Design Flaws Research Articles

The Impact of Media Coverage of Performance Information on the Budget Spending Intentions of Government Officials and Citizens in South Korea

This research investigates the impact of media coverage of performance information on the budget spending intentions of both public officials and citizens. It delves into the mechanisms through which media coverage shapes government performance assessment and explores how negative media portrayal affects budgetary decisions, distinguishing between budget inefficiencies, policy design flaws, and budget shortages as key content categories. The findings elucidate divergent budget spending intentions between public officials and citizens, emphasizing the intricate interplay between the tone and content of media reports and their influence on budgetary intentions. This study highlights the pivotal yet often neglected aspect of news content in molding public and official perceptions of government performance. Furthermore, it accentuates the essentiality of proactive government communication strategies in managing public perception, advocating for the institutionalization of performance information dissemination to effectively address the nuances of both successful and unsuccessful policy measures.

Experimental and numerical study on mechanical properties of a modified type of energy-dissipative hold-down for CLT structures

The connections ensure lateral and shear resistance in CLT buildings, facilitating crucial interactions between walls and floors. CLT connectors are widely used at present and take strength as the control index, but they have poor energy dissipation performance and are not suitable for middle- and high-rise buildings in earthquake-prone zones. This study proposes a modified version of an existing energy dissipative hold-down connection that rectifies its flaws by incorporating innovative design and material solutions. An experimental study is conducted with quasi-static monotonic and reversed cyclic loading tests to investigate modified hold-down connection failure mechanisms and mechanical properties. Notable failure modes included steel rib ruptures and debonding between rubber and steel plate, with steel rib rupture as a dominant failure mechanism. Despite such failures, the connection maintained functionality, attributed to the effective bonding between the rubber and the steel bracket. The load-displacement curves of the hold-down exhibit a bi-linear pattern with the yielding point caused by the yielding of steel ribs. Almost all the specimens were classified as highly ductile, with ductility values exceeding 9.0 and an equivalent viscous damping ratio between 10 % and 18 %, indicating significant ductility and energy-dissipative capabilities. Furthermore, a simplified FEM model of the modified hold-down is established using ABAQUS software and validated against the experimental results. In addition, a parametric study was conducted to investigate the influences of modified design parameters on the mechanical properties and failure modes. The results of the comparison between the test and FEM model show the robustness of the proposed model in estimating the initial stiffness, post-yield stiffness, and yield force. Ultimately, the modified energy dissipation hold-down effectively rectifies former design flaws over its previous version, resulting in significantly improved performance, high energy dissipation capacity, and ductility by mitigating the brittle failures. This study provides a technical solution for future research to enhance the seismic resilience of modern high-rise CLT buildings through the real-world implementation of this type of modified hold-down connections.

Characteristics and Research Waste of Randomized Clinical Trials in Melanoma.

Numerous large-scale RCTs have propelled the melanoma treatment strategies. Research waste (RW) presents a significant challenge in translating the outcomes of RCTs into clinical practice. Currently, RW has not yet reported in the melanoma-related RCTs. In January 2024, we searched ClinicalTrials.gov for phase 3/4 RCTs registered from January 2000 to December 2023 using "melanoma" as a keyword. We recorded the information listed on the website and searched PubMed and Scopus for the publication and citation status of the RCTs. A completed RCT required at least 47 months of preparation time for publication, hence RCTs completed after December 2019 but not yet published were excluded in the analysis of publication status. A total of 165 RCTs were included in the analysis. Melanoma RCTs primarily studied pharmacological interventions, with the registrations for immunotherapy increasing annually. In the analysis of RW, 103 RCTs were included, of which 41 RCTs (41/103, 39.8%) were unpublished. Of the 62 published RCTs, 19 (19/62, 30.6%) reported insufficiently, and 19 had avoidable design flaws (19/62, 30.6%). Ultimately, 64 (64/103, 62.1%) RCTs were judged to have RW. Registration after 2010, conducting studies in multiple countries, using multiple drug interventions, and having survival as primary outcomes were independent protective factors against RW. Thirty-four RCTs (34/62, 54.8%) were cited by guidelines, and 21 RCTs (21/62, 33.9%) reused their prospective data. We describe the characteristics of phase III/IV RCTs related to melanoma conducted over the past two decades and identify a substantial degree of RW. The protective factors against RW revealed in this study can provide references for the rational and efficient conduct of new RCTs in the future.

Non-firm vs priority access: On the long run average and marginal costs of renewables in Australia

In Australia, the National Electricity Market (NEM) has experienced a rapid expansion of Variable Renewable Electricity (VRE) projects, not without obstacles. Entry frictions such as movements in Marginal Loss Factors and/or network congestion adversely impacted ∼15% of new projects. Are these the expected results in a workably functioning market, or due to market design defects? Policy advisors have sought to reform the NEM's non-firm, open-access regime. As VRE market shares increase, curtailment will increase rapidly through excess generation and/or network congestion, given the ratio of maximum-to-average wind output is 3 times, and solar PV is 4 times. But access reform focused solely on congestion and curtailment may have unintended consequences as a careful analysis of the difference between average and marginal curtailment rates demonstrates. Malalignment between market conventions and access policy may distort entry, raise consumer prices and harm welfare. Our model results confirm that switching from open- to priority access in Australia's NEM and REZ in particular damages consumer and producer welfare materially.

Visual perception and user satisfaction in video see-through head-mounted displays: a mixed-methods evaluation

ObjectiveOur study addresses the challenges limiting the adoption of Extended Reality (XR) Head-Mounted Displays (HMDs), mainly focusing on device quality and cybersickness. We aim to investigate the impact of hardware and software on user experience and task performance while wearing Video See-Through (VST) HMDs. We employ a novel methodology designed to bridge the gaps identified in previous research.MethodsThis study uses a convergent mixed-methods approach, combining qualitative and quantitative data in a within-subjects evaluation involving 20 participants. This comprehensive evaluation examines visual perception, visual quality, and user experience through a range of tasks. Usability, comfort, and cybersickness are assessed, with insights derived from both user performance metrics and subjective measures collected through in-depth interviews and comments. The study includes three distinct HMDs—two prototypes (PD1 and PD2) and one commercial device (CD1)—to provide a broad analysis of the technology.FindingsOur findings reveal that while participants were generally satisfied with VST mode, their preferences varied across devices. CD1 was preferred for its realistic color representation and superior reading task performance due to its high-resolution display and camera. However, visual disturbances and temporal issues differed across devices, with CD1 exhibiting fewer artifacts when stationary but showing more disturbances when participants were moving. Participants found PD1 and PD2 more comfortable for extended use and fewer cybersickness symptoms, but they highlighted color and display resolution issues. These variations underscore the importance of considering both qualitative and quantitative measures in HMD evaluations.ConclusionThis mixed-methods evaluation emphasizes the limitations of relying solely on visual perception performance measures for VST HMDs. By integrating both quantitative and qualitative insights, we offer a more detailed evaluation framework to identify design flaws and user experience issues that quantitative metrics alone might miss. This methodology contributes to the field by illustrating how a mixed-methods approach provides a broader perspective on XR technology, guiding future improvements and enhancing VST adoption in future applications.

Verification of Railway Control Systems Using Model Checking and CTL, Explained Through a Case Study

Systematic faults can often occur during the development of a system. The later such faults are discovered, the more expensive it can be to correct them. In systems engineering practice, there are many methods and tools to reduce the likelihood of systematic faults. In this paper, we present the application of a formal model–based verification technique – called model checking – to assist railway engineers in designing and verifying the safety-related functionality of railway control systems. The proposed process is part of a specification-verification environment that facilitates the construction of correct, complete, consistent, and verifiable functional specifications during development. The results and experience in model checking are illustrated by a case study of a vehicle detection point, a common component in this domain. The model checking of the case study has been performed in the widely used UPPAAL modeling and simulation framework, which can also verify formal properties and generate a counterexample in case of a property violation. By analyzing the counterexample, the designer can gain insights into the system's behavior and identify potential design flaws or failures. Model checking can be used to achieve a higher quality functional specification that is typically more complete and/or contains fewer faults compared to the traditional development approach.

Including validation of process control systems’ engineering into the technical debt classification

The Technical Debt (TD) concept depicts a situation in which a technical compromise is selected despite a better solution available. The associated risks to TD may be critical if TD is overlooked or not fixed properly. For instance, the product might not be used safely (in the healthcare supplies industry) or be contaminated (in the food & beverage sector) due to a design fault not adequately addressed. This work extends the TD classification for process automation systems that need to undergo a validation process according to Good Automated Manufacturing Practice (GAMP), which is required for pharmaceutical production or food processing, for example. The approach analysed industrial engineering documents to identify such TD types and sub-types. Three selected TD use cases confirmed by industry experts are reported. The presented meta-analysis approach on engineering documents can be employed as a TD identification method for such process control systems. The TD classification for process automation was thereby enlarged for an especially critical type of machine that may harm the health of many humans.

In vivo safety and pulmonary vein isolation performance of a new cryoballoon for the treatment of atrial fibrillation.

Cryoablation to achieve pulmonary vein (PV) isolation has become one of the standard approaches for atrial fibrillation (AF) ablation. The Arctic Front series cryoballoon and Achieve circular mapping catheter (Medtronic) inherently possess design defects that have been associated with unfavorite clinical outcomes. Lately, a new cryoablation system (Nordica Cryoablation System, Synaptic Medical) was developed with improved design of the cryoballoon and circular mapping catheter to address the inadequacies of current cryoablation technology. An animal study was conducted to test the efficacy and safety in performing PVI with the Nordica Cryoablation System. Pulmonary vein isolation with the Nordica Cryoablation System was performed on 12 PVs of six healthy canines. Acute PVI and peri-procedural complications were recorded. All animals underwent a repeat EP study at least 4 weeks after index procedures followed by pathological and histological assessments of the heart and collateral/downstream organs after planned euthanasia. Acute PV isolation was achieved in all targeted PVs with 50% of PVs being isolated with a single cryoablation application. There were no major peri-procedural complications or device malfunction events. All PVs remained isolated after 29-30 days follow-up. Histological examination showed transmural cryo-lesions at treated sites with minimal inflammation, neovascularization, and neointima formation but no significant injury to adjacent tissue or embolization in downstream organs. Acute and durable PVI can be achieved by using the novel Nordica Cryoablation System. Ablation with this new cryoablation system is associated with transmural lesions at targeted myocardium but creates no injury to the collateral tissues or downstream organs.

Five aspects of research waste in biomedicine: A scoping review.

The number of published journal articles has grown exponentially during the last 30 years, which may have led to some wasteful research. However, the terminology associated with research waste remains unclear. To address this, we aimed to identify, define, and categorize the aspects of research waste in published biomedical reports. In this scoping review, we systematically searched for biomedical literature reports from 1993 to 2023 in two databases, focusing on those addressing and defining research waste. Through data charting, we analyzed and categorized the aspects of research waste. Based on 4285 initial records in the searches, a total of 832 reports were included in the analysis. The included reports were primarily narrative reviews (26%) and original reports (21%). We categorized research waste into five aspects: methodological, invisible, negligible, underreported, and structural (MINUS) research waste. More than half of the reports (56%) covered methodological research waste concerning flaws in study design, study conduct, or analysis. Invisible research waste covered nonpublication, discontinuation, and lack of data-sharing. Negligible research waste primarily concerned unnecessary repetition, for example, stemming from the absence of preceding a trial with a systematic review of the literature. Underreported research waste mainly included poor reporting, resulting in a lack of transparency. Structural research waste comprised inadequate management, collaboration, prioritization, implementation, and dissemination. MINUS encapsulates the five main aspects of research waste. Recognizing these aspects of research waste is important for addressing and preventing further research waste and thereby ensuring efficient resource allocation and scientific integrity.

Strength Evaluation of the Flow Passage Stationary Structures of a Large Francis Turbine Unit

Abstract The multifield design and multifield coupling performance of the Francis turbine unit is a topic that needs to be studied deeply. In this paper, the strength evaluation of the stationary structures of the flow passage of a large Francis turbine unit under extreme conditions has been performed based on the fluid-structure coupling theory. The calculated stationary structures include the spiral casing, bottom ring, and head cover. The pressure load applied on the structures is 1.5 times the maximum head of the unit. The results show that there is stress concentration in the spiral casing, and the weld length with equivalent stress greater than 345 MPa reaches 800 mm; the maximum stress at the rib plate of the head cover reaches 357 MPa, which is greater than the yield limit 345MPa. Based on the evaluation results, the local and overall defects of the unit design can be found. The suggested strength evaluation methodology can provide references for the optimization of the unit and a theoretical basis for the operation of the unit.

Exploration of a method for insight into accessibility design flaws based on touch dynamics

The widespread use of smartphones implies that intelligent systems must address the negative emotions experienced by a diverse user group when encountering usability difficulties. Therefore, exploring the relationship between users’ emotions and operational behaviors is crucial for further enhancing the accessibility of intelligent systems. Touch dynamics, as a method of dynamic touch data monitoring, has already provided many models for emotion recognition, which are beneficial in gaining insight into users’ accessibility needs for smartphones and exploring intelligent solutions to design issues. This paper validates this aspect through interviews and experimental studies. The study first conducted an open-ended interview, and then used a touch behavior experiment with emotional labels and a questionnaire to validate the association between accessibility design flaws in intelligent systems and user emotions. The interview results show that middle-aged and older smartphone users have difficulty activating accessibility tools independently. Consequently, this paper establishes a dataset for emotion classification based on touch gesture data, which is used to gain insight into implicit difficulties in the interaction process through negative emotions. From a touch experiment and questionnaire survey of 57 sample users, there is approximately a 78.57% match between the accessibility needs of intelligent systems and users’ negative emotions, with interaction fluency and interface cognition being the main reasons for this phenomenon. Therefore, touch dynamics, as a non-invasive method of emotion recognition, can use negative emotional feedback to gain insights into user needs that are difficult to detect by other methods. This has application value for enhancing users’ emotional experience and promoting a transformation in interaction design thinking.

How accessible are cities for visually impaired pedestrians? A case of Greater London

Urban planning and design aim to encourage active mobility by promoting various models that assess a city’s transportability and accessibility. In practice, these models are not attuned to a huge part of the population that have mobility impairments, therefore they uphold a flawed city design and prevent these populations from being an equal part of the inclusive city vision. We suggest an approach to develop new visually impaired mobility accessibility indices of urban space using open-source geospatial data and showcase them across different wards and boroughs in Greater London. Results show the various urban accessibility levels for visually impaired pedestrians, pointing to existing problems this community faces when navigating the city, such as challenging street network connectivity and dangerous walking areas. These indices can be used for more inclusive city planning and design, enhancing urban mobility and walkability equality, and improving this community’s quality of life.

Enabling Health Information Recommendation Using Crowdsourced Refinement in Web-Based Health Information Applications: User-Centered Design Approach and EndoZone Informatics Case Study.

In the digital age, search engines and social media platforms are primary sources for health information, yet their commercial interests-focused algorithms often prioritize irrelevant content. Web-based health applications by reputable sources offer a solution to circumvent these biased algorithms. Despite this advantage, there remains a significant gap in research on the effective integration of content-ranking algorithms within these specialized health applications to ensure the delivery of personalized and relevant health information. This study introduces a generic methodology designed to facilitate the development and implementation of health information recommendation features within web-based health applications. We detail our proposed methodology, covering conceptual foundation and practical considerations through the stages of design, development, operation, review, and optimization in the software development life cycle. Using a case study, we demonstrate the practical application of the proposed methodology through the implementation of recommendation functionalities in the EndoZone platform, a platform dedicated to providing targeted health information on endometriosis. Application of the proposed methodology in the EndoZone platform led to the creation of a tailored health information recommendation system known as EndoZone Informatics. Feedback from EndoZone stakeholders as well as insights from the implementation process validate the methodology's utility in enabling advanced recommendation features in health information applications. Preliminary assessments indicate that the system successfully delivers personalized content, adeptly incorporates user feedback, and exhibits considerable flexibility in adjusting its recommendation logic. While certain project-specific design flaws were not caught in the initial stages, these issues were subsequently identified and rectified in the review and optimization stages. We propose a generic methodology to guide the design and implementation of health information recommendation functionality within web-based health information applications. By harnessing user characteristics and feedback for content ranking, this methodology enables the creation of personalized recommendations that align with individual user needs within trusted health applications. The successful application of our methodology in the development of EndoZone Informatics marks a significant progress toward personalized health information delivery at scale, tailored to the specific needs of users.

Revisiting the success of co‐management in forest protected areas of Bangladesh: Untangling the interplay of power, participation, and community empowerment

AbstractThis narrative review critically assesses the implementation and purported success of co‐management in forest management in Bangladesh. Co‐management has gained global popularity, celebrated for its participatory approach to natural resource conflict resolution, yet critiqued for potential design flaws, susceptibility to elite capture, and perpetuating power imbalances in predominantly top‐down management cultures. Despite two decades of application and reports of positive outcomes in managing forest protected areas of Bangladesh, concerns persist regarding the authenticity of its success and sustainability, particularly in terms of power dynamics and effective community participation in decision‐making processes. The review delves into these aspects, revealing instances where successes might be superficial, overlooking the underlying issues of power disparity among stakeholders. It highlights the crucial role of enhancing social capital within co‐management frameworks to foster institutionalization and sustainability. Recommendations include advancing robust collaboration and communication, alongside the adoption of adaptive management practices to navigate the complex interplay of natural, social, and institutional challenges.

Power deposition in the He bath induced by the Z gradient coil in the 11.7 T Iseult magnet: theory versus measurements

Gradient-magnet interactions increase with higher field magnets and stronger gradient coils. Perhaps the most sensitive aspect is magnet quench, which can be induced by a loss of superconductivity of the main coil caused by a rise of the temperature of the He bath with gradient activity. Predicting power depositions thereby can be a very valuable tool to avoid dangerous frequency zones but also eventually correct design flaws. In this work, we report model predictions compared to measurements of power deposition in the He bath of the Iseult 11.7 T magnet for the Z gradient coil axis.

Fault diagnosis of axial piston pump based on multi-source subdomain adaptation and sensor data fusion

The axial piston pump is the core component in hydraulic systems. Its condition monitoring and fault diagnosis are crucial to ensure the safe and reliable operation of hydraulic systems. However, most of the existing fault diagnosis methods for axial piston pumps use the same working condition data. In actual operation, axial piston pump often experience varying loads, and the collected data is typically correlated but has different distributions. Therefore, a transfer learning method of multi-source subdomain adaptation and sensor fusion (MSASF) is proposed for fault diagnosis of axial piston pump. The proposed MSASF has three modules, a shared feature extraction module, a domain-specific feature extraction module and an output decision module. Firstly, the adaptive weighted fusion of multi-sensor data features is realized by the shared feature extraction module and the common features of multi-source heterogeneous data are extracted. Secondly, in the domain-specific feature extraction module, multi-branch network is used to extract features of each pair of source and target domains and the local maximum mean difference is utilized to align the sub-domain distribution of each pair of source and target domains. Finally, in the output decision module, the distribution distance between each pair of source domain and target domain is calculated using maximum mean discrepancy to obtain its weighted score. Combined with the classification output of each source domain, the final diagnosis decision is made. A dataset was constructed for the axial piston pump design fault experiment, and four sets of transfer tasks were designed to compare with those of seven classic methods. The experimental results showed that the proposed MSASF method exhibits a superior domain adaptation effect and fault diagnosis performance.

A call for open science in forensics

The modern canon of open science consists of five “schools of thought” that justify unfettered access to the fruits of scientific research: i) public engagement, ii) democratic right of access, iii) efficiency of knowledge gain, iv) shared technology, and v) better assessment of impact. Here, we introduce a sixth school: due process. Due process under the law includes a right to “discovery” by a defendant of potentially exculpatory evidence held by the prosecution. When such evidence is scientific, due process becomes a Constitutional mandate for open science. To illustrate the significance of this new school, we present a case study from forensics, which centers on a federally funded investigation that reports summary statistics indicating that identification decisions made by forensic firearms examiners are highly accurate. Because of growing concern about validity of forensic methods, the larger scientific community called for public release of the complete analyzable dataset for independent audit and verification. Those in possession of the data opposed release for three years while summary statistics were used by prosecutors to gain admissibility of evidence in criminal trials. Those statistics paint an incomplete picture and hint at flaws in experimental design and analysis. Under the circumstances, withholding the underlying data in a criminal proceeding violates due process. Following the successful open-science model of drug validity testing through “clinical trials,” which place strict requirements on experimental design and timing of data release, we argue for registered and open “forensic trials” to ensure transparency and accountability.

Visualization analysis of urban planning assistant decision network 3D system based on intelligent computing

In recent years, with the continuous development of urban construction and the continuous expansion of urban population, the contradiction between spatial planning and actual urban needs in urban construction has become increasingly acute. However, planning decisions based on traditional urban planning renderings and two-dimensional (2D) planar plans are no longer in line with the actual development needs and specific development status of the city. Urban planning 3D auxiliary systems can improve the accuracy and precision of urban planning decisions. By providing planners with detailed 3D spatial models of the urban environment, potential design defects or conflicts can be identified before urban construction starts. This can reduce costs and risks related to urban development and help create a more livable and sustainable urban environment. This article analyzed and studied urban planning problems based on a three-dimensional (3D) auxiliary system of intelligent computing. In order to examine the effectiveness of intelligent computing 3D auxiliary systems in urban planning and construction, three indicators of development sustainability, transportation network convenience, and urban livability were established for effectiveness evaluation. The final experimental results showed that the average score of the 3D urban planning assistance system based on intelligent computing in urban development sustainability was 9.29 points, transportation convenience score was 92.08 points, and urban livability score was 9.249 points.

Improving and comparing performance of machine learning classifiers optimized by swarm intelligent algorithms for code smell detection

In complex systems, the maintenance phase engenders the emergence of code smells due to incessant shifts in requirements and designs, stringent timelines, and the developer's relative inexperience. While not conventionally classified as errors, code smells inherently signify flawed design structures that lead to future bugs and errors. It increases the software budget and eventually makes the system hard to maintain or completely obsolete. To mitigate these challenges, practitioners must detect and refactor code smells. However, the theoretical interpretation of smell definitions and intelligent establishment of threshold values pose a significant conundrum. Supervised machine learning emerges as a potent strategy to address these problems and alleviate the dependence on expert intervention. The learning mechanism of these algorithms can be refined through data pre-processing and hyperparameter tuning. Selecting the best values for hyperparameters can be tedious and requires an expert. This study introduces an innovative paradigm that fuses twelve swarm-based, meta-heuristic algorithms with two machine learning classifiers, optimizing their hyperparameters, eliminating the need for an expert, and automating the entire code smell detection process. Through this synergistic approach, the highest post-optimization accuracy, precision, recall, F-measure, and ROC-AUC values are 99.09%, 99.20%, 99.09%, 98.06%, and 100%, respectively. The most remarkable upsurge is 35.9% in accuracy, 53.79% in precision, 35.90% in recall, 44.73% in F-measure, and 36.28% in ROC-AUC. Artificial Bee Colony, Grey Wolf, and Salp Swarm Optimizer are the top-performing swarm-intelligent algorithms. God and Data Class are the most readily detectable smells with optimized classifiers. Statistical tests underscore the profound impact of employing swarm-based algorithms to optimize machine learning classifiers, corroborated by statistical tests. This seamless integration enhances classifier performance, automates code smell detection, and offers a robust solution to a persistent software engineering challenge.

Underpass Water Logging System Using IOT and ML

In recent years, the surge in population growth has exacerbated numerous challenges for both humans and the environment, including issues like inadequate infrastructure and frequent occurrences of waterlogging in underpasses. During heavy rainfall, underpasses often become inundated, posing significant risks to passing vehicles and exacerbating traffic congestion. This is primarily due to ineffective drainage systems and flawed designs for diverting rainwater away from the underpasses. To address these pressing issues, this paper proposes an IoT-based solution aimed at monitoring and managing heavy traffic within underpasses. The primary objective is to establish a comprehensive framework capable of continuously monitoring the water levels within underpasses. By leveraging IoT technology, this framework can activate warning signs and implement traffic control measures in real-time to mitigate the risks posed by waterlogging and alleviate traffic congestion. This innovative approach not only offers a proactive solution to the immediate challenges faced by underpasses but also lays the foundation for a more sustainable and efficient urban infrastructure management system. Through the integration of IoT sensors and intelligent control mechanisms, this framework promises to enhance the resilience of underpasses to adverse weather conditions while optimizing traffic flow, ultimately contributing to safer and more livable urban environments . Keywords — Internet of Things, sensors, Wi-Fi module, LCD, cloud architecture.