Design Stage Research Articles

Dreams and fears in the process of creative thinking in children from areas affected by the armed conflict in Colombia

The development of creativity and creative thinking in early school-age children is a strategy to foster future capabilities for innovation and change. It is also a strategy to instill resilience in these children, enabling them to face the challenges posed by the various environments that surround teaching and learning processes. This article analyzes the dreams and fears expressed by children from educational institutions located in municipalities affected by the armed conflict in Colombia, within the framework of a route designed to develop creativity and innovative thinking. A qualitative narrative analysis methodology was used to characterize and analyze the narratives of 68 co-creativity teams, involving 408 children. The results show that the narratives are influenced not only by the context in which the children live but also by the consequences of the armed conflict in the areas where the schools are located. The findings suggest that educational strategies like the one studied must incorporate elements that allow for adaptation to the context from the design stage, with a differential approach, to generate the expected positive effects in the territories where they are implemented.

Design optimization of continuous fiber composites with thermo-mechanical coupling and load uncertainties

This paper introduces a theoretical framework for the design optimization of continuous fiber composites reinforced with continuous fiber trajectories subject to thermo-mechanical coupling and load uncertainties. Different uniform temperature variations are applied in the structure to investigate the influence of ambient temperature change on the structural performance. To consider the external load uncertainties, a robust design optimization model is proposed where the loads are modeled as hybrid variables, namely magnitudes as random variables and directions as interval variables, with the robust objective determined through a hybrid orthogonal polynomial expansion method. Furthermore, we use a level-set function to represent the structural boundary, with its evolution driven by shape derivatives calculated based on uncertainty analysis. The continuous fiber paths are subsequently determined by the level-set isoline extracted from the structural boundary, which in turn influences the structural mechanical performance due to the material anisotropy of composites. The continuity of continuous fiber and the equal space between adjacent trajectories largely ensure the additive manufacturability of the composites. Three numerical examples are presented to demonstrate the effectiveness of the developed framework. The results show that the ambient temperature variations and load uncertainties largely impact the optimized topology and fiber infill patterns of composites, thus are important to be considered in the design stage. Moreover, the optimized structure can have a 5-fold stiffness per unit mass compared with the initial design thus largely increasing the material efficiency in carrying external uncertain loads.

Improved Estimation of the Seismically Induced Active Earth Thrust on a Cantilever Retaining Wall at the Preliminary Design Stage

Improved Estimation of the Seismically Induced Active Earth Thrust on a Cantilever Retaining Wall at the Preliminary Design Stage

Analyzing the Impact of Multiple Foundation Stiffness Correlation on the Natural Frequency of Offshore wind turbines

The analysis of wind turbine behavior should avoid unplanned resonance, as it can increase fatigue damage. It is essential to rigorously evaluate the natural frequency of wind turbines in the initial design stage. This estimation can be done through two steps, the first one is the computing of the fixed base natural frequency of the wind turbine. The second is the estimation of the foundation stiffness effect. This paper examines the error margin of four correlations of foundation stiffness namely Randolph, Davies and Budhu, DNV, and Higgins in the estimation of the natural frequency of wind turbines. The fixed base natural frequency was estimated in this paper using a special-purpose finite element computer program called TurbiSoft through beam and volume elements. A reference 5.0 MW offshore wind turbine and 9 other turbines from different wind farms have been analyzed. For the fixed base natural frequency, obtained results demonstrate the reliability of the finite element program TurbiSoft through an error margin between 1-4% for the reference 5.0 MW offshore wind turbine. For the natural frequency of the whole system, the estimated error marking was between 9-20% which is an important value.This significant error is attributed to the low accuracy of these four correlation formulas for predicting the foundation flexibility contribution. The results from the four correlation formulas used are quite similar, with a difference in the error margin of less than 1%. However, the largest error margins are observed with the Higgins formula, which has been originally developed for short monopiles, even though the analyzed monopiles can be considered short, with monopile slenderness ratios less than 8.

Development of an integrated statistics pocket book on culture and Islamic value

This research discusses the development of a statistical pocketbook integrated with Islamic values and culture to enhance students' understanding and appreciation of statistics within a cultural and religious context. This research aims to develop a statistical pocket book that meets valid criteria. This research uses the Research and Development (R&D) method. The development model used is ADDIE which consists of 5 development stages, namely: (1) analysis stage, (2) design stage, (3) development stage, (4) implementation stage, (5) evaluation stage. However, this development research only uses four stages, namely (1) analysis, (2) design, (3) development and evaluation. This research was conducted at FTIK IAIN Manado. Data collection was carried out using questionnaires and tests. Instruments were a marketing/content expert validation sheet and a media/design expert questionnaire validation sheet. Based on the results of the questionnaire analysis, the results obtained were that the statistics pocket book integrated with Islamic values and culture met the valid criteria for use in statistics learning, seen from the assessment results for validation by content/material experts (85%) with very valid categories and media/design experts (91 %) is also in the very valid category, the average percentage of the practicality test is 91% in the very practical category. So, the Statistics pocketbook that has been developed is valid and practical for use in learning because it is integrated with Islamic values and culture.

Application of Reverse Vaccinology and Immunoinformatics to Design a Multitope Vaccine against Gastrointestinal Cancer-inducing Cryptosporidium Parvum

Cryptosporidium parvum (C. parvum) is an apicomplexan protozoan known as a frequent cause of diarrhea. Because of its severe outbreaks and the association with different types of gastrointestinal cancers, it became an urgent need to develop effective solutions against that parasite. In the current study, the complete proteome of C. parvum was analyzed, and after applying several filtration steps, two proteins, namely Glycoprotein 60 (gp40/15) and thrombospondin-related adhesive protein (TRAP C-1), were selected as the protein candidates for epitope prediction. Next, CTL, HTL and BCL epitopes of each protein candidate were defined, and the best epitopes of each category were assembled alongside suitable linkers and adjuvants to initiate a potential multitope vaccine construct finally. That construct was evaluated for several properties, including its antigenicity, allergenicity, stability, secondary and tertiary structure, and the ability of that 3D predicted model to bind to TLR4. Furthermore, the stability of the constructed vaccine ligand in the TLR4 receptor was deeply investigated through a molecular dynamics simulation. The current study describes the stages of the multitope construct design. It demonstrates the results of that construct computational evaluation where the generated scores support the nomination of that potential vaccine as a solution for C. parvum infection, and further wet lab experiments are required to validate our current findings.

Fair voting outcomes with impact and novelty compromises? Unravelling biases in electing participatory budgeting winners.

Participatory budgeting, as a paradigm for democratic innovations, engages citizens in the distribution of a public budget to projects, which they propose and vote for implementation. So far, voting algorithms have been proposed and studied in social choice literature to elect projects that are popular, while others prioritize a proportional representation of voters' preferences, for instance, the rule of equal shares. However, the anticipated impact and novelty in the broader society by the winning projects, as selected by different algorithms, remains totally under-explored, lacking both a universal theory of impact for voting and a rigorous unifying framework for impact and novelty assessments. This article tackles this grand challenge towards new axiomatic foundations for designing effective and fair voting methods. This is through new and striking insights derived from a large-scale analysis of biases over 345 real-world voting outcomes, characterized for the first time by a novel portfolio of impact and novelty metrics. We find strong causal evidence that equal shares comes with impact loss in several infrastructural projects of different cost levels that have been so far over-represented. However, it also comes with a novel, yet over-represented, impact gain in welfare, education and culture. We discuss the broader implications of these results and how impact loss can be mitigated at the stage of campaign design and project ideation.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Co-designing transport models as a heuristic planning tool.

Recently the transportation sector has witnessed several new technologically driven disruptions that have amplified the complexity of city planning and policymaking. Traditional well-established processes of decision-making in urban planning and transportation are proving insufficient to deal with this degree of complexity and uncertainty. This paper proposes an alternative approach, combining qualitative and normative urban design, with quantitative and predictive transport modelling. This requires urban designers and transport modellers to co-create goal-driven and agile transport models that act as a heuristic tool to guide planning decisions in early design stages. Heuristic modelling is informed by design optioning and vice versa in an iterative loop. A case study is presented to demonstrate how this approach is operationalized to study the impacts of automated vehicles on urban planning. Design workshops are used as a method to elicit responses from stakeholders, which are used to co-create the simulation models. This collaborative process grounds the research in real-world practice and enhances the communication of design proposals and research findings across disciplines. By integrating design thinking methods with agent-based transport simulations, this approach provides a better understanding of emergent effects in complex urban systems and improves stakeholder engagement in the planning process.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Merger remedies in the era of the Digital Markets Act (DMA): the impact of the DMA on the EU Merger Control Regulation (EUMR) in designing commitments

ABSTRACT The Digital Markets Act (DMA) and the EU Merger Control Regulation (EUMR) are complementary tools that could apply concurrently to mergers involving gatekeepers. Yet, potential tensions between the DMA and the EUMR have been unexplored. It is this paper's objective to shed light on the interplay between the EUMR and the DMA, in the context of commitments design for gatekeeper acquisitions. This paper argues that the DMA could influence the EUMR in designing remedies, since these tools may be taking a similar approach to addressing the harmful effects of gatekeepers’ practices. Accordingly, the new DMA obligations could impact future commitments design under the EUMR in two ways. First, at the theory of harm stage, because of the DMA's deterrent effect. Second, at the remedy design stage, because of the principle of proportionality. Therefore, the DMA could restrict the EUMR's power to design merger commitments, in the context of gatekeeper acquisitions.

The Role of Memory in LLMs: Persistent Context for Smarter Conversations

Memory in LLMs has given way to more logical and sensible interactions between the system and the user. This is different from other models that are session bound, such that the responses to any one query are not related to past and future interactions with the same user, but memory-enabled LLMs retain information across sessions and continually update interactions with the person they are communicating with. The role of permanent memory in LLMs is considered in this work, provided through the analysis of the role of memory mechanisms in maintaining conversation flows, improving user interaction, and supporting practical applications in various industries, including customer service, healthcare, and education. Discussing how the idea and architectures of memory correspond to storage and retrieval procedures and the management of memory in LLMs this paper outlines the opportunities and challenges for AI systems that want to include contextual intelligence but also remain ethical. The synthesis of important concepts underlines the promising prospects of memory-augmented models in improving the communication with users and points to the imperatively important aspect of controlling the memory process at the design stage of LLMs. We also offer recommendations for privacy and ethical concerns that should be avoided in the case of future AI memory advancements in an effort to pursue sustainable technological progress while also incorporating user-oriented values into the process.

Lembar Kerja Peserta Didik Berdasarkan Model Pembelajaran Generatif untuk Materi Gelombang Cahaya Kelas XI SMA

This research aims to develop LKPD based on a generative learning model on light wave material for class XI SMA that is valid and practical. The generative learning model was chosen because it is able to encourage students to actively build their understanding through interaction, reflection and discussion. This model has proven effective in improving critical thinking and problem-solving skills in physics learning. The developed worksheet is designed following the syntax of the generative learning model: orientation, cognitive conflict, disclosure, construct, application, and reflection, to support in-depth learning and link theory with real application. This research uses the Research and Development (R&D) method with the 4D development model (define, design, develop, disseminate). The define stage includes needs analysis and problem identification. At the design stage, the LKPD was designed by taking into account the content, structure, and aesthetic components. The development stage involves validity testing by experts, well as practicality testing by teachers and students. The dissemination stage is planned for wider application. The results showed that this LKPD has a very high level of validity with a validation index value of 0.94 in the content aspect and 0.86 in the structure aspect, which means that this LKPD meets the eligibility standards of the Merdeka curriculum. The practicality test shows that the LKPD is very practical with a teacher assessment score of 95% and a student assessment of 87%, so it is feasible to use it in the real field because it has been declared valid and practical.

Comparison of inelasticity creep failure evaluation codes for elevated-temperature non-nuclear pressure equipment

PurposeTo ensure the reliable and safe operation of elevated-temperature pipes and equipment in the long term, it is essential to thoroughly assess the creep rupture life. Nevertheless, there is currently no design code that specifies a creep rupture life evaluation method for non-nuclear elevated-temperature equipment. The paper aims to discuss this issue.Design/methodology/approachAn analysis was conducted to compare the differences and conservativeness in calculating creep strain using three major codes (ASME-CC-2843, API-579 and BS-7910) based on the results of the 316H creep constitutive model and creep strain prediction. In addition, the creep resistances of 316H, 304H and 347H were compared. Subsequently, the ANSYS Usercreep subroutine was developed to compare the discrepancies between different codes under multiaxial stress conditions using numerical simulations.FindingsBS-7910 employs the Norton creep model with calculation parameters for the average creep strain rate, which is not applicable for the engineering design stage. ASME-CC2843 code primarily focuses on the primary and secondary creep stages, making it more suitable for non-nuclear pipeline and equipment design. For 316H, the creep strain curves predicted by ASME-CC2843 and API-579 typically intersect at a specific point. By combining the creep strain predicted by ASME-CC2843 and API-579, 347H exhibits superior predicted creep resistance compared to 316H, whereas 316H exhibited better predicted creep resistance than 304H.Originality/valueThis study provides a guide for future evaluation methods and material choices for non-nuclear equipment and pipelines operating at elevated temperatures.

Designing Multi-Family Residences in the Post-COVID-19 Era: Addressing Workspace Privacy Needs

The COVID-19 pandemic profoundly affected every aspect of human life. Among the myriad changes, it catalyzed a significant shift in the way we perceive and use our living spaces. The home, traditionally seen as a refuge from work and external pressures, rapidly became a multifunctional space, doubling as an office, school, gym, and recreation center. Before the pandemic, open-plan living was on the rise, championing multifunctional spaces. However, with the sudden need for remote work, the demand for dedicated home offices or quiet corners became evident. People began to value having a distinct, quiet workspace that would not disturb other members of the household. In this paper, we highlight the importance of incorporating a separate room, distanced from the main private areas of a home, during the early design stages. This approach enhances privacy and subsequently boosts the psychological well-being of the household occupants. The research contributes to building-system integration by demonstrating how architectural configurations and spatial design elements can be optimized to enhance building performance, functionality, and occupant comfort in multi-family residential structures. The aim of this study is to explore the correlations between spatial design quality and occupants’ productivity while working from home. It employs a mixed-methods approach that combines various techniques to provide comprehensive analyses.

PEak: A Single Source of Truth for Hardware Design and Verification

Domain-specific languages for hardware can significantly enhance designer productivity, but sometimes at the cost of ease of verification. On the other hand, ISA specification languages are too static to be used during early stage design space exploration. We present PEak, an open-source hardware design and specification language, which aims to improve both design productivity and verification capability. PEak does this by providing a single source of truth for functional models, formal specifications, and RTL. PEak has been used in several academic projects, and PEak-generated RTL has been included in three fabricated hardware accelerators. In these projects, the formal capabilities of PEak were crucial for enabling both novel design space exploration techniques and automated compiler synthesis.

The Effects of an Adaptive Ventilation Control System on Indoor Air Quality and Energy Consumption

Indoor air quality (IAQ) and energy consumption (Q) are well-known building estimators, but they are used separately. Energy consumption is used during the design stage, while IAQ is used during operation. The novelty of our approach is that we propose using both estimators simultaneously during building operations. The purpose of this study was to find an adaptive ventilation strategy that maintained good indoor air quality with minimal energy consumption. The second novelty of our approach consists of IAQ estimation. While the operation of ventilation systems depends only on the indoor carbon dioxide (CO2) concentration at present, our novel approach uses a more global IAQ index that includes four different air pollutants. Physical models are used for the hourly prediction of the two indices: global IAQ and Q. This study presents a comparative analysis of several ventilation operations strategies: fixed versus adaptive. The main findings show that a decrease in the ventilation rate, na, from 3.5 h−1 to 2.0 h−1 leads to a diminishment in energy consumption of 42.9%, maintaining the global IAQ index under the limited health risk value (VRL). Moreover, an adaptive ventilation strategy of na, maintaining the global IAQ index value under VRL, achieves a further reduction in energy consumption of 72.9%, highlighting its efficiency.

Enhancing productivity with custom GPTs to support curriculum development

At the Centre for Digital Transformation of Health, we develop a range of postgraduate and professional development courses designed to upskill the healthcare workforce in digital transformation. Our course development is informed by the ADDIE framework (Branch, 2009). During the design stage, we leverage the Understanding by Design (UbD) framework by Wiggins and McTighe (2005). UbD uses a backwards design process that starts with the outcomes in mind that constructively align with the assessment and learning activities. This process can be challenging for subject matter experts (SMEs) with little pedagogical training (Cho and Trent, 2005; Michael and Libarkin, 2016), particularly in designing topic-level learning outcomes using Bloom’s Taxonomy (Bloom et al., 1956); outlining key understandings, the big ideas and their practical applications (Wiggins & McTighe, 2005); and separating what learners should know from how that knowledge will be applied. Consequently, substantial hours are dedicated to 1:1 coaching sessions to ensure effective development of learning outcomes and content. Our driving research question is how can generative AI improve our efficiency of working with SMEs with little pedagogical knowledge? We therefore integrated ChatGPT into the curriculum design process (Conrad and Hall, 2024). However, instead of using a standard instance of ChatGPT that relies on effective prompt engineering by the user, we iteratively developed two custom GPTs (Bloomify and UnderstandMe), using OpenAI’s GPTbuilder. These GPTs constrain and customise ChatGPT’s output without requiring coding knowledge. The build process starts by explaining to the GPTbuilder what you would like your custom GPT to help with, followed by iterative prompting about specific functions, behaviours, and additional materials to constrain the GPT’s responses. Bloomify translates unrefined topic aims from SMEs into three bloomified learning outcomes across three Bloom’s levels for the SME to consider, iterate and improve upon. UnderstandMe uses the topic outcome created by Bloomify and helps the SME conceptualise the big ideas, key understandings, and the practical application of the knowledge they will learn in the topic. This approach keeps the SME at the centre of the process, rather than offloading the entire curriculum design process to ChatGPT, which was described by Conrad & Hall (2024). Early results of implementing the GPTs are promising. We observed a significant boost in efficiency, enabling us to complete twice as many UbD templates per hour of coaching. This suggests that GPTs could offer a substantial improvement in time efficiency and offer a simple way of reducing the cognitive burden of the backwards design process for SMEs and learning designers. These time savings are then reallocated to other aspects of the course development process providing the opportunity for richer collaboration between SME and learning designer. We have provided links to both GPTs, both of which are discipline-agnostic, to support the broader learning design and academic community through the backwards design process within their respective disciplines. Further evaluation of these tools will focus SME perspectives of using the GPT during collaborative course development and to investigate how these tools will influence the social norms of course design in the future.

Evaluate the Differential Effectiveness of the Case Management and Primary Nursing Models in the Implementation of Discharge Planning.

This study aims to compare the effectiveness of the case management model and the primary nursing care model by focusing on hospital stay length, readmission, follow-up resource utilisation and survival. To improve patient continuity of care, a discharge planning team has been established at the hospital to implement the service concept of long-term medical care. The team works with a multidisciplinary medical team to provide case management, which ensures high-quality patient care. Retrospective case-control study. This study collected data from the medical record information system database and the Ministry of Health and Welfare's care service management information system to explore medical and follow-up care utilisation of patients discharged between 2017 and 2018. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, with the checklist used to ensure transparent and complete reporting of the methodology and results. To ensure comparability between the case management model group and the primary nursing model group, propensity score matching was used. After matching, 660 individuals from the case management model group and 2876 individuals from the primary nursing model group were selected for further analysis. In this study, patients were primarily involved in the research as participants, providing data through their medical records for analysis. However, no direct involvement from the public or patients was used in the planning or design stages of the research. The study found that factors such as activities of daily living (ADL) score ≤ 60 points, catheterisation, poor chronic disease control and inadequate primary caregiver capacity can lead to longer hospitalisations. Males and patients with catheters have a higher risk of readmission within 30 days, and men, those aged ≥ 75 years, those with ADL score ≤ 60, catheterisation, pressure sores or unclean wounds, financial problems, insufficient primary caregiver capacity and those readmitted within 14 days after discharge had significantly increased mortality after discharge. Although the case management model group had higher hospitalisation days, they had lower readmission rates and higher survival rates than the primary nursing model group. Early consultation with the case manager for discharge planning can help patients to continue to receive care and utilise relevant resources after returning home. Identifying and addressing patient-specific factors can significantly improve patient outcomes by reducing hospitalizations and readmissions, and lowering mortality rates. The case management model is more effective than the primary nursing care model in reducing readmission rates and increasing survival rates. Early consultation with case managers for discharge planning is crucial to ensuring patient care continuity and resource utilization.

SAVAGE: Simulation of Virtual Reality-Based for Building Fire Victim Rescue Learning Media

Airports are very dynamic and complex environments, making them high-risk places for incidents and accidents, both due to the aircraft's movement and to the building facilities or structures at the airport. Emergency service personnel must have high skills in emergency response, quick decision-making abilities, and a deep understanding of the various dangerous situations that may be encountered in the field. Continuous education and training are essential to ensure their readiness and ability to deal with emergencies. This study aims to develop Virtual Reality-based Search and Rescue learning media to improve the skills and understanding of training participants in search and rescue operations. This learning media is designed to provide a realistic and interactive simulation experience, allowing participants to practice rescue procedures in various dangerous scenarios without real risk. The development methods used in this study include the stages of needs analysis, design, development, implementation, and evaluation (ADDIE). At the analysis stage, the identification of training needs and competencies that must be achieved is carried out. The design stage involves designing Virtual Reality scenarios that cover various field conditions and rescue techniques. Effectiveness is evaluated by measuring the increase in skills and understanding of participants before and after using Virtual Reality media. The study results indicate that this learning media effectively improves the operational and decision-making skills of training participants in emergency situations. The feasibility assessment by media experts obtained an average score of 88.72%. Then, the feasibility assessment by material experts obtained an average score of 88.90%. After conducting a product trial on students, the evaluation results were 81.30%. Based on the results of the validation and trial of this product, Virtual Reality-based learning media can be recommended as an innovative and efficient training tool for Search and Rescue learning media.

Study Of Tandem Rotor Dual Wake Interaction With Downstream Stator Under Unsteady Numerical Approach

Abstract This paper highlights the intricate rotor-stator interaction between a tandem bladed rotor and a single-bladed stator in the light of unsteady numerical simulations. A low speed tandem bladed compressor stage has been conceptualized and experimentally validated against targeted performance goal. With the evident pressure rise capability of the tandem bladed compressor stage, it becomes obligatory to investigate the rotorstator interaction owing to its dominant effect on overall stage performance. The multi-passage rotor-stator unsteady simulations have been performed using blade transformation methods in ANSYS CFX. Due to the presence of two highly loaded rotor blades, the tandem rotor exhibits peculiar rotorstator interaction in terms of multiple wake impingement on the stator. Incorporating tandem blading on the rotor instead of the stator (which is more common) constricts the design envelope in terms of choice of blade axial overlap and percentage pitch. The variation of aerodynamic loading from hub to tip for both the rotor blades results in spanwise varying wake strength. The initially distinct wake structures merge resulting into a thicker wake. Additionally, the rotor blades are highly loaded in the tip region which results in the complex interaction between end-wall boundary layer and tip leakage flow. Cumulatively, these conditions constitute a challenging aerodynamic field for the downstream stator. The study focuses on the qualitative interaction between the rotor wakes and blockage with the downstream stator and put forwards some aspects of the tandem rotor-single stator stage design especially for core compressors of aero engine application.

Evaluation of an Infinite-Level Inverter Operation Powered by a DC–DC Converter in Open and Closed Loop

This paper evaluates the open- and closed-loop DC–DC converter operation within a DC coupling multilevel inverter architecture to obtain an infinite-level stepped sinusoidal voltage. Adding a cascade controller to the DC–DC converter should reduce the settling time and increase the number of levels in the output voltage waveform; it could decrease the speed error and phase shift concerning the sinusoidal reference signal. The proposed methodology consists of implementing an experimental multilevel inverter with DC coupling through a single-phase bridge inverter energized from a BUCK converter. Trigger signals for the two converters are obtained from a control circuit based in an ATMEGA644P microcontroller to explore its capabilities in power electronics applications. A digital controller is also implemented to evaluate the operation of the BUCK converter in open and closed loop and observe its influence in the stepped sinusoidal output voltage. The evaluation is performed to energize a resistive load with common output voltage in multilevel inverters, i.e., 3, 5, 7, 11, and infinity levels. Results show that during the design stage, fast dynamic elements, like the storage capacitor, can be used to obtain a minimum THD because the settling time is sufficiently fast, the speed error remains small, and there is no need for a controller. A digital controller requires processing time, and although in theory it can reduce the settling time to a minimum, the processor introduces latency in the control signals generation, producing the opposite effect. Controller complexity of the digital controller must be considered because it increases processing time and influences the efficiency of the closed-loop operation.