Search results for: type i error

Authors: George Mahalu

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The Chua diode has been configured over time in various ways, using electronic structures like operational amplifiers (AOs) or devices with gas or semiconductors. When discussing the use of semiconductor devices, tunnel diodes (Esaki diodes) are most often considered, and more recently, transistorized configurations such as lambda diodes. The paperwork proposed here uses in the modeling a lambda diode type configuration consisting of two junction field effect transistors (JFET). The original scheme is created in the MULTISIM electronic simulation environment and is analyzed in order to identify the conditions for the appearance of evolutionary unpredictability specific to nonlinear dynamic systems with chaos-induced behavior. The chaotic deterministic oscillator is one autonomous type, a fact that places it in the class of Chua’s type oscillators, the only significant and most important difference being the presence of a nonlinear device like the one mentioned structure above. The chaotic behavior is identified both by means of strange attractor-type trajectories and visible during the simulation and by highlighting the hypersensitivity of the system to small variations of one of the input parameters. The results obtained through simulation and the conclusions drawn are useful in the further research of ways to implement such constructive electronic solutions in theoretical and practical applications related to modern small signal amplification structures, to systems for encoding and decoding messages through various modern ways of communication, as well as new structures that can be imagined both in modern neural networks and in those for the physical implementation of some requirements imposed by current research with the aim of obtaining practically usable solutions in quantum computing and quantum computers.

Keywords: chua, diode, memristor, chaos

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Authors: Emily Rowe

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Introduction: Balance assessments can be used to help evaluate a person’s risk of falls, determine causes of balance deficits and inform intervention decisions. It is widely accepted that instrumented quantitative analysis can be more reliable and specific than semi-qualitative ordinal scales or itemised scoring methods. However, the uptake of quantitative methods is hindered by expense, lack of portability, and set-up requirements. During stepping, foot placement is actively coordinated with the body centre of mass (COM) kinematics during pre-initiation. Based on this, the potential to use COM velocity just prior to foot off and foot placement error as an outcome measure of dynamic balance is currently being explored using complex 3D motion capture. Inertial sensors and pressure mats might be more practical technologies for measuring these parameters in clinical settings. Objective: The aim of this study was to test the criterion validity and test-retest reliability of a synchronised inertial sensor and pressure mat-based approach to measure foot placement error and COM velocity while stepping. Methods: Trials were held with 15 healthy participants who each attended for two sessions. The trial task was to step onto one of 4 targets (2 for each foot) multiple times in a random, unpredictable order. The stepping target was cued using an auditory prompt and electroluminescent panel illumination. Data was collected using 3D motion capture and a combined inertial sensor-pressure mat system simultaneously in both sessions. To assess the reliability of each system, ICC estimates and their 95% confident intervals were calculated based on a mean-rating (k = 2), absolute-agreement, 2-way mixed-effects model. To test the criterion validity of the combined inertial sensor-pressure mat system against the motion capture system multi-factorial two-way repeated measures ANOVAs were carried out. Results: It was found that foot placement error was not reliably measured between sessions by either system (ICC 95% CIs; motion capture: 0 to >0.87 and pressure mat: <0.53 to >0.90). This could be due to genuine within-subject variability given the nature of the stepping task and brings into question the suitability of average foot placement error as an outcome measure. Additionally, results suggest the pressure mat is not a valid measure of this parameter since it was statistically significantly different from and much less precise than the motion capture system (p=0.003). The inertial sensor was found to be a moderately reliable (ICC 95% CIs >0.46 to >0.95) but not valid measure for anteroposterior and mediolateral COM velocities (AP velocity: p=0.000, ML velocity target 1 to 4: p=0.734, 0.001, 0.000 & 0.376). However, it is thought that with further development, the COM velocity measure validity could be improved. Possible options which could be investigated include whether there is an effect of inertial sensor placement with respect to pelvic marker placement or implementing more complex methods of data processing to manage inherent accelerometer and gyroscope limitations. Conclusion: The pressure mat is not a suitable alternative for measuring foot placement errors. The inertial sensors have the potential for measuring COM velocity; however, further development work is needed.

Keywords: dynamic balance, inertial sensors, portable, pressure mat, reliability, stepping, validity, wearables

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Koushik Roy, Sourav Gur, Sudib K. Mishra

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Evidence of pulse type features in near-fault ground motions has raised serious concern to the structural engineering community, in view of their possible implications on the behavior of structures located on the fault regions. Studies in the recent past explore the effects of pulse type ground motion on the special structures, such as transmission towers in view of their high flexibility. Identically, long period sloshing of liquid in the storage tanks under dynamic loading might increase their failure vulnerability under near-fault pulses. Therefore, the behavior of the elevated liquid storage tank is taken up in this study. Simple lumped mass model is considered, with the bilinear force-deformation hysteresis behavior. Set of near-fault seismic ground acceleration time histories are adopted for this purpose, along with the far-field records for comparison. It has been demonstrated that pulse type motions lead to significant increase of the responses; in particular, sloshing of the fluid mass could be as high as 5 times, then the far field counterpart. For identical storage capacity, slender tanks are found to be more vulnerable than the broad ones.

Keywords: far-field motion, hysteresis, liquid storage tank, near fault earthquake, sloshing

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Authors: Pisut Boonkaew, Jatuporn Thongsri

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In hard disk drive manufacturing industry, the process of reducing an unnecessary part and qualifying the quality of part before assembling is important. Thus, clamp was designed and fabricated as a fixture for holding in testing process. Basically, testing by trial and error consumes a long time to improve. Consequently, the simulation was brought to improve the part and reduce the time taken. The problem is the present clamp has a low life expectancy because of the critical stress that occurred. Hence, the simulation was brought to study the behavior of stress and compressive force to improve the clamp expectancy with all probability of designs which are present up to 27 designs, which excluding the repeated designs. The probability was calculated followed by the full fractional rules of six sigma methodology which was provided correctly. The six sigma methodology is a well-structured method for improving quality level by detecting and reducing the variability of the process. Therefore, the defective will be decreased while the process capability increasing. This research focuses on the methodology of stress and fatigue reduction while compressive force still remains in the acceptable range that has been set by the company. In the simulation, ANSYS simulates the 3D CAD with the same condition during the experiment. Then the force at each distance started from 0.01 to 0.1 mm will be recorded. The setting in ANSYS was verified by mesh convergence methodology and compared the percentage error with the experimental result; the error must not exceed the acceptable range. Therefore, the improved process focuses on degree, radius, and length that will reduce stress and still remain in the acceptable force number. Therefore, the fatigue analysis will be brought as the next process in order to guarantee that the lifetime will be extended by simulating through ANSYS simulation program. Not only to simulate it, but also to confirm the setting by comparing with the actual clamp in order to observe the different of fatigue between both designs. This brings the life time improvement up to 57% compared with the actual clamp in the manufacturing. This study provides a precise and trustable setting enough to be set as a reference methodology for the future design. Because of the combination and adaptation from the six sigma method, finite element, fatigue and linear regressive analysis that lead to accurate calculation, this project will able to save up to 60 million dollars annually.

Keywords: clamp, finite element analysis, structural, six sigma, linear regressive analysis, fatigue analysis, probability

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Authors: Adewoyin O. Olusegun, Emmanuel O. Joshua, Marvel L. Akinyemi

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The heterogeneous nature of the subsurface requires the use of factual information to deal with rather than assumptions or generalized equations. Therefore, there is need to determine the actual rate of settlement possible in the soil before structures are built on it. This information will help in determining the type of foundation design and the kind of reinforcement that will be necessary in constructions. This paper presents a simplified and a faster approach for determining foundation settlement in any type of soil using real field data acquired from seismic refraction techniques and cone penetration tests. This approach was also able to determine the depth of settlement of each strata of soil. The results obtained revealed the different settlement time and depth of settlement possible.

Keywords: heterogeneous, settlement, foundation, seismic, technique

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Authors: Kelvin Lo

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Nowadays, numerical modelling in geotechnical engineering is very common but sophisticated. Many advanced input settings and considerable computational efforts are required to optimize the design to reduce the construction cost. To optimize a design, it usually requires huge numerical models. If the optimization is conducted manually, there is a potentially dangerous consequence from human errors, and the time spent on the input and data extraction from output is significant. This paper presents an automation process introduced to numerical modelling (Plaxis 2D) of a trench excavation supported by a secant-pile retaining structure for a top-down tunnel project. Python code is adopted to control the process, and numerical modelling is conducted automatically in every 20m chainage along the 200m tunnel, with maximum retained height occurring in the middle chainage. Python code continuously changes the geological stratum and excavation depth under groundwater flow conditions in each 20m section. It automatically conducts trial and error to determine the required pile length and the use of props to achieve the required factor of safety and target displacement. Once the bending moment of the pile exceeds its capacity, it will increase in size. When the pile embedment reaches the default maximum length, it will turn on the prop system. Results showed that it saves time, increases efficiency, lowers design costs, and replaces human labor to minimize error.

Keywords: automation, numerical modelling, Python, retaining structures

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Authors: Salah Abdul Hameed Saleh, Ghada Hasan

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The aim of this work is to produce an empirical model for the determination of particulate matter (PM10) concentration in the atmosphere using visible bands of Landsat 8 OLI satellite image over Kirkuk city- IRAQ. The suggested algorithm is established on the aerosol optical reflectance model. The reflectance model is a function of the optical properties of the atmosphere, which can be related to its concentrations. The concentration of PM10 measurements was collected using Particle Mass Profiler and Counter in a Single Handheld Unit (Aerocet 531) meter simultaneously by the Landsat 8 OLI satellite image date. The PM10 measurement locations were defined by a handheld global positioning system (GPS). The obtained reflectance values for visible bands (Coastal aerosol, Blue, Green and blue bands) of landsat 8 OLI image were correlated with in-suite measured PM10. The feasibility of the proposed algorithms was investigated based on the correlation coefficient (R) and root-mean-square error (RMSE) compared with the PM10 ground measurement data. A choice of our proposed multispectral model was founded on the highest value correlation coefficient (R) and lowest value of the root mean square error (RMSE) with PM10 ground data. The outcomes of this research showed that visible bands of Landsat 8 OLI were capable of calculating PM10 concentration with an acceptable level of accuracy.

Keywords: air pollution, PM10 concentration, Lansat8 OLI image, reflectance, multispectral algorithms, Kirkuk area

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Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

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Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

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Authors: Ahmed Altalb

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Fertilizers are natural materials, or industrial contain nutrients, which help to improve soil fertility and is considered (nitrogen, phosphorus, and potassium) is important elements for the growth of crops properly. Fertilization is necessary in order to improve the quality of agricultural products and the recovery in agricultural activities. The use of organic fertilizers and chemical lead to reduce the loss of nutrients in agricultural soils, and this leads to an increase in the production of agricultural crops. Fertilizers are one of the key factors in the increase of agricultural production as well as other factors such as irrigation and improved seeds and Prevention and others; the fertilizers will continue to be a cornerstone of the agriculture in order to produce the food to feed of world population. The use of fertilizers has become commonplace today, especially the chemical fertilizers for the development of agricultural production, due to the provision of nutrients for plants and in high concentrations and easily dissolves in water and ease of use. The choose the right type of fertilizer depends on the soil type and the type of crop. In this subject, find the relationship between the agricultural extension and the optimal use of fertilizers. The extension plays the important role in the advise and educate of farmers in how they optimal use the fertilizers in a scientific way. This article aims to identify the concept the fertilizers. Identify the role of fertilizers in increasing the agricultural production, identify the role of agricultural extension in the optimal use of fertilizers and rural development.

Keywords: agricultural, extension, fertilizers, production

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Authors: A. Albar, U. Schwingenschlogel

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Device applications of transparent conducting oxides require a thorough understanding of the physical and chemical properties of the involved interfaces. We use ab-initio calculations within density functional theory to investigate the electronic states at the SnO/SnO2 hetero-interface. Tin dioxide and monoxide are transparent materials with high n-type and p-type mobilities, respectively. This work aims at exploring the modifications of the electronic states, in particular the charge transfer, in the vicinity of the hetero-interface. The (110) interface is modeled by a super-cell approach in order to minimize the mismatch between the lattice parameters of the two compounds. We discuss the electronic density of states as a function of the distance to the interface.

Keywords: density of states, ab-initio calculations, interface states, charge transfer

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Authors: Elizaveta S. Prokofyeva, Svetlana V. Maltseva, Roman D. Zaitsev

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Rapidly evolving modern data analysis technologies in healthcare play a large role in understanding the operation of the system and its characteristics. Nowadays, one of the key tasks in urban healthcare is to optimize the resource allocation. Thus, the application of data analysis in medical institutions to solve optimization problems determines the significance of this study. The purpose of this research was to establish the dependence between the indicators of the effectiveness of the medical institution and its resources. Hospital discharges by diagnosis; hospital days of in-patients and in-patient average length of stay were selected as the performance indicators and the demand of the medical facility. The hospital beds by type of care, medical technology (magnetic resonance tomography, gamma cameras, angiographic complexes and lithotripters) and physicians characterized the resource provision of medical institutions for the developed models. The data source for the research was an open database of the statistical service Eurostat. The choice of the source is due to the fact that the databases contain complete and open information necessary for research tasks in the field of public health. In addition, the statistical database has a user-friendly interface that allows you to quickly build analytical reports. The study provides information on 28 European for the period from 2007 to 2016. For all countries included in the study, with the most accurate and complete data for the period under review, predictive models were developed based on historical panel data. An attempt to improve the quality and the interpretation of the models was made by cluster analysis of the investigated set of countries. The main idea was to assess the similarity of the joint behavior of the variables throughout the time period under consideration to identify groups of similar countries and to construct the separate regression models for them. Therefore, the original time series were used as the objects of clustering. The hierarchical agglomerate algorithm k-medoids was used. The sampled objects were used as the centers of the clusters obtained, since determining the centroid when working with time series involves additional difficulties. The number of clusters used the silhouette coefficient. After the cluster analysis it was possible to significantly improve the predictive power of the models: for example, in the one of the clusters, MAPE error was only 0,82%, which makes it possible to conclude that this forecast is highly reliable in the short term. The obtained predicted values of the developed models have a relatively low level of error and can be used to make decisions on the resource provision of the hospital by medical personnel. The research displays the strong dependencies between the demand for the medical services and the modern medical equipment variable, which highlights the importance of the technological component for the successful development of the medical facility. Currently, data analysis has a huge potential, which allows to significantly improving health services. Medical institutions that are the first to introduce these technologies will certainly have a competitive advantage.

Keywords: data analysis, demand modeling, healthcare, medical facilities

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Authors: Vafa Delphi, Maryam Delphi, Talieh Zarifian, Enayatolah Bakhshi

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Background and Aim: Bilingualism is a common phenomenon in many countries of the world and May be consistent consonant errors in the speech of bilingual children. The aim of this study was to evaluate Phonological skills include occurrence proportion, frequency and type of phonological processes in Persian-Arabic speaking children in Ahvaz city, the center of Khuzestan. Method: This study is descriptive-analytical and cross-sectional. Twenty-eight children aged 36-48 months were divided into two groups Persian monolingual and Persian-Arabic bilingual: (14 participants in each group). Sampling was recruited randomly based on inclusion criteria from kindergartens of the Ahvaz city in Iran. The tool of this study was the Persian Phonological Test (PPT), a subtest of Persian Diagnostic Evaluation Articulation and Phonological test. In this test, Phonological processes were investigated in two groups: structure and substitution processes. Data was investigated using SPSS software and the U Mann-Whitney test. Results: The results showed that the proportion occurrence of substitution process was significantly different between two groups of monolingual and bilingual (P=0/001), But the type of phonological processes didn’t show a significant difference in both monolingual and bilingual children of the Persian-Arabic.The frequency of phonological processes is greater in bilingual children than monolingual children. Conclusion: The study showed that bilingualism has no effect on type of phonological processes, but this can be effective on the frequency of processes. Since the type of phonological processes in bilingual children is similar to monolingual children So we can conclude the Persian_arabic bilingual children's phonological system is similar to monolingual children.

Keywords: Persian-Arabic bilingual child, phonological processes, the proportion occurrence of syllable structure, the proportion occurrence of substitution

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Authors: Roland Tolulope Loto, Cleophas Akintoye Loto, Abimbola Patricia Popoola

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The inhibiting action of 2-dimethylamine on the electrochemical behaviour of austenitic stainless steel (type 304) in dilute hydrochloric was evaluated through weight-loss method, open circuit potential measurement and potentiodynamic polarization tests at specific concentrations of the organic compound. Results obtained reveal that the compound performed effectively giving a maximum inhibition efficiency of 79% at 12.5% concentration from weight loss analysis and 80.9% at 12.5% concentration from polarization tests. The average corrosion potential of -321 mV was obtained the same concentration from other tests which is well within passivation potentials on the steel thus, providing good protection against corrosion in the acid solutions. 2-dimethylamine acted through physiochemical interaction at the steel/solution interface from thermodynamic calculations and obeyed the Langmuir adsorption isotherm. The values of the inhibition efficiency determined from the three methods are in reasonably good agreement. Polarization studies showed that the compounds behaved as cathodic type inhibitor.

Keywords: corrosion, 2-dimethylamine, inhibition, adsorption, hydrochloric acid, steel

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Authors: K. A. Sudjatmi, Endiah Puji Hastuti, Surip Widodo, Reinaldy Nazar

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Any pretensions to stop the production of TRIGA fuel elements by TRIGA reactor fuel elements manufacturer should be anticipated by the operating agency of TRIGA reactor to replace the cylinder type fuel element with plate type fuel element, that available on the market. This away was performed the calculation on U3Si2Al fuel with uranium enrichment of 19.75% and a load level of 2.96 gU/cm3. Maximum power that can be operated on free convection cooling mode at the BANDUNG TRIGA reactor fuel plate was 600 kW. This study has been conducted thermalhydraulic characteristic calculation model of the reactor core power 2MW. BANDUNG TRIGA reactor core fueled plate type is composed of 16 fuel elements, 4 control elements and one irradiation facility which is located right in the middle of the core. The reactor core is cooled using a pump which is already available with flow rate 900 gpm. Analysis on forced convection cooling mode with flow from the top down from 10%, 20%, 30% and so on up to a 100% rate of coolant flow. performed using the COOLOD-N2 code. The calculations result showed that the 2 MW power with inlet coolant temperature at 37 °C and cooling rate percentage of 50%, then the coolant temperature, maximum cladding and meat respectively 64.96 oC, 124.81 oC, and 125.08 oC, DNBR (departure from nucleate boiling ratio)=1.23 and OFIR (onset of flow instability ratio)=1:00. The results are expected to be used as a reference for determining the power and cooling rate level of the BANDUNG TRIGA reactor core plate types fueled.

Keywords: TRIGA, COOLOD-N2, plate type fuel element, force convection, thermal hydraulic characteristic

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Authors: Gauri Shankar Shah

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Objectives: The Type I diabetes mellitus in children is frequently a missed diagnosis and children presents in emergency with diabetic ketoacidosis having significant morbidity and mortality. The present study was done to find out the clinical presentation and outcome at a tertiary-care centre. Methods: This was retrospective analysis of data of Type I diabetes mellitus reporting to our centre during last one year (2012-2013). Results: There were 12 patients (8 males) and the age group was 4-14 years (mean ± 3.7). The presenting symptoms were fever, vomiting, altered sensorium and fast breathing in 8 (66.6%), 6 (50%), 4 (33.3%), and 4 (33.3%) cases, respectively. The classical triad of polyuria, polydypsia, and polyphagia were present only in two patients (33.2%). Seizures and epigastric pain were found in two cases each (33.2%). The four cases (33.3%) presented with diabetic ketoacidosis due to discontinuation of insulin doses, while 2 had hyperglycemia alone. The hemogram revealed mean hemoglobin of 12.1± 1.6 g/dL and total leukocyte count was 22,883.3 ± 10,345.9 per mm3, with polymorphs percentage of 73.1 ± 9.0%. The mean blood sugar at presentation was 740 ± 277 mg/ dl (544–1240). HbA1c ranged between 7.1-8.8 with mean of 8.1±0.6 %. The mean sodium, potassium, blood ph, pCO2, pO2 and bicarbonate were 140.8 ± 6.9 mEq/L, 4.4 ± 1.8mEq/L, 7.0 ± 0.2, 20.2 ± 10.8 mmHg, 112.6 ± 46.5 mmHg and 9.2 ± 8.8 mEq/L, respectively. All the patients were managed in pediatric intensive care unit as per our protocol, recovered and discharged on intermediate insulin given twice daily. Conclusions: Thus, it shows that these patients have uncontrolled hyperglycemia and often presents in emergency with ketoacidosis and deranged biochemical profile. The regular administration of insulin, frequent monitoring of blood sugar and health education are required to have better metabolic control and good quality of life.

Keywords: type I diabetes mellitus, hyperglycemia, outcome, glycemic control

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Authors: Christian Lavault

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In this paper, the generalized fractional integral operators of two generalized Mittag-Leffler type functions are investigated. The special cases of interest involve the generalized M-series and K-function, both introduced by Sharma. The two pairs of theorems established herein generalize recent results about left- and right-sided generalized fractional integration operators applied here to the M-series and the K-function. The note also results in important applications in physics and mathematical engineering.

Keywords: Fox–Wright Psi function, generalized hypergeometric function, generalized Riemann– Liouville and Erdélyi–Kober fractional integral operators, Saigo's generalized fractional calculus, Sharma's M-series and K-function

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Authors: Thierry Pauporté

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Wide bandgap n-type oxide layers (TiO2, SnO2, ZnO etc.) play key roles in perovskite solar cells. They act as electron transport layers, and they permit the charge separation. They are also the substrate for the preparation of perovskite in the direct architecture. Therefore, they have a strong influence on the perovskite loading, its crystallinity and they can induce a degradation phenomenon upon annealing. The interface between the oxide and the perovskite is important, and the quality of this heterointerface must be optimized to limit the recombination of charges phenomena and performance losses. One can also play on the oxide and use two oxide contact layers for improving the device stability and durability. These aspects will be developed and illustrated on the basis of recent results obtained at Chimie-ParisTech.

Keywords: oxide, hybrid perovskite, solar cells, impedance

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Authors: Amir M. Shikhli, Refaat H. Abdel-Razek, Salaheddine Bendak

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Innovation is considered to be one of the key factors that influence long-term success of any company. The problem of many organizations in developing countries is trying to implement innovation without a strong basis within the organizational culture to support it. The objective of this study is to assess the effects of organizational culture on innovation in one of the biggest information technology organizations in UAE, Injazat Data System. First, an Organizational Culture Assessment Instrument (OCAI) was used as a survey and Competing Value Framework as a model to analyze the existing culture within the organization and determine its characteristics. Following that, a modified version of the Community Innovation Survey (CIS) was used to determine innovation types introduced by the organization. Then multiple linear regression analysis was used to find out the effects of existing organizational culture on innovation. Results show that existing organizational culture is composed of a combination of Hierarchy (29.4%), Clan (25.8%), Market (24.9%) and Adhocracy (19.9%). Results of the second survey show that the organization focuses on organizational innovation (26.8%) followed by market and product innovations (25.6%) and finally process innovation (22.0%). Regression analysis results reveal that for each innovation type there is a recommended combination of the four culture types. For product innovation, the combination is 47.4% Clan, 17.9% Adhocracy, 1.0% Market and 33.3% Hierarchy; for process innovation it is 19.7% Clan, 45.2% Adhocracy, 32.0% Market and 3.1% Hierarchy; for organizational innovation the combination is 5.4% Clan, 32.7% Adhocracy, 6.0% Market and 55.9% Hierarchy; and for market innovation it is 25.5% Clan, 42.6% Adhocracy, 32.6% Market and 8.4% Hierarchy. Based on these recommended combinations, this study suggests two ways to enhance the innovation culture in the organization. First, if the management decides on the innovation type to be enhanced, a comparison between the existing culture and the recommended combination of selected innovation types will lead to difference in percentages of each culture type. Then further analysis should show how to modify the existing culture to match the recommended combination. Second, if the innovation type is not selected, but the management wants to enhance innovation culture in the organization, the difference in percentages of each culture type will lead to finding out the recommended combination of culture types that gives the narrowest gap between existing culture and recommended combination.

Keywords: developing countries, organizational culture, innovation types, product innovation, process innovation, organizational innovation, marketing innovation

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Authors: Siwarak Kitchanapaibul, Warren Gillibrand, Rob Burton

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The prevalence of diabetes mellitus has been rising all over the world. Self-management is required for diabetes mellitus patients. The objective of this study is to explore the self-management among the ethnic groups with type 2 diabetes mellitus in Thailand, an upper middle-income country which is located in South East Asia. The ethnic groups in Thailand are a minority group which has limited education and a different culture, language, costume and lifestyle from Thai people. The qualitative exploratory study was used in this study. In-depth interviews with semi-structured open questions were conducted by 20 participants from purposive sampling. These participants were the ethnic groups who have type 2 diabetes mellitus, received the services from a region hospital, understood Thai and were willing to participate. Content analysis was adopted for the study. The results showed that all of the participants controlled their diet before the appointment day and never miss their appointment. Only 3 participants did their exercise while 2 participants stated that they occasionally forgot to take medicine. 10 participants use the herbs for reducing the sugar level. 12 participants drank a lot of water after a lapse in the diet because they believed that water could dilute the sugar. The findings identified 5 themes; ‘controlling diet before appointment day’; ‘drinking water after a lapse in diet’; ‘medication being a vital importance’; ‘exercise is unimportant’; and ‘taking herbs for sugar reduction’. The results of this study are important to the health professionals to understand the self-management of Ethnic groups and use the data to create the appropriate intervention for promoting health among the ethnic groups with type 2 diabetes mellitus in Thailand. The findings will lead to the revision of health policy and the procedure for promoting health in this special ethnic groups.

Keywords: self-management, diabetes, ethnic groups, Thailand

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Authors: Sonia Gonzalez Cruz

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Subtitling activities allow for acquiring and developing certain translation skills, and they also have a great impact on the students' motivation. Active subtitling is a relatively recent activity that has generated a lot of interest particularly in the field of second-language acquisition, but it is also present within both the didactics of general translation and language teaching for translators. It is interesting to analyze the level of inclusion of these new resources into the existent curricula and observe to what extent these different teaching methods are being used in the translation classroom. Although subtitling has already become an independent discipline of study and it is considered to be a type of translation on its own, it is necessary to do further research on the different didactic varieties that this type of audiovisual translation offers. Therefore, this project is framed within the field of the didactics of translation, and it focuses on the relationship between the didactics of general translation and active subtitling as a didactic tool. Its main objective is to analyze the inclusion of interlinguistic active subtitling in general translation curricula at different universities. As it has been observed so far, the analyzed curricula do not make any type of reference to the use of this didactic tool in general translation classrooms. However, they do register the inclusion of other audiovisual activities such as dubbing, script translation or video watching, among others. By means of online questionnaires and interviews, the main goal is to confirm the results obtained after the observation of the curricula and find out to what extent subtitling has actually been included into general translation classrooms.

Keywords: subtitling, general translation, didactics, translation competence

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Authors: M. Pramila Devi, N. V. N. Indra Kiran

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Control charts, predominantly in the form of X-bar chart, are important tools in statistical process control (SPC). They are useful in determining whether a process is behaving as intended or there are some unnatural causes of variation. A process is out of control if a point falls outside the control limits or a series of point’s exhibit an unnatural pattern. In this paper, a study is carried out on four training algorithms for CCPs recognition. For those algorithms optimal structure is identified and then they are studied for type I and type II errors for generalization without early stopping and with early stopping and the best one is proposed.

Keywords: control chart pattern recognition, neural network, backpropagation, generalization, early stopping

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Authors: Sonal Budhiraja, Biswabrata Pradhan

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This work considers statistical inference based on progressive Type-I interval censored data with random removal. The scheme of progressive Type-I interval censoring with random removal can be described as follows. Suppose n identical items are placed on a test at time T0 = 0 under k pre-fixed inspection times at pre-specified times T1 < T2 < . . . < Tk, where Tk is the scheduled termination time of the experiment. At inspection time Ti, Ri of the remaining surviving units Si, are randomly removed from the experiment. The removal follows a binomial distribution with parameters Si and pi for i = 1, . . . , k, with pk = 1. In this censoring scheme, the number of failures in different inspection intervals and the number of randomly removed items at pre-specified inspection times are observed. Asymptotic properties of the maximum likelihood estimators (MLEs) are established under some regularity conditions. A β-content γ-level tolerance interval (TI) is determined for two parameters Weibull lifetime model using the asymptotic properties of MLEs. The minimum sample size required to achieve the desired β-content γ-level TI is determined. The performance of the MLEs and TI is studied via simulation.

Keywords: asymptotic normality, consistency, regularity conditions, simulation study, tolerance interval

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Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

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Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial Information Science, remote sensing, surface elevation changes,

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Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

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Authors: Yalçın Kılıç, İbrahim Kani

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The conversion of hydrocarbons to carbonyl compounds by oxidation reaction is one of the most important reactions in the synthesis of fine chemicals. As a result of the oxidation of hydrocarbons containing aliphatic sp3-CH groups in their structures, aldehydes, ketones or carboxylic acids can be obtained. In this study, OSSO-type 2,2'-[1,4-butanedylbis(thio)]bis-benzoic acid (tsabutH2) ligand and [Zn(µ-tsabut)(phen)]n complex (where phen = 1,10-phenantroline) were synthesized and their structures were characterized by single crystal x-ray diffraction method. The catalytic efficiency of the complex in the catalytic oxidation studies of organic compounds such as cyclohexane, ethylbenzene, diphenylmethane, and p-xylene containing sp3-C-H in its structure was investigated.

Keywords: metal complex, OSSO-type ligand, catalysis, oxidation

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Authors: Hager Elsheikh, Matthias Sendler, Juliana Glaubnitz

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In pancreatitis, an inflammatory reaction occurs in the pancreatic secretory cells due to premature activation of proteases, leading to pancreatic self-digestion and necrotic cell death of acinar cells. Acute pancreatitis in patients is characterized by a severe immune reaction that could lead to serious complications, such as organ failure or septic shock, if left untreated. Chronic pancreatitis is a recurrence of episodes of acute pancreatitis resulting in a fibro-inflammatory immune response, in which the type 2 immune response is primarily driven by AAMs in the pancreas. One of the most important signaling pathways for M2 macrophage activation is the IL-4/STAT6 pathway. Pancreatic fibrosis is induced by the hyperactivation of pancreatic stellate cells by dysregulation in the inflammatory response, leading to further damage, autodigestion and possibly necrosis of pancreatic acinar cells. The aim of this research is to investigate the effect of STAT6 knockout in disease severity and development of fibrosis wound healing in the presence of different macrophage populations, regulated by the type 2 immune response, after inducing chronic and/or acute pancreatitis in mice models via cerulean injection. We further investigate the influence of the JAK/STAT6 signaling pathway on the balance of fibrosis and regeneration in STAT6 deficient and wild-type mice. The characterization of resident and recruited macrophages will provide insight into the influence of the JAK/STAT6 signaling pathway on infiltrating cells and, ultimately, tissue fibrosis and disease severity.

Keywords: acute and chronic pancreatitis, tissue regeneration, macrophage polarization, Gastroenterology

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Authors: M. Nili, S. Tavasoli, A. R. Yazdandoost

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In this paper, an experimental investigation on the effect of Isfahan Ground Granulate Blast Furnace Slag (GGBS) on the compressive strength development of self-consolidating concrete (SCC) and normal concrete (NC) was performed. For this purpose, Portland cement type I was replaced with GGBS in various Portions. For NC and SCC Mixes, 10*10*10 cubic cm specimens were tested in 7, 28 and 91 days. It must be stated that in this research water to cement ratio was 0.44, cement used in cubic meter was 418 Kg/m³ and Superplasticizer (SP) Type III used in SCC based on Poly-Carboxylic acid. The results of experiments have shown that increasing GGBS Percentages in both types of concrete reduce Compressive strength in early ages.

Keywords: compressive strength, GGBS, normal concrete, self-consolidating concrete

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Authors: Wenqi Liu, Reginald Bailey

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This study explores an advanced approach to enhancing B2B sales forecasting by integrating machine learning models with a rule-based decision framework. The methodology begins with the development of a machine learning classification model to predict conversion likelihood, aiming to improve accuracy over traditional methods like logistic regression. The classification model's effectiveness is measured using metrics such as accuracy, precision, recall, and F1 score, alongside a feature importance analysis to identify key predictors. Following this, a machine learning regression model is used to forecast sales value, with the objective of reducing mean absolute error (MAE) compared to linear regression techniques. The regression model's performance is assessed using MAE, root mean square error (RMSE), and R-squared metrics, emphasizing feature contribution to the prediction. To bridge the gap between predictive analytics and decision-making, a rule-based decision model is introduced that prioritizes customers based on predefined thresholds for conversion probability and predicted sales value. This approach significantly enhances customer prioritization and improves overall sales performance by increasing conversion rates and optimizing revenue generation. The findings suggest that this combined framework offers a practical, data-driven solution for sales teams, facilitating more strategic decision-making in B2B environments.

Keywords: sales forecasting, machine learning, rule-based decision model, customer prioritization, predictive analytics

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Authors: Ledeza Jordan Babiano

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Translating statements into mathematical notations is one of the processes in word problem-solving. However, based on the literature, students still have difficulties with this skill. The purpose of this study was to investigate the translation errors of the students when they translate algebraic word problems into mathematical structures and locate the errors via the lens of the Translation-Verification Model. Moreover, this qualitative research study employed content analysis. During the data-gathering process, the students were asked to answer a six-item algebra word problem questionnaire, and their answers were analyzed by experts through blind coding using the Translation-Verification Model to determine their translation errors. After this, a focus group discussion was conducted, and the data gathered was analyzed through thematic analysis to determine the causes of the students’ translation errors. It was found out that students’ prevalent error in translation was the interpretation error, which was situated in the Attribute construct. The emerging themes during the FGD were: (1) The procedure of translation is strategically incorrect; (2) Lack of comprehension; (3) Algebra concepts related to difficulty; (4) Lack of spatial skills; (5) Unprepared for independent learning; and (6) The content of the problem is developmentally inappropriate. These themes boiled down to the major concept of independent learning preparedness in solving mathematical problems. This concept has subcomponents, which include contextual and conceptual factors in translation. Consequently, the results provided implications for instructors and professors in Mathematics to innovate their teaching pedagogies and strategies to address translation gaps among students.

Keywords: mathematical structure, algebra word problems, translation, errors

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