Search results for: barrel diagnostic

Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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Authors: El Oualid Mokhnache, Noureddine Ramdani

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The choice of gun barrel materials is crucial to ensure the maximum high rate of fire. The high rate of fire causes wear-out damage and shuts off mechanical properties (hardness, strength, wear resistance, etc.) and ballistic properties (bullet speed, dispersion and precision, longevity of barrel, etc). To overcome these kinds of problems, a deep understanding of the effect of the firing cycle on the mechanical and ballistic properties of the barrel is regarded as crucial to improving its characteristics. In the present work, a real experimental test of firing by using a high steel barrel with 7.62x39 ammunition was carried. Microstructural observations by using SEM were investigated. Hardness evolution through the barrel of both barrels labeled as reference barrels and as fired barrels were compared and discussed. Ballistic properties during the firing test, including speed of projectile and precision dispersion, are revealed and discussed as well. The aim of the present communication is about to discuss the relationship between pressure distribution versus mechanical properties through the wall barrel. Ballistic properties, including speed of the projectile, dispersion, and precision results during the shooting process, were investigated. Microstructure observations of the as-rifled barrel in comparison with the as-reference barrel were performed as well.

Keywords: barrel, ballistic, pressure, microstructure evolution, hardness

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Authors: Wei Tian, Jie Liang, Hammad Naveed

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Beta-barrel membrane proteins are found in the outer membrane of gram-negative bacteria, mitochondria, and chloroplasts. They carry out diverse biological functions, including pore formation, membrane anchoring, enzyme activity, and bacterial virulence. In addition, beta-barrel membrane proteins increasingly serve as scaffolds for bacterial surface display and nanopore-based DNA sequencing. Due to difficulties in experimental structure determination, they are sparsely represented in the protein structure databank and computational methods can help to understand their biophysical principles. We have developed a novel computational method to predict the 3D structure of beta-barrel membrane proteins using evolutionary coupling (EC) constraints and a reduced state space. Combined with an empirical potential function, we can successfully predict strand register at > 80% accuracy for a set of 49 non-homologous proteins with known structures. This is a significant improvement from previous results using EC alone (44%) and using empirical potential function alone (73%). Our method is general and can be applied to genome-wide structural prediction.

Keywords: beta-barrel membrane proteins, structure prediction, evolutionary constraints, reduced state space

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Authors: Hamed Bagheri, Seyd Javid Shariati

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The effects of type and amount of solvent on lubricant which is used in disposable medical devices are investigated in this article. Two kinds of common solvent, n-Hexane and n-Heptane, are used. The mechanical behavior of syringe has shown that n-Heptane has better mixing ratio and also more effective spray process in the barrel of syringe than n-Hexane because of similar solubility parameter to silicon oil. The results revealed that movement of plunger in the barrel increases when pure silicone is used because non-uniform film is created on the surface of barrel, and also, it seems that the form of silicon is converted from oil to gel due to sterilization process. The results showed that the convenient mixing ratio of solvent/lubricant oil is 80/20.

Keywords: disposal medical devices, lubricant oil, solvent effect, solubility parameter

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Authors: Arnab Majumdar, Sanjoy Sadhukhan

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Although gun barrel steels are an important variety from defense view point, available literatures are very limited. In the present work, an IF grade Ni-Cr-Mo-V high strength low alloy steel is produced in Electric Earth Furnace-ESR Route. Ingot was hot forged to desired dimension with a reduction ratio of 70-75% followed by homogenization, hardening and tempering treatment. Sample chemistry, NMIR, macro and micro structural analyses were done. Mechanical properties which include tensile, impact, and fracture toughness were studied. Ultrasonic testing was done to identify internal flaws. The existing high strength low alloy Ni-Cr-Mo-V steel shows improved properties in modified processing route and heat treatment schedule in comparison to properties noted earlier for manufacturing of gun barrels. The improvement in properties seems to withstand higher explosive loads with the same amount of steel in gun barrel application.

Keywords: gun barrel steels, IF grade, chemistry, physical properties, thermal and mechanical processing, mechanical properties, ultrasonic testing

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Authors: Tehreem Fatima, Enjun Xia

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The research investigates the relationship between total oil consumption and transport oil consumption, GDP, oil price, and oil reserve in order to forecast future oil demand in China. Annual time series data is used over the period of 1980 to 2015, and for this purpose, an oil demand function is estimated by applying structural time series model (STSM). The technique also uncovers the Underline energy demand trend (UEDT) for China oil demand and GDP, oil reserve, oil price and UEDT are considering important drivers of China oil demand. The long-run elasticity of total oil consumption with respect to GDP and price are (0.5, -0.04) respectively while GDP, oil reserve, and price remain (0.17; 0.23; -0.05) respectively. Moreover, the Estimated results of long-run elasticity of transport oil consumption with respect to GDP and price are (0.5, -0.00) respectively long-run estimates remain (0.28; 37.76;-37.8) for GDP, oil reserve, and price respectively. For both model estimated underline energy demand trend (UEDT) remains nonlinear and stochastic and with an increasing trend of (UEDT) and based on estimated equations, it is predicted that China total oil demand somewhere will be 9.9 thousand barrel per day by 2025 as compare to 9.4 thousand barrel per day in 2015, while transport oil demand predicting value is 9.0 thousand barrel per day by 2020 as compare to 8.8 thousand barrel per day in 2015.

Keywords: china, forecasting, oil, structural time series model (STSM), underline energy demand trend (UEDT)

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Authors: Sohail Imran, Tariq Mahmood

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In complex healthcare diagnostic investigation process, medical practitioners have to focus on ways to standardize their processes to perform high quality care and optimize the time and costs. Process mining techniques can be applied to extract process related knowledge from data without considering causal and dynamic dependencies in business domain and processes. The application of process mining is effective in diagnostic investigation. It is very helpful where a treatment gives no dispositive evidence favoring it. In this paper, we applied process mining to discover important process flow of diagnostic investigation for hepatitis patients. This approach has some benefits which can enhance the quality and efficiency of diagnostic investigation processes.

Keywords: process mining, healthcare, diagnostic investigation process, process flow

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Authors: Vijayan Narayananayar

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Identifying learning gaps is crucial in ensuring learners have the necessary knowledge and skills to succeed. The Learning and Teaching (L&T) approach requires tutors to identify gaps in knowledge and improvise learning activities to close them. One approach to identifying learning gaps is through diagnostic assessment, which uses well-structured questions and answer options. The paper focuses on the use of diagnostic assessment as a learning and teaching approach in a foundational module at a polytechnic. The study used diagnostic assessment over two semesters, including the COVID and post-COVID semesters, to identify gaps in learning. The design of the diagnostic activity, pedagogical intervention, and survey responses completed by learners were analyzed. Results showed that diagnostic assessment can be an effective tool for identifying learning gaps and designing interventions to address them. Additionally, the use of diagnostic assessment provides an opportunity for tutors to engage with learners on a one-to-one basis, tailoring teaching to individual needs. The paper also discusses the design of diagnostic questions and answer options, including characteristics that need to be considered in achieving the target of identifying learning gaps. The implications of using diagnostic assessment as a learning and teaching approach include bridging the gap between theory and practice, and ensuring learners are equipped with skills necessary for their future careers. This paper can be useful in helping educators and practitioners to incorporate diagnostic assessment into their L&T approach.

Keywords: assessment, learning & teaching, diagnostic assessment, analytics

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Authors: S. Sina, B. Zeinali, M. Karimipourfard, F. Lotfalizadeh, M. Sadeghi, E. Zamani, M. Zehtabian, R. Faghihi

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Proper dosimetery is very essential in diagnostic radiology. The goal of this study is to verify the application of LiF:Mg, Cu, P (TLD100H) in obtaining the entrance skin dose (ESD) of patients undergoing diagnostic radiology. The results of dosimetry performed by TLD-100H were compared with those obtained by TLD100, which is a common dosimeter in diagnostic radiology. The results show a close agreement between the dose measured by the two dosimeters. According to the results of this study, the TLD-100H dosimeters have higher sensitivities (i.e. signal(nc)/dose) than TLD-100. Therefore, it is suggested that the TLD-100H are effective dosimeters for dosimetry in low dose fields.

Keywords: entrance skin dose, TLD, diagnostic radiology, dosimeter

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Authors: Kyaw Zin Htut

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In this article, the synthesis of the efficiency of intelligent diagnostic system in the aircraft measuring devices is described. The technology developments of the diagnostic system are considered based on the model errors of the gyro instruments, which are used to measure the parameters of the aircraft. The synthesis of the diagnostic intelligent system is considered on the example of the problem of assessment and forecasting errors of the gyroscope devices on the onboard aircraft. The result of the system is to detect of faults of the aircraft measuring devices as well as the analysis of the measuring equipment to improve the efficiency of its work.

Keywords: diagnostic, dynamic system, errors of gyro instruments, model errors, assessment, prognosis

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Authors: Zhidong Zhang, Yingchen Yang

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In this study, a diagnostic assessment model for Mastery Engineering Learning was established based on a group of undergraduate students who studied in an engineering course. A diagnostic assessment model can examine both students' learning process and report achievement results. One very unique characteristic is that the diagnostic assessment model can recognize the errors and anything blocking students in their learning processes. The feedback is provided to help students to know how to solve the learning problems with alternative strategies and help the instructor to find alternative pedagogical strategies in the instructional designs. Dynamics is a core course in which is a common course being shared by several engineering programs. This course is a very challenging for engineering students to solve the problems. Thus knowledge acquisition and problem-solving skills are crucial for student success. Therefore, developing an effective and valid assessment model for student learning are of great importance. Diagnostic assessment is such a model which can provide effective feedback for both students and instructor in the mastery of engineering learning.

Keywords: diagnostic assessment, mastery learning, engineering, bayesian network model, learning processes

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Authors: Yuxuan Tang

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Cognitive diagnostic assessment has received much attention in second language education, and assessment for it can provide pedagogically useful feedback for language learners. However, there is a lack of research on how students interpret and use cognitive diagnostic feedback. Thus the present study aims to adopt a mixed-method approach mainly to explore the relationship between the goal-orientation and students' response to cognitive diagnostic feedback. Almost 200 Chinese undergraduates from two universities in Xi'an, China, will be invited to do a cognitive diagnostic reading test, and each student will receive specialized cognitive diagnostic feedback, comprising of students' reading attributes mastery level generated by applying a well-selected cognitive diagnostic model, students' perceived reading ability assessed by a self-assessing questionnaire and students’ level position in the whole class. And a goal-orientation questionnaire and a self-generated questionnaire on the perception of feedback will be given to students the moment they receive feedback. In addition, interviews of students will be conducted on their future plans to see whether they have awareness of carrying out studying plans. The study aims to find a new perspective towards how students use and interpret cognitive diagnostic feedback in terms of their different goal-orientation (self-based, task-based, and other-based goals) by applying the newest goal orientation model, which is an important construct of motivation in psychology, seldom researched under language learning area. And the study is expected to provide evidence on how diagnostic feedback promotes students' learning under the educational belief of assessment for learning. Practically speaking, according to the personalized diagnostic feedback, students can take remedial self-learning more purposefully, and teachers can target students' weaknesses to adjust teaching methods and carry out tailored teaching.

Keywords: assessment for learning, cognitive diagnostic assessment, goal-orientation, personalized feedback

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Authors: Wenbo Du, Xiaomei Ma

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With the empowerment of Cognitive Diagnostic Assessment (CDA), various domains of language testing and assessment have been investigated to dig out more diagnostic information. What is noticeable is that most of the extant empirical CDA-based research puts much emphasis on individual-level diagnostic purpose with very few concerned about learners’ group-level performance. Even though the personalized diagnostic feedback is the unique feature that differentiates CDA from other assessment tools, group-level diagnostic information cannot be overlooked in that it might be more practical in classroom setting. Additionally, the group-level diagnostic information obtained via current CDA always results in a “flat pattern”, that is, the mastery/non-mastery of all tested skills accounts for the two highest proportion. In that case, the outcome does not bring too much benefits than the original total score. To address these issues, the present study attempts to apply cluster analysis for group classification and quantile regression analysis to pinpoint learners’ performance at different proficiency levels (beginner, intermediate and advanced) thus to enhance the interpretation of the CDA results extracted from a group of EFL learners’ reading performance on a diagnostic reading test designed by PELDiaG research team from a key university in China. The results show that EM method in cluster analysis yield more appropriate classification results than that of CDA, and quantile regression analysis does picture more insightful characteristics of learners with different reading proficiencies. The findings are helpful and practical for instructors to refine EFL reading curriculum and instructional plan tailored based on the group classification results and quantile regression analysis. Meanwhile, these innovative statistical methods could also make up the deficiencies of CDA and push forward the development of language testing and assessment in the future.

Keywords: cognitive diagnostic assessment, diagnostic feedback, EFL reading, quantile regression

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Authors: M. Barański

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This paper presents a several diagnostic methods designed to electrical machines especially for permanent magnets (PM) machines. Those machines are commonly used in small wind and water systems and vehicles drives. Those methods are preferred by the author in periodic diagnostic of electrical machines. The special attention should be paid to diagnostic method of turn-to-turn insulation and vibrations. Both of those methods were created in Institute of Electrical Drives and Machines Komel. The vibration diagnostic method is the main thesis of author’s doctoral dissertation. This is method of determination the technical condition of PM electrical machine basing on its own signals is the subject of patent application No P.405669. Specific structural properties of machines excited by permanent magnets are used in this method - electromotive force (EMF) generated due to vibrations. There was analysed number of publications which describe vibration diagnostic methods and tests of electrical machines with permanent magnets and there was no method found to determine the technical condition of such machine basing on their own signals.

Keywords: electrical vehicle, generator, main insulation, permanent magnet, thermography, turn-to-traction drive, turn insulation, vibrations

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Authors: Arya Pirooz

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The effects of different fuels (DME, RME B100, and SME B100) on barrel engines were studied as a general, single dimensional investigation for characterization of these types of engines. A base computational model was created as reference point to be used as a point of comparison with different cases. The models were computed using the commercial computational fluid dynamics program, Diesel-RK. The base model was created using basic dimensions of the PAMAR-3 engine with inline unit injectors. Four fuel cases were considered. Optimized models were also considered for diesel and DME cases with respect to injection duration, fuel, injection timing, exhaust and intake port opening, CR, angular offset. These factors were optimized for highest BMEP, combined PM and NOx emissions, and highest SFC. Results included mechanical efficiency (eta_m), efficiency and power, emission characteristics, combustion characteristics. DME proved to have the highest performing characteristics in relation to diesel and RME fuels for this type of barrel engine.

Keywords: DME, RME, Diesel-RK, characterization, inline unit injector

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Authors: Mohamed Hamada Abdelkader Fayed

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Background: To evaluate the diagnostic accuracy of (ADD-RS) with D-dimer as a screening test to exclude AAS. Methods: We conducted research for the studies examining the diagnostic accuracy of (ADD- RS)+ D-dimer to exclude the diagnosis of AAS, We searched MEDLINE, Embase, and Cochrane of Trials up to 31 December 2020. Results: We identified 3 studies using (ADD-RS) with D-dimer as a diagnostic tool for AAS, involving 3261 patients were AAS was diagnosed in 559(17.14%) patients. Overall results showed that the pooled sensitivities were 97.6 (95% CI 0.95.6, 99.6) at (ADD-RS)≤1(low risk group) with D-dimer and 97.4(95% CI 0.95.4,, 99.4) at (ADD-RS)>1(High risk group) with D-dimer., the failure rate was 0.48% at low risk group and 4.3% at high risk group respectively. Conclusions: (ADD-RS) with D-dimer was a useful screening test with high sensitivity to exclude Acute Aortic Syndrome.

Keywords: aortic dissection detection risk score, D-dimer, acute aortic syndrome, diagnostic accuracy

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Authors: Reza Gheisari, Paulo J. Bartolo, Nicholas Goddard

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Polymeric micro-cantilevers (Cs) are rapidly becoming popular for MEMS applications such as chemo- and bio-sensing as well as purely electromechanical applications such as microrelays. Polymer materials present suitable physical and chemical properties combined with low-cost mass production. Hence, micro-cantilevers made of polymers indicate much more biocompatibility and adaptability of rapid prototyping along with mechanical properties. This research studies the effects of three process and one size factors on the filling behaviour in micro cavity, and the role of each in the replication of micro parts using different polymer materials i.e. polypropylene (PP) SABIC 56M10 and acrylonitrile butadiene styrene (ABS) Magnum 8434. In particular, the following factors are considered: barrel temperature, mould temperature, injection speed and the thickness of micro features. The study revealed that the barrel temperature and the injection speed are the key factors affecting the flow length of micro features replicated in PP and ABS. For both materials, an increase of feature sizes improves the melt flow. However, the melt fill of micro features does not increase linearly with the increase of their thickness.

Keywords: flow length, micro cantilevers, micro injection moulding, microfabrication

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Authors: Eun Young Park, Jongwon Park

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A physical touch of a product can provide ample diagnostic information about the product attributes and quality. However, consumers’ product judgments and purchases can be erroneously influenced by non-diagnostic haptic information. For example, consumers’ evaluations of the coffee they drink could be affected by the heaviness of a cup that is used for just serving the coffee. This important issue has received little attention in prior research. The present research contributes to the literature by identifying when and how non-diagnostic haptic information can have an influence and why such influence occurs. Specifically, five studies experimentally varied the content of non-diagnostic haptic information, such as the weight of a cup (heavy vs. light) and the texture of a cup holder (smooth vs. rough), and then assessed the impact of the manipulation on product judgments and decisions. Results show that non-diagnostic haptic information has a biasing impact on consumer judgments. For example, the heavy (vs. light) cup increases consumers’ perception of the richness of coffee in it, and the rough (vs. smooth) texture of a cup holder increases the perception of the healthfulness of fruit juice in it, which in turn increases consumers’ purchase intentions of the product. When consumers are cognitively distracted during the touch experience, the impact of the content of haptic information is no longer evident, but the valence (positive vs. negative) of the haptic experience influences product judgments. However, consumers are able to avoid the impact of non-diagnostic haptic information, if and only if they are both knowledgeable about the product category and undistracted from processing the touch experience. In sum, the nature of the influence by non-diagnostic haptic information (i.e., assimilation effect vs. contrast effect vs. null effect) is determined by the content and valence of haptic information, the relative impact of which depends on whether consumers can identify the content and source of the haptic information. Theoretically, to our best knowledge, this research is the first to document the empirical evidence of the interplay between cognitive and affective processes that determines the impact of non-diagnostic haptic information. Managerial implications are discussed.

Keywords: consumer behavior, haptic information, product judgments, touch effect

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Authors: Justina I. R. Udotong, Essien U. Essien

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Diagnostic enzymes like aspartate aminotransferase (AST), alanine aminotransferase (ALT) and alkaline phosphatase (ALP) were determined as indices of heavy metal pollution in Tilapia guinensis. Three different sets of fishes treated with lead (Pb), iron (Fe) and copper (Cu) were used for the study while a fourth group with no heavy metal served as a control. Fishes in each of the groups were exposed to 2.65 mg/l of Pb, 0.85 mg/l of Fe and 0.35 mg/l of Cu in aerated aquaria for 96 hours. Tissue fractionation of the liver tissues was carried out and the three diagnostic enzymes (AST, ALT, and ALP) were estimated. Serum levels of the same diagnostic enzymes were also measured. The mean values of the serum enzyme activity for ALP in each experimental group were 19.5±1.62, 29.67±2.17 and 1.15±0.27 IU/L for Pb, Fe and Cu groups compared with 9.99±1.34 IU/L enzyme activity in the control. This result showed that Pb and Fe caused increased release of the enzyme into the blood circulation indicating increased tissue damage while Cu caused a reduction in the serum level as compared with the level in the control group. The mean values of enzyme activity obtained in the liver were 102.14±6.12, 140.17±2.06 and 168.23±3.52 IU/L for Pb, Fe and Cu groups, respectively compared to 91.20±9.42 IU/L enzyme activity for the control group. The serum and liver AST and ALT activities obtained in Pb, Fe, Cu and control groups are reported. It was generally noted that the presence of the heavy metal caused liver tissues damage and consequent increased level of the diagnostic enzymes in the serum.

Keywords: diagnostic enzymes, enzyme activity, heavy metals, tissues investigations

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Authors: Imad Khan, Imran Shafi, Sarmad Farooq

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Large diameter pipes, barrels, tubes, and ducts are used in a variety of applications covering civil and defense-related technologies. This may include heating/cooling networks, sign poles, bracing, casing, and artillery and tank gun barrels. These large diameter assemblies require regular inspection and cleaning to increase their life and reduce replacement costs. This paper describes the design, development, and testing results of an efficient yet simplified, low maintenance mechanical design controlled with minimal essential electronics using an electric motor for a non-technical staff. The proposed solution provides a simplified user interface and an automated cleaning mechanism that requires a single user to optimally clean pipes and barrels in the range of 105 mm to 203 mm caliber. The proposed system employs linear motion of specially designed brush along the barrel using a chain of specific strength and a pulley anchor attached to both ends of the barrel. A specially designed and manufactured gearbox is coupled with an AC motor to allow movement of contact brush with high torque to allow efficient cleaning. A suitably powered AC motor is fixed to the front adapter mounted on the muzzle side whereas the rear adapter has a pulley-based anchor mounted towards the breach block in case of a gun barrel. A mix of soft nylon and hard copper bristles-based large surface brush is connected through a strong steel chain to motor and anchor pulley. The system is equipped with limit switches to auto switch the direction when one end is reached on its operation. The testing results based on carefully established performance indicators indicate the superiority of the proposed user-friendly cleaning mechanism vis-à-vis its life cycle cost.

Keywords: pipe cleaning mechanism, limiting switch, pipe cleaning robot, large pipes

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Authors: Ananda Perera

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Computer-Assisted Medical Evaluation of Symptoms (CAMEOS) is a medical expert system designed to help General Practices (GPs) make an accurate diagnosis. CAMEOS comprises a knowledge base, user input, inference engine, reasoning module, and output statement. The knowledge base was developed by the author. User input is an Html file. The physician user collects data in the consultation. Data is sent to the inference engine at servers. CAMEOS uses set theory to simulate diagnostic reasoning. The program output is a list of differential diagnoses, the most probable diagnosis, and the diagnostic reasoning.

Keywords: CDSS, computerized decision support systems, expert systems, general practice, diagnosis, diagnostic systems, primary care diagnostic system, artificial intelligence in medicine

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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: Okhee Woo, Hye Seon Shin

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Purpose: To investigate the diagnostic power of digital breast tomosynthesis (DBT) in evaluation of breast microcalcifications and usefulness as a pre-procedural study for stereotactic biopsy in comparison with full-field digital mammogram (FFDM) and FFDM plus magnification image (FFDM+MAG). Methods and Materials: An IRB approved retrospective observer performance study on DBT, FFDM, and FFDM+MAG was done. Image quality was rated in 5-point scoring system for lesion clarity (1, very indistinct; 2, indistinct; 3, fair; 4, clear; 5, very clear) and compared by Wilcoxon test. Diagnostic power was compared by diagnostic values and AUC with 95% confidence interval. Additionally, procedural report of biopsy was analysed for patient positioning and adequacy of instruments. Results: DBT showed higher lesion clarity (median 5, interquartile range 4-5) than FFDM (3, 2-4, p-value < 0.0001), and no statistically significant difference to FFDM+MAG (4, 4-5, p-value=0.3345). Diagnostic sensitivity and specificity of DBT were 86.4% and 92.5%; FFDM 70.4% and 66.7%; FFDM+MAG 93.8% and 89.6%. The AUCs of DBT (0.88) and FFDM+MAG (0.89) were larger than FFDM (0.59, p-values < 0.0001) but there was no statistically significant difference between DBT and FFDM+MAG (p-value=0.878). In 2 cases with DBT, petit needle could be appropriately prepared; and other 3 without DBT, patient repositioning was needed. Conclusion: DBT showed better image quality and diagnostic values than FFDM and equivalent to FFDM+MAG in the evaluation of breast microcalcifications. Evaluation with DBT as a pre-procedural study for breast stereotactic biopsy can lead to more accurate localization and successful biopsy and also waive the need for additional magnification images.

Keywords: DBT, breast cancer, stereotactic biopsy, mammography

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Authors: Hyun-Woo Cho

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Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Suprit Pradhan, Tshering Yangzom

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Even with availability of the modern day online insulation diagnostic technologies like partial discharge monitoring, the measurements like Dissipation Factor (tanδ), DC High Voltage Insulation Currents, Polarization Index (PI) and Insulation Resistance Measurements are still widely used as a diagnostic tools to assess the condition of stator insulation in hydro power plants. To evaluate the condition of stator winding insulation in one of the generators that have been operated since 1999, diagnostic tests were performed on the stator bars of 15 MVA generators of Basochhu Hydropower Plant. This paper presents diagnostic study done on the data gathered from the measurements which were performed in 2015 and 2016 as part of regular maintenance as since its commissioning no proper aging data were maintained. Measurement results of Dissipation Factor, DC High Potential tests and Polarization Index are discussed with regard to their effectiveness in assessing the ageing condition of the stator insulation. After a brief review of the theoretical background, the strengths of each diagnostic method in detecting symptoms of insulation deterioration are identified. The interesting results observed from Basochhu Hydropower Plant is taken into consideration to conclude that Polarization Index and DC High Voltage Insulation current measurements are best suited for the detection of humidity and contamination problems and Dissipation Factor measurement is a robust indicator of long-term ageing caused by oxidative degradation.

Keywords: dissipation Factor (tanδ), polarization Index (PI), DC High Voltage Insulation Current, insulation resistance (IR), Tan Delta Tip-Up, dielectric absorption ratio

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Authors: C. S. Saini

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The composite flour blend consisting of corn, pearl millet, black gram and wheat bran in the ratio of 80:5:10:5 was taken to prepare the extruded product and their effect on physical properties of extrudate was studied. The extrusion process was conducted in laboratory by using twin screw extruder. The physical characteristics evaluated include lateral expansion, bulk density, water absorption index, water solubility index, rehydration ratio and moisture retention. The Central Composite Rotatable Design (CCRD) was used to decide the level of processing variables i.e. feed moisture content (%), screw speed (rpm), and barrel temperature (oC) for the experiment. The data obtained after extrusion process were analyzed by using response surface methodology. A second order polynomial model for the dependent variables was established to fit the experimental data. The numerical optimization studies resulted in 127°C of barrel temperature, 246 rpm of screw speed, and 14.5% of feed moisture as optimum variables to produce acceptable extruded product. The responses predicted by the software for the optimum process condition resulted in lateral expansion 126 %, bulk density 0.28 g/cm3, water absorption index 4.10 g/g, water solubility index 39.90 %, rehydration ratio 544 % and moisture retention 11.90 % with 75 % desirability.

Keywords: black gram, corn flour, extrusion, physical characteristics

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Authors: K. Hinde, R. Bookun, P. Tran

Abstract:

Percutaneous CT guided biopsies provide a fast, minimally invasive, cost effective and safe method for obtaining tissue for histopathology and culture. Standards for diagnostic yield vary depending on whether the tissue is being obtained for histopathology or culture. We present a retrospective audit from Western Health in Melbourne Australia over a 12-month period which aimed to determine the diagnostic yield, technical success and complication rate for CT guided bone biopsies and identify factors affecting these results. The digital imaging storage program (Synapse Picture Archiving and Communication System – Fujifilm Australia) was analysed with key word searches from October 2015 to October 2016. Nineteen CT guided bone biopsies were performed during this time. The most common referring unit was oncology, work up imaging included CT, MRI, bone scan and PET scan. The complication rate was 0%, overall diagnostic yield was 74% with a technical success of 95%. When performing biopsies for histologic analysis diagnostic yield was 85% and when performing biopsies for bacterial culture diagnostic yield was 60%. There was no significant relationship identified between size of lesion, distance of lesion to skin, lesion appearance on CT, the number of samples taken or gauge of needle to diagnostic yield or technical success. CT guided bone biopsy at Western Health meets the standard reported at other major clinical centres for technical success and safety. It is a useful investigation in identification of primary malignancy in distal bone metastases.

Keywords: bone biopsy, computed tomography, core biopsy, histopathology

Procedia PDF Downloads 188

Authors: Jae Ni Jang, SoYoon Park, Sukhee Park, Yumin Song, Jae Won Kim, Keum Nae Kang, Young Uk Kim

Abstract:

Objectives: Patellofemoral pain syndrome (PFPS) is a common clinical condition characterized by anterior knee pain. Here, we investigated the quadriceps tendon cross-sectional area (QTCSA) as a novel predictor for the diagnosis of PFPS. By examining the association between the QTCSA and PFPS, we aimed to provide a more valuable diagnostic parameter and more equivocal assessment of the diagnostic potential of PFPS by comparing the QTCSA with the quadriceps tendon thickness (QTT), a traditional measure of quadriceps tendon hypertrophy. Patients and Methods: This retrospective study included 30 patients with PFPS and 30 healthy participants who underwent knee magnetic resonance imaging. T1-weighted turbo spin echo transverse magnetic resonance images were obtained. The QTCSA was measured on the axial-angled phases of the images by drawing outlines, and the QTT was measured at the most hypertrophied quadriceps tendon. Results: The average QTT and QTCSA for patients with PFPS (6.33±0.80 mm and 155.77±36.60 mm², respectively) were significantly greater than those for healthy participants (5.77±0.36 mm and 111.90±24.10 mm2, respectively; both P<0.001). We used a receiver operating characteristic curve to confirm the sensitivities and specificities for both the QTT and QTCSA as predictors of PFPS. The optimal diagnostic cutoff value for QTT was 5.98 mm, with a sensitivity of 66.7%, a specificity of 70.0%, and an area under the curve of 0.75 (0.62–0.88). The optimal diagnostic cutoff value for QTCSA was 121.04 mm², with a sensitivity of 73.3%, a specificity of 70.0%, and an area under the curve of 0.83 (0.74–0.93). Conclusion: The QTCSA was found to be a more reliable diagnostic indicator for PFPS than QTT.

Keywords: patellofemoral pain syndrome, quadriceps muscle, hypertrophy, magnetic resonance imaging

Procedia PDF Downloads 31

Authors: Muhammad Iqbal, Edi Istiyono

Abstract:

Misconceptions are one of the problems in physics learning where students' understanding is not in line with scientific theory. The aim of this research is to find diagnostic tools to identify misconceptions and how to remediate physics misconceptions. In this research, the articles that will be reviewed come from the Scopus database related to physics misconceptions from 2013-2023. The articles obtained from the Scopus database were then selected according to the Prisma model, so 29 articles were obtained that focused on discussing physics misconceptions, especially regarding diagnostic tools and remediation methods. Currently, the most widely used diagnostic tool is the four-tier test, which is able to measure students' misconceptions in depth by knowing whether students are guessing or not and from then on, there is also a trend toward five-tier diagnostic tests with additional sources of information obtained. So that the origin of students' misconceptions is known. There are several ways to remediate student misconceptions, namely 11 ways and one of the methods used is digital practicum so that abstract things can be visualized into real ones. This research is limited to knowing what tools are used to diagnose and remediate misconceptions, so it is not yet known how big the effect of remediation methods is on misconceptions. The researcher recommends that in the future further research can be carried out to find out the most appropriate remediation method for remediating student misconceptions.

Keywords: misconception, remediation, systematic review, tools

Procedia PDF Downloads 25