas.
Full article
(This article belongs to the Topic Effectiveness and Sustainable Application on Educational Technology)
►▼
Show Figures
Figure 1
Open AccessArticle
A Comparative Analysis of Oak Wood Defect Detection Using Two Deep Learning (DL)-Based Software
by
Branimir Jambreković, Filip Veselčić, Iva Ištok, Tomislav Sinković, Vjekoslav Živković and Tomislav Sedlar
Appl. Syst. Innov. 2024, 7(2), 30; https://doi.org/10.3390/asi7020030 - 15 Apr 2024
Abstract
The world’s expanding population presents a challenge through its rising demand for wood products. This requirement contributes to increased production and, ultimately, the high-quality and efficient utilization of basic materials. Detecting defects in wood elements, which are inevitable when working with a natural
[...] Read more.
The world’s expanding population presents a challenge through its rising demand for wood products. This requirement contributes to increased production and, ultimately, the high-quality and efficient utilization of basic materials. Detecting defects in wood elements, which are inevitable when working with a natural material such as wood, is one of the difficulties associated with the issue above. Even in modern times, people still identify wood defects by visually scrutinizing the sawn surface and marking the defects. Industrial scanners equipped with software based on convolutional neural networks (CNNs) allow for the rapid detection of defects and have the potential to accelerate production and eradicate human subjectivity. This paper evaluates the suitability of defect recognition software in industrial scanners against software specifically designed for this task within a research project conducted using Adaptive Vision Studio, focusing on feature detection techniques. The research revealed that the software installed as part of the industrial scanner is more effective for analyzing knots (77.78% vs. 70.37%), sapwood (100% vs. 80%), and ambrosia wood (60% vs. 20%), while the software derived from the project is more effective for analyzing cracks (70% vs. 65%), ingrown bark (42.86% vs. 28.57%), and wood rays (81.82% vs. 27.27%).
Full article
(This article belongs to the Special Issue Advancements in Deep Learning and Its Applications)
►▼
Show Figures
Figure 1
Open AccessArticle
The Role of ChatGPT in Elevating Customer Experience and Efficiency in Automotive After-Sales Business Processes
by
Piotr Sliż
Appl. Syst. Innov. 2024, 7(2), 29; https://doi.org/10.3390/asi7020029 - 28 Mar 2024
Abstract
Purpose: The advancements in deep learning and AI technologies have led to the development of such language models, in 2022, as OpenAI’s ChatGPT. The primary objective of this paper is to thoroughly examine the capabilities of ChatGPT within the realm of business-process management
[...] Read more.
Purpose: The advancements in deep learning and AI technologies have led to the development of such language models, in 2022, as OpenAI’s ChatGPT. The primary objective of this paper is to thoroughly examine the capabilities of ChatGPT within the realm of business-process management (BPM). This exploration entails analyzing its practical application, particularly through process-mining techniques, within the context of automotive after-sales processes. Originality: this article highlights the issue of possible ChatGPT application in selected stages of after-sales processes in the automotive sector. Methods: to achieve the main aim of this paper, methods such as a literature review, participant observation, unstructured interviews, CRISP-DM methodology, and process mining were used. Findings: This study emphasizes the promising impact of implementing the ChatGPT OpenAI tool to enhance processes in the automotive after-sales sector. Conducted in 2023, shortly after the tool’s introduction, the research highlights its potential to contribute to heightened customer satisfaction within the after-sales domain. The investigation focuses on the process-execution time. A key premise is that waiting time represents an additional cost for customers seeking these services. Employing process-mining methodologies, the study identifies stages characterized by unnecessary delays. Collaborative efforts with domain experts are employed to establish benchmark durations for researched processes’ stages. The study proposes the integration of ChatGPT to improve and expedite stages, including service reception, reception check-out, repair and maintenance, and claim repair. This holistic approach aligns with the current imperatives of business-process improvement and optimalization, aiming to enhance operational efficiency and customer-centric service delivery in the automotive after-sales sector.
Full article
(This article belongs to the Section Information Systems)
►▼
Show Figures
Figure 1
Journal Menu
► ▼ Journal Menu-
- ASI Home
- Aims & Scope
- Editorial Board
- Topical Advisory Panel
- Instructions for Authors
- Special Issues
- Topics
- Sections & Collections
- Article Processing Charge
- Indexing & Archiving
- Editor’s Choice Articles
- Most Cited & Viewed
- Journal Statistics
- Journal History
- Journal Awards
- Society Collaborations
- Conferences
- Editorial Office
Journal Browser
► ▼ Journal BrowserHighly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Education Sciences, Administrative Sciences, Economies, Sustainability, ASI
Effectiveness and Sustainable Application on Educational Technology
Topic Editors: Jian-Hong Ye, Yung-Wei Hao, Yu-Feng Wu, Savvas A. ChatzichristofisDeadline: 31 August 2024
Topic in
Applied Sciences, ASI, Bioengineering, Electronics, Healthcare
Applied System on Biomedical Engineering, Healthcare and Sustainability 2024
Topic Editors: Teen-Hang Meen, Chun-Yen Chang, Charles Tijus, Po-Lei Lee, Kuei-Shu HsuDeadline: 31 December 2024
Conferences
Special Issues
Special Issue in
ASI
Software Engineering for IoT: Latest Advances and Prospects
Guest Editor: Luca MainettiDeadline: 20 June 2024
Special Issue in
ASI
Advanced Technologies and Methods in Mechanical Fault Diagnostics and Prognostics
Guest Editors: Naipeng Li, Shiqian ChenDeadline: 30 June 2024
Special Issue in
ASI
New Challenges of Innovation, Sustainability, Resilience in X.0 Era
Guest Editors: Mario Nardo, Maryam GallabDeadline: 30 August 2024
Special Issue in
ASI
Advanced Technologies and Methodologies in Education 4.0
Guest Editors: Sarantos Psycharis, Konstantinos Kalovrektis, Apostolis XenakisDeadline: 1 September 2024
Topical Collections
Topical Collection in
ASI
Feature Paper Collection in Applied System Innovation
Collection Editor: Christos Douligeris
Topical Collection in
ASI
Feature Paper Collection on Civil Engineering and Architecture
Collection Editor: Luís Bragança