Search results for: scalable automation testing

Authors: Francesco Colcerasa, Fabio Pisani

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We contribute to the subjective well-being literature testing the relationship between life satisfaction and inequality of opportunity in health, measured through the Human Opportunity Index calculated at the national level using individual socio-economic data from the cross-country European Social Survey sample. We compute several indexes of opportunity inequality in health, each obtained according to a different combination of circumstances (gender, immigrant status, parents’ education). We find a robust and significant relationship where life satisfaction is higher in correspondence with low levels of health opportunity inequality. The result is twofold. On the one hand, the importance of the well-being of other types of inequality than income inequality emerges. On the other hand, the socioeconomic roots of inequality in health are investigated, suggesting that circumstances at birth have a role in future well-being. Several rationales for the nexus between life satisfaction and inequality of opportunity in health are possible, which we investigate by splitting the sample. Among others, we find a prominent role of pro-social preferences – formalized as interest towards own offspring (which can be interpreted as intergenerational justice) – as a mediating factor of the relationship.

Keywords: Inequality of opportunity, subjective wellbeing, health, health inequality, inequality of opportunity in health

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Authors: R. R. Ali, W. A. W. A. Rahman, R. M. Kasmani, H. Hasbullah, N. Ibrahim, A. N. Sadikin, U. A. Asli

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In this study, tapioca starch which acts as natural polymer was added in the blend in order to produce biodegradable product. Low density polyethylene (LDPE) and tapioca starch blends were prepared by extrusion and the test sample by injection moulding process. Ethylene vinyl acetate (EVA) acts as compatibilizer while glycerol as processing aid was added in the blend. The blends were characterized by using melt flow index (MFI), fourier transform infrared (FTIR) and the effects of water absorption to the sample. As the starch content increased, MFI of the blend was decreased. Tensile testing were conducted shows the tensile strength and elongation at break decreased while the modulus increased as the starch increased. For the biodegradation, soil burial test was conducted and the loss in weight was studied as the starch content increased. Morphology studies were conducted in order to show the distribution between LDPE and starch.

Keywords: biopolymers, degradable polymers, starch based polyethylene, injection moulding

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Authors: Adrian Priceputu, Elena Mihaela Stan

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Our research addresses a critical challenge in renewable energy: improving efficiency and reducing the costs associated with the installation of ground-mounted photovoltaic (PV) panels. The most commonly used foundation solution is metal piles - with various sections adapted to soil conditions and the structural model of the panels. However, direct foundation systems are also sometimes used, especially in brownfield sites. Although metal micropiles are generally the first design option, understanding and predicting their bearing capacity, particularly under varied soil conditions, remains an open research topic. CPT Method and Current Challenges: Metal piles are favored for PV panel foundations due to their adaptability, but existing design methods rely heavily on costly and time-consuming in situ tests. The Cone Penetration Test (CPT) offers a more efficient alternative by providing valuable data on soil strength, stratification, and other key characteristics with reduced resources. During the test, a cone-shaped probe is pushed into the ground at a constant rate. Sensors within the probe measure the resistance of the soil to penetration, divided into cone penetration resistance and shaft friction resistance. Despite some existing CPT-based design approaches for metal piles, these methods are often cumbersome and difficult to apply. They vary significantly due to soil type and foundation method, and traditional approaches like the LCPC method involve complex calculations and extensive empirical data. The method was developed by testing 197 piles on a wide range of ground conditions, but the tested piles were very different from the ones used for PV pile foundations, making the method less accurate and practical for steel micropiles. Project Objectives and Methodology: Our research aims to develop a calculation method for metal micropile foundations using CPT data, simplifying the complex relationships involved. The goal is to estimate the pullout bearing capacity of piles without additional laboratory tests, streamlining the design process. To achieve this, a case study was selected which will serve for the development of an 80ha solar power station. Four testing locations were chosen spread throughout the site. At each location, two types of steel profiles (H160 and C100) were embedded into the ground at various depths (1.5m and 2.0m). The piles were tested for pullout capacity under natural and inundated soil conditions. CPT tests conducted nearby served as calibration points. The results served for the development of a preliminary equation for estimating pullout capacity. Future Work: The next phase involves validating and refining the proposed equation on additional sites by comparing CPT-based forecasts with in situ pullout tests. This validation will enhance the accuracy and reliability of the method, potentially transforming the foundation design process for PV panels.

Keywords: cone penetration test, foundation optimization, solar power stations, steel pile foundations

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Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

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This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

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Authors: Syed Ali Shahbaz Shah

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In the last few years, Bituminous Asphaltic roads are becoming popular day by day in the world. Plenty of research has been carried out to identify many advantages like safety, environmental effects, and comfort. Some other benefits are minimal noise and skid resistance enhancement. Besides the benefits of asphaltic roads, the permeable structure of the road also causes some distress, and raveling is one of the crucial defects. The main reason behind this distress is the failure of adhesion between bitumen mortar, specifically due to excessive load from heavy traffic. The main focus of this study is to identify the root cause and propose both the long-term and the short-term solutions of raveling on a specific road section depicting the overall road situation from the bridge of Kahuta road towards the intersection of the Islamabad express highway. The methodology adopted for this purpose is visual inspections in-situ. It was noted that there were chunks of debris on the road surface, which indicates that the asphalt binder is aged the most probably. Further laboratory testing would confirm that either asphalt binder is aged or inadequate compaction was adept during cold weather paving.

Keywords: asphaltic roads, asphalt binder, distress, raveling

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Authors: Andrew Couch, Nicholas Loyd, Nathan Tenhundfeld

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The rapid emergence of technology observably induces disruptive effects that carry implications for internal organizational dynamics as well as external market opportunities, strategic pressures, and threats. An examination of the historical tendencies of technology innovation shows that the body of managerial knowledge for addressing such disruption is underdeveloped. Fundamentally speaking, the impacts of innovation are unique and situationally oriented. Hence, the appropriate managerial response becomes a complex function that depends on the nature of the emerging technology, the posturing of internal organizational dynamics, the rate of technological growth, and much more. This research considers a particular case of mismanagement, the BP Texas City Refinery explosion of 2005, that carries notable discrepancies on the basis of human factors principles. Moreover, this research considers the modern technological climate (shaped by Industry 4.0 technologies) and seeks to arrive at an appropriate conceptual lens by which human factors principles and Industry 4.0 may be favorably integrated. In this manner, the careful examination of these phenomena helps to better support the sustainment of human factors principles despite the disruptive impacts that are imparted by technological innovation. In essence, human factors considerations are assessed through the application of principles that stem from usability engineering, the Swiss Cheese Model of accident causation, human-automation interaction, signal detection theory, alarm design, and other factors. Notably, this stream of research supports a broader framework in seeking to guide organizations amid the uncertainties of Industry 4.0 to capture higher levels of adoption, implementation, and transparency.

Keywords: Industry 4.0, human factors engineering, management, case study

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Authors: McClain Thiel

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Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.

Keywords: monocular distancing, computer vision, facial analysis, 3D localization

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Authors: Ahmadur Rahman, Showkat Ahmad Lone, Ariful Islam

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In this article, we have estimated the parameters for the failure times of units based on the sampling technique adaptive type-I progressive hybrid censoring under the step-stress partially accelerated life tests for competing risk. The failure times of the units are assumed to follow an exponential distribution. Maximum likelihood estimation technique is used to estimate the unknown parameters of the distribution and tampered coefficient. Confidence interval also obtained for the parameters. A simulation study is performed by using Monte Carlo Simulation method to check the authenticity of the model and its assumptions.

Keywords: adaptive type-I hybrid progressive censoring, competing risks, exponential distribution, simulation, step-stress partially accelerated life tests

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Authors: Khalid Abdullah Alshuhail, Syrif Junidi, Ideisan Abu-Abdoum, Abdulsalam Aldawoud

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For the intention of reducing energy consumption, a proposed construction brick was made of imitation termite mound soil referred here as termite brick (TB). To calculate the thermal performance, a real case model was constructed by using this biomimetic brick for testing purposes. This paper aims at investigating the thermal performance of this brick during different climatic months. Its thermal behaviour was thoroughly studied over the course of four months by using continuous method (CMm). The main parameters were focused on temperature and relative humidity. It was found that the TB does not perform similarly in all four months and/or in all orientations. Each four-month model study was deeply analyzed. By using the CMm method, the model was also examined. The measuring period shows generally that internal temperature and internal humidity are higher in the roof within 2 degrees and lowest at north wall orientation. The relative humidity was also investigated systematically. The paper reveals more interesting findings.

Keywords: building material, continious monitoring, orientation, wall, temprature

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Authors: Ian Omung'a

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Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Sumudu Sameera Perera Kimmantudawage, Chapal Khasnabis

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Technology is changing at a rapid rate, with innovations in robotics being hailed and tested in countries such as Japan, the United States and Australia, however the conversation in a public health context is stagnant. While obvious barriers to robotics use in low and middle-income countries and regions exist, the avoidance of attempting to address these regions of the world may potentially lead to an ever-increasing divide between those of high income countries and those of less. A systematic review was undertaken to determine the number of projects involving research, development and testing of robotics considered low and middle-income regions. Major findings indicate that an overwhelmingly significant number of projects failed to consider low and middle-income countries or regions. These results are unsurprising however alarming, as bridging the divide is an important step forward in achieving the UN Sustainable Development Goals by 2030. It is hoped that this research would spawn future robotics research that focusses on lower and middle-income regions.

Keywords: assistive technology, health equality, robotics, socioeconomic

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Authors: Kwame Sarkodie, William Cheung, Andrew R. Fergursson

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The characterization of multiphase flow has gained enormous attention for most petroleum and chemical industrial processes. In order to fully characterize fluid phases in a stream or containment, there needs to be a profound knowledge of the existing composition of fluids present. This introduces a problem for real-time monitoring of fluid dynamics such as fluid distributions, and phase fractions. This work presents a simple technique of correlating absorbance spectrums of water, oil and air bubble present in containment. These spectra absorption outputs are derived by using an Fourier Infrared spectrometer. During the testing, air bubbles were introduced into static water column and oil containment and with light absorbed in the infrared regions of specific wavelength ranges. Attenuation coefficients are derived for various combinations of water, gas and oil which reveal the presence of each phase in the samples. The results from this work are preliminary and viewed as a build up to the design of a multiphase flow rig which has an infrared sensor pair to be used for multiphase flow characterization.

Keywords: attenuation, infrared, multiphase, spectroscopy

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Authors: Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle

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The near-field synthetic aperture radar (SAR) imaging is an advanced nondestructive testing and evaluation (NDT&E) technique. This paper investigates the complex-valued signal processing related to the near-field SAR imaging system, where the measurement data turns out to be noncircular and improper, meaning that the complex-valued data is correlated to its complex conjugate. Furthermore, we discover that the degree of impropriety of the measurement data and that of the target image can be highly correlated in near-field SAR imaging. Based on these observations, A modified generalized sparse Bayesian learning algorithm is proposed, taking impropriety and noncircularity into account. Numerical results show that the proposed algorithm provides performance gain, with the help of noncircular assumption on the signals.

Keywords: complex-valued signal processing, synthetic aperture radar, 2-D radar imaging, compressive sensing, sparse Bayesian learning

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Authors: Pemika Ketsuwan, Pitt Supaphol, Manit Nithitanakul

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A typical used of ethylene methyl acrylate (EMA) gasket is in the manufacture of optical lens, and often, they are deteriorated rapidly due to high temperature during the process. The objective of this project is to improve the thermal stability of the EMA copolymer gasket by preparing EMA with cellulose and silica composites. Hydroxy propyl methyl cellulose (HPMC) and Carboxy methyl cellulose (CMC) were used in preparing of EMA/cellulose composites and fumed silica (SiO2) was used in preparing EMA/silica composites with different amounts of filler (3, 5, 7, 10, 15 wt.%), using a twin screw extruder at 160 °C and the test specimens were prepared by the injection molding machine. The morphology and dispersion of fillers in the EMA matrix were investigated by field emission scanning electron microscopy (FESEM). The thermal stability of the composite was determined by thermal gravimetric analysis (TGA), and differential scanning calorimeter (DSC). Mechanical properties were evaluated by tensile testing. The developed composites were found to enhance thermal and mechanical properties when compared to that of the EMA copolymer alone.

Keywords: ethylene methyl acrylate, HPMC, Silica, Thermal stability

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Authors: Bih Ni Lee

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This paper discusses the unending coronavirus (Covid-19) pandemic. The activity of detecting, testing those with symptoms, and isolating their contacts is the most effective method of stopping the chain of coronavirus infection. The number of cases of coronavirus continues to increase with some reporting a cure, but not a few die. Efforts to treat and prevent continue to fight COVID-19 with flu-like symptoms. The importance of the study is to identify smartphone applications that can track the movement of individuals in an effort to curb the spread of COVID-19, especially in Malaysia. This research method used a literature review, which included new insights into the quality of action and scientific papers. It synthesized information gleaned from a variety of sources. The findings of the study are that the Government of Malaysia has launched three main applications to track the movement of individuals, namely Gerak Malaysia, MyTrace, MySejahtera. Similarly, every state in Malaysia has its own state government application to track individual movements. Overall, Malaysia is one of the countries in the world that has successfully curbed the spread of COVID-19; Covid-19 cases in Malaysia are under control.

Keywords: COVID-19 app, national security council, Gerak Malaysia, MyTrace, MySejahtera

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Authors: Jaylina Rana, Chanakya Arya, John Stehle

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Hybrid precast twinwall concrete units, mainly used in basement, core and crosswall construction, are now being adopted in water retaining tank structures. Their use offers many advantages compared with conventional in-situ concrete alternatives, however, the design could be optimised further via a deeper understanding of the unique load transfer mechanisms in the system. In the tank application, twinwall units, which consist of two precast concrete biscuits connected by steel lattices and in-situ concrete core, are subject to bending. Uncertainties about the degree of composite action between the precast biscuits and hence flexural performance of the units necessitated laboratory tests to investigate the interface shear resistance. Testing was also required to assess both the leakage performance and buildability of a variety of joint details. This paper describes some aspects of this novel approach to the design/construction of tank structures as well as selected results from some of the tests that were carried out.

Keywords: hybrid construction, twinwall, precast construction, composite action

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Authors: Abolfazl Ghelichi, Ghasem Modarresi

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The problem with interpretation courses arises from the fact that Interpretation Courses at University levels are presented by most of the instructors based on listening activities and testing listening performance while interpretation strategies have been underrated. The data are gathered from30 students majoring in Translation Studies to fulfill the major aims of the study including. The study aimed at: 1) examining the significant relationship between specific interpretation strategies and interpretation performance of translation students in interpretation courses, 2) investigating the significant difference between males and females in their interpretation performance, and 3) exploring the interpretation strategies which are more effective for the translation students to improve their interpretation performance from students’ opinions. The results of the study revealed that there was a statistically significant difference in the mean scores for the two groups. The experimental group outperformed the control group in their interpretation performance and the effect size was large. However, there was no significant difference between male and female with respect to their cognition [t (28) =.79, p<.05]. As for the results obtained from the interviews with the students, the commonalities emerged from the students’ responses were analyzed and reported by the researchers.

Keywords: anticipation, interpretation performance, interpretation strategy, shadowing

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Authors: Siti Nur Aida Mario, Farah Hafifee Ahmad, Rudy Tawie

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Soil Stabilization has been widely implemented in the construction industry nowadays. Peat soil is well known as one of the most problematic soil among the engineers. The procedures need to take into account both physical and engineering properties of the stabilized peat soil. This paper presents a result of plasticity index and hardening of treated peat soil with various dosage of additives. In order to determine plasticity of the treated peat soil, atterberg limit test which comprises plastic limit and liquid limit test has been conducted. Determination of liquid limit in this experimental study is by using cone penetrometer. Vicat testing apparatus has been used in the hardening test which the penetration of the plunger is recorded every one hour for 24 hours. The results show that the plasticity index of peat soil stabilized with 80% FAAC and 20% OPC has the lowest plasticity index and recorded the fastest initial setting time. The significant of this study is to promote greener solution for future soil stabilization industry.

Keywords: additives, hardening, peat soil, plasticity index, soil stabilization

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Abdurrasheed Sa'id, Abubakar Isma'il, Waheed Alayande

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This study focused on carrying out numerical simulations of Kangimi reservoir sedimentation by reviewing different numerical sediment transport models, and GSTARS3 was selected. The model was developed using the 1977 data. It was calibrated by simulating the 2012 profile and sediment deposition and compared with 2012 hydrographic survey results of NWRI. The model was validated by simulating the 2016 deposition and compared the results with NWRI estimates. Also, the performance of the proposed model was tested using statistical parameters such as MSE (Mean Square Error), MAPE (Mean Average Percentage Error) and R2 (Coefficient of determination) with values of 1.32m, 0.17% and 0.914 respectively which shows strong agreement. After the calibration, validation and performance testing the model was used to simulate the 2032 and 2062 profiles and deposition. The results showed that by 2032 the reservoir will be silted by 25.34MCM or 43.3% of the design capacity and 60.7% of the capacity by the year 2062. A number of sedimentation mitigation measures were recommended.

Keywords: NWRI- national water resources institute, sedimentation, GSTARS3, model

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Authors: Perminder JitKaur, Santosh Satya, K. K. Pant, S. N. Naik

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Bamboo is extensively used in construction industry. Low durability of bamboo due to fungus infestation and termites attack under storage puts certain constrains for it usage as modern structural material. Looking at many chemical formulations for bamboo treatment leading to severe harmful environment effects, research on eco-friendly preservatives for bamboo treatment has been initiated world-over. In the present studies, eco-friendly preservative for bamboo treatment has been developed. To validate its application for structural purposes, investigation of effect of treatment on compressive strength has been investigated. Neem oil(25%) integrated with copper naphthenate (0.3%) on dilution with kerosene oil impregnated into bamboo culm at 2 bar pressure, has shown weight loss of only 3.15% in soil block analysis method. The results of compressive strength analysis using The results from compressive strength analysis using HEICO Automatic Compression Testing Machine, reveal that preservative treatment has not altered the structural properties of bamboo culms. Compressive strength of control (11.72 N/mm2) and above treated samples (11.71 N/mm2) was found to be comparable.

Keywords: D. strictus, bamboo, neem oil, presure treatment, compressive strength

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Authors: A. Mohammed, R. Lewis, M. Marshall

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Commonly used coatings to protect tools in die casting were used. A heat treatment and then surface coating can have a large effect on erosion damage. Samples have been tested to evaluate their resistances to erosive wear and to assess how this compares with behaviour seen for untreated material. Five commercial (PN + TiN), (PN + TiAlCN), (TiN X 2), (TiN), and (TiAlCN) coatings have been evaluated for their wear resistance. The objective was to permit an optimized selection of coatings to be used to give good resistance to erosive wear. A test-Rig has been developed to study the erosive wear in aluminium die casting and provide an environment similar to industrial operation that is more practical than using actual machines. These surfaces were analysed using a Scanning Electron Microscope (SEM) and Optical Microscopes each with a different level of resolution. Examination of coating materials revealed an important parameter associated with the failure of the coating materials.This was adhesion of the coating material to the substrate surface. A well-adhered coating withstands wear much better compared to the poorest-adhering coating.

Keywords: solid particle erosion, PVD-coatings, steel, erosion testing

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Authors: A. E. Dumitriu

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The LHCb experiment is situated at one of the four points around CERN’s Large Hadron Collider, being a single-arm forward spectrometer covering 10 mrad to 300 (250) mrad in the bending (non-bending) plane, designed primarily to study particles containing b and c quarks. Each one of LHCb’s sub-detectors specializes in measuring a different characteristic of the particles produced by colliding protons, its significant detection characteristics including a high precision tracking system and 2 ring-imaging Cherenkov detectors for particle identification. The major two topics that I am currently concerned in are: the RIVET project (Robust Independent Validation of Experiment and Theory) which is an efficient and portable tool kit of C++ class library useful for validation and tuning of Monte Carlo (MC) event generator models by providing a large collection of standard experimental analyses useful for High Energy Physics MC generator development, validation, tuning and regression testing and V0 analysis for 2013 LHCb NoBias type data (trigger on bunch + bunch crossing) at √s=2.76 TeV.

Keywords: LHCb physics, RIVET plug-in, RIVET, CERN

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Authors: Alaa Fezai, Anuj Sharma, Wolfgang Mueller-Hirsch, André Zimmermann

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Viscoelastic materials have been widely used in the automotive industry over the last few decades with different functionalities. Besides their main application as a simple and efficient surface damping treatment, they may ensure optimal operating conditions for on-board electronics as thermal interface or sealing layers. The dynamic behavior of viscoelastic materials is generally dependent on many environmental factors, the most important being temperature and strain rate or frequency. Prior to the reliability analysis of systems including viscoelastic layers, it is, therefore, crucial to accurately predict the dynamic and lifetime behavior of these materials. This includes the identification of the dynamic material parameters under critical temperature and frequency conditions along with a precise damage localization and identification methodology. The goal of this work is twofold. The first part aims at applying an inverse viscoelastic material-characterization approach for a wide frequency range and under different temperature conditions. For this sake, dynamic measurements are carried on a single lap joint specimen using an electrodynamic shaker and an environmental chamber. The specimen consists of aluminum beams assembled to adapter plates through a viscoelastic adhesive layer. The experimental setup is reproduced in finite element (FE) simulations, and frequency response functions (FRF) are calculated. The parameters of both the generalized Maxwell model and the fractional derivatives model are identified through an optimization algorithm minimizing the difference between the simulated and the measured FRFs. The second goal of the current work is to guarantee an on-line detection of the damage, i.e., delamination in the viscoelastic bonding of the described specimen during frequency monitored end-of-life testing. For this purpose, an inverse technique, which determines the damage location and size based on the modal frequency shift and on the change of the mode shapes, is presented. This includes a preliminary FE model-based study correlating the delamination location and size to the change in the modal parameters and a subsequent experimental validation achieved through dynamic measurements of specimen with different, pre-generated crack scenarios and comparing it to the virgin specimen. The main advantage of the inverse characterization approach presented in the first part resides in the ability of adequately identifying the material damping and stiffness behavior of soft viscoelastic materials over a wide frequency range and under critical temperature conditions. Classic forward characterization techniques such as dynamic mechanical analysis are usually linked to limitations under critical temperature and frequency conditions due to the material behavior of soft viscoelastic materials. Furthermore, the inverse damage detection described in the second part guarantees an accurate prediction of not only the damage size but also its location using a simple test setup and outlines; therefore, the significance of inverse numerical-experimental approaches in predicting the dynamic behavior of soft bonding layers applied in automotive electronics.

Keywords: damage detection, dynamic characterization, inverse approaches, vibration testing, viscoelastic layers

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Authors: Nirmani Wijenayake, Louise Lutze-Mann, Lucy Jo, John Wilson, Vivian Yeung, Dean Lovett, Kim Snepvangers

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Sessional academic staff at universities have the most influence and impact on student learning, engagement, and experience as they have the most direct contact with undergraduate students. A blended technology-enhanced program was created for the development and support of sessional staff to ensure adequate training is provided to deliver quality educational outcomes for the students. This program combines innovative mixed media educational modules, a peer-driven support forum, and face-to-face workshops to provide a comprehensive training and support package for staff. Additionally, the program encourages the development of learning communities and peer mentoring among the sessional staff to enhance their support system. In 2018, the program was piloted on 100 sessional staff in the School of Biotechnology and Biomolecular Sciences to evaluate the effectiveness of this model. As part of the program, rotoscope animations were developed to showcase ‘typical’ interactions between staff and students. These were designed around communication, confidence building, consistency in grading, feedback, diversity awareness, and mental health and wellbeing. When surveyed, 86% of sessional staff found these animations to be helpful in their teaching. An online platform (Moodle) was set up to disseminate educational resources and teaching tips, to host a discussion forum for peer-to-peer communication and to increase critical thinking and problem-solving skills through scenario-based lessons. The learning analytics from these lessons were essential in identifying difficulties faced by sessional staff to further develop supporting workshops to improve outcomes related to teaching. The face-to-face professional development workshops were run by expert guest speakers on topics such as cultural diversity, stress and anxiety, LGBTIQ and student engagement. All the attendees of the workshops found them to be useful and 88% said they felt these workshops increase interaction with their peers and built a sense of community. The final component of the program was to use an adaptive e-learning platform to gather feedback from the students on sessional staff teaching twice during the semester. The initial feedback provides sessional staff with enough time to reflect on their teaching and adjust their performance if necessary, to improve the student experience. The feedback from students and the sessional staff on this model has been extremely positive. The training equips the sessional staff with knowledge and insights which can provide students with an exceptional learning environment. This program is designed in a flexible and scalable manner so that other faculties or institutions could adapt components for their own training. It is anticipated that the training and support would help to build the next generation of educators who will directly impact the educational experience of students.

Keywords: designing effective instruction, enhancing student learning, implementing effective strategies, professional development

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Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

Abstract:

The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

Procedia PDF Downloads 341

Authors: Clemens Pizzinini, Philipp Rosner, David Ziegler, Markus Lienkamp

Abstract:

Transportation is a constitutional part of most supply and value chains in modern economies. Smallholder farmers in rural Ethiopia face severe challenges along their supply and value chains. In particular, suitable, affordable, and available transport services are in high demand. To develop a context-specific technical solutions, a problem-to-solution methodology based on the interaction with technology is developed. With this approach, we fill the gap between proven transportation assessment frameworks and general user-centered techniques. Central to our approach is an electric test vehicle that is implemented in rural supply and value chains for research, development, and testing. Based on our objective and the derived methodological requirements, a set of existing methods is selected. Local partners are integrated into an organizational framework that executes major parts of this research endeavour in the Arsi Zone, Oromia Region, Ethiopia.

Keywords: agricultural value chain, participatory methods, agile methods, sub-Saharan Africa, Ethiopia, electric vehicle, transport service

Procedia PDF Downloads 56

Authors: Walid M. Adel, Liang Guo-Zhu

Abstract:

To investigate the characterization of the mechanical properties of composite solid propellant (CSP) based on hydroxyl-terminated polybutadiene (HTPB) at different temperatures and strain rates, uniaxial tensile tests were conducted over a range of temperatures -60 °C to +76 °C and strain rates 0.000164 to 0.328084 s^-1 using a conventional universal testing machine. From the experimental data, it can be noted that the mechanical properties of AP/HTPB propellant are mainly dependent on the applied strain rate and the temperature condition. The stress-strain responses exhibited an initial yielding followed by the viscoelastic phase, which was strongly affected by the strain rate and temperature. It was found that the mechanical properties increased with both increasing strain rate and decreasing temperature. Based on the experimental tests, the master curves of the tensile properties are drawn using predetermined shift factor and the results were discussed. This work is a first step in preliminary investigation the nonlinear viscoelasticity behavior of CSP.

Keywords: AP/HTPB composite solid propellant, mechanical behavior, nonlinear viscoelastic, tensile test, strain rate

Procedia PDF Downloads 214

Authors: Anbang Liu, Huaqing Xie, Zihua Wu, Xiaoxiao Yu, Yuanyuan Wang

Abstract:

Due to the temperature-dependence and mutual coupling of thermoelectric parameters, the Thomson effect always exists, which is derived from temperature gradients during thermoelectric conversion. The synergistic effect between the Thomson effect and non-equilibrium heat transport of charge carriers leads to local heat absorption or release in thermoelements, thereby affecting its power generation performance and conversion efficiency. This study verified and analyzed the influence and mechanism of the Thomson effect on N-type skutterudite thermoelement through quasi-steady state testing under approximate vacuum conditions. The results indicate the temperature rise/fall of N-type thermoelement at any position is affected by Thomson heat release/absorption. Correspondingly, the Thomson effect also contributes advantageously/disadvantageously to the output power of N-type skutterudite thermoelement when the Thomson coefficients are positive/negative. In this work, the output power can be promoted or decreased maximally by more than 27% due to the presence of Thomson heat when the absolute value of the Thomson coefficient is around 36 μV/℃.

Keywords: Thomson effect, heat transport, thermoelectric conversion, numerical simulation

Procedia PDF Downloads 43