Search results for: estimating cyclone intensity

Authors: Jui-Teng Liao

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The selected-response (SR) format has been commonly adopted to assess academic reading in both formal and informal testing (i.e., standardized assessment and classroom assessment) because of its strengths in content validity, construct validity, as well as scoring objectivity and efficiency. When developing a second language (L2) reading test, researchers indicate that the longer the test (e.g., more test items) is, the higher reliability and validity the test is likely to produce. However, previous studies have not provided specific guidelines regarding the optimal length of a test or the most suitable number of test items or reading passages. Additionally, reading tests often include different question types (e.g., factual, vocabulary, inferential) that require varying degrees of reading comprehension and cognitive processes. Therefore, it is important to investigate the impact of question types on the number of items in relation to the score reliability of L2 reading tests. Given the popularity of the SR question format and its impact on assessment results on teaching and learning, it is necessary to investigate the degree to which such a question format can reliably measure learners’ L2 reading comprehension. The present study, therefore, adopted the generalizability (G) theory to investigate the score reliability of the SR format in L2 reading tests focusing on how many test items a reading test should include. Specifically, this study aimed to investigate the interaction between question types and the number of items, providing insights into the appropriate item count for different types of questions. G theory is a comprehensive statistical framework used for estimating the score reliability of tests and validating their results. Data were collected from 108 English as a second language student who completed an English reading test comprising factual, vocabulary, and inferential questions in the SR format. The computer program mGENOVA was utilized to analyze the data using multivariate designs (i.e., scenarios). Based on the results of G theory analyses, the findings indicated that the number of test items had a critical impact on the score reliability of an L2 reading test. Furthermore, the findings revealed that different types of reading questions required varying numbers of test items for reliable assessment of learners’ L2 reading proficiency. Further implications for teaching practice and classroom-based assessments are discussed.

Keywords: second language reading assessment, validity and reliability, Generalizability theory, Academic reading, Question format

Procedia PDF Downloads 88

Authors: Johnson Adafin, James O. B. Rotimi, Suzanne Wilkinson, Abimbola O. Windapo

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An aspect of client expenditure management that requires attention is the level of accuracy achievable in design-stage elemental cost planning. This has been a major concern for construction clients and practitioners in New Zealand (NZ). Pre-tender estimating inaccuracies are significantly influenced by the level of risk information available to estimators. Proper cost planning activities should ensure the production of a project’s likely construction costs (initial and final), and subsequent cost control activities should prevent unpleasant consequences of cost overruns, disputes and project abandonment. If risks were properly identified and priced at the design stage, observed variance between design-stage elemental cost plans (ECPs) and final tender sums (FTS) (initial contract sums) could be reduced. This study investigates the variations between design-stage ECPs and FTS of construction projects, with a view to identifying risk factors that are responsible for the observed variance. Data were sourced through interviews, and risk factors were identified by using thematic analysis. Access was obtained to project files from the records of study participants (consultant quantity surveyors), and document analysis was employed in complementing the responses from the interviews. Study findings revealed the discrepancies between ECPs and FTS in the region of -14% and +16%. It is opined in this study that the identified risk factors were responsible for the variability observed. The values obtained from the analysis would enable greater accuracy in the forecast of FTS by Quantity Surveyors. Further, whilst inherent risks in construction project developments are observed globally, these findings have important ramifications for construction projects by expanding existing knowledge on what is needed for reasonable budgetary performance and successful delivery of construction projects. The findings contribute significantly to the study by providing quantitative confirmation to justify the theoretical conclusions generated in the literature from around the world. This therefore adds to and consolidates existing knowledge.

Keywords: accuracy, design-stage, elemental cost plan, final tender sum

Procedia PDF Downloads 268

Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

Procedia PDF Downloads 335

Authors: Sunday B. Alabi, Edikan P. Felix, Aniediong M. Umo

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Crystal size distribution is of great importance in the sugar factories. It determines the market value of granulated sugar and also influences the cost of production of sugar crystals. Typically, sugar is produced using fed-batch vacuum evaporative crystallizer. The crystallization quality is examined by crystal size distribution at the end of the process which is quantified by two parameters: the average crystal size of the distribution in the mean aperture (MA) and the width of the distribution of the coefficient of variation (CV). Lack of real-time measurement of the sugar crystal size hinders its feedback control and eventual optimisation of the crystallization process. An attractive alternative is to use a soft sensor (model-based method) for online estimation of the sugar crystal size. Unfortunately, the available models for sugar crystallization process are not suitable as they do not contain variables that can be measured easily online. The main contribution of this paper is the development of a regression model for estimating the sugar crystal size as a function of input variables which are easy to measure online. This has the potential to provide real-time estimates of crystal size for its effective feedback control. Using 7 input variables namely: initial crystal size (Lo), temperature (T), vacuum pressure (P), feed flowrate (Ff), steam flowrate (Fs), initial super-saturation (S0) and crystallization time (t), preliminary studies were carried out using Minitab 14 statistical software. Based on the existing sugar crystallizer models, and the typical ranges of these 7 input variables, 128 datasets were obtained from a 2-level factorial experimental design. These datasets were used to obtain a simple but online-implementable 6-input crystal size model. It seems the initial crystal size (Lₒ) does not play a significant role. The goodness of the resulting regression model was evaluated. The coefficient of determination, R² was obtained as 0.994, and the maximum absolute relative error (MARE) was obtained as 4.6%. The high R² (~1.0) and the reasonably low MARE values are an indication that the model is able to predict sugar crystal size accurately as a function of the 6 easy-to-measure online variables. Thus, the model can be used as a soft sensor to provide real-time estimates of sugar crystal size during sugar crystallization process in a fed-batch vacuum evaporative crystallizer.

Keywords: crystal size, regression model, soft sensor, sugar, vacuum evaporative crystallizer

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Authors: Yousef Abdulaziz Almolhem

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Geographically, the most Arabic countries locate in areas confined to arid or semiarid regions. For this reason, most of our countries have adopted the seawater desalination as a strategy to overcome this problem. For example, the water supply of AUE, Kuwait, and Saudi Arabia is almost 100% from the seawater desalination plants. Many areas in Saudia Arabia and other countries in the world suffer from lack of fresh water which hinders the development of these areas, despite the availability of saline water and high solar radiation intensity. Furthermore, most developing countries do not have sufficient meteorological data to evaluate if the solar radiation is enough to meet the solar desalination. A mathematical model was developed to simulate and predict the thermal behavior of the solar still which used direct solar energy for distillation of seawater. Measurement data were measured in the Environment and Natural Resources Department, Faculty of Agricultural and Food sciences, King Faisal University, Saudi Arabia, in order to evaluate the present model. The simulation results obtained from this model were compared with the measured data. The main results of this research showed that there are slight differences between the measured and predicted values of the elements studied, which is resultant from the change of some factors considered constants in the model such as the sky clearance, wind velocity and the salt concentration in the water in the basin of the solar still. It can be concluded that the present model can be used to estimate the average total solar radiation and the thermal behavior of the solar still in any area with consideration to the geographical location.

Keywords: mathematical model, sea water, distillation, solar radiation

Procedia PDF Downloads 283

Authors: Badriah Alayidi, Emad Alyahya

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Background: Most people with Multiple Sclerosis (MS) report worsening balance as the condition progresses. Poor balance control is also well known to be a significant risk factor for both falling and fear of falling. The increased risk of falls with disease progression thus makes balance control an essential target of gait rehabilitation amongst people with MS. Intervention programs have developed various methods to improve balance control, and accumulating evidence suggests that exercise programs may help people with MS improve their balance. Among these methods, virtual reality (VR) is growing in popularity as a balance-training technique owing to its potential benefits, including better compliance and greater user happiness. However, it is not clear if a VR environment will induce different balance control mechanisms in MS as compared to healthy individuals or traditional environments. Therefore, this study aims to examine how individuals with MS control their balance in a VR setting. Methodology: The proposed study takes an empirical approach to estimate and determine the role of balance response in persons with MS using a VR environment. It will use primary data collected through patient observations, physiological and biomechanical evaluation of balance, and data analysis. Results: The preliminary systematic review and meta-analysis indicated that there was variability in terms of the outcome assessing balance response in people with MS. The preliminary results of these assessments have the potential to provide essential indicators of the progression of MS and contribute to the individualization of treatment and evaluation of the interventions’ effectiveness. The literature describes patients who have had the opportunity to experiment in VR settings and then used what they have learned in the real world, suggesting that this VR setting could be more appealing than conditional settings. The findings of the proposed study will be beneficial in estimating and determining the effect of VR on balance control in persons with MS. In previous studies, VR was shown to be an interesting approach to neurological rehabilitation, but more data are needed to support this approach in MS. Conclusions: The proposed study enables an assessment of balance and evaluations of a variety of physiological implications related to neural activity as well as biomechanical implications related to movement analysis.

Keywords: multiple sclerosis, virtual reality, postural control, balance

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Authors: Ivannys Cappas Perez

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Worldwide the population of older adults is increasing. The World Health Organization (2022) estimates that it will double by 2050. Informal caregivers of older adults may experience contradictory impulses, overload, and multiple losses before the death of the older adult in their care. The general purpose of research was to identify and describe the affective ambivalence in informal caregivers of older adults in the face of loss and grief processes. The dimensions under study were affective ambivalence, informal caregivers of older adults, loss processes and the grieving process. A qualitative approach methodology and an empirical phenomenological design were used through Clark Moustakas' Multiangulation Model to describe, categorize and interpret, intentionality, temporality and intersubjectivity a problem never studied. Among the findings was the feminization of the role. Affective ambivalence is manifested through emotions, feelings, thoughts and behavior, including non-verbal language. The assumption of the role is highly influenced by an affective and moral factor, where a minimum of 35 hours per week are invested in without family and financial support. It was found that the participants experience objective and subjective overload. Furthermore, because of the role, they experienced loss of life, loss of aspects of themselves, loss of objects, emotional losses, and losses linked to development. On the other hand, up to two types of grief were found simultaneously. Finally, the presence of affective ambivalence was found with the same intensity 13 years after the loss of the older adult under care.

Keywords: affective ambivalence, informal caregivers of older adults, loss processes, grief processes

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Authors: Bahareh Montakhabi

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Earthquake is known as one of the deadliest natural disasters, with a high potential for damage to life and property. Some of Iran's cities were completely destroyed after major earthquakes, and the people of the region suffered a lot of mental, financial and psychological damage. Tehran is one of the cities located on the fault line. According to experts, the only city that could be severely damaged by a moderate earthquake in Earthquake Engineering Intensity Scale (EEIS) (70% destruction) is Tehran because Tehran is built precisely on the fault. Seismic risk assessment (SRA) of cities in the scale of urban areas and neighborhoods is the first phase of the earthquake crisis management process, which can provide the information required to make optimal use of available resources and facilities in order to reduce the destructive effects and consequences of an earthquake. This study has investigated strategies to promote safety and reduce the vulnerability of worn-out urban textures in the District 12 of Tehran to the potential risk of earthquake aimed at prioritizing the factors affecting the vulnerability of worn-out urban textures to earthquake crises and how to reduce them, using the analytical-exploratory method, analytical hierarchy process (AHP), Expert choice and SWOT technique. The results of SWAT and AHP analysis of the vulnerability of the worn-out textures of District 12 to internal threats (1.70) and external threats (2.40) indicate weak safety of the textures of District 12 regarding internal and external factors and a high possibility of damage.

Keywords: risk management, vulnerability, worn-out textures, earthquake

Procedia PDF Downloads 193

Authors: V.Barbakadze, L.Gogilashvili, L.Amiranashvili, M.Merlani, K.Mulkijanyan

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The high-molecular fractions from the several species of two genera (Symphytum and Anchusa) of Boraginaceae family Symphytum asperum, S. caucasicum, S. officinale, and Anchusa italica were isolated. According to IR, 13C and 1H NMR, 2D heteronuclear 1H/13C HSQC spectral data and 1D NOE experiment, the main structural element of these preparations was found to be a regularly substituted polyoxyethylene, namely poly[3-(3,4-dihydroxyenyl)glyceric acid] (PDPGA) or poly[oxy-1-carboxy-2-(3,4-dihydroxyphenyl)ethylene]. Such caffeic acid-derived biopolymer to our knowledge has not been known and has been identified for the first time. This compound represents a new class of natural polyethers with a residue of 3-(3,4-dihydroxyphenyl)glyceric acid as the repeating unit. Most of the carboxylic groups of PDPGA from A. italica unlike the polymer of S. asperum, S. caucasicum, and S. officinale are methylated. The 2D DOSY experiment gave the similar diffusion coefficient for the methylated and non-methylated signals of A. italica PDPGA. Both sets of signals fell in the same horizontal. This would imply a similar molecular weight for methylated and non-methylated polymers. This was further evidenced by graphic representations of the intensity decay of the 1H signals of aromatic H-2″ and H-1 at δ 7.16 and 5.24 and that of the methoxy group at δ 3.85. These three signals essentially showed the same curve shape. According to results of in vitro and in vivo experiments PDPGA of S.asperum and S.caucasicum could be considered as potential anti-inflammatory, wound healing and anti-cancer therapeutic agent.

Keywords: caffeic acid-derived polyether, poly[3-(3, 4-dihydroxyphenyl)glyceric acid], poly[oxy-1-carboxy-2-(3, 4-dihydroxyphenyl)ethylene], symphytum, anchusa

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

Procedia PDF Downloads 340

Authors: Hong Nguyen Thi Hai, Ryota Konda, Dat Kieu Tuan, Cao Tran Thanh, Khang Phung Van, Hau Tran Tin, Harry Wu

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Melaleuca cajuputi is a moderately fast-growing species and considered as a multi-purpose tree as it provides fuelwood, piles and frame poles in construction, leaf essential oil and honey. It occurs in Australia, Papua New Guinea, and South-East Asia. M. cajuputi plantation can be harvested on 6-7 year rotations for wood products. Its timber can also be used for pulp and paper, fiber and particle board, producing quality charcoal and potentially sawn timber. However, most reported M. cajuputi breeding programs have been focused on oil production rather than wood production. In this study, breeding program of M. cajuputi aimed to improve wood production was examined by estimating genetic parameters for growth (tree height, diameter at breast height (DBH), and volume), stem form, stiffness (modulus of elasticity (MOE)), bark thickness and bark ratio in a half-sib family progeny trial including 80 families in the Mekong Delta of Vietnam. MOE is one of the key wood properties of interest to the wood industry. Non-destructive wood stiffness was measured indirectly by acoustic velocity using FAKOPP Microsecond Timer and especially unaffected by bark mass. Narrow-sense heritability for the seven traits ranged from 0.13 to 0.27 at age 7 years. MOE and stem form had positive genetic correlations with growth while the negative correlation between bark ratio and growth was also favorable. Breeding for simultaneous improvement of multiple traits, faster growth with higher MOE and reduction of bark ratio should be possible in M. cajuputi. Index selection based on volume and MOE showed genetic gains of 31 % in volume, 6 % in MOE and 13 % in stem form. In addition, heritability and age-age genetic correlations for growth traits increased with time and optimal early selection age for growth of M. cajuputi based on DBH alone was 4 years. Selected thinning resulted in an increase of heritability due to considerable reduction of phenotypic variation but little effect on genetic variation.

Keywords: acoustic velocity, age-age correlation, bark thickness, heritability, Melaleuca cajuputi, stiffness, thinning effect

Procedia PDF Downloads 182

Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

Procedia PDF Downloads 160

Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

Procedia PDF Downloads 275

Authors: Benzerara Mohammed, Redjel Bachir, Kebaili Bachir

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The cracking of the concrete is a more crucial problem with the development of the complex structures related to technological progress. The projections in the knowledge of the breaking process make it possible today for better prevention of the risk of the fracture. The breaking strength brutal of a quasi-fragile material like the concrete called Toughness, is measured by a breaking value of the factor of intensity of the constraints K1C for which the crack is propagated, it is an intrinsic property of material. Many studies reported in the literature treating of the concrete were carried out on specimens which are in fact inadequate compared to the intrinsic characteristic to identify. We started from this established fact, in order to compare the evolution of the parameter of toughness K1C measured by calling upon ordinary concrete specimens of three prismatics geometries different (10*10*84) cm³ and (5*20*120) cm³ &(12*20*120) cm³ containing from the side notches various depths simulating of the cracks was set up. The notches are carried out using triangular pyramidal plates into manufactured out of sheet coated placed at the centre of the specimens at the time of the casting, then withdrawn to leave the trace of a crack. The tests are carried out in 3 points bending test in mode 1 of fracture, by using the techniques of mechanical fracture. The evolution of the parameter of toughness K1C measured with the three geometries specimens gives almost the same results. They are acceptable and return in the beach of the results determined by various researchers (toughness of the ordinary concrete turns to the turn of the 1 MPa √m). These results inform us about the presence of an economy on the level of the geometrie specimen (5*20*120) cm³, therefore to use plates specimens later if one wants to master the toughness of this material complexes, astonishing but always essential that is the concrete.

Keywords: elementary representative volume, concrete, fissure, toughness

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Authors: Dinesh Pathaka, Tomas Wagnera, J. M. Nunzib

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We investigated blends of MdPVV.PCBM.AIS for photovoltaic application. AgInSe2 powder was synthesized by sealing and heating the stoichiometric constituents in evacuated quartz tube ampule. Fine grinded AIS powder was dispersed in MD-MOPVV and PCBM with and without surfactant. Different concentrations of these particles were suspended in the polymer solutions and spin casted onto ITO glass. Morphological studies have been performed by atomic force microscopy and optical microscopy. The blend layers were also investigated by various techniques like XRD, UV-VIS optical spectroscopy, AFM, PL, after a series of various optimizations with polymers/concentration/deposition/ suspension/surfactants etc. XRD investigation of blend layers shows clear evidence of AIS dispersion in polymers. Diode behavior and cell parameters also revealed it. Bulk heterojunction hybrid photovoltaic device Ag/MoO3/MdPVV.PCBM.AIS/ZnO/ITO was fabricated and tested with standard solar simulator and device characterization system. The best performance and photovoltaic parameters we obtained was an open-circuit voltage of about Voc 0.54 V and a photocurrent of Isc 117 micro A and an efficiency of 0.2 percent using a white light illumination intensity of 23 mW/cm2. Our results are encouraging for further research on the fourth generation inorganic organic hybrid bulk heterojunction photovoltaics for energy. More optimization with spinning rate/thickness/solvents/deposition rates for active layers etc. need to be explored for improved photovoltaic response of these bulk heterojunction devices.

Keywords: thin films, photovoltaic, hybrid systems, heterojunction

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Authors: Anton S. Perin, Vladimir M. Shandarov

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Compensation for the nonlinear diffraction of narrow laser beams with wavelength of 532 and the formation of photonic waveguides and waveguide circuits due to the contribution of pyroelectric effect to the nonlinear response of lithium niobate crystal have been experimentally demonstrated. Complete compensation for the linear and nonlinear diffraction broadening of light beams is obtained upon uniform heating of an undoped sample from room temperature to 55 degrees Celsius. An analysis of the light-field distribution patterns and the corresponding intensity distribution profiles allowed us to estimate the spacing for the channel waveguides. The observed behavior of bright soliton beams may be caused by their coherent interaction, which manifests itself in repulsion for anti-phase light fields and in attraction for in-phase light fields. The experimental results of this study showed a fundamental possibility of forming optically complex waveguide structures in lithium niobate crystals with pyroelectric mechanism of nonlinear response. The topology of these structures is determined by the light field distribution on the input face of crystalline sample. The optical induction of channel waveguide elements by interacting spatial solitons makes it possible to design optical systems with a more complex topology and a possibility of their dynamic reconfiguration.

Keywords: self-action, soliton, lithium niobate, piroliton, photorefractive effect, pyroelectric effect

Procedia PDF Downloads 167

Authors: Hendradi Hardhienata, Tony Sumaryada, Sri Setyaningsih

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Current progress in the field of nonlinear optics has enabled precise surface characterization in semiconductor materials. Nonlinear optical techniques are favorable due to their nondestructive measurement and ability to work in nonvacuum and ambient conditions. The advance of the bond hyperpolarizability models opens a wide range of nanoscale surface investigation including the possibility to detect molecular orientation at the surface of silicon and zincblende semiconductors, investigation of electric field induced second harmonic fields at the semiconductor interface, detection of surface impurities, and very recently, study surface defects such as twin boundary in wurtzite semiconductors. In this work, we show using nonlinear optical techniques, e.g. nonlinear bond models how arbitrary polarization of the incoming electric field in Rotational Anisotropy Spectroscopy experiments can provide more information regarding the origin of the nonlinear sources in zincblende and wurtzite semiconductor structure. In addition, using hyperpolarizability consideration, we describe how the nonlinear susceptibility tensor describing SHG can be well modelled using only few parameter because of the symmetry of the bonds. We also show how the third harmonic intensity feature shows considerable changes when the incoming field polarization angle is changed from s-polarized to p-polarized. We also propose a method how to investigate surface reconstruction and defects in wurtzite and zincblende structure at the nanoscale level.

Keywords: surface characterization, bond model, rotational anisotropy spectroscopy, effective hyperpolarizability

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Iin Mayasari

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This study aims at exploring the influence of aspects of entrepreneurial marketing on a firm’s performance. Entrepreneurs are not only supported by resources control to obtain sustainable competitive advantage, but it should also be supported by intangible resources. Entrepreneurial marketing provides the opportunity for entrepreneurs to proactively find better ways to create value for desired customers, to create innovation, and to build customer equity. Entrepreneurial marketing has the medium between entrepreneurship and marketing, and serves as an umbrella for many of the emergent perspectives on marketing. It has eight underlying dimensions. They are proactiveness, calculated risk-taking, innovativeness, an opportunity focus, entrepreneurial orientation, resource leveraging, customer intensity, and value creating. The research method of the study was a qualitative study by having an interview with 8 small companies in Kudus Region, the Central Java, Indonesia. The interviewees were the owner and the manager of the company that had the scope work of small business enterprise in wood crafting industry. The interview was related to the implementation of the elements of the entrepreneurial marketing. The result showed that the small business enterprises had implemented the elements of entrepreneurial marketing in supporting their daily activities. The understanding based on the theoretical implementation was well executed by the owner and managers. The problems in managing small business enterprises were related to the full support by the government and the branding management. Furthermore, the innovation process should be improved especially the use of internet to promote the product, to expand the market and to increase the firm’s performance.

Keywords: entrepreneurial marketing, innovativeness, risk taking, opportunity focus

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Authors: Nermin Isik, Ozlem Derinbay Ekici

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The cat is one of the potential hosts for parasitic zoonoses, such as Toxocara cati, Ancylostoma braziliense, A. tubaeforme, Uncinaria stenocephala, Cryptosporidium sp, Giardia sp. This study was performed to determine the prevalence and intensity of intestinal parasites in household cats in Konya, Turkey. In this study, a total of 100 stool samples with different ages and sex were used as a material. They were examined for infections with endoparasites by the use of native, Fulleborn flotation and Benedek sedimentation methods in University of Selcuk, Faculty of Veterinary Medicine, Department of Parasitology. The overall prevalence of intestinal parasites was 15%. A total of 6 parasite species was recorded: Giardia sp (6%), Toxocara cati (4%), Isospora sp (3%), Joyeuxiella pasqualei, Taenia sp (1%), Trichuris sp (1%). The most common intestinal parasites in cats were Giardia sp (6%) and Toxocara cati (4%). Younger cats up to 1 year of age were more frequently infected with endoparasites than animals over 1 year of age (p < 0.05). Giardia sp and Toxocara cati were detected significantly more often in younger than 1 year of age (p < 0.05). In fecal examination, Toxocara cati, Ancylostoma sp. Joyeuxiella pasqualei, Dipylidium caninum, Trichuris sp were found in cats in Turkey. In this study, based on microscopic and macroscopic fecal examinations, Giardia sp (6%), Toxocara cati (4%), Isospora sp (3%), Joyeuxiella pasqualei (%2), Taenia sp (1%), Trichuris sp (1%) was detected in cats. In conclusion, zoonotic intestinal parasites in household cats such as Giardia sp and Toxocara cati should be considered more seriously and it is necessary to take precautions against these infections. Cats should be routinely checked by faecal examination for endoparasite infections.

Keywords: cat, intestinal parasites, faecal, Turkey

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Authors: Lucy Patricia Onundo, Wilfred Njoroge Mwema

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The tidal power potential available for electricity generation from Mombasa and Lamu sites in Kenya will be examined. Several African countries in the Western Indian Ocean endure insufficiencies in the power sector, including both generation and distribution. One important step towards increasing energy security and availability is to intensify the use of renewable energy sources. The access to cost-efficient hydropower is low in Mombasa and Lamu hence Ocean energy will play an important role. Global-Level resource assessments and oceanographic literature and data have been compiled in an analysis between technology-specific requirements for ocean energy technologies (salinity, tide, tidal current, wave, Ocean thermal energy conversion, wind and solar) and the physical resources in Lamu and Mombasa. The potential for tide and tidal current power is more restricted but may be of interest at some locations. The theoretical maximum power produced over a tidal cycle is determined by the product of the forcing tide and the undisturbed volumetric flow-rate. The extraction of the maximum power reduces the flow-rate, but a significant portion of the maximum power can be extracted with little change to the tidal dynamics. Two-dimensional finite-element, numerical simulations designed and developed agree with the theory. Temporal variations in resource intensity, as well as the differences between small-scale and large-scale applications, are considered.

Keywords: energy assessment, marine tidal power, renewable energy, tidal dynamics

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Authors: S. Shankar Bharathi

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Inspection of surface defects on metallic components has always been challenging due to its specular property. Occurrences of defects such as scratches, rust, pitting are very common in metallic surfaces during the manufacturing process. These defects if unchecked can hamper the performance and reduce the life time of such component. Many of the conventional image processing algorithms in detecting the surface defects generally involve segmentation techniques, based on thresholding, edge detection, watershed segmentation and textural segmentation. They later employ other suitable algorithms based on morphology, region growing, shape analysis, neural networks for classification purpose. In this paper the work has been focused only towards detecting scratches. Global and other thresholding techniques were used to extract the defects, but it proved to be inaccurate in extracting the defects alone. However, this paper does not focus on comparison of different segmentation techniques, but rather describes a novel approach towards segmentation combined with hausdorff dilation distance. The proposed algorithm is based on the distribution of the intensity levels, that is, whether a certain gray level is concentrated or evenly distributed. The algorithm is based on extraction of such concentrated pixels. Defective images showed higher level of concentration of some gray level, whereas in non-defective image, there seemed to be no concentration, but were evenly distributed. This formed the basis in detecting the defects in the proposed algorithm. Hausdorff dilation distance based on mathematical morphology was used to strengthen the segmentation of the defects.

Keywords: metallic surface, scratches, segmentation, hausdorff dilation distance, machine vision

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Authors: Chiqian Zhang, Kyle D. McIntosh, Nathan Sienkiewicz, Ian Struewing, Erin A. Stelzer, Jennifer L. Graham, Jingrang Lu

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Phytoplankton plays an essential role in freshwater aquatic ecosystems and is the primary group synthesizing organic carbon and providing food sources or energy to ecosystems. Therefore, the identification and quantification of phytoplankton are important for estimating and assessing ecosystem productivity (carbon fixation), water quality, and eutrophication. Microscopy is the current gold standard for identifying and quantifying phytoplankton composition and abundance. However, microscopic analysis of phytoplankton is time-consuming, has a low sample throughput, and requires deep knowledge and rich experience in microbial morphology to implement. To improve this situation, quantitative polymerase chain reaction (qPCR) was considered for phytoplankton identification and quantification. Using qPCR to assess phytoplankton composition and abundance, however, has not been comprehensively evaluated. This study focused on: 1) conducting a comprehensive performance comparison of qPCR and microscopy techniques in identifying and quantifying phytoplankton and 2) examining the use of qPCR as a tool for assessing eutrophication. Twelve large rivers located throughout the United States were evaluated using data collected from 2017 to 2019 to understand the relation between qPCR-based phytoplankton abundance and eutrophication. This study revealed that temporal variation of phytoplankton abundance in the twelve rivers was limited within years (from late spring to late fall) and among different years (2017, 2018, and 2019). Midcontinent rivers had moderately greater phytoplankton abundance than eastern and western rivers, presumably because midcontinent rivers were more eutrophic. The study also showed that qPCR- and microscope-determined phytoplankton abundance had a significant positive linear correlation (adjusted R² 0.772, p-value < 0.001). In addition, phytoplankton abundance assessed via qPCR showed promise as an indicator of the eutrophication status of those rivers, with oligotrophic rivers having low phytoplankton abundance and eutrophic rivers having (relatively) high phytoplankton abundance. This study demonstrated that qPCR could serve as an alternative tool to traditional microscopy for phytoplankton quantification and eutrophication assessment in freshwater rivers.

Keywords: phytoplankton, eutrophication, river, qPCR, microscopy, spatiotemporal variation

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Authors: Arulselvi Subramanian, Albert Venencia, Sanjeev Bhoi

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Coagulopathy of trauma is an early endogenous coagulation abnormality that occurs shortly resulting in high mortality. In emergency trauma situations, viscoelastic tests may be better in identifying the various phenotypes of coagulopathy and demonstrate the contribution of platelet function to coagulation. We aimed to determine thrombin generation and clot strength, by estimating a ratio of Maximum amplitude and R-time (MA-R ratio) for identifying trauma coagulopathy and predicting subsequent mortality. Methods: We conducted a prospective cohort analysis of acutely injured trauma patients of the adult age groups (18- 50 years), admitted within 24hrs of injury, for one year at a Level I trauma center and followed up on 3rd day and 5th day of injury. Patients with h/o coagulation abnormalities, liver disease, renal impairment, with h/o intake of drugs were excluded. Thromboelastography was done and a ratio was calculated by dividing the MA by the R-time (MA-R). Patients were further stratified into sub groups based on the calculated MA-R quartiles. First sampling was done within 24 hours of injury; follow up on 3rd and 5thday of injury. Mortality was the primary outcome. Results: 100 acutely injured patients [average, 36.6±14.3 years; 94% male; injury severity score 12.2(9-32)] were included in the study. Median (min-max) on admission MA-R ratio was 15.01(0.4-88.4) which declined 11.7(2.2-61.8) on day three and slightly rose on day 5 13.1(0.06-68). There were no significant differences between sub groups in regard to age, or gender. In the lowest MA-R ratios subgroup; MA-R1 (<8.90; n = 27), injury severity score was significantly elevated. MA-R2 (8.91-15.0; n = 23), MA-R3 (15.01-19.30; n = 24) and MA-R4 (>19.3; n = 26) had no difference between their admission laboratory investigations, however slight decline was observed in hemoglobin, red blood cell count and platelet counts compared to the other subgroups. Also significantly prolonged R time, shortened alpha angle and MA were seen in MA-R1. Elevated incidence of mortality also significantly correlated with on admission low MA-R ratios (p 0.003). Temporal changes in the MA-R ratio did not correlated with mortality. Conclusion: The MA-R ratio provides a snapshot of early clot function, focusing specifically on thrombin burst and clot strength. In our observation, patients with the lowest MA-R time ratio (MA-R1) had significantly increased mortality compared with all other groups (45.5% MA-R1 compared with <25% in MA-R2 to MA-R3, and 9.1% in MA-R4; p < 0.003). Maximum amplitude and R-time may prove highly useful to predict at-risk patients early, when other physiologic indicators are absent.

Keywords: coagulopathy, trauma, thromboelastography, mortality

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Authors: Usama Shahid, Muhammad Zunnurain Hussain

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This research paper presents a comprehensive analysis of a sentiment analysis approach that employs valence and arousal as its foundational pillars, in comparison to traditional techniques. Sentiment analysis is an indispensable task in natural language processing that involves the extraction of opinions and emotions from textual data. The valence and arousal dimensions, representing the intensity and positivity/negativity of emotions, respectively, enable the creation of four quadrants, each representing a specific emotional state. The study seeks to determine the impact of utilizing these quadrants to identify distinct emotional states on the accuracy and efficiency of sentiment analysis, in comparison to traditional techniques. The results reveal that the valence and arousal-based approach outperforms other approaches, particularly in identifying nuanced emotions that may be missed by conventional methods. The study's findings are crucial for applications such as social media monitoring and market research, where the accurate classification of emotions and opinions is paramount. Overall, this research highlights the potential of using valence and arousal as a framework for sentiment analysis and offers invaluable insights into the benefits of incorporating specific types of emotions into the analysis. These findings have significant implications for researchers and practitioners in the field of natural language processing, as they provide a basis for the development of more accurate and effective sentiment analysis tools.

Keywords: sentiment analysis, valence and arousal, emotional states, natural language processing, machine learning, text analysis, sentiment classification, opinion mining

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Authors: Hammad T. Janjuhah, Josep Sanjuan, Mohamed K. Salah

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Biological and chemical activities in carbonates are responsible for the complexity of the pore system. Primary porosity is generally of natural origin while secondary porosity is subject to chemical reactivity through diagenetic processes. To understand the integrated part of hydrocarbon exploration, it is necessary to understand the carbonate pore system. However, the current porosity classification scheme is limited to adequately predict the petrophysical properties of different reservoirs having various origins and depositional environments. Rock classification provides a descriptive method for explaining the lithofacies but makes no significant contribution to the application of porosity and permeability (poro-perm) correlation. The Central Luconia carbonate system (Malaysia) represents a good example of pore complexity (in terms of nature and origin) mainly related to diagenetic processes which have altered the original reservoir. For quantitative analysis, 32 high-resolution images of each thin section were taken using transmitted light microscopy. The quantification of grains, matrix, cement, and macroporosity (pore types) was achieved using a petrographic analysis of thin sections and FESEM images. The point counting technique was used to estimate the amount of macroporosity from thin section, which was then subtracted from the total porosity to derive the microporosity. The quantitative observation of thin sections revealed that the mouldic porosity (macroporosity) is the dominant porosity type present, whereas the microporosity seems to correspond to a sum of 40 to 50% of the total porosity. It has been proven that these Miocene carbonates contain a significant amount of microporosity, which significantly complicates the estimation and production of hydrocarbons. Neglecting its impact can increase uncertainty about estimating hydrocarbon reserves. Due to the diversity of geological parameters, the application of existing porosity classifications does not allow a better understanding of the poro-perm relationship. However, the classification can be improved by including the pore types and pore structures where they can be divided into macro- and microporosity. Such studies of microporosity identification/classification represent now a major concern in limestone reservoirs around the world.

Keywords: overview of porosity classification, reservoir characterization, microporosity, carbonate reservoir

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Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

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In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

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Authors: R. Sarada Jayalakshmi Devi B. Bhaskar, S. Khayum Ahammed, T. N. V. K. V. Prasad

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Use of bioagents and biofungicides is safe to manage the plant diseases and to avoid human health hazards which improves food security. Myconanotechnology is the study of nanoparticles synthesis using fungi and their applications. The present work reports on preparation, characterization and antifungal activity of biogenic silver nanoparticles produced by the fungus Trichoderma sp. which was collected from groundnut rhizosphere. The culture filtrate of Trichoderma sp. was used for the reduction of silver ions (Ag+) in AgNO3 solution to the silver (Ag0) nanoparticles. The different ages (4 days, 6 days, 8 days, 12 days, and 15 days) of culture filtrates were screened for the synthesis of silver nanoparticles. Synthesized silver nanoparticles were characterized using UV-Vis spectrophotometer, particle size and zeta potential analyzer, Fourier Transform Infrared Spectrophotometer (FTIR) and Transmission Electron Microscopy. Among all the treatments the silver nitrate solution treated with six days aged culture filtrate of Trichoderma sp. showed the UV absorption peak at 440 nm with maximum intensity (0.59) after 24 hrs incubation. The TEM micrographs showed the spherical shaped silver nanoparticles with an average size of 30 nm. The antifungal activity of silver nanoparticles against Aspergillus niger causing collar rot disease in groundnut and aspergillosis in humans showed the highest per cent inhibition at 100 ppm concentration (74.8%). The results points to the usage of these mycogenic AgNPs in agriculture to control plant diseases.

Keywords: groundnut rhizosphere, Trichoderma sp., silver nanoparticles synthesis, antifungal activity

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Authors: Jagadish Rao Padubidri, Mehak Bhandary, Sowmya J. Rao

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Introduction: The significance of the human foot and its measurements in identifying an individual has been proved a lot of times by different studies in different geographical areas and its association to the stature and gender of the individual has been justified by many researches. In our study we have used different foot measurements including the length, width, malleol height and navicular height for establishing its association to stature and gender and to find out its accuracy. The purpose of this study is to show the relation of foot measurements with stature and gender, and to derive Multiple and Logistic regression equations for stature and gender estimation in South Indian population. Materials and Methods: The subjects for this study were 200 South Indian students out of which 100 were females and 100 were males, aged between 18 to 24 years. The data for the present study included the stature, foot length, foot breath, foot malleol height, foot navicular height of both right and left foot. Descriptive statistics, T-test and Pearson correlation coefficients were derived between stature, gender and foot measurements. The stature was estimated from right and left foot measurements for both male and female South Indian population using multiple regression analysis and logistic regression analysis for gender estimation. Results: The means, standard deviation, stature, right and left foot measurements and T-test in male population were higher than in females. LFL (Left foot length) is more than RFL (Right Foot length) in male groups, but in female groups the length of both foot are almost equal [RFL=226.6, LFL=227.1]. There is not much of difference in means of RFW (Right foot width) and LFW (Left foot width) in both the genders. Significant difference were seen in mean values of malleol and navicular height of right and left feet in male gender. No such difference was seen in female subjects. Conclusions: The study has successfully demonstrated the correlation of foot length in stature estimation in all the three study groups in both right and left foot. Next in parameters are Foot width and malleol height in estimating stature among male and female groups. Navicular height of both right and left foot showed poor relationship with stature estimation in both male and female groups. Multiple regression equations for both right and left foot measurements to estimate stature were derived with standard error ranging from 11-12 cm in males and 10-11 cm in females. The SEE was 5.8 when both male and female groups were pooled together. The logistic regression model which was derived to determine gender showed 85% accuracy and 92.5% accuracy using right and left foot measurements respectively. We believe that stature and gender can be estimated with foot measurements in South Indian population.

Keywords: foot length, gender, stature, South Indian

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