Search results for: software cumulative failure prediction

Authors: Jongsung Kim, Daegun Han, Myungjin Lee, Soojun Kim, Hung Soo Kim

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Recently, the frequency and magnitude of natural disasters are gradually increasing due to climate change. Especially in Korea, large-scale damage caused by heavy rainfall frequently occurs due to rapid urbanization. Therefore, this study proposed a Heavy rain Damage Risk Index (HDRI) using PSR (Pressure – State - Response) structure for heavy rain risk assessment. We constructed pressure index, state index, and response index for the risk assessment of each local government in Gyeonggi-do province, and the evaluation indices were determined by principal component analysis. The indices were standardized using the Z-score method then HDRIs were obtained for 31 local governments in the province. The HDRI is categorized into three classes, say, the safest class is 1st class. As the results, the local governments of the 1st class were 15, 2nd class 7, and 3rd class 9. From the study, we were able to identify the risk class due to the heavy rainfall for each local government. It will be useful to develop the heavy rainfall prediction function by risk class, and this was performed in this issue. Also, this risk class could be used for the decision making for efficient disaster management. Acknowledgements: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B3005695).

Keywords: natural disaster, heavy rain risk assessment, HDRI, PSR

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Authors: C. E. Sutton, A. Varvani-Farahani

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Fatigue damage and life prediction of particle metal matrix composites (PMMCs) under uniaxial and multiaxial loading conditions were investigated. Three PMM composite materials of Al6061/Al2O3/20p-T6, Al6061/Al2O3/22p-T6 and Al6061/SiC/17w-T6 tested under tensile, torsion, and combined tension-torsion fatigue cycling were evaluated with various fatigue damage models. The fatigue damage models of Smith-Watson-Topper (S. W. T.), Ellyin, Brown-Miller, Fatemi-Socie, and Varvani were compared for their capability to assess the fatigue damage of materials undergoing various loading conditions. Fatigue life predication results were then evaluated by implementing material-dependent coefficients that factored in the effects of the particle reinforcement in the earlier developed Varvani model. The critical plane-energy approach incorporated the critical plane as the plane of crack initiation and early stage of crack growth. The strain energy density was calculated on the critical plane incorporating stress and strain components acting on the plane. This approach successfully evaluated fatigue damage values versus fatigue lives within a narrower band for both uniaxial and multiaxial loading conditions as compared with other damage approaches studied in this paper.

Keywords: fatigue damage, life prediction, critical plane approach, energy approach, PMM composites

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Authors: Ravneet Kaur

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The concept of Agile Requirements Engineering and Management is not new. However, the struggle to figure out how traditional Requirements Management Process fits within an Agile framework remains complex. This paper talks about a process that can merge the organization’s traditional Requirements Management Process nicely into the Agile Software Development Process. This process provides Traceability of the Product Backlog to the external documents on one hand and User Stories on the other hand. It also gives sufficient evidence that the system will deliver the right functionality with good quality in the form of various statistics and reports. In the nutshell, by overlaying a process on top of Agile, without disturbing the Agility, we are able to get synergic benefits in terms of productivity, profitability, its reporting, and end to end visibility to all Stakeholders. The framework can be used for just-in-time requirements definition or to build a repository of requirements for future use. The goal is to make sure that the business (specifically, the product owner) can clearly articulate what needs to be built and define what is of high quality. To accomplish this, the requirements cycle follows a Scrum-like process that mirrors the development cycle but stays two to three steps ahead. The goal is to create a process by which requirements can be thoroughly vetted, organized, and communicated in a manner that is iterative, timely, and quality-focused. Agile is quickly becoming the most popular way of developing software because it fosters continuous improvement, time-boxed development cycles, and more quickly delivering value to the end users. That value will be driven to a large extent by the quality and clarity of requirements that feed the software development process. An agile, lean, and timely approach to requirements as the starting point will help to ensure that the process is optimized.

Keywords: requirements management, Agile

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Authors: Burak Erkayman, Emin Gundogar, Hayrettin Evirgen, Murat Sarı

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With the increasing competition in recent years, airline companies tend to manage their operations aiming fewer losses in a robust manner. Airline operations are complex operations and have the necessity of being performed just in time and more knock-on relevant elements in the event of a disruption. In this study a knowledge based decision support system is suggested and software is developed. The developed software includes knowledge bases which are based on expert experience and government regulations, model bases and data bases. The results of the suggested approach are presented and improvable aspects of the approach are discussed.

Keywords: knowledge based systems, irregular operations, decision support systems, flight disruptions management

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Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha

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When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.

Keywords: contract risk assessment, NLP, transfer learning, question answering

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Authors: Reinhard Hermawan Lasut, Henki Wibowo Ashadi

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The use of materials in Indonesia's construction sector requires engineers and practitioners to develop efficient construction technology, one of the materials used in cold-formed steel. Generally, the use of cold-formed steel is used in the construction of roof trusses found in houses or factories. The failure of the roof truss structure causes errors in the calculation analysis in the form of cross-sectional dimensions or frame configuration. The roof truss structure, vertical distance effect to the span length at the edge of the frame carries the compressive load. If the span is too long, local buckling will occur which causes problems in the frame strength. The model analysis uses various shapes of roof trusses, span lengths and angles with analysis of the structural stiffness matrix method. Model trusses with one-fifth shortened span and one-sixth shortened span also The trusses model is reviewed with increasing angles. It can be concluded that the trusses model by shortening the span in the compression area can reduce deflection and the model by increasing the angle does not get good results because the higher the roof, the heavier the load carried by the roof so that the force is not channeled properly. The shape of the truss must be calculated correctly so the truss is able to withstand the working load so that there is no structural failure.

Keywords: cold-formed, trusses, deflection, stiffness matrix method

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Authors: Ahmed M. AlHasem

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The Kuwaiti society has long been aware of climatic changes and their annual dates and trying to link them to astronomy in an attempt to forecast the future weather conditions. The reason for this concern is that many of the economic, social and living activities of the society depend deeply on the nature of the weather conditions directly and indirectly. In other words, Kuwaiti society, like the case of many human societies, has in the past tried to predict climatic conditions by linking them to astronomy or popular statements to indicate the timing of climate changes. Accordingly, this study was devoted to scientific investigation based on the statistical analysis of climatic data to show the accuracy and compatibility of some of the most important elements of the cultural heritage in relation to climate change and to relate it scientifically to precise climatic measurements for decades. The research has been divided into 10 topics, each topic has been focused on one legacy, whether by linking climate changes to the appearance/disappearance of star or a popular statement inherited through generations, through explain the nature and timing and thereby statistical analysis to indicate the proportion of accuracy based on official climatic data since 1962. The study's conclusion is that the relationship is weak and, in some cases, non-existent between the popular heritage and the actual climatic data. Therefore, it does not have a dependable relationship and a reliable scientific prediction between both the popular heritage and the forecast of weather conditions.

Keywords: astronomy, cultural heritage, statistical analysis, weather prediction

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Authors: Elena A. Troubitsyna

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Designers of modern safety-critical control systems are increasingly relying on networking to provide the systems with advanced functionality and satisfy customer’s needs. However, networking nature of modern control systems also brings new technological challenges associated with ensuring system safety in the presence of openness and hence, potential security threats. In this paper, we propose a methodology that relies on systems-theoretic analysis to enable an integrated analysis of safety and security requirements of controlling software. We demonstrate how to create a safety case – a structured argument about system safety – with explicit representation of both safety and security goals. Our approach provides the designers with a systematic approach to analysing safety and security interdependencies while designing safety-critical control systems.

Keywords: controlling software, integrated analysis, security, safety-security co-engineering

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Authors: Assem I. El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent Railway Control System (MARCS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, multi-agent, railway control, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

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Authors: Iftekhar Hassan, Sayedil Morsalin, Easir A Khan

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Accidents involving fire occur frequently in recent times and their causes showing a great deal of variety which require intervention methods and risk assessment strategies are unique in each case. On September 4, 2020, a fire and explosion occurred in a confined space caused by a methane gas leak from an underground pipeline in Baitus Salat Jame mosque during Night (Esha) prayer in Narayanganj District, Bangladesh that killed 34 people. In this research, this incident is simulated using Fire Dynamics Simulator (FDS) software to analyze and understand the nature of the accident and associated consequences. FDS is an advanced computational fluid dynamics (CFD) system of fire-driven fluid flow which solves numerically a large eddy simulation form of the Navier–Stokes’s equations for simulation of the fire and smoke spread and prediction of thermal radiation, toxic substances concentrations and other relevant parameters of fire. This study focuses on understanding the nature of the fire and consequence evaluation due to thermal radiation caused by vapor cloud explosion. An evacuation modeling was constructed to visualize the effect of evacuation time and fractional effective dose (FED) for different types of agents. The results were presented by 3D animation, sliced pictures and graphical representation to understand fire hazards caused by thermal radiation or smoke due to vapor cloud explosion. This study will help to design and develop appropriate respond strategy for preventing similar accidents.

Keywords: consequence modeling, fire and explosion, fire dynamics simulation (FDS), thermal radiation

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Authors: Polycarp A. Igbojekwe, Chizoba Amajuoyi, Peterson Nwokorie

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The main purpose of this study was to carry out a survey of customer’s aggression towards hotel workers and make contributions on the prevalence and rationale behind customer’s aggression. Data for the study were gathered with a four-point Likert type rating scale. Samples were drawn from frontline hotel employees, managers and customers of twelve (12) hotels selected from three zones of Imo State. Data analyses were conducted using simple percentage, descriptive statistics; and Z-test statistical technique was used to test hypotheses. Among other factors, service failure and verbal abuse by service providers and poor quality product compared to price were identified by customers as the three major factors that can lead to customer aggression. Frontline employees indentified verbal abuse as the most common mode of aggression and that customer aggression causes emotional disturbance in them. The study also revealed that customer aggression is more prevalent in the 1&2 star hotels than it is in 3-5 star hotels. Most of the hotels have not institutionalized systematic approaches needed to effectively face the challenges of customer aggression, thus, customer aggression has become a common feature in the industry. Frontline jobs demand high emotional input. Therefore, we recommend that frontline employees should be given emotional support by their managers and also trained on how to cope with emotional disturbance.

Keywords: customer aggression, emotional disturbance, employee well-being, service failure, verbal abuse

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Authors: Bilal Haider, Farhan Aadil

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A Vehicular Ad hoc Network (VANET) provides various services to end-users traveling on the road at high speeds. However, this high-speed mobility of mobile nodes can cause frequent service disruptions. Various mobility management protocols exist for managing node mobility, but due to their centralized nature, they tend to suffer in the VANET environment. In this research, we proposed a distributed mobility management protocol using software-defined networks (SDN) for VANETs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple infrastructural nodes. The protocol is based on the classical Proxy Mobile IP version 6 (PMIPv6). It is evident from simulation results that this work has improved the network performance with respect to nodes throughput, delay, and packet loss.

Keywords: SDN, VANET, mobility management, optimization

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Bharat Kumar, Deepak Kumar, Vijay Chaudhry

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Zirconium alloys are used as core components of nuclear reactors due to their high wear resistance, good corrosion properties, and good mechanical stability at high temperatures. Water flows inside the pressure tube through fuel claddings, which produces vibration of these core components and results in the wear of some components. Some components are subjected to the environment of coolant water containing LiOH which results in the corrosion of these components. The present work simulates some of these conditions to determine the failure mechanisms under these conditions and the effect of various parameters on them. Friction and wear experiments were performed varying the surrounding environment (room temperature, high temperature, and water submerged), duration, frequency, and displacement amplitude. Electrochemical corrosion experiments were performed by varying the concentration of LiOH in water. The worn and corroded surfaces were analyzed using scanning electron microscopy (SEM) to analyze the wear and corrosion mechanism and energy dispersive x-ray spectroscopy (EDS) and Raman spectroscopy to analyze the tribo-oxide layer formed during the wear and oxide layer formed during the corrosion. Wear increases with frequency and amplitude, and corrosion increases with LiOH concentration in water.

Keywords: zirconium alloys, wear, oxide layer, corrosion, EIS, linear polarization

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Saeid Shahraki, Mohammad Mahdi Kaekha

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1030 steel, a kind of carbon steel used in homogenization, cold-forming, quenching, and tempering conditions, is generally utilized in small parts resisting medium stress, such as connection foundations, hydraulic cylinders, tiny gears, pins, clamps, automotive normal forging parts, camshafts, levers, pundits, and nuts. In this study, AC3 software was used to measure the effect of carbon and manganese percentage, dimensions and geometry of pieces, the type of the cooling fluid, temperature, and time on hardness and the content of 1030 steel phases. Next, the results are compared with the analytical values obtained from the Lumped Capacity Method.

Keywords: 1030Steel, AC3software, heat treatment, lumped capacity method

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Authors: Ahmad Shahin, Walid Moudani, Ali Bekraki

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This research aims at presenting a predictive data mining model to handle an accurate diagnosis of acute appendicitis with patients for the purpose of maximizing the health service quality, minimizing morbidity/mortality, and reducing cost. However, acute appendicitis is the most common disease which requires timely accurate diagnosis and needs surgical intervention. Although the treatment of acute appendicitis is simple and straightforward, its diagnosis is still difficult because no single sign, symptom, laboratory or image examination accurately confirms the diagnosis of acute appendicitis in all cases. This contributes in increasing morbidity and negative appendectomy. In this study, the authors propose to generate an accurate model in prediction of patients with acute appendicitis which is based, firstly, on the segmentation technique associated to ABC algorithm to segment the patients; secondly, on applying fuzzy logic to process the massive volume of heterogeneous and noisy data (age, sex, fever, white blood cell, neutrophilia, CRP, urine, ultrasound, CT, appendectomy, etc.) in order to express knowledge and analyze the relationships among data in a comprehensive manner; and thirdly, on applying dynamic programming technique to reduce the number of data attributes. The proposed model is evaluated based on a set of benchmark techniques and even on a set of benchmark classification problems of osteoporosis, diabetes and heart obtained from the UCI data and other data sources.

Keywords: healthcare management, acute appendicitis, data mining, classification, decision tree

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Authors: Te Kīpa Kēpa B. Morgan, Oliver W. Mcmillan, Dylan N. Taute, Tumanako N. Fa'aui

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Epistemologies are ways of knowing. Indigenous Peoples are aware that they do not perceive and experience the world in the same way as others. So it is important when empowering Indigenous epistemologies, such as that of the New Zealand Māori, to also be able to represent a scientific understanding within the same analysis. A geothermal development assessment tool has been developed by adapting the Mauri Model Decision Making Framework. Mauri is a metric that is capable of representing the change in the life-supporting capacity of things and collections of things. The Mauri Model is a method of grouping mauri indicators as dimension averages in order to allow holistic assessment and also to conduct sensitivity analyses for the effect of worldview bias. R-shiny is the coding platform used for this Vision Mātauranga research which has created an expert decision support tool (DST) that combines a stakeholder assessment of worldview bias with an impact assessment of mauri-based indicators to determine the sustainability of proposed geothermal development. The initial intention was to develop guidelines for quantifying mātauranga Māori impacts related to geothermal resources. To do this, three typical scenarios were considered: a resource owner wishing to assess the potential for new geothermal development; another party wishing to assess the environmental and cultural impacts of the proposed development; an assessment that focuses on the holistic sustainability of the resource, including its surface features. Indicator sets and measurement thresholds were developed that are considered necessary considerations for each assessment context and these have been grouped to represent four mauri dimensions that mirror the four well-being criteria used for resource management in Aotearoa, New Zealand. Two case studies have been conducted to test the DST suitability for quantifying mātauranga Māori and other biophysical factors related to a geothermal system. This involved estimating mauri0meter values for physical features such as temperature, flow rate, frequency, colour, and developing indicators to also quantify qualitative observations about the geothermal system made by Māori. A retrospective analysis has then been conducted to verify different understandings of the geothermal system. The case studies found that the expert DST is useful for geothermal development assessment, especially where hapū (indigenous sub-tribal grouping) are conflicted regarding the benefits and disadvantages of their’ and others’ geothermal developments. These results have been supplemented with evaluations for the cumulative impacts of geothermal developments experienced by different parties using integration techniques applied to the time history curve of the expert DST worldview bias weighted plotted against the mauri0meter score. Cumulative impacts represent the change in resilience or potential of geothermal systems, which directly assists with the holistic interpretation of change from an Indigenous Peoples’ perspective.

Keywords: decision support tool, holistic geothermal assessment, indigenous knowledge, mauri model decision-making framework

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Authors: Pierre van Tonder, Dinesh Muthoo, Kim twiname

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Many existing and newly built structures are constructed on the design basis of the engineer and the workmanship of the construction company. However, when considering larger structures where more people are exposed to the building, its structural integrity is of great importance considering the safety of its occupants (Raghu, 2013). But how can the structural integrity of a building be monitored efficiently and effectively. This is where the fourth industrial revolution step in, and with minimal human interaction, data can be collected, analysed, and stored, which could also give an indication of any inconsistencies found in the data collected, this is where the Fibre Bragg Grating (FBG) monitoring system is introduced. This paper illustrates how data can be collected and converted to develop stress – strain behaviour and to produce bending moment diagrams for the utilisation and prediction of the structure’s integrity. Embedded fibre optic sensors were used in this study– fibre Bragg grating sensors in particular. The procedure entailed making use of the shift in wavelength demodulation technique and an inscription process of the phase mask technique. The fibre optic sensors considered in this report were photosensitive and embedded in the slab and beams for data collection and analysis. Two sets of fibre cables have been inserted, one purposely to collect temperature recordings and the other to collect strain and temperature. The data was collected over a time period and analysed used to produce bending moment diagrams to make predictions of the structure’s integrity. The data indicated the fibre Bragg grating sensing system proved to be useful and can be used for structural health monitoring in any environment. From the experimental data for the slab and beams, the moments were found to be64.33 kN.m, 64.35 kN.m and 45.20 kN.m (from the experimental bending moment diagram), and as per the idealistic (Ultimate Limit State), the data of 133 kN.m and 226.2 kN.m were obtained. The difference in values gave room for an early warning system, in other words, a reserve capacity of approximately 50% to failure.

Keywords: fibre bragg grating, structural health monitoring, fibre optic sensors, beams

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Authors: Frederic Heymes, Michael Albrecht Birk, Roland Eyssette

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Boiling Liquid Expanding Vapor Explosion (BLEVE) has been a well know industrial accident for over 6 decades now, and yet it is still poorly predicted and avoided. BLEVE is created when a vessel containing a pressure liquefied gas (PLG) is engulfed in a fire until the tank rupture. At this time, the pressure drops suddenly, leading the liquid to be in a superheated state. The vapor expansion and the violent boiling of the liquid produce several shock waves. This works aimed at understanding the contribution of vapor ad liquid phases in the overpressure generation in the near field. An experimental work was undertaken at a small scale to reproduce realistic BLEVE explosions. Key parameters were controlled through the experiments, such as failure pressure, fluid mass in the vessel, and weakened length of the vessel. Thirty-four propane BLEVEs were then performed to collect data on scenarios similar to common industrial cases. The aerial overpressure was recorded all around the vessel, and also the internal pressure changed during the explosion and ground loading under the vessel. Several high-speed cameras were used to see the vessel explosion and the blast creation by shadowgraph. Results highlight how the pressure field is anisotropic around the cylindrical vessel and highlights a strong dependency between vapor content and maximum overpressure from the lead shock. The time chronology of events reveals that the vapor phase is the main contributor to the aerial overpressure peak. A prediction model is built upon this assumption. Secondary flow patterns are observed after the lead. A theory on how the second shock observed in experiments forms is exposed thanks to an analogy with numerical simulation. The phase change dynamics are also discussed thanks to a window in the vessel. Ground loading measurements are finally presented and discussed to give insight into the order of magnitude of the force.

Keywords: phase change, superheated state, explosion, vapor expansion, blast, shock wave, pressure liquefied gas

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Authors: Mirzaii Khadigeh

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Background and objectives: Sexual health education is an important part of health promotion services. The major role of sex education is on mothers’ shoulders. So, they have to be equipped with enough knowledge, attitude and self-efficacy for teens’ education. The present study aimed to determine the effect of team-learning and multimedia software on mothers’ knowledge, attitudes and self-efficacy in sexual health education to 12-14-year-old sons in Mashhad in 1395. Materials and methods: In this research, two experimental and one control group were employed using random sampling, which was done on 132 mothers of high school pupils. They were randomly assigned into experimental and control groups. The data were collected using demographic information and a researcher-constructed questionnaire to investigate the mothers’ knowledge, attitude, and self-efficacy and DASS21(The Depression, Anxiety and Stress Scale). They were run after confirming their reliability and validity. Intervention for the multimedia group was in the form of four CDs- each for 45 minutes- that were given to the mothers each week. At the end of the fourth week, a question-and-answer session was administered for 60 minutes. The team-learning group received intervention once a week (totally four weeks). Two weeks later, the data were collected and analyzed via Chi-square, Fisher, Kruskal-Wallis and ANOVA. Findings: Knowledge, attitude and self-efficacy of mothers in sexual health before the intervention did not have any significant differences (p >0.05). At the end of the study, the difference between the scores of the knowledge, attitude and self-efficacy in the three groups was meaningfully different (p < 0/001), but the difference between the two groups of multimedia and team-learning was not significant (p> 0.05 ). Discussion and conclusion: The result reported the efficacy of both team-leaning and multimedia software, which implies that the multimedia software training method was as effective as team-learning training one on the knowledge, attitude and self-efficacy of mothers. But, the multimedia training method is highly advised due to its availability, flexibility, and interest.

Keywords: training one on the knowledge, attitude, self-efficacy of mothers, boys

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Authors: Mohammad Reza Ramezani, Shahriyar Afandizadeh

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Since the intersections play a crucial role in traffic delay, it is significant to evaluate them precisely. In this paper, three critical intersections in Tehran (Capital of Iran) had been simulated. The main purpose of this paper was to optimize the public transit delay. The simulation had three different phase in three intersections of Tehran. The first phase was about the current condition of intersection; the second phase was about optimized signal timing and the last phase was about prioritized public transit access. The Aimsun software was used to simulate all phases, and the Synchro software was used to optimization of signals as well. The result showed that the implement of optimization and prioritizing system would reduce about 50% of delay for public transit.

Keywords: transit signal priority, intersection optimization, public transit, simulation

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Authors: Daniel K. Gameti

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The paper explored the effects of active and passive entrepreneurship education methods on the venture creation intention of undergraduate students in Ghana. The study also examined the moderating effect of gender and negative personal characteristics (risk tolerance, stress tolerance and fear of failure) on students’ venture creation intention. Deductive approach was used in collecting quantitative data from 555 business students from one public university and one private university through self-administered questionnaires. Descriptive statistic was used to determine the dominant method of entrepreneurship education used in Ghana. Further, structural equation model was used to test four hypotheses. The results of the study show that the dominant method of education used in Ghana was lectures and the least method used was field trip. The study further revealed that passive methods of education are less effective compared to active methods which were statistically significant in venture creation intention among students. There was also statistical difference between male and female students’ venture creation intention but stronger among male students and finally, the only personal characteristics that influence students’ intention was stress tolerance because risk tolerance and fear of failure were statistically insignificant.

Keywords: entrepreneurship education, Ghana, moderating variables, venture creation intention, undergraduate students

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Authors: Keshari Shrestha, Philip Vatterott

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Introduction: Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare and potentially fatal drug-related syndrome. DRESS classically presents with a diffuse maculopapular rash, fevers, and eosinophilia more than three weeks after drug exposure. DRESS can present with multi-organ involvement, with liver damage being the most common and severe. Pulmonary involvement is a less common manifestation and is associated with poor clinical outcomes. Chest imaging is often nonspecific, and symptoms can range from mild cough to acute respiratory distress syndrome (ARDS) . This is a case of a 49-year-old female with a history of recent clostridium difficile colitis status post treatment with oral vancomycin who presented with rash, acute liver and kidney failure, as well as diffuse nodular alveolar lung opacities concerning for DRESS syndrome with multi-organ involvement. Clinical Course: This patient initially presented to an outside hospital with clostridium difficile colitis, acute liver injury, and acute kidney injury. She developed a desquamating maculopapular rash in the setting of recent oral vancomycin, meloxicam, and furosemide initiation. She was hospitalized on two additional occasions with worsening altered mental status, liver injury, and acute kidney injury and was initiated on intermittent hemodialysis. Notably, she was found to have systemic eosinophilia (4100 cells/microliter) several weeks prior. She was transferred to this institution for further management where she was found to have encephalopathy, jaundice, lower extremity edema, and diffuse bilateral rhonchorous breath sounds on pulmonary examination. The patient was started on methylprednisolone for suspected DRESS syndrome. She underwent an evaluation for alternative causes of her organ failure. Her workup included a negative infectious, autoimmune, metabolic, toxic, and malignant work-up. Abdominal computed tomography (CT) and ultrasound were remarkable for evidence of hepatic steatosis and possible cirrhotic morphology. Additionally, a chest CT demonstrated diffuse and symmetric nodular alveolar lung opacities with peripheral sparing not consistent with acute respiratory distress syndrome or edema. Ultimately, her condition continued to decline, and she required intubation on several occasions. On hospital day 25 she succumbed to distributive shock in the setting of probable sepsis and multi-organ failure. Discussion: DRESS syndrome occurs in 1 in 1,000 to 10,000 patients with a mortality rate of around 10%. Anti-convulsant, anti-bacterial, anti-viral, and sulfonamide drugs are the most common drugs implicated in the development of DRESS syndrome; however, the list of offending agents is extensive . The diagnosis of DRESS syndrome is made after excluding other causes of disease such as infectious and autoimmune etiologies. The RegiSCAR scoring system is used to diagnose DRESS syndrome with 2-3 points indicating possible disease, 4-5 probable disease, and >5 definite disease. This patient scored a 7 on the RegiSCAR scale for eosinophilia, rash, organ involvement, and exclusion of other causes (infectious and autoimmune). While the pharmacologic trigger in this case is unknown, it is speculated to be caused by vancomycin, meloxicam, or furosemide due to the favorable timeline of initiation. Despite aggressive treatment, DRESS syndrome can often be fatal. Because of this, early diagnosis and treatment of patients with suspected DRESS syndrome is imperative.

Keywords: drug reaction with eosinophilia and systemic symptoms, multi-organ failure, pulmonary involvement, renal failure

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Authors: Jaan-Willem Simon, Bertram Stier, Brett Bednarcyk, Evan Pineda, Stefanie Reese

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Textile composites, in which the reinforcing fibers are woven or braided, have become very popular in numerous applications in aerospace, automotive, and maritime industry. These textile composites are advantageous due to their ease of manufacture, damage tolerance, and relatively low cost. However, physics-based modeling of the mechanical behavior of textile composites is challenging. Compared to their unidirectional counterparts, textile composites introduce additional geometric complexities, which cause significant local stress and strain concentrations. Since these internal concentrations are primary drivers of nonlinearity, damage, and failure within textile composites, they must be taken into account in order for the models to be predictive. The macro-scale approach to modeling textile-reinforced composites treats the whole composite as an effective, homogenized material. This approach is very computationally efficient, but it cannot be considered predictive beyond the elastic regime because the complex microstructural geometry is not considered. Further, this approach can, at best, offer a phenomenological treatment of nonlinear deformation and failure. In contrast, the mesoscale approach to modeling textile composites explicitly considers the internal geometry of the reinforcing tows, and thus, their interaction, and the effects of their curved paths can be modeled. The tows are treated as effective (homogenized) materials, requiring the use of anisotropic material models to capture their behavior. Finally, the micro-scale approach goes one level lower, modeling the individual filaments that constitute the tows. This paper will compare meso- and micro-scale approaches to modeling the deformation, damage, and failure of textile-reinforced polymer matrix composites. For the mesoscale approach, the woven composite architecture will be modeled using the finite element method, and an anisotropic damage model for the tows will be employed to capture the local nonlinear behavior. For the micro-scale, two different models will be used, the one being based on the finite element method, whereas the other one makes use of an embedded semi-analytical approach. The goal will be the comparison and evaluation of these approaches to modeling textile-reinforced composites in terms of accuracy, efficiency, and utility.

Keywords: multiscale modeling, continuum damage model, damage interaction, textile composites

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Authors: S. Jurado, E. Pazmino

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Determination of the medial axis of a porous media sample is a non-trivial problem of interest for several disciplines, e.g., hydrology, fluid dynamics, contaminant transport, filtration, oil extraction, etc. However, the computational tools available for researchers are limited and restricted. The primary aim of this work was to develop a series of algorithms to extract porosity, medial axis structure, and pore-throat size distributions from porous media domains. A complementary objective was to provide the algorithms as free computational software available to the academic community comprising researchers and students interested in 3D data processing. The burn algorithm was tested on porous media data obtained from High-Resolution X-Ray Microtomography (HRXMT) and idealized computer-generated domains. The real data and idealized domains were discretized in voxels domains of 550³ elements and binarized to denote solid and void regions to determine porosity. Subsequently, the algorithm identifies the layer of void voxels next to the solid boundaries. An iterative process removes or 'burns' void voxels in sequence of layer by layer until all the void space is characterized. Multiples strategies were tested to optimize the execution time and use of computer memory, i.e., segmentation of the overall domain in subdomains, vectorization of operations, and extraction of single burn layer data during the iterative process. The medial axis determination was conducted identifying regions where burnt layers collide. The final medial axis structure was refined to avoid concave-grain effects and utilized to determine the pore throat size distribution. A graphic user interface software was developed to encompass all these algorithms, including the generation of idealized porous media domains. The software allows input of HRXMT data to calculate porosity, medial axis, and pore-throat size distribution and provide output in tabular and graphical formats. Preliminary tests of the software developed during this study achieved medial axis, pore-throat size distribution and porosity determination of 100³, 320³ and 550³ voxel porous media domains in 2, 22, and 45 minutes, respectively in a personal computer (Intel i7 processor, 16Gb RAM). These results indicate that the software is a practical and accessible tool in postprocessing HRXMT data for the academic community.

Keywords: medial axis, pore-throat distribution, porosity, porous media

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Authors: Ian Walsh, Terry Nguyen-Khuong, Christopher H. Taron, Pauline M. Rudd

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Glycoproteins and their covalently bonded glycans play critical roles in the immune system, cell communication, disease and disease prognosis. Ultra performance liquid chromatography (UPLC) coupled with mass spectrometry is conventionally used to qualitatively and quantitatively characterise glycan structures in a given sample. Exoglycosidases are enzymes that catalyze sequential removal of monosaccharides from the non-reducing end of glycans. They naturally have specificity for a particular type of sugar, its stereochemistry (α or β anomer) and its position of attachment to an adjacent sugar on the glycan. Thus, monitoring the peak movements (both in the UPLC and MS1) after application of exoglycosidases provides a unique and effective way to annotate sugars with high detail - i.e. differentiating positional and linkage isomers. Manual annotation of an exoglycosidase experiment is difficult and time consuming. As such, with increasing sample complexity and the number of exoglycosidases, the analysis could result in manually interpreting hundreds of peak movements. Recently, we have implemented pattern recognition software for automated interpretation of UPLC-MS1 exoglycosidase digestions. In this work, we explain the software, indicate how much time it will save and provide example usage showing the annotation of positional and linkage isomers in Immunoglobulin G, apolipoprotein J, and simple glycan standards.

Keywords: bioinformatics, automated glycan assignment, liquid chromatography, mass spectrometry

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Authors: S. F. Halim, H. F. Naguib, S. N. Lawandy, R. S. Hegazy, M. N. Baheg

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The main drawbacks of the traditional carbon fabric reinforced epoxy resin (CFRP) are low strain failure, delamination between composites layers, and low impact resistance due to the brittleness of epoxy resin. The aim of this study is to enhance the fracture properties of the CFRP composites laminates via the variation of composite's designs. A series of composites were fabricated in which bidirectional (00/900) carbon fabric (CF) layers were laid inside the resin matrix with orientation codes as F1 [(00, 900)/ (00, 900)], F2 [(900, 00)/ (00, 900)] and F3 [(00,900)/ (900, 00). The mechanical and dynamic properties of the composites were estimated. In addition, the morphology of samples surface was examined by scanning electron microscope (SEM) after impact fracture. The results revealed that the CFRP properties could be tailored fitting specific applications by controlling the fabric orientation inside the CFRP composite design. F2 orientation [(900, 00)/ (00.900)] showed the highest tensile and flexural strength values. On the other hand, the impact strength values of composites were in the order F1 > F2 > F3. The storage modulus, loss modulus, and glass transition temperature Tg values obtained from the dynamic mechanical analysis (DMA) examination was in the order F1 > F2 > F3. The variation in the properties of the composite was clearly explained by the SEM micrographs as the failure of F3 orientation properties was referred to as the complete breakage of the CF layers upon fracture.

Keywords: carbon fiber, CFRP, composites, epoxy resins, flexural strength

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Authors: Suchart Tripopsakul

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This paper uses data from the Global Entrepreneurship Monitor (GEM) to investigate the difference of attitudes towards entrepreneurial intention (EI). EI is generally assumed to be the single most relevant predictor of entrepreneurial behavior. The aim of this paper is to examine a range of attitudes effect on individual’s intent to start a new venture. A cross-cultural comparison between Asia and Europe is used to further investigate the possible differences between potential entrepreneurs from these distinct national contexts. The empirical analysis includes a GEM data set of 10 countries (n = 10,306) which was collected in 2013. Logistic regression is used to investigate the effect of individual’s attitudes on EI. Independent variables include individual’s perceived capabilities, the ability to recognize business opportunities, entrepreneurial network, risk perceptions as well as a range of socio-cultural attitudes. Moreover, a cross-cultural comparison of the model is conducted including six ASEAN (Malaysia, Indonesia, Philippines, Singapore, Vietnam and Thailand) and four European nations (Spain, Sweden, Germany, and the United Kingdom). The findings support the relationship between individual’s attitudes and their entrepreneurial intention. Individual’s capability, opportunity recognition, networks and a range of socio-cultural perceptions all influence EI significantly. The impact of media attention on entrepreneurship and was found to influence EI in ASEAN, but not in Europe. On the one hand, Fear of failure was found to influence EI in Europe, but not in ASEAN. The paper develops and empirically tests attitudes toward Entrepreneurial Intention between ASEAN and Europe. Interestingly, fear of failure was found to have no significant effect in ASEAN, and the impact of media attention on entrepreneurship and was found to influence EI in ASEAN. Moreover, the resistance of ASEAN entrepreneurs to the otherwise high rates of fear of failure and high impact of media attention are proposed as independent variables to explain the relatively high rates of entrepreneurial activity in ASEAN as reported by GEM. The paper utilizes a representative sample of 10,306 individuals in 10 countries. A range of attitudes was found to significantly influence entrepreneurial intention. Many of these perceptions, such as the impact of media attention on entrepreneurship can be manipulated by government policy. The paper also suggests strategies by which Asian economy in particular can benefit from their apparent high impact of media attention on entrepreneurship.

Keywords: an entrepreneurial intention, attitude, GEM, ASEAN and Europe

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Authors: Seyed Mehdi Seyed Alizadeh, Christoph Arns, Shane Latham

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Geomechanical characterization of rocks in detail and its possible implications on flow properties is an important aspect of reservoir characterization workflow. In order to gain more understanding of the microstructure evolution of reservoir rocks under stress a series of axisymmetric triaxial tests were performed on two different analogue rock samples. In-situ compression tests were coupled with high resolution micro-Computed Tomography to elucidate the changes in the pore/grain network of the rocks under pressurized conditions. Two outcrop sandstones were chosen in the current study representing a various cementation status of well-consolidated and weakly-consolidated granular system respectively. High resolution images were acquired while the rocks deformed in a purpose-built compression cell. A detailed analysis of the 3D images in each series of step-wise compression tests (up to the failure point) was conducted which includes the registration of the deformed specimen images with the reference pristine dry rock image. Digital Image Correlation (DIC) technique based on the intensity of the registered 3D subsets and particle tracking are utilized to map the displacement fields in each sample. The results suggest the complex architecture of the localized shear zone in well-cemented Bentheimer sandstone whereas for the weakly-consolidated Castlegate sandstone no discernible shear band could be observed even after macroscopic failure. Post-mortem imaging a sister plug from the friable rock upon undergoing continuous compression reveals signs of a shear band pattern. This suggests that for friable sandstones at small scales loading mode may affect the pattern of deformation. Prior to mechanical failure, the continuum digital image correlation approach can reasonably capture the kinematics of deformation. As failure occurs, however, discrete image correlation (i.e. particle tracking) reveals superiority in both tracking the grains as well as quantifying their kinematics (in terms of translations/rotations) with respect to any stage of compaction. An attempt was made to quantify the displacement field in compression using continuum Digital Image Correlation which is based on the reference and secondary image intensity correlation. Such approach has only been previously applied to unconsolidated granular systems under pressure. We are applying this technique to sandstones with various degrees of consolidation. Such element of novelty will set the results of this study apart from previous attempts to characterize the deformation pattern in consolidated sands.

Keywords: deformation mechanism, displacement field, shear behavior, triaxial compression, X-ray micro-CT

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