Search results for: measuring accuracy

Authors: Hassina Gheribi, Salim Boukebbab

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The measurement of the parts manufactured on CMM (coordinate measuring machine) is based on the association of a surface of perfect geometry to the group of dots palpated via a mathematical calculation of the distances between the palpated points and itself surfaces. Surfaces not being never perfect, they are measured by a number of points higher than the minimal number necessary to define them mathematically. However, the central problems of three-dimensional metrology are the estimate of, the orientation parameters, location and intrinsic of this surface. Including the numerical uncertainties attached to these parameters help the metrologist to make decisions to be able to declare the conformity of the part to specifications fixed on the design drawing. During this paper, we will present a data-processing model in Visual Basic-6 which makes it possible automatically to determine the whole of these parameters, and their uncertainties.

Keywords: coordinate measuring machines (CMM), associated surface, uncertainties of measurement, acquisition and modeling

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Authors: Nayoma Ranawaka

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The demand for the high quality internationally comparable financial information has been increased than ever with the expansion of economic activities beyond its national boundaries. Thus, the necessity of converging accounting practices across the world is now continuously discussed with greater emphasis. The global convergence to International Financial Reporting Standards has been one of the main objectives of the International Accounting Standards Setting Board (IASB) since its establishment in 2001. Accordingly, Sri Lanka has adopted IFRSs in 2012. Among the other standards as a newly introduced standard by the IASB, IFRS 13 plays a pivotal role as it deals with the Fair Value Accounting (FVA). Therefore, it is valuable to obtain knowledge about the consequences of implementing IFRS 13 in Sri Lanka and compare results across nations. According to the IFRS Jurisdictional provision of Sri Lanka, Institute of Chartered Accountants of Sri Lanka has taken official steps to adopt IFRS 13 by introducing SLFRS 13 with de jure convergence. Then this study was identified the de facto convergence of the SLFRS 13 in measuring the Fair Value of Financial Instruments in the Sri Lankan context. Accordingly, the objective of this study is to explore the consequences to financial reporting by implementing SLFRS 13 on measuring the financial instruments. In order to achieve the objective of the study expert interview and in-depth interviews with the interviewees from the selected three case studies and their independent auditor were carried out using customized three different interview guides. These three cases were selected from three different industries; Banking, Manufacturing and Finance. NVivo version 10 was used to analyze the data collected through in-depth interviews. Then the content analysis was carried out and conclusions were derived based on the findings. Contribution to the knowledge by this study can be identified in different aspects. Findings of this study facilitate accounting practitioners to get an overall picture of application of fair value standard in measuring the financial instruments and to identify the challenges and barriers to the adoption process. Further, assist auditors in carrying out their audit procedures to check the level of compliance to the fair value standard in measuring the financial instruments. Moreover, this would enable foreign investors in assessing the reliability of the financial statements of their target investments as a result of SLFRS 13 in measuring the FVs of the FIs. The findings of the study could be used to open new avenues of thinking for policy formulators to provide the necessary infrastructure to eliminate disparities exists among different regulatory bodies to facilitate full convergence and thereby growth of the economy. Further, this provides insights to the dynamics of FVA implementation that are also relevant for other developing countries.

Keywords: convergence, fair value, financial instruments, IFRS 13

Procedia PDF Downloads 110

Authors: Auwal Abubakar, Ahmed Ahidjo, Shazril Imran Shaukat, Noor Khairiah A. Karim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

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Background: The use of optical surface imaging systems (OSISs) is increasingly becoming popular in radiotherapy practice, especially during breast cancer treatment. This study reviews the accuracy of the available commercial OSISs for breast radiotherapy. Method: A literature search was conducted and identified the available commercial OSISs from different manufacturers that are integrated into radiotherapy practice for setup verification during breast radiotherapy. Studies that evaluated the accuracy of the OSISs during breast radiotherapy using cone beam computed tomography (CBCT) as a reference were retrieved and analyzed. The physics and working principles of the systems from each manufacturer were discussed together with their respective strength and limitations. Results: A total of five (5) different commercially available OSISs from four (4) manufacturers were identified, each with a different working principle. Six (6) studies were found to evaluate the accuracy of the systems during breast radiotherapy in conjunction with CBCT as a goal standard. The studies revealed that the accuracy of the system in terms of mean difference ranges from 0.1 to 2.1 mm. The correlation between CBCT and OSIS ranges between 0.4 and 0.9. The limit of agreements obtained using bland Altman analysis in the studies was also within an acceptable range. Conclusion: The OSISs have an acceptable level of accuracy and could be used safely during breast radiotherapy. The systems are non-invasive, ionizing radiation-free, and provide real-time imaging of the target surface at no extra concomitant imaging dose. However, the system should only be used to complement rather than replace x-ray-based image guidance techniques such as CBCT.

Keywords: optical surface imaging system, Cone beam computed tomography (CBCT), surface guided radiotherapy, Breast radiotherapy

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Authors: Zhu Xinxin, Wang Hui, Yang Kai

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Heat flux is one of the most important test parameters in the ground thermal protection test. Slug calorimeter is selected as the main sensor measuring heat flux in arc wind tunnel test due to the convenience and low cost. However, because of excessive lateral heat transfer and the disadvantage of the calculation method, the heat flux measurement error of the slug calorimeter is large. In order to enhance measurement accuracy, the heat insulation structure and heat flux calculation method of slug calorimeter were improved. The heat transfer model of the slug calorimeter was built according to the energy conservation principle. Based on the heat transfer model, the insulating sleeve of the hollow structure was designed, which helped to greatly decrease lateral heat transfer. And the slug with insulating sleeve of hollow structure was encapsulated using a package shell. The improved insulation structure reduced heat loss and ensured that the heat transfer characteristics were almost the same when calibrated and tested. The heat flux calibration test was carried out in arc lamp system for heat flux sensor calibration, and the results show that test accuracy and precision of slug calorimeter are improved greatly. In the meantime, the simulation model of the slug calorimeter was built. The heat flux values in different temperature rise time periods were calculated by the simulation model. The results show that extracting the data of the temperature rise rate as soon as possible can result in a smaller heat flux calculation error. Then the different thermal contact resistance affecting calculation error was analyzed by the simulation model. The contact resistance between the slug and the insulating sleeve was identified as the main influencing factor. The direct comparison calibration correction method was proposed based on only heat flux calibration. The numerical calculation correction method was proposed based on the heat flux calibration and simulation model of slug calorimeter after the simulation model was solved by solving the contact resistance between the slug and the insulating sleeve. The simulation and test results show that two methods can greatly reduce the heat flux measurement error. Finally, the improved slug calorimeter was tested in the arc wind tunnel. And test results show that the repeatability accuracy of improved slug calorimeter is less than 3%. The deviation of measurement value from different slug calorimeters is less than 3% in the same fluid field. The deviation of measurement value between slug calorimeter and Gordon Gage is less than 4% in the same fluid field.

Keywords: correction method, heat flux calculation, heat insulation structure, heat transfer model, slug calorimeter

Procedia PDF Downloads 105

Authors: Pelangi Wiyantika

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Sustainable energy is the main concern in According to solve any problems on energy sectors. One of the sustainable energy that has lack of presentation is Geothermal energy which has developed lately as the new promising sustainable energy. Indonesia as country that has been passed by the ring of fire zone has many geothermal sources. This is the good opportunity to elaborate and learn more about geothermal as sustainable and renewable energy. Geothermal systems have special characteristic whom the zone of sources can be detected by measuring the resistivity of the subsurface. There are many methods to measuring the anomaly of the systems. One of the best method is Magnetotelluric approchment. Magnetotelluric is the passive method which the resistivity is obtained by injecting the eddy current of rocks in the subsurface with the sources. The sources of Magnetotelluric method can be obtained from lightning or solar wind which has the frequencies each below 1 Hz and above 1 Hz.

Keywords: geothermal, magnetotelluric, renewable energy, resistivity, sustainable energy

Procedia PDF Downloads 285

Authors: Heng Han, Zhilei Liang, Xiangong Zhou

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In this paper, the finite element method is used to study the temperature field of the main cable of the suspension bridge, and the calculation method of the average temperature of the cross-section of the main cable suitable for the construction control of the cable system is proposed; By comparing and analyzing the temperature field of the main cable with five diameters, a reasonable diameter limit for calculating the average temperature of the cross section of the main cable by finite element method is proposed. The results show that the maximum error of this method is less than 1℃, which meets the requirements of construction control accuracy; For the main cable with a diameter greater than 400mm, the surface temperature measuring points combined with the finite element method shall be used to calculate the average cross-section temperature.

Keywords: suspension bridge, main cable, temperature field, finite element

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Authors: Philipp Wenger, Michael Beltle, Stefan Tenbohlen, Uwe Riechert

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The integration of renewable energy introduces new challenges to the transmission grid, as the power generation is located far from load centers. The associated necessary long-range power transmission increases the demand for high voltage direct current (HVDC) transmission lines and DC distribution grids. HVDC gas-insulated switchgears (GIS) are considered being a key technology, due to the combination of the DC technology and the long operation experiences of AC-GIS. To ensure long-term reliability of such systems, insulation defects must be detected in an early stage. Operational experience with AC systems has proven evidence, that most failures, which can be attributed to breakdowns of the insulation system, can be detected and identified via partial discharge (PD) measurements beforehand. In AC systems the identification of defects relies on the phase resolved partial discharge pattern (PRPD). Since there is no phase information within DC systems this method cannot be transferred to DC PD diagnostic. Furthermore, the behaviour of e.g. free-moving particles differs significantly at DC: Under the influence of a constant direct electric field, charge carriers can accumulate on particles’ surfaces. As a result, a particle can lift-off, oscillate between the inner conductor and the enclosure or rapidly bounces at just one electrode, which is known as firefly motion. Depending on the motion and the relative position of the particle to the electrodes, broadband electromagnetic PD pulses are emitted, which can be recorded by ultra-high frequency (UHF) measuring methods. PDs are often accompanied by light emissions at the particle’s tip which enables optical detection. This contribution investigates PD characteristics of free moving metallic particles in a commercially available 300 kV SF6-insulated HVDC-GIS. The influences of various defect parameters on the particle motion and the PD characteristic are evaluated experimentally. Several particle geometries, such as cylinder, lamella, spiral and sphere with different length, diameter and weight are determined. The applied DC voltage is increased stepwise from inception voltage up to UDC = ± 400 kV. Different physical detection methods are used simultaneously in a time-synchronized setup. Firstly, the electromagnetic waves emitted by the particle are recorded by an UHF measuring system. Secondly, a photomultiplier tube (PMT) detects light emission with a wavelength in the range of λ = 185…870 nm. Thirdly, a high-speed camera (HSC) tracks the particle’s motion trajectory with high accuracy. Furthermore, an electrically insulated electrode is attached to the grounded enclosure and connected to a current shunt in order to detect low frequency ion currents: The shunt measuring system’s sensitivity is in the range of 10 nA at a measuring bandwidth of bw = DC…1 MHz. Currents of charge carriers, which are generated at the particle’s tip migrate through the gas gap to the electrode and can be recorded by the current shunt. All recorded PD signals are analyzed in order to identify characteristic properties of different particles. This includes e.g. repetition rates and amplitudes of successive pulses, characteristic frequency ranges and detected signal energy of single PD pulses. Concluding, an advanced understanding of underlying physical phenomena particle motion in direct electric field can be derived.

Keywords: current shunt, free moving particles, high-speed imaging, HVDC-GIS, UHF

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Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

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Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

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Authors: M. Fathy, I. Maarouf, S. El-Sayary

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Our buildings are responsible for around 50% of energy consumption and most of this consumption because of spaces design, low heat isolation building material and occupant presence and behavior in buildings beside non-efficient architectural treatments. It has been shown to have large impact on heating, cooling and ventilation demand, energy consumption of lighting and appliances, and building controls. This paper aims to focus on passive treatments in Wakala Buildings in Cairo and how far it meets the LEED Criteria as the LEED – Leadership in Energy and Environmental Design – considered the widest spread rating system in the world. By studying Wakala buildings in Cairo, there are a lot of environmental potentials in it in the field of passive treatments and energy efficiency that could be found in examples by surveying and analyzing Wakala buildings. Besides the environmental treatments through the natural materials and façade architectural treatments, there is a measuring phase to declare the efficiency of the Wakala building through temperature decline between outdoor and indoor the Wakala building. Also, measuring how far the indoor conditions matched the thermal comfort for occupants. After measuring the Wakala buildings, it is the role of applying the criteria of LEED rating system to find out how fare Wakala buildings meet the LEED rating system criteria. After all, the building technologies used in Wakala buildings in the field of passive design and caused that energy efficiency would be clear and what is needed for Wakala buildings to have a LEED Certification.

Keywords: energy awareness, historical commercial buildings, LEED, Wakala buildings

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: distillation, machine learning, neural networks, quantization

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Authors: Luís Farinha, João J. Ferreira

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Nowadays innovation represents a challenge crucial to remaining globally competitive. This study seeks to develop a conceptual model aimed at measuring the dynamic interactions of the triple/quadruple helix, balancing innovation and entrepreneurship initiatives as pillars of regional competitiveness – the Regional Helix Scoreboard (RHS). To this aim, different strands of literature are identified according to their focus on specific regional competitiveness governance mechanisms. We put forward an overview of the state-of-the-art of research and is duly assessed in order to develop and propose a framework of analysis that enables an integrated approach in the context of collaborative dynamics. We conclude by presenting the RHS for the study of regional competitiveness dynamics, which integrates and associates different backgrounds and identifies a number of key performance indicators for research challenges.

Keywords: entrepreneurship, KPIs, innovation, performance measurement, regional competitiveness, regional helix scoreboard

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Authors: Ritchie Ann Dionela, Jorilyn Tabuena

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This study measured the economic empowerment of women from small-scale fisheries and agriculture sector of Sebaste, Antique. There were a total of 199 respondents selected using stratified random sampling. The Five Domains of Empowerment (5DE) Index was used in measuring the economic empowerment of study participants. Through this composite index, it was determined how women scored in the five domains of empowerment, namely production, resources, income, leadership, and time. The result of the study shows that women fishers are more economically empowered than women farmers. The two sectors showed high disparity in their scores on input in productive decision; autonomy in production; ownership of assets; control over use of income; group member; speaking in public; workload; and leisure. Group member indicator contributed largely to the disempowered population in both sectors. Although income of women farmers is higher than that of women fishers, the latter are still economically empowered which suggests that economic empowerment is not dependent on income alone. The study recommends that fisheries and agriculture organization for women should be established so that their needs and concerns will be heard and addressed. It is further recommended that government projects focused on enhancing women empowerment should also give importance on other factors such as organization and leisure and not just income to totally promote of women empowerment. Further studies on measuring women’s empowerment using other methods should be pursued to provide more information on women’s well-being.

Keywords: agriculture, composite index, fisheries, women economic empowerment

Procedia PDF Downloads 211

Authors: Man-Hong Lai, Dinusha S. Gunawardena, Kok-Sing Lim, Harith Ahmad

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In this paper, we have reported birefringence manipulation in regenerated high-birefringent fiber Bragg grating (RPMG) by using CO2 laser annealing method. The results indicate that the birefringence of RPMG remains unchanged after CO2 laser annealing followed by a slow cooling process, but reduced after the fast cooling process (~5.6×10-5). After a series of annealing procedures with different cooling rates, the obtained results show that slower the cooling rate, higher the birefringence of RPMG. The volume, thermal expansion coefficient (TEC) and glass transition temperature (Tg) change of stress applying part in RPMG during the cooling process are responsible for the birefringence change. Therefore, these findings are important to the RPMG sensor in high and dynamic temperature environment. The measuring accuracy, range and sensitivity of RPMG sensor are greatly affected by its birefringence value. This work also opens up a new application of CO2 laser for fiber annealing and birefringence modification.

Keywords: birefringence, CO2 laser annealing, regenerated gratings, thermal stress

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Authors: Amr Abdel Azim Ali, G. A. Elsheikh, Moutaz Hegazy

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This paper presents verification of a modeling and simulation for a Spacecraft (SC) attitude and orbit control system. Detailed formulation of coupled SC orbital and attitude equations of motion is performed in order to achieve accepted accuracy to meet the requirements of multitargets tracking and orbit correction complex modes. Correction of the target parameter based on the estimated state vector during shooting time to enhance pointing accuracy is considered. Time-optimal nonlinear feedback control technique was used in order to take full advantage of the maximum torques that the controller can deliver. This simulation provides options for visualizing SC trajectory and attitude in a 3D environment by including an interface with V-Realm Builder and VR Sink in Simulink/MATLAB. Verification data confirms the simulation results, ensuring that the model and the proposed control law can be used successfully for large and fast tracking and is robust enough to keep the pointing accuracy within the desired limits with considerable uncertainty in inertia and control torque.

Keywords: attitude and orbit control, time-optimal nonlinear feedback control, modeling and simulation, pointing accuracy, maximum torques

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

Procedia PDF Downloads 241

Authors: Sayna Bahraini, Wendy Gifford, Ian Graham, Liquaa Wazni, Suzettee Bremault-Phillips, Rebekah Hackbusch, Catrine Demers, Mary Egan

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Objective: Guidelines for palliative and spiritual care emphasize the importance of screening patients for spiritual suffering. The aim of this review was to synthesize the research evidence on the accuracy of measures used to screen adults for spiritual suffering. Methods: A systematic review has been conducted. We searched five scientific databases to identify relevant articles. Two independent reviewers screened extracted data and assessed study methodological quality. Results: We identified five articles that yielded information on 24 spiritual screening measures. Among all identified measures, the 2-item Meaning/Joy & Self-Described Struggle has the highest sensitivity (82-87%), and the revised Rush protocol has the highest specificity (81-90%). The methodological quality of all included studies was low. Significance of Results: While most of the identified spiritual screening measures are brief (comprise 1 to 12 number of items), few have sufficient accuracy to effectively screen patients for spiritual suffering. We advise clinicians to use their critical appraisal skills and clinical judgment when selecting and using any of the identified measures to screen for spiritual suffering.

Keywords: screening, suffering, spirituality, diagnostic test accuracy, systematic review

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Authors: Mohammad Samarah, Benjamin Stark, Jennifer Kindle, Langley Payton

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Innovation is a key driver for companies, society, and economic growth. However, assessing and measuring innovation for individuals as well as organizations remains difficult. Our i5-Score presented in this study will help to overcome this difficulty and facilitate measuring the innovation potential. The score is based on a framework we call the 5Gs of innovation which defines specific innovation attributes. Those are 1) the drive for long-term goals 2) the audacity to generate new ideas, 3) the openness to share ideas with others, 4) the ability to grow, and 5) the ability to maintain high levels of optimism. To validate the i5-Score, we conducted a study at Florida Polytechnic University. The results show that the i5-Score is a good measure reflecting the innovative mindset of an individual or a group. Thus, the score can be utilized for evaluating, refining and enhancing innovation capabilities.

Keywords: Change Management, Innovation Attributes, Organizational Development, STEM and Venture Creation

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Authors: Ahmed A. D. Sarhan, Mum Wai Yip, M. Sayuti, Lim Siew Fen

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Ti6Al4V alloy is highly used in the automotive and aerospace industry due to its good machining characteristics. Micro EDM drilling is commonly used to drill micro hole on extremely hard material with very high depth to diameter ratio. In this study, the parameters of micro-electrical discharge machining (EDM) in drilling of Ti6Al4V alloy is optimized for higher machining accuracy with less hole-dilation and hole taper ratio. The micro-EDM machining parameters includes, peak current and pulse on time. Fuzzy analysis was developed to evaluate the machining accuracy. The analysis shows that hole-dilation and hole-taper ratio are increased with the increasing of peak current and pulse on time. However, the surface quality deteriorates as the peak current and pulse on time increase. The combination that gives the optimum result for hole dilation is medium peak current and short pulse on time. Meanwhile, the optimum result for hole taper ratio is low peak current and short pulse on time.

Keywords: Micro EDM, Ti-6Al-4V alloy, fuzzy logic based analysis, optimization, machining accuracy

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Authors: Zahra Ebrahimi, Abbas Moradan

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This study investigated the effect of applying different layers of activity for different Iranian intermediate EFL learner’s oral proficiency and two of its components (fluency and accura-cy) for the beneficial use of films within speaking classes. For this purpose, thirty Iranian EFL intermediate learners were selected based on availability sampling, they were divided into one experimental group and one control group, each consisting of 15 participants, who were proved to be homogeneous based on the results obtained from IELTS oral proficien-cy test prior to the treatment. Experimental Group received the treatment which was apply-ing different layers of speaking tasks according to learners’ level of fluency and accuracy. Control group received ordinal treatment of speaking classrooms. The materials for this study consisted of 11 English movies for each session, voice-recorder device, and IELTS oral proficiency tests as well as two interviews based on Ur’s oral scale for measuring fluen-cy and accuracy. The treatment was run for 12 sessions in six weeks. At the end of the treatment, all the students both in experimental and control group were given a post-test interview based on Ur’s scale. To compare and contrast the amount of progress of the learners in different groups the results of the pre-test and post-test of speaking were analysed by using T-tests. Moreover, Multivariate analysis of variance was also used to check the hypotheses. Results showed that application of different layers of activity with regard to students’ level, led to a significantly superior performance in experimental group. Thus, this study verified the positive effect of implementation of different layers of activity and tasks to achieve progress in speaking skill. It can also help to create a less stressful at-mosphere of learning in which all the students will be given specific time to speak and lead them to be autonomous learners.

Keywords: differentiated instruction, learners’ style, multiple intelligence, speaking skill, task-based activities

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Authors: S. F. Wong, W. I. Ho, B. Lin, Q. Huang

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ERP has been used in many enterprises for management, the accuracy of the production forecasting module is vital to the decision making of the enterprise, and the profit is affected directly. Therefore, enhancing the accuracy of the production forecasting module can also increase the efficiency and profitability. To deal with a lot of data, a suitable, reliable and accurate statistics model is necessary. LSSVM and Grey System are two main models to be studied in this paper, and a case study is used to demonstrate how the combination model is effective to the result of forecasting.

Keywords: ERP, grey system, LSSVM, production forecasting

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Authors: Monika Rawat, Rahul Kumar

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Input output Buffer Information Specification (IBIS) models are used for describing the analog behavior of the Input Output (I/O) buffers of a digital device. They are widely used to perform signal integrity analysis. Advantages of using IBIS models include simple structure, IP protection and fast simulation time with reasonable accuracy. As design complexity of driver and receiver increases, capturing exact behavior from transistor level model into IBIS model becomes an essential task to achieve better accuracy. In this paper, an improvement in existing methodology of generating IBIS model for complex I/O interfaces such as Inter-Integrated Circuit (I2C) and Low Voltage Differential Signaling (LVDS) is proposed. Furthermore, the accuracy and computational performance of standard method and proposed approach with respect to SPICE are presented. The investigations will be useful to further improve the accuracy of IBIS models and to enhance their wider acceptance.

Keywords: IBIS, signal integrity, open-drain buffer, low voltage differential signaling, behavior modelling, transient simulation

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

Procedia PDF Downloads 132

Authors: Ahmad H. Abdelgwad, Galal E. Nadim, Tarek M. Said, Amr M. Gody

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The prime objective of this manuscript is to provide intensive review of the techniques used for permittivity measurements. The measurement techniques, relevant for any desired application, rely on the nature of the measured dielectric material, both electrically and physically, the degree of accuracy required, and the frequency of interest. Regardless of the way that distinctive sorts of instruments can be utilized, measuring devices that provide reliable determinations of the required electrical properties including the obscure material in the frequency range of interest can be considered. The challenge in making precise dielectric property or permittivity measurements is in designing of the material specimen holder for those measurements (RF and MW frequency ranges) and adequately modeling the circuit for reliable computation of the permittivity from the electrical measurements. If the RF circuit parameters such as the impedance or admittance are estimated appropriately at a certain frequency, the material’s permittivity at this frequency can be estimated by the equations which relate the way in which the dielectric properties of the material affect on the parameters of the circuit.

Keywords: dielectric permittivity, free space measurement, waveguide techniques, coaxial probe, cavity resonator

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Authors: Nofiu A. Musa, Olubola Babalola

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The study explored the effect of ICT on the accuracy of Preliminary Cost Estimates (PCEs) prepared by quantity surveying consulting firms in Nigeria for building projects, with a view to determining the desirability of the adoption and use of the technological innovation for preliminary estimating. Thus, data pertinent to the study were obtained through questionnaire survey conducted on a sample of one hundred and eight (108) quantity surveying firms selected from the list of registered firms compiled by the Nigerian Institute of Quantity Surveyors (NIQS), Lagos State Chapter through systematic random sampling. The data obtained were analyzed with SPSS version 17 using student’s t-tests at 5% significance level. The results obtained revealed that the mean bias and co-efficient of variation of the PCEs of the firms are significantly less at post ICT adoption period than the pre ICT adoption period, F < 0.05 in each case. The paper concluded that the adoption and use of the Technological Innovation (ICT) has significantly improved the accuracy of the Preliminary Cost Estimates (PCEs) of building projects, hence, it is desirable.

Keywords: accepted tender price, accuracy, bias, building projects, consistency, information and communications technology, preliminary cost estimates

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Authors: Mohamed Elhosieny Aly Ismail

Abstract:

The paper illustrates the total voltage and current harmonic distortion impact caused by fast-charging an electric bus and maintaining standard limit compliance. Measuring the current harmonic level in the range of 2 kHz-9 kHz. Also, the impact of the total demand distortions current caused by fast charger electric bus on the utility by measuring at the point of common coupling and comparing the measurement with IEEE519 -2014 standard. The results show that the total harmonic current distortion for the charger is within the limits of IEC 61000-3-12 and the fifth harmonic current was the most dominant frequency then the seventh harmonic current. The harmonic current in the range of 2 kHz- 9 kHz shows the frequency 5.1kHz is the most dominant frequency.

Keywords: electric vehicle, total harmonic distortion, IEEE519-2014, IEC 61000-3-12, super harmonic distortion

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

Abstract:

Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

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Authors: Mohit Taneja, Ravi Kiran, S. C. Bose

Abstract:

Entrepreneurs’ role in achieving Sustainable development goals is crucial as the growth potential of any region depends upon the number and the success rate of entrepreneurial firms. This paper is an effort to examine the relationship between Sustainable growth (SG) with Entrepreneurial attitude (EA) and Entrepreneurial intention (EI) in the context of the Indian economy. The mediation effect of EI between EA and SG has been considered. Partial least square (PLS) –Structural Equation Model (SEM) software was used to design the framework. Students enrolled in entrepreneurship courses of higher educational institutes (HEI) of Punjab, Haryana, and the National Capital Region NCR were contacted for data collection. The National Institutional Ranking Framework (NIRF) framework was used in selecting HEIs and data collected from 589 students was considered for analysis. McGee’s multi-dimensional scale for measuring ESE and the scale of Linan & Chen for measuring EI & ES (SG) was used. Results highlight that EA has a strong impact on EI (p≤ 0.001) and EI has a positive and strong relationship with SG (ES) as β value for the same is 0.683 (p≤ 0.001). The current study also reflects the mediating effect of EI among EA and ES, as the results show that the combined β value of both EA and EI (i.e.0.684*0.683= 0.467) is more than the direct influence of EA on ES (β=0.265). EA, with the mediating effect of EI can enhance the opportunity for achieving SG, which suggests that in order to increase the venture success rate and to attain SG, emphasis should be given to EI along with EA. The study has been investigated in three regions of India. Future studies can be extended to other South Asian countries for generalization.

Keywords: entrepreneurship, sustainable growth, entrepreneurship intention, entrepreneurship attitude

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Authors: Md Abdullah Al Mashud, M. Tariquzzaman, M. Jahangir Alam, Tapan Kumar Godder, M. Mahbubur Rahman

Abstract:

This paper presents a Monte Carlo (MC) method-based dose distributions on lung tumor for 6 MV photon beam to improve the dosimetric accuracy for cancer treatment. The polystyrene which is tissue equivalent material to the lung tumor density is used in this research. In the empirical calculations, TRS-398 formalism of IAEA has been used, and the setup was made according to the ICRU recommendations. The research outcomes were compared with the state-of-the-art experimental results. From the experimental results, it is observed that the proposed based approach provides more accurate results and improves the accuracy than the existing approaches. The average %variation between measured and TPS simulated values was obtained 1.337±0.531, which shows a substantial improvement comparing with the state-of-the-art technology.

Keywords: lung tumour, Monte Carlo, polystyrene, Elekta synergy, Monaco planning system

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Authors: F. Viprey, H. Nouira, S. Lavernhe, C. Tournier

Abstract:

Manufacturing of freeform parts may be achieved on 5-axis machine tools currently considered as a common means of production. In particular, the geometrical quality of the freeform parts depends on the accuracy of the multi-axis structural loop, which is composed of several component assemblies maintaining the relative positioning between the tool and the workpiece. Therefore, to reach high quality of the geometries of the freeform parts the geometric errors of the 5 axis machine should be evaluated and compensated, which leads one to master the deviations between the tool and the workpiece (volumetric accuracy). In this study, a novel hole-bar design was developed and used for the characterization of the geometric errors of a RRTTT 5-axis machine tool. The hole-bar standard design is made of Invar material, selected since it is less sensitive to thermal drift. The proposed design allows once to extract 3 intrinsic parameters: one linear positioning and two straightnesses. These parameters can be obtained by measuring the cylindricity of 12 holes (bores) and 11 cylinders located on a perpendicular plane. By mathematical analysis, twelve 3D points coordinates can be identified and correspond to the intersection of each hole axis with the least square plane passing through two perpendicular neighbour cylinders axes. The hole-bar was calibrated using a precision CMM at LNE traceable the SI meter definition. The reversal technique was applied in order to separate the error forms of the hole bar from the motion errors of the mechanical guiding systems. An inter-comparison was additionally conducted between four NMIs (National Metrology Institutes) within the EMRP IND62: JRP-TIM project. Afterwards, the hole-bar was integrated in RRTTT 5-axis machine tool to identify its volumetric errors. Measurements were carried out in real time and combine raw data acquired by the Renishaw RMP600 touch probe and the linear and rotary encoders. The geometric errors of the 5 axis machine were also evaluated by an accurate laser tracer interferometer system. The results were compared to those obtained with the hole bar.

Keywords: volumetric errors, CMM, 3D hole-bar, inter-comparison

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Authors: Tomiwa, Akinyemi Clement

Abstract:

Tropical regions experience diverse and complex precipitation patterns, posing significant challenges for accurate rainfall estimation and forecasting. This study addresses the problem of effectively classifying tropical rain types and refining the Z-R (Reflectivity-Rain Rate) relationship to enhance rainfall estimation accuracy. Through a combination of remote sensing, meteorological analysis, and machine learning, the research aims to develop an advanced classification framework capable of distinguishing between different types of tropical rain based on their unique characteristics. This involves utilizing high-resolution satellite imagery, radar data, and atmospheric parameters to categorize precipitation events into distinct classes, providing a comprehensive understanding of tropical rain systems. Additionally, the study seeks to improve the Z-R relationship, a crucial aspect of rainfall estimation. One year of rainfall data was analyzed using a Micro Rain Radar (MRR) located at The Federal University of Technology Akure, Nigeria, measuring rainfall parameters from ground level to a height of 4.8 km with a vertical resolution of 0.16 km. Rain rates were classified into low (stratiform) and high (convective) based on various microstructural attributes such as rain rates, liquid water content, Drop Size Distribution (DSD), average fall speed of the drops, and radar reflectivity. By integrating diverse datasets and employing advanced statistical techniques, the study aims to enhance the precision of Z-R models, offering a more reliable means of estimating rainfall rates from radar reflectivity data. This refined Z-R relationship holds significant potential for improving our understanding of tropical rain systems and enhancing forecasting accuracy in regions prone to heavy precipitation.

Keywords: remote sensing, precipitation, drop size distribution, micro rain radar

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