Search results for: errors analysis

Authors: Kuan-Jen Lai, Fang-Yi Lin, Shang-Rong Huang, Yun-Zheng Zeng, Po-Chieh Hsu, Jay Wu

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The normalized glandular dose (DgN) estimates the energy deposition of mammography in clinical practice. The Monte Carlo simulations frequently use uniformly mixed phantom for calculating the conversion factor. However, breast tissues are not uniformly distributed, leading to errors of conversion factor estimation. This study constructed a three-layer phantom to estimated more accurate of normalized glandular dose. In this study, MCNP code (Monte Carlo N-Particles code) was used to create the geometric structure. We simulated three types of target/filter combinations (Mo/Mo, Mo/Rh, Rh/Rh), six voltages (25 ~ 35 kVp), six HVL parameters and nine breast phantom thicknesses (2 ~ 10 cm) for the three-layer mammographic phantom. The conversion factor for 25%, 50% and 75% glandularity was calculated. The error of conversion factors compared with the results of the American College of Radiology (ACR) was within 6%. For Rh/Rh, the difference was within 9%. The difference between the 50% average glandularity and the uniform phantom was 7.1% ~ -6.7% for the Mo/Mo combination, voltage of 27 kVp, half value layer of 0.34 mmAl, and breast thickness of 4 cm. According to the simulation results, the regression analysis found that the three-layer mammographic phantom at 0% ~ 100% glandularity can be used to accurately calculate the conversion factors. The difference in glandular tissue distribution leads to errors of conversion factor calculation. The three-layer mammographic phantom can provide accurate estimates of glandular dose in clinical practice.

Keywords: Monte Carlo simulation, mammography, normalized glandular dose, glandularity

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Authors: Maryam Khalilzadeh Poshtegal, Seyed Ahmad Mirbagheri, Mojtaba Noury

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In this paper, by application of the input yearly data of rainfall, temperature and flow to the Urmia Lake, the simulation of water level fluctuation were applied by means of three models. According to the climate change investigation the fluctuation of lakes water level are of high interest. This study investigate data-driven models, support vector machines (SVM), SVM method which is a new regression procedure in water resources are applied to the yearly level data of Lake Urmia that is the biggest and the hyper saline lake in Iran. The evaluated lake levels are found to be in good correlation with the observed values. The results of SVM simulation show better accuracy and implementation. The mean square errors, mean absolute relative errors and determination coefficient statistics are used as comparison criteria.

Keywords: simulation, water level fluctuation, urmia lake, support vector machine

Procedia PDF Downloads 332

Authors: Stefanie Santorsola, Natasha Frank

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Improving healthcare safety necessitates examining current trends and beliefs about safety and devising strategies to improve. Errors in healthcare continue to increase and be experienced by patients, which is preventable and directly correlated to a breakdown in healthcare communication. TeamSTEPPS is an evidence-based process designed to improve the quality and safety of healthcare by improving communication and team processes. Communication is at the core of effective team collaboration and is vital for patient safety. TeamSTEPPS offers insights and strategies for improving communication and teamwork and reducing preventable errors to create a safer healthcare environment for patients. The academic, clinical, and educational environment for nursing students is vital in preparing them for professional practice by providing them with foundational knowledge and abilities. This environment provides them with a prime opportunity to learn about errors and the importance of effective communication to enhance patient safety, as nursing students are often unprepared to deal with errors. Proactively introducing and discussing errors through a supportive culture during the nursing student’s academic beginnings has the potential to carry key concepts into practice to improve and enhance patient safety. TeamSTEPPS has been used globally and has collectively positively impacted improvements in patient safety and teamwork. A workshop study was introduced in winter 2023 of registered practical nurses (RPN) students bridging to the baccalaureate nursing program; the majority of the RPNs in the bridging program were actively employed in a variety of healthcare facilities during the semester. The workshop study did receive academic institution ethics board approval, and participants signed a consent form prior to participating in the study. The premise of the workshop was to introduce TeamSTEPPS and a variety of strategies to these students and have students keep a reflective journal to incorporate the presented communication strategies in their practicum setting and keep a reflective journal on the effect and outcomes of the strategies in the healthcare setting. Findings from the workshop study supported the objective of the project, resulting in students verbalizing notable improvements in team functioning in the healthcare environment resulting from the incorporation of enhanced communication strategies from TeamSTEPPS that they were introduced to in the workshop study. Implication for educational institutions is the potential of further advancing the safety literacy and abilities of nursing students in preparing them for entering the workforce and improving safety for patients.

Keywords: teamstepps, education, patient safety, communication

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Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

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Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

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Authors: Sakshi Chopra, Ashima Nehra, Sumit Sinha, Harsimarpreet Kaur, Ravindra Mohan Pandey

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Background: Cognitive rehabilitation aims to retrain brain injured individuals with cognitive deficits to restore or compensate lost functions. As illiterates or people with low literacy levels represent a significant proportion of the world, specific rehabilitation modules for such populations are indispensable. Literacy is significantly associated with all neuropsychological measures and retraining programs widely use written or spoken techniques which essentially require the patient to read or write. So, the aim of the study was to develop and standardize a literacy free neuropsychological rehabilitation program for improving cognitive functioning in patients with mild and moderate Traumatic Brain Injury (TBI). Several studies have pointed out to the impairments seen in memory, executive functioning, and attention and concentration post-TBI, so the rehabilitation program focussed on these domains. Visual item memorization, stick constructions, symbol cancellations, and colouring techniques were used to construct the retraining program. Methodology: The development of the program consisted of planning, preparing, analyzing, and revising the different modules. The construction focussed on areas of retraining immediate and delayed visual memory, planning ability, focused and divided attention, concentration, and response inhibition (to control irritability and aggression). A total of 98 home based retraining modules were prepared in the 4 domains (42 for memory, 42 for executive functioning, 7 for attention and concentration, and 7 for response inhibition). The standardization was done on 20 healthy controls to review, select and edit items. For each module, the time, errors made and errors per second were noted down, to establish the difficulty level of each module and were arranged in increasing level of difficulty over a period of 6 weeks. The retraining tasks were then administered on 11 brain injured individuals (5 after Mild TBI and 6 after Moderate TBI). These patients were referred from the Trauma Centre to Clinical Neuropsychology OPD, All India Institute of Medical Sciences, New Delhi, India. Results: The time was taken, errors made and errors per second were analysed for all domains. Education levels were divided into illiterates, up to 10 years, 10 years to graduation and graduation and above. Mean and standard deviations were calculated. Between group and within group analysis was done using the t-test. The performance of 20 healthy controls was analyzed and only a significant difference was observed on the time taken for the attention tasks and all other domains had non-significant differences in performance between different education levels. Comparing the errors, time taken between patient and control group, there was a significant difference in all the domains at the 0.01 level except the errors made on executive functioning, indicating that the tool can successfully differentiate between healthy controls and patient groups. Conclusions: Apart from the time taken for symbol cancellations, the entire cognitive rehabilitation program is literacy free. As it taps the major areas of impairment post-TBI, it could be a useful tool to rehabilitate the patient population with low literacy levels across the world. The next step is already underway to test its efficacy in improving cognitive functioning in a randomized clinical controlled trial.

Keywords: cognitive rehabilitation, illiterates, India, traumatic brain injury

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Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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Authors: Rachid Ed-Dali, Khalid Elasri

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Mass media seem to provide a rich content for language acquisition. Exposure to television, the Internet, the mobile phone and other technological gadgets and devices helps enrich the student’s lexicon positively as well as negatively. The difficulties encountered by students while learning and acquiring second languages in addition to their eagerness to comprehend the content of a particular program prompt them to diversify their methods so as to achieve their targets. The present study highlights the significance of certain media channels and their involvement in language acquisition with the employment of the Natural Approach to further grasp whether students, especially secondary and high school students, learn and acquire errors through watching subtitled television programs. The chief objective is investigating the deductive and inductive relevance of certain programs beside the involvement of peripheral learning while acquiring mistakes.

Keywords: errors, mistakes, Natural Approach, peripheral learning, solecism

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Authors: Jaejun Jong

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Fake news has recently become a serious international problem. Therefore, researchers and policymakers worldwide have sought to understand fake news and develop strategies to combat it. This study consists of two primary parts: (1) a literature review of how surveys were used to understand fake news and identify problems caused by fake news, and (2) a discussion of how surveys were used to fight back against fake news in educational settings. This second section specifically analyzes surveys used to evaluate a South Korean elementary school program designed to improve students’ metacognition and critical thinking. This section seeks to identify potential problems that may occur in the elementary school setting. The literature review shows that surveys can help people to understand fake news based on its traits rather than its definition due to the lack of agreement on the definition of fake news. The literature review also shows that people are not good at identifying fake news or evaluating their own ability to identify fake news; indeed, they are more likely to share information that aligns with their previous beliefs. In addition, the elementary school survey data shows that there may be substantial errors in the program evaluation process, likely caused by processing errors or the survey procedure, though the exact cause is not specified. Such a significant error in evaluating the effects of the educational program prevents teachers from making proper decisions and accurately evaluating the program. Therefore, identifying the source of such errors would improve the overall quality of education, which would benefit both teachers and students.

Keywords: critical thinking, elementary education, program evaluation, survey

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Authors: Palanisamy Sivanandy, Tan Tyng Wei, Tan Wee Loon, Lim Chong Yee

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Background: Patient safety has become a major concern over recent years with elevated medication errors; particularly prescribing and dispensing errors. Meticulous prescription screening and diligent drug dispensing is therefore important to prevent drug-related adverse events from inflicting harm to patients. Hence, pharmacists play a significant role in this scenario. The evaluation of patient safety in a pharmacy setup is crucial to contemplate current practices, attitude and perception of pharmacists towards patient safety. Method: The questionnaire for Pharmacy Survey on Patient Safety Culture developed by the Agency for Healthcare and Research Quality (AHRQ) was used to assess patient safety. Main objectives of the study was to evaluate the attitude and perception of pharmacists towards patient safety in retail pharmacies setup in Malaysia. Results: 417 questionnaire were distributed via convenience sampling in three different states of Malaysia, where 390 participants were responded and the response rate was 93.52%. The overall positive response rate (PRR) was ranged from 31.20% to 87.43% and the average PRR was found to be 67%. The overall patient safety grade for our pharmacies was appreciable and it ranges from good to very good. The study found a significant difference in the perception of senior and junior pharmacists towards patient safety. The internal consistency of the questionnaire contents /dimensions was satisfactory (Cronbach’s alpha - 0.92). Conclusion: Our results reflect that there was positive attitude and perception of retail pharmacists towards patient safety. Despite this, various efforts can be implemented in the future to amplify patient safety in retail pharmacies setup.

Keywords: patient safety, attitude, perception, positive response rate, medication errors

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Authors: Rafsan Al Mamun, Md. Motaharul Islam, Rabana Tajrin, Nabiha Noor, Shafinaz Qader

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In an attempt to enrich the lives of billions of people by providing proper information, security and a way of communicating with others, the need for efficient and improved satellites is constantly growing. Thus, there is an increasing demand for better error detection and correction (EDAC) schemes, which are capable of protecting the data onboard the satellites. The paper is aimed towards detecting and correcting such errors using a special algorithm called the Hamming Code, which uses the concept of parity and parity bits to prevent single-bit errors onboard a satellite in Low Earth Orbit. This paper focuses on the study of Low Earth Orbit satellites and the process of generating the Hamming Code matrix to be used for EDAC using computer programs. The most effective version of Hamming Code generated was the Hamming (16, 11, 4) version using MATLAB, and the paper compares this particular scheme with other EDAC mechanisms, including other versions of Hamming Codes and Cyclic Redundancy Check (CRC), and the limitations of this scheme. This particular version of the Hamming Code guarantees single-bit error corrections as well as double-bit error detections. Furthermore, this version of Hamming Code has proved to be fast with a checking time of 5.669 nanoseconds, that has a relatively higher code rate and lower bit overhead compared to the other versions and can detect a greater percentage of errors per length of code than other EDAC schemes with similar capabilities. In conclusion, with the proper implementation of the system, it is quite possible to ensure a relatively uncorrupted satellite storage system.

Keywords: bit-flips, Hamming code, low earth orbit, parity bits, satellite, single error upset

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Authors: Alla Levina, Sergey Taranov

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The classical approach to the providing noise immunity and integrity of information that process in computing devices and communication channels is to use linear codes. Linear codes have fast and efficient algorithms of encoding and decoding information, but this codes concentrate their detect and correct abilities in certain error configurations. To protect against any configuration of errors at predetermined probability can robust codes. This is accomplished by the use of perfect nonlinear and almost perfect nonlinear functions to calculate the code redundancy. The paper presents the error-correcting coding scheme using biorthogonal wavelet transform. Wavelet transform applied in various fields of science. Some of the wavelet applications are cleaning of signal from noise, data compression, spectral analysis of the signal components. The article suggests methods for constructing linear codes based on wavelet decomposition. For developed constructions we build generator and check matrix that contain the scaling function coefficients of wavelet. Based on linear wavelet codes we develop robust codes that provide uniform protection against all errors. In article we propose two constructions of robust code. The first class of robust code is based on multiplicative inverse in finite field. In the second robust code construction the redundancy part is a cube of information part. Also, this paper investigates the characteristics of proposed robust and linear codes.

Keywords: robust code, linear code, wavelet decomposition, scaling function, error masking probability

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Authors: Johanna Renny Octavia, Meliana Nurdin, Ignatius Kevin Kurniawan, Ricca Aksara

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It is widely believed that usability evaluation is necessary to evaluate a website design for further improvement. Traditional methods of usability evaluation have given sufficient insights to reveal usability problems of websites. Eye-tracking analysis has been considered as a useful method that adds a powerful dimension to web usability evaluation. It allows web designers and usability researchers to understand exactly what users do and do not see on a web page, thus disclose more information on web usability and provide a more complete insights on a website design. This paper elaborates on moving beyond traditional methods of web usability evaluation by integrating eye-tracking analysis to enhance the evaluation of website design, and presents three case studies to support this approach. In these case studies, eye movement metrics such as gaze plots and fixation-derived metrics, and user performance data such as task completion times and number of errors were recorded as objective measurements that can inform the necessity for website design improvements.

Keywords: design, eye-tracking, usability evaluation, website

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Authors: Renate Krassnig, Gloria M. Hohenberger, Uldis Berzins, Stefen Fischerauer

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Background: Only a few reports discuss the effectiveness of intraoperative radiographs for placing femoral components. Therefore there is no international standard in using intraoperative imaging in the proceeding of total hip replacement. Method: Case report; an 84-year-old female patient underwent changing the components of the Total hip arthroplasty (THA) because of aseptic loosening. Due to circumstances, the surgeon decided to implant a cemented femoral component. The procedure was without any significant abnormalities. The first postoperative radiograph was planned after recovery – as usual. The x-ray imaging showed a misplaced femoral component. Therefore a CT-scan was performed additionally and the malposition of the cemented femoral component was confirmed. The patient had to undergo another surgery – removing of the cemented femoral component and implantation of a new well placed one. Conclusion: Intraoperative imaging of the femoral component is not a common standard but this case shows that intraoperative imaging is a useful method for detecting errors and gives the surgeon the opportunity to correct errors intraoperatively.

Keywords: femoral component, intraoperative imaging, malplacement, revison

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Authors: A. S. Ibrahim Mamane, S. Giljean, M.-J. Pac, G. L’Hostis

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Fiber reinforced composite laminates are particularly subject to residual stresses due to their heterogeneity and the complex chemical, mechanical and thermal mechanisms that occur during their processing. Residual stresses are now well known to cause damage accumulation, shape instability, and behavior disturbance in composite parts. Many works exist in the literature on techniques for minimizing residual stresses in thermosetting and thermoplastic composites mainly. To study in-depth the influence of processing mechanisms on the formation of residual stresses and to minimize them by establishing a reliable correlation, it is essential to be able to measure very precisely the profile of residual stresses in the composite. Residual stresses are important data to consider when sizing composite parts and predicting their behavior. The incremental hole drilling is very effective in measuring the gradient of residual stresses in composite laminates. This method is semi-destructive and consists of drilling incrementally a hole through the thickness of the material and measuring relaxation strains around the hole for each increment using three strain gauges. These strains are then converted into residual stresses using a matrix of coefficients. These coefficients, called calibration coefficients, depending on the diameter of the hole and the dimensions of the gauges used. The reliability of the incremental hole drilling depends on the accuracy with which the calibration coefficients are determined. These coefficients are calculated using a finite element model. The samples’ features and the experimental conditions must be considered in the simulation. Any mismatch can lead to inadequate calibration coefficients, thus introducing errors on residual stresses. Several calibration coefficient correction methods exist for isotropic material, but there is a lack of information on this subject concerning composite laminates. In this work, a Python program was developed to automatically generate the adequate finite element model. This model allowed us to perform a parametric study to assess the influence of experimental errors on the calibration coefficients. The results highlighted the sensitivity of the calibration coefficients to the considered errors and gave an order of magnitude of the precisions required on the experimental device to have reliable measurements. On the basis of these results, improvements were proposed on the experimental device. Furthermore, a numerical method was proposed to correct the calibration coefficients for different types of materials, including thick composite parts for which the analytical approach is too complex. This method consists of taking into account the experimental errors in the simulation. Accurate measurement of the experimental errors (such as eccentricity of the hole, angular deviation of the gauges from their theoretical position, or errors on increment depth) is therefore necessary. The aim is to determine more precisely the residual stresses and to expand the validity domain of the incremental hole drilling technique.

Keywords: fiber reinforced composites, finite element simulation, incremental hole drilling method, numerical correction of the calibration coefficients, residual stresses

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Authors: Abdelbaset M. Elghriani, Abdelsalam M. Maatuk, Isam Denna, Amira Abdulla Werfalli

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Electronic prescription software (e-prescribing) benefits patients and physicians by preventing handwriting errors and giving accurate prescriptions. E-prescribing allows prescriptions to be written and sent to pharmacies electronically instead of using handwritten notes. Significant factors that may affect the adoption of e-prescription systems include lacking technical support, financial resources to operate the systems, and change resistance from some clinicians, which have been identified as barriers to the implementation of e-prescription systems. This study aims to explore the trends and opinions of physicians and pharmacists about e-prescriptions and to identify the obstacles and benefits of the application of e-prescriptions in the health care system. A cross-sectional descriptive study was conducted at three Libyan public hospitals. Data were collected through a self-constructed questionnaire to assess the opinions regarding potential constraining factors and benefits of implementing an e-prescribing system in hospitals. Data presented as mean, frequency distribution table, cross-tabulation, and bar charts. Data analysis was performed, and the results show that technical, financial, and organizational obstacles are the most important obstacles that prevent the application of e-prescribing systems in Libyan hospitals. In addition, there was awareness of the benefits of e-prescribing, especially reducing medication dispensing errors, and a desire of physicians and pharmacists to use electronic prescriptions.

Keywords: physicians, e-prescribing, health care system, pharmacists

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Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz

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In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.

Keywords: software quality, fuzzy logic, perception, prediction

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Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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Authors: Maxime Merheb, Rachel Matar

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Retrieving ancient DNA sequences which in return permit the entire genome sequencing from fossils have extraordinarily improved in recent years, thanks to sequencing technology and other methodological advances. In any case, the quest to search for ancient DNA is still obstructed by the damage inflicted on DNA which accumulates after the death of a living organism. We can characterize this damage into three main categories: (i) Physical abnormalities such as strand breaks which lead to the presence of short DNA fragments. (ii) Modified bases (mainly cytosine deamination) which cause errors in the sequence due to an incorporation of a false nucleotide during DNA amplification. (iii) DNA modifications referred to as blocking lesions, will halt the PCR extension which in return will also affect the amplification and sequencing process. We can clearly see that the issues arising from breakage and coding errors were significantly decreased in recent years. Fast sequencing of short DNA fragments was empowered by platforms for high-throughput sequencing, most of the coding errors were uncovered to be the consequences of cytosine deamination which can be easily removed from the DNA using enzymatic treatment. The methodology to repair DNA sequences is still in development, it can be basically explained by the process of reintroducing cytosine rather than uracil. This technique is thus restricted to amplified DNA molecules. To eliminate any type of damage (particularly those that block PCR) is a process still pending the complete repair methodologies; DNA detection right after extraction is highly needed. Before using any resources into extensive, unreasonable and uncertain repair techniques, it is vital to distinguish between two possible hypotheses; (i) DNA is none existent to be amplified to begin with therefore completely un-repairable, (ii) the DNA is refractory to PCR and it is worth to be repaired and amplified. Hence, it is extremely important to develop a non-enzymatic technique to detect the most degraded DNA.

Keywords: ancient DNA, DNA barcodong, enzymatic repair, PCR

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Authors: M. Pieńko, A. Robak, E. Błazik-Borowa, J. Szer

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This paper presents the results of analysis of 100 full-scale scaffolding structures in terms of compliance with legal acts and safety of use. In 2016 and 2017, authors examined scaffolds in Poland located at buildings which were at construction or renovation stage. The basic elements affecting the safety of scaffolding use such as anchors, supports, platforms, guardrails and toe-boards have been taken into account. All of these elements were checked in each of considered scaffolding. Based on the analyzed scaffoldings, the most common errors concerning assembly process and use of scaffolding were collected. Legal acts on the scaffoldings are not always clear, and this causes many issues. In practice, people realize how dangerous the use of incomplete scaffolds is only when the accident occurs. Despite the fact that the scaffolding should ensure the safety of its users, most accidents on construction sites are caused by fall from a height.

Keywords: façade scaffolds, load capacity, practice, safety of people

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Authors: Hu Zhenxing, Gao Jianxin

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Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

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Authors: Sabrina Azzi, Michal Iglewski, Véronique Nabelsi

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Diagnosis error problem is frequent and one of the most important safety problems today. One of the main objectives of our work is to propose an ontological representation that takes into account the diagnostic criteria in order to improve the diagnostic. We choose pneumonia disease since it is one of the frequent diseases affected by diagnosis errors and have harmful effects on patients. To achieve our aim, we use a semi-automated method to integrate diverse knowledge sources that include publically available pneumonia disease guidelines from international repositories, biomedical ontologies and electronic health records. We follow the principles of the Open Biomedical Ontologies (OBO) Foundry. The resulting ontology covers symptoms and signs, all the types of pneumonia, antecedents, pathogens, and diagnostic testing. The first evaluation results show that most of the terms are covered by the ontology. This work is still in progress and represents a first and major step toward a development of a diagnosis decision support system for pneumonia.

Keywords: Clinical decision support system, Diagnostic errors, Ontology, Pneumonia

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Authors: Kassa Endalamaw Rewnu

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The variability properties of a quasar sample, spectroscopically complete to magnitude J = 22.0, are investigated on a time baseline of 2 years using three different photometric bands (U, J and F). The original sample was obtained using a combination of different selection criteria: colors, slitless spectroscopy and variability, based on a time baseline of 1 yr. The main goals of this work are two-fold: first, to derive the percentage of variable quasars on a relatively short time baseline; secondly, to search for new quasar candidates missed by the other selection criteria; and, thus, to estimate the completeness of the spectroscopic sample. In order to achieve these goals, we have extracted all the candidate variable objects from a sample of about 1800 stellar or quasi-stellar objects with limiting magnitude J = 22.50 over an area of about 0.50 deg2. We find that > 65% of all the objects selected as possible variables are either confirmed quasars or quasar candidates on the basis of their colors. This percentage increases even further if we exclude from our lists of variable candidates a number of objects equal to that expected on the basis of `contamination' induced by our photometric errors. The percentage of variable quasars in the spectroscopic sample is also high, reaching about 50%. On the basis of these results, we can estimate that the incompleteness of the original spectroscopic sample is < 12%. We conclude that variability analysis of data with small photometric errors can be successfully used as an efficient and independent (or at least auxiliary) selection method in quasar surveys, even when the time baseline is relatively short. Finally, when corrected for the different intrinsic time lags corresponding to a fixed observed time baseline, our data do not show a statistically significant correlation between variability and either absolute luminosity or redshift.

Keywords: nuclear activity, galaxies, active quasars, variability

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Authors: Thuvanan Borvornvitchotikarn, Werasak Kurutach

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Mutual information (MI) is widely used in medical image registration. In the different medical images analysis, it is difficult to choose an optimal bins size number for calculating the probability distributions in MI. As the result, this paper presents a new adaptive bins number selection approach that named a hybrid EMPCA-Scott approach. This work combines an expectation maximization principal component analysis (EMPCA) and the modified Scott’s rule. The proposed approach solves the binning problem from the various intensity values in medical images. Experimental results of this work show the lower registration errors compared to other adaptive binning approaches.

Keywords: mutual information, EMPCA, Scott, probability distributions

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Authors: Hui Luo, Zhenhong Li, Zhen Dong

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The analysis of multi-temporal InSAR (MTInSAR) such as persistent scatterer (PS) and small baseline subset (SBAS) techniques usually relies on temporal/spatial phase unwrapping (PU). Unfortunately, it always fails to unwrap the phase for two reasons: 1) spatial phase jump between adjacent pixels larger than π, such as layover and high discontinuous terrain; 2) temporal phase discontinuities such as time varied atmospheric delay. To overcome these limitations, a least-square based PU method is introduced in this paper, which incorporates baseline-combination interferograms and adjacent phase gradient network. Firstly, permanent scatterers (PS) are selected for study. Starting with the linear baseline-combination method, we obtain equivalent 'small baseline inteferograms' to limit the spatial phase difference. Then, phase different has been conducted between connected PSs (connected by a specific networking rule) to suppress the spatial correlated phase errors such as atmospheric artifact. After that, interval phase difference along arcs can be computed by least square method and followed by an outlier detector to remove the arcs with phase ambiguities. Then, the unwrapped phase can be obtained by spatial integration. The proposed method is tested on real data of TerraSAR-X, and the results are also compared with the ones obtained by StaMPS(a software package with 3D PU capabilities). By comparison, it shows that the proposed method can successfully unwrap the interferograms in urban areas even when high discontinuities exist, while StaMPS fails. At last, precise DEM errors can be got according to the unwrapped interferograms.

Keywords: phase unwrapping, time series, InSAR, urban areas

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

Abstract:

Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: wavelet transform, computational error, computational duration, strong ground motion data

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Authors: Shuting Ji, Yueming Zhang, Jing Zhao

Abstract:

The output error of the globoidal cam mechanism can be considered as a relevant indicator of mechanism performance, because it determines kinematic and dynamical behavior of mechanical transmission. Based on the differential geometry and the rigid body transformations, the mathematical model of surface geometry of the globoidal cam is established. Then we present the analytical expression of the output error (including the transmission error and the displacement error along the output axis) by considering different manufacture and assembly errors. The effects of the center distance error, the perpendicular error between input and output axes and the rotational angle error of the globoidal cam on the output error are systematically analyzed. A globoidal cam mechanism which is widely used in automatic tool changer of CNC machines is applied for illustration. Our results show that the perpendicular error and the rotational angle error have little effects on the transmission error but have great effects on the displacement error along the output axis. This study plays an important role in the design, manufacture and assembly of the globoidal cam mechanism.

Keywords: globoidal cam mechanism, manufacture error, transmission error, automatic tool changer

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Authors: Abdelrahman Abdelazim

Abstract:

Most industries are looking for technologies that are easy to use, efficient and fast to accomplish. To implement these, factories tend to use advanced systems that could alter complicity to simplicity and rudimentary to advancement. Cloud Manufacturing is a new movement that aims to mirror and integrate cloud computing into manufacturing. Amongst cloud manufacturing various advantages are decreasing the human involvements and increasing the dependency on automated machines, which in turns decreases human errors and increases efficiency. A reliable and extraordinary performance processes with minimum errors are highly desired factors of today’s manufacturers. At the glance it seems to be the best alternative, however, the implementation of a cloud system can be very challenging. This work investigates cloud manufacturing in details, it outlines its advantages and disadvantages by converting a local factory in Kuwait to a cloud-ready system. Initially the flow of the factory’s manufacturing process has been analyzed identifying the bottlenecks and illustrating how cloud manufacturing can eliminate them. Following this an automation process has been analyzed and implemented. A comparison between the process before and after the adaptation has been carried out showing the effects on the cost, the output and the efficiency of the process.

Keywords: cloud manufacturing, automation, Kuwait industrial sector, advanced digital manufacturing

Procedia PDF Downloads 751

Authors: Alireza Karimi

Abstract:

Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Semion Kertzman, Pinhas Dannon

Abstract:

Impulsive behaviour and the underlying brain processes are hypothesized to be central in the development and maintenance of pathological gambling. Inhibition ability can be differentially impaired in pathological gamblers (PGs). Aims: This study aimed to compare the ability of eight widely used inhibition measures to discriminate between PGs and healthy controls (HCs). Methods: PGs (N=51) and demographically matched HCs (N=51) performed cognitive inhibition (the Stroop), motor inhibition (the Go/NoGo) and reflective inhibition (the Matching Familiar Figures (MFFT)) tasks. Results: An augmented total interference response time in the Stroop task (η² =0.054), a large number of commission errors (η² =0.053) in the Go/NoGo task, and the total number of errors in the MFFT (η² =0.05) can discriminate PGs from HCs. Other measures are unable to differentiate between PGs and HCs. No significant correlations were observed between inhibition measures. Conclusion: Inhibition measures varied in the ability to discriminate PGs from HCs. Most inhibition measures were not relevant to gambling behaviour. PGs do not express rash, impulsive behaviour, such as quickly choosing an answer without thinking. In contrast, in PGs, inhibition impairment was related to slow-inaccurate performance.

Keywords: pathological gambling, impulsivity, neurocognition, addiction

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Authors: Omer Burak Iskender, Keck Voon Ling, Vincent Dubanchet, Luca Simonini

Abstract:

This paper presents Guidance and Control (G&C) strategy to approach and synchronize with potentially rotating targets. The proposed strategy generates and tracks a safe trajectory for space servicing missions, including tasks like approaching, inspecting, and capturing. The main objective of this paper is to validate the G&C laws using a Hardware-In-the-Loop (HIL) setup with realistic rendezvous and docking equipment. Throughout this work, the assumption of full relative state feedback is relaxed by onboard sensors that bring realistic errors and delays and, while the proposed closed loop approach demonstrates the robustness to the above mentioned challenge. Moreover, G&C blocks are unified via the Model Predictive Control (MPC) paradigm, and the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description. In this work, G&C is formulated as a convex optimization problem where constraints such as thruster limits and the output constraints are explicitly handled. Furthermore, the Monte-Carlo method is used to evaluate the robustness of the proposed method to the initial condition errors, the uncertainty of the target's motion and attitude, and actuator errors. A capture scenario is tested with the robotic test bench that has onboard sensors which estimate the position and orientation of a drifting satellite through camera imagery. Finally, the approach is compared with currently used robust H-infinity controllers and guidance profile provided by the industrial partner. The HIL experiments demonstrate that the proposed strategy is a potential candidate for future space servicing missions because 1) the algorithm is real-time implementable as convex programming offers deterministic convergence properties and guarantee finite time solution, 2) critical physical and output constraints are respected, 3) robustness to sensor errors and uncertainties in the system is proven, 4) couples translational motion with rotational motion.

Keywords: dual quaternion, model predictive control, real-time experimental test, rendezvous and docking, spacecraft autonomy, space servicing

Procedia PDF Downloads 114