Search results for: multivariate time series data

Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Ahaggar, occupying a large area of Algeria, is characterized by a rich wetlands area to be preserved and managed both in time and space. The management of a large area, by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information...), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Remote sensing imaging data have been very useful in the last decade in very interesting applications. They can aid in several domains such as the detection and identification of diverse wetland surface targets, topographical details, and geological features... In this work, we try to extract automatically wetlands area using multispectral remotely sensed data on-board the Earth Observing 1 (EO-1) and Landsat satellite. Both are high-resolution multispectral imager with a 30 m resolution. The instrument images an interesting surface area. We have used images acquired over the several area of interesting in the National Park of Ahaggar in the south of Algeria. An Extraction Algorithm is applied on the several spectral index obtained from combination of different spectral bands to extract wetlands fraction occupation of land use. The obtained results show an accuracy to distinguish wetlands area from the other lad use themes using a fine exploitation on spectral index.

Keywords: multispectral data, EO1, landsat, wetlands, Ahaggar, Algeria

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Authors: Preeyaphorn Kosa, Thanutch Sukwimolseree

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The climate change is a main parameter which affects the element of hydrological cycle especially runoff. Then, the purpose of this study is to determine the impact of the climate change on surface runoff using land use map on 2008 and daily weather data during January 1, 1979 to September 30, 2010 for SWAT model. SWAT continuously simulate time model and operates on a daily time step at basin scale. The results present that the effect of temperature change cannot be clearly presented on the change of runoff while the rainfall, relative humidity and evaporation are the parameters for the considering of runoff change. If there are the increasing of rainfall and relative humidity, there is also the increasing of runoff. On the other hand, if there is the increasing of evaporation, there is the decreasing of runoff.

Keywords: climate, runoff, SWAT, upper Mun River basin

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Authors: Oluseun A. Sanuade, Sanlinn I. Kaka, Adesoji O. Akanji, Olukole A. Akinbiyi

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Prospect evaluation of ‘the ‘ADE’ field was done using 3D seismic data and well log data. The field is located in the offshore Niger Delta where water depth ranges from 450 to 800 m. The objectives of this study are to explore deeper prospects and to ascertain the kind of traps that are favorable for the accumulation of hydrocarbon in the field. Six horizons with major and minor faults were identified and mapped in the field. Time structure maps of these horizons were generated and using the available check-shot data the maps were converted to top structure maps which were used to calculate the hydrocarbon volume. The results show that regional structural highs that are trending in northeast-southwest (NE-SW) characterized a large portion of the field. These highs were observed across all horizons revealing a regional post-depositional deformation. Three prospects were identified and evaluated to understand the different opportunities in the field. These include stratigraphic pinch out and bi-directional downlap. The results of this study show that the field has potentials for new opportunities that could be explored for further studies.

Keywords: hydrocarbon, play, prospect, stratigraphy

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Authors: Y. Mateyshina, A.Ulihin, N.Uvarov

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Electrolytes with different type of charge carrier can find widely application in different using, e.g. sensors, electrochemical equipments, batteries and others. One of important components ensuring stable functioning of the equipment is electrolyte. Electrolyte has to be characterized by high conductivity, thermal stability, and wide electrochemical window. In addition to many advantageous characteristic for liquid electrolytes, the solid state electrolytes have good mechanical stability, wide working range of temperature range. Thus search of new system of solid electrolytes with high conductivity is an actual task of solid state chemistry. Families of alkali perchlorates and nitrates have been investigated by us earlier. In literature data about transport properties of alkali nitrites are absent. Nevertheless, alkali nitrites MeNO2 (Me= Li+, Na+, K+, Rb+ and Cs+), except for the lithium salt, have high-temperature phases with crystal structure of the NaCl-type. High-temperature phases of nitrites are orientationally disordered, i.e. non-spherical anions are reoriented over several equivalents directions in the crystal lattice. Pure lithium nitrite LiNO2 is characterized by ionic conductivity near 10-4 S/cm at 180°C and more stable as compared with lithium nitrate and can be used as a component for synthesis of composite electrolytes. In this work composite solid electrolytes in the binary system LiNO2 - A (A= MgO, -Al2O3, Fe2O3, CeO2, SnO2, SiO2) were synthesized and their structural, thermodynamic and electrical properties investigated. Alkali nitrite was obtained by exchange reaction from water solutions of barium nitrite and alkali sulfate. The synthesized salt was characterized by X-ray powder diffraction technique using D8 Advance X-Ray Diffractometer with Cu K radiation. Using thermal analysis, the temperatures of dehydration and thermal decomposition of salt were determined.. The conductivity was measured using a two electrode scheme in a forevacuum (6.7 Pa) with an HP 4284A (Precision LCR meter) in a frequency range 20 Hz < ν < 1 MHz. Solid composite electrolytes LiNO2 - A A (A= MgO, -Al2O3, Fe2O3, CeO2, SnO2, SiO2) have been synthesized by mixing of preliminary dehydrated components followed by sintering at 250°C. In the series of nitrite of alkaline metals Li+-Cs+, the conductivity varies not monotonically with increasing radius of cation. The minimum conductivity is observed for KNO2; however, with further increase in the radius of cation in the series, the conductivity tends to increase. The work was supported by the Russian Foundation for Basic research, grant #14-03-31442.

Keywords: conductivity, alkali nitrites, composite electrolytes, transport properties

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Authors: Laila Mahtout, Kerami Ahmed, Rabhi Souhila

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The objective of this work is to reduce the impact on the environment of an acid dye (Black Eriochrome T) using catalytic photo-degradation in the presence of the semiconductor powder (TiO₂) previously characterized. A series of tests have been carried out in order to demonstrate the influence of certain parameters on the degree of dye degradation by titanium dioxide in the presence of UV rays, such as contact time, the powder mass and the pH of the solution. X-ray diffraction analysis of the powder showed that the anatase structure is predominant and the rutile phase is presented by peaks of low intensity. The various chemical groups which characterize the presence of the bands corresponding to the anatase and rutile form and other chemical functions have been detected by the Fourier Transform Infrared spectroscopy. The photo degradation of the NET by TiO₂ is very interesting because it gives encouraging results. The study of photo-degradation at different concentrations of the dye showed that the lower concentrations give better removal rates. The degree of degradation of the dye increases with increasing pH; it reaches the maximum value at pH = 9. The ideal mass of TiO₂ which gives the high removal rate is 1.2 g/l. Thermal treatment of TiO₂ with the addition of CuO with contents of 5%, 10%, and 15% respectively gives better results of degradation of the NET dye. The high percentage of elimination is observed at a CuO content of 15%.

Keywords: acid dye, ultraviolet rays, degradation, photocatalyse

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Authors: Faizan Ahmad, Jenna Wong

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Time lag between peak values of horizontal and vertical seismic waves is a well-known phenomenon. Horizontal and vertical seismic waves, secondary and primary waves in nature respectively, travel through different layers of soil and the travel time is dependent upon the medium of wave transmission. In seismic analysis, many standardized codes do not require the actual vertical acceleration to be part of the analysis procedure. Instead, a factor load addition for a particular site is used to capture strength demands in case of vertical excitation. This study reviews the effects of vertical accelerations to analyze the behavior of a linearly rubber isolated structure in different time lag situations and frequency content by application of historical and simulated ground motions using SAP2000. The response of the structure is reviewed under multiple sets of ground motions and trends based on time lag and frequency variations are drawn. The accuracy of these results is discussed and evaluated to provide reasoning for use of real vertical excitations in seismic analysis procedures, especially for isolated structures.

Keywords: seismic analysis, vertical accelerations, time lag, isolated structures

Procedia PDF Downloads 315

Authors: R. Premasiri, W. A. H. A. Abeygunasekara, S. M. Hewavidana, T. Jananthan, R. M. S. Madawala, K. Vaheeshan

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Forecasting the potential for disastrous events such as landslides has become one of the major necessities in the current world. Most of all, the landslides occurred in Sri Lanka are found to be triggered mostly by intense rainfall events. The study area is the landslide near Gerandiella waterfall which is located by the 41st kilometer post on Nuwara Eliya-Gampala main road in Kotmale Division in Sri Lanka. The landslide endangers the entire Kotmale town beneath the slope. Geographic Information System (GIS) platform is very much useful when it comes to the need of emulating the real-world processes. The models are used in a wide array of applications ranging from simple evaluations to the levels of forecast future events. This project investigates the possibility of developing a dynamic model to map the spatial distribution of the slope stability. The model incorporates several theoretical models including the infinite slope model, Green Ampt infiltration model and Perched ground water flow model. A series of rainfall values can be fed to the model as the main input to simulate the dynamics of slope stability. Hydrological model developed using GIS is used to quantify the perched water table height, which is one of the most critical parameters affecting the slope stability. Infinite slope stability model is used to quantify the degree of slope stability in terms of factor of safety. DEM was built with the use of digitized contour data. Stratigraphy was modeled in Surfer using borehole data and resistivity images. Data available from rainfall gauges and piezometers were used in calibrating the model. During the calibration, the parameters were adjusted until a good fit between the simulated ground water levels and the piezometer readings was obtained. This model equipped with the predicted rainfall values can be used to forecast of the slope dynamics of the area of interest. Therefore it can be investigated the slope stability of rainfall induced landslides by adjusting temporal dimensions.

Keywords: factor of safety, geographic information system, hydrological model, slope stability

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Authors: Tomoaki Hashimoto

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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: Jairo Alejandro Fernandez Ortega

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Objective: Regarding effects of training velocity on strength in the functional condition of older adults controversy exists. The purpose of this study was to examine the effects of a twelve-week strength training program (PE) performed at high speed (GAV) versus a traditionally executed program (GBV), on functional performance, maximum strength and muscle power in a group of older adult women. Methodology: 86 women aged between 60-81 years participated voluntarily in the study and were assigned randomly to the GAV (three series at 40% 1RM at maximum speed, with maximum losses of 10% speed) or to the GBV (three series with three sets at 70% of 1RM). Both groups performed three weekly trainings. The maximum strength of upper and lower limbs (1RM), prehensile strength, walking speed, maximum power, mean propulsive velocity (MPV) and functional performance (senior fitness test) were evaluated before and after the PE. Results: Significant improvements were observed (p < 0.05) in all the tests in the two groups after the twelve weeks of training. However, the results of GAV were significantly (P < 0.05) higher than those of the GBV, in the tests of agility and dynamic equilibrium, stationary walking, sitting and standing, walking speed over 4 and 6 meters, MPV and peak power. In the tests of maximum strength and prehensile force, the differences were not significant. Conclusion: Strength training performed at high speeds seems to have a better effect on functional performance and muscle power than strength training performed at low speed.

Keywords: power training, resistance exercise, aging, strength, physical performance, high-velocity, resistance training

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Authors: Ioan Corneliu Salisteanu, Valentin Dogaru Ulieru, Mihaita Nicolae Ardeleanu, Alin Pohoata, Bogdan Salisteanu, Stefan Broscareanu

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Creating a personalized statistic for an individual within the population using IT systems, based on the searches and intercepted spheres of interest they manifest, is just one 'atom' of the artificial intelligence analysis network. However, having the ability to generate statistics based on individual data intercepted from large demographic areas leads to reasoning like that issued by a human mind with global strategic ambitions. The DiaMOTO device is a technical sensory system that allows the interception of car events caused by a driver, positioning them in time and space. The device's connection to the vehicle allows the creation of a source of data whose analysis can create psychological, behavioural profiles of the drivers involved. The SiaMOTO system collects data from many vehicles equipped with DiaMOTO, driven by many different drivers with a unique fingerprint in their approach to driving. In this paper, we aimed to explain the software infrastructure of the SiaMOTO system, a system designed to monitor and improve driver driving behaviour, as well as the criteria and algorithms underlying the intelligent analysis process.

Keywords: artificial intelligence, data processing, driver behaviour, driver monitoring, SiaMOTO

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Authors: Tahnee West

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Drama education is increasingly understood as a useful tool in promoting positive social change and cultural awareness. The effects of both positive and negative peer relationships are also a researched facet of education systems. Despite this, very little research has been conducted in the intersection of these two areas, even given current, significant public interest surrounding multicultural relationships. This research addresses a problem faced by educators and students: facilitating meaningful multicultural relationships. The research explores the following question in an Australian context: in what ways does Drama education affect peer relationships between culturally diverse students? In doing so, the study explores the various challenges and experiences of a multicultural group of adolescents, in terms of forming and maintaining effective intercultural friendships, while participating in a series of drama workshops. The project presents a starting point for providing educators with strategies for inclusivity and relationship development amongst diverse student populations. Findings show that Drama education can positively affect culturally diverse young people’s peer relationships; interactions between participants and data collected in focus groups throughout the eight-week Drama program show a steady improvement in sense of trust, support, tolerance, empathy, familiarity with other participants, and enjoyment. Data also points to a positive correlation between the Drama activities and improved conflict resolution and communication skills, as well as an improved understanding of the other participants’ cultures. Diversities and commonalities within the group were explored, with similarities encouraging social cohesion, and decreasing cultural ‘cliques’.

Keywords: cultural diversity, drama education, friendship, multicultural, peer relationships

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Maryam Panahiazar, Andrew M. Bishara, Yorick Chern, Roohallah Alizadehsani, Dexter Hadleye, Ramin E. Beygui

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Early detection plays a crucial role in enhancing the outcome for a patient with coronary artery disease (CAD). We utilized a big data analytics platform on ~23,000 patients with CAD from a total of 960,129 UCSF patients in 8 years. We traced the patients from their first encounter with a physician to diagnose and treat CAD. Characteristics such as demographic information, comorbidities, vital, lab tests, medications, and procedures are included. There are statistically significant gender-based differences in patients younger than 60 years old from the time of the first physician encounter to coronary artery bypass grafting (CABG) with a p-value=0.03. There are no significant differences between the patients between 60 and 80 years old (p-value=0.8) and older than 80 (p-value=0.4) with a 95% confidence interval. This recognition would affect significant changes in the guideline for referral of the patients for diagnostic tests expeditiously to improve the outcome by avoiding the delay in treatment.

Keywords: electronic medical records, coronary artery disease, data analytics, young women

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: Hilary Rutto, Mbali Chiliza, Tumisang Seodigeng

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The study on reactivity of calcined calcium-based material is very important in dry flue gas desulphurisation (FGD) process, so as to produce absorbent with high sulphur dioxide capture capacity during the hydration process. The effect of calcining temperature and time on the reactivity of calcined limestone material were investigated. In this study, the reactivity was measured using a pH stat apparatus and also confirming the result by performing citric acid reactivity test. The reactivity was calculated using the shrinking core model. Based on the experiments, a mathematical model is developed to correlate the effect of time and temperature to the reactivity of absorbent. The calcination process variables were temperature (700 -1000°C) and time (1-6 hrs). It was found that reactivity increases with an increase in time and temperature.

Keywords: reactivity, citric acid, calcination, time

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Authors: Mariia Khramova, Sergio Martinez, Duc Nguyen

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Modern electronic devices, particularly smartphones, are characterised by extremely high environmental footprint and short product lifecycle. Every year manufacturers release new models with even more superior performance, which pushes the customers towards new purchases. As a result, millions of devices are being accumulated in the urban mine. To tackle these challenges the concept of circular economy has been introduced to promote repair, reuse and recycle of electronics. In this case, electronic devices, that previously ended up in landfills or households, are getting the second life, therefore, reducing the demand for new raw materials. Smartphone reuse is gradually gaining wider adoption partly due to the price increase of flagship models, consequently, boosting circular economy implementation. However, along with reuse of communication device, circular economy approach needs to ensure the data of the previous user have not been 'reused' together with a device. This is especially important since modern smartphones are comparable with computers in terms of performance and amount of data stored. These data vary from pictures, videos, call logs to social security numbers, passport and credit card details, from personal information to corporate confidential data. To assess how well the data privacy requirements are followed on smartphones second-hand market, a sample of 100 Android smartphones has been purchased from IT Asset Disposition (ITAD) facilities responsible for data erasure and resell. Although devices should not have stored any user data by the time they leave ITAD, it has been possible to retrieve the data from 19% of the sample. Applied techniques varied from manual device inspection to sophisticated equipment and tools. These findings indicate significant barrier in implementation of circular economy and a limitation of smartphone reuse. Therefore, in order to motivate the users to donate or sell their old devices and make electronic use more sustainable, data privacy on second-hand smartphone market should be significantly improved. Presented research has been carried out in the framework of sustainablySMART project, which is part of Horizon 2020 EU Framework Programme for Research and Innovation.

Keywords: android, circular economy, data privacy, second-hand phones

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Authors: Elene Tatunashvili, Bun Chan, Philippe E. Nashar, Christopher S. P. McErlean

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The reduction of aryl diazonium salts is one of the most efficient ways to generate aryl radicals for use in a wide range of transformations, including Sandmeyer-type reactions, Meerwein arylations of olefins and Gomberg-Bachmann-Hey arylations of heteroaromatic systems. The aryl diazonium species can be reduced electrochemically, by UV irradiation, inner-sphere and outer-sphere single electron transfer processes (SET) from metal salts, SET from photo-excited organic catalysts or fragmentation of adducts with weak bases (acetate, hydroxide, etc.). This paper details an approach for the metal-free reduction of aryl diazonium salts, which facilitates the efficient synthesis of various aromatic compounds under exceedingly mild reaction conditions. By measuring the oxidation potential of a number of organic molecules, a series of nucleophiles were identified that reduce aryl diazonium salts via the addition-fragmentation mechanism. This approach leads to unprecedented operational simplicity: The reactions are very rapid and proceed in the open air; there is no need for external irradiation or heating, and the process is compatible with a large number of radical reactions. We illustrate these advantages by using the addition-fragmentation strategy to regioselectively arylate a series of heterocyclic compounds, to synthesize ketones by arylation of silyl enol ethers, and to synthesize benzothiophene and phenanthrene derivatives by radical annulation reactions.

Keywords: diazonium salts, hantzsch esters, oxygen, radical reactions, synthetic methods

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Authors: Nurlan Smagulov, Aiman Konkabayeva, Akerke Sadykova, Arailym Serik

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Introduction. Adverse environmental factors do not immediately lead to pathological changes in the body. They can exert the growth of pre-pathology characterized by shifts in physiological, biochemical, immunological and other indicators of the body state. These disorders are unstable, reversible and indicative of body reactions. There is an opportunity to objectively judge the internal structure of the adaptive body reactions at the level of individual organs and systems. In order to obtain a stable response of the body to the chronic effects of unfavorable environmental factors of low intensity (compared to production environment factors), a time called the «lag time» is needed. The obtained results without considering this factor distort reality and, for the most part, cannot be a reliable statement of the main conclusions in any work. A technique is needed to reduce methodological errors and combine mathematical logic using statistical methods and a medical point of view, which ultimately will affect the obtained results and avoid a false correlation. Objective. Development of a methodology for assessing and predicting the environmental factors impact on the population health considering the «lag time.» Methods. Research objects: environmental and population morbidity indicators. The database on the environmental state was compiled from the monthly newsletters of Kazhydromet. Data on population morbidity were obtained from regional statistical yearbooks. When processing static data, a time interval (lag) was determined for each «argument-function» pair. That is the required interval, after which the harmful factor effect (argument) will fully manifest itself in the indicators of the organism's state (function). The lag value was determined by cross-correlation functions of arguments (environmental indicators) with functions (morbidity). Correlation coefficients (r) and their reliability (t), Fisher's criterion (F) and the influence share (R2) of the main factor (argument) per indicator (function) were calculated as a percentage. Results. The ecological situation of an industrially developed region has an impact on health indicators, but it has some nuances. Fundamentally opposite results were obtained in the mathematical data processing, considering the «lag time». Namely, an expressed correlation was revealed after two databases (ecology-morbidity) shifted. For example, the lag period was 4 years for dust concentration, general morbidity, and 3 years – for childhood morbidity. These periods accounted for the maximum values of the correlation coefficients and the largest percentage of the influencing factor. Similar results were observed in relation to the concentration of soot, dioxide, etc. The comprehensive statistical processing using multiple correlation-regression variance analysis confirms the correctness of the above statement. This method provided the integrated approach to predicting the degree of pollution of the main environmental components to identify the most dangerous combinations of concentrations of leading negative environmental factors. Conclusion. The method of assessing the «environment-public health» system (considering the «lag time») is qualitatively different from the traditional (without considering the «lag time»). The results significantly differ and are more amenable to a logical explanation of the obtained dependencies. The method allows presenting the quantitative and qualitative dependence in a different way within the «environment-public health» system.

Keywords: ecology, morbidity, population, lag time

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Authors: M. Khairudin

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This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

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Authors: Taiyo Matsumura, Kuninori Takahashi, Takashi Ono

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The purpose of this research is to improve the convenience of waiting for trains at level crossings and stations and to prevent accidents resulting from forcible entry into level crossings, by providing level crossing users and passengers with information that tells them when the next train will pass through or arrive. For this paper, we proposed methods for estimating operation by means of an average value method, variable response smoothing method, and exponential smoothing method, on the basis of open data, which has low accuracy, but for which performance schedules are distributed in real time. We then examined the accuracy of the estimations. The results showed that the application of an exponential smoothing method is valid.

Keywords: exponential smoothing method, open data, operation estimation, train schedule

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Authors: Amjad Al Shammari, Ashraf Ibrahim, Laila Seada

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Background and Objectives: Incidence of thyroid carcinoma has been increasing world-wide. In the present study, we evaluated diagnostic accuracy of Fine needle aspiration (FNA) and its efficiency in early detecting neoplastic lesions of thyroid gland over a 3-year period. Methods: Data have been retrieved from pathology files in King Khalid Hospital. For each patient, age, gender, FNA, site & size of nodule and final histopathologic diagnosis were recorded. Results: Study included 490 cases where 419 of them were female and 71 male. Male to female ratio was 1:6. Mean age was 43 years for males and 38 for females. Cases with confirmed histopathology were 131. In 101/131 (77.1%), concordance was found between FNA and histology. In 30/131 (22.9%), there was discrepancy in diagnosis. Total malignant cases were 43, out of which 14 (32.5%) were true positive and 29 (67.44%) were false negative. No false positive cases could be found in our series. Conclusion: FNA could diagnose benign nodules in all cases, however, in malignant cases, ultrasound findings have to be taken into consideration to avoid missing of a microcarcinoma in the contralateral lobe.

Keywords: FNA, hail, histopathology, thyroid

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Authors: Rochelyn Dona, Serdar Satar

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The aim of this study was to evaluate the biological parameters of A. fabae Scopoli (Hemiptera: Aphididae). Developmental, survival, and reproductive data were collected for Aphis fabae reared on detached bean leaves (Phaseolus vulgaris L.) ‘pinto beans’ at five temperature regimes (12, 16, 20, 24, and 28 °C), 65% relative humidity (RH), relative and a photoperiod of 16:8 (LD) h. The developmental times of immature stages ranged from 16, 65 days at 12°C to 5.70 days at 24°C, but a slight increase again at 28°C (6.62 days). At 24°C from this study presented the developmental threshold for A. fabae slightly to 24°C. The average longevity of mature females significantly decreased from 42.32 days at 12°C to 16.12 days at 28°C. The reproduction rate per female was 62.27 at 16°C and 12.72 at 28°C. The mean generation period of the population ranged from 29.24 at 12°C to 11.50 at 28°C. The highest intrinsic rate of increase (rm = 0.41) were recorded at 24°C, the lowest at 12°C (rm = 0.15). It was evident that temperatures over 28°C augmented the development time, accelerated the death ratio of the nymphal stages, Shrunk Adult longevity, and reduced fecundity. The optimal range of temperature for the population growth of A. fabae on the bean was 16°C-24°C, according to this study.

Keywords: developmental time, intrinsic rate, reproduction period, temperature dependence

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Authors: Milind Chaudhari, Suhail Balasinor

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Due to massive deforestation and an ever-increasing population, the organic content of the soil is depleting at a much faster rate. Due to this, there is a big chance that the entire food production in the world will drop by 40% in the next two decades. Vertical farming can help in aiding food production by leveraging big data and cloud computing to ensure plants are grown naturally by providing the optimum nutrients sunlight by analyzing millions of data points. This paper outlines the most important parameters in vertical farming and how a combination of big data and AI helps in calculating and analyzing these millions of data points. Finally, the paper outlines how different organizations are controlling the indoor environment by leveraging big data in enhancing food quantity and quality.

Keywords: big data, IoT, vertical farming, indoor farming

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Authors: Saadan Man, Razidah Othmanjaludin, Madiha Baharuddin

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Nowadays, the pharmaceutical products are produced through the mixing of active and complex ingredient, naturally or synthetically; and involve extensive use of prohibited animal products. This article studies the challenges faced from fiqh perspective in the production of halal pharmaceutical products which frequently contain impure elements or prohibited animal derivatives according to Islamic law. This study is qualitative which adopts library research as well as field research by conducting series of interviews with the several related parties. The gathered data is analyzed from Sharia perspective by using some instruments especially the principle of Maqasid of Sharia. This study shows that the halal status of pharmaceutical products depends on the three basic elements: the sources of the basic ingredient; the processes involved in three phases of production, i.e., before, during and after; and the possible effects of the products. Various fiqh challenges need to be traversed in producing halal pharmaceutical products including the sources of the ingredients, the logistic process, the tools used, and the procedures of productions. Thus, the whole supply chain of production of pharmaceutical products must be well managed in accordance to the halal standard.

Keywords: fiqh, halal pharmaceutical, pharmaceutical products, Malaysia

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Authors: Masoud Swalehe, Semra Günay

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Developed countries are losing many lives to non-communicable diseases as compared to their developing counterparts. The effects of these diseases are mostly sudden and manifest at a very short time prior to death or a dangerous attack and this has consolidated the significance of emergency medical system (EMS) as one of the vital areas of healthcare service delivery. The primary objective of this research is to reduce ambulance response times (RT) of Eskişehir province EMS since a number of studies have established a relationship between ambulance response times and survival chances of patients especially out of hospital cardiac arrest (OHCA) victims. It has been found out that patients who receive out of hospital medical attention in few (4) minutes after cardiac arrest because of low ambulance response times stand higher chances of survival than their counterparts who take longer times (more than 12 minutes) to receive out of hospital medical care because of higher ambulance response times. The study will make use of geographic information systems (GIS) technology to dynamically reallocate ambulance resources according to demand and time so as to reduce ambulance response times. Geospatial-time distribution of ambulance calls (demand) will be used as a basis for optimal ambulance deployment using system status management (SSM) strategy to achieve much demand coverage with the same number of ambulance resources to cause response time reduction. Drive-time polygons will be used to come up with time specific facility coverage areas and suggesting additional facility candidate sites where ambulance resources can be moved to serve higher demands making use of network analysis techniques. Emergency Ambulance calls’ data from 1st January 2014 to 31st December 2014 obtained from Eskişehir province health directorate will be used in this study. This study will focus on the reduction of ambulance response times which is a key Emergency Medical Services performance indicator.

Keywords: emergency medical services, system status management, ambulance response times, geographic information system, geospatial-time distribution, out of hospital cardiac arrest

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Authors: Sudeepti Dayal, Neelesh Gupta

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In terms of transmission, bigger the size of any image, longer the time the channel takes for transmission. It is understood that the bandwidth of the channel is fixed. Therefore, if the size of an image is reduced, a larger number of data or images can be transmitted over the channel. Compression is the technique used to reduce the size of an image. In terms of storage, compression reduces the file size which it occupies on the disk. Any image is based on two parameters, region of interest and non-region of interest. There are several algorithms of compression that compress the data more economically. In this paper we have reviewed region of interest and non-region of interest based compression techniques and the algorithms which compress the image most efficiently.

Keywords: compression ratio, region of interest, DCT, DWT

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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Authors: Simon B.A. Egli, Katja Rost

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Literature on redistributive preferences has proliferated in past decades. A core assumption behind it is that variation in redistributive preferences can explain different levels of redistribution. In contrast, this paper considers the reverse. What if it is redistribution that changes redistributive preferences? The core assumption behind the argument is that if self-interest - which we label concrete preferences - and ideology - which we label abstract preferences - come into conflict, the former will prevail and lead to an adjustment of the latter. To test the hypothesis, data from a survey conducted in Switzerland during the first wave of the COVID-19 crisis is used. A significant portion of the workforce at the time unexpectedly received state money through the short-time working program. Short-time work was used as a proxy for self-interest and was tested (1) on the support given to hypothetical, ailing firms during the crisis and (2) on the prioritization of justice principles guiding state action. In a first step, several models using OLS-regressions on political orientation were estimated to test our hypothesis as well as to check for non-linear effects. We expected support for ailing firms to be the same regardless of ideology but only for people on short-time work. The results both confirm our hypothesis and suggest a non-linear effect. Far-right individuals on short-time work were disproportionally supportive compared to moderate ones. In a second step, ordered logit models were estimated to test the impact of short-time work and political orientation on the rankings of the distributive justice principles need, performance, entitlement, and equality. The results show that being on short-time work significantly alters the prioritization of justice principles. Right-wing individuals are much more likely to prioritize need and equality over performance and entitlement when they receive government assistance. No such effect is found among left-wing individuals. In conclusion, we provide moderate to strong evidence that unexpectedly finding oneself at the receiving end changes redistributive preferences if personal ideology is antithetical to redistribution. The implications of our findings on the study of populism, personal ideologies, and political change are discussed.

Keywords: COVID-19, ideology, redistribution, redistributive preferences, self-interest

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Authors: Bara' Al-Mistarehi

Abstract:

Documentation and assessment of conservation state of an archaeological structure is a significant procedure in any management plan. However, it has always been a challenge to apply this with a low coast and safe methodology. It is also a time-demanding procedure. Therefore, a low cost, efficient methodology for documenting the state of a structure is needed. In the scope of this research, this paper will employ digital photogrammetry and laser scanner to one of highly significant structures in Germany, The Old Castle (German: Altes Schloss). The site is well known for its unique features. However, the castle suffers from serious deterioration threats because of the environmental conditions and the absence of continuous monitoring, maintenance and repair plans. Digital photogrammetry is a generally accepted technique for the collection of 3D representations of the environment. For this reason, this image-based technique has been extensively used to produce high quality 3D models of heritage sites and historical buildings for documentation and presentation purposes. Additionally, terrestrial laser scanners are used, which directly measure 3D surface coordinates based on the run-time of reflected light pulses. These systems feature high data acquisition rates, good accuracy and high spatial data density. Despite the potential of each single approach, in this research work maximum benefit is to be expected by a combination of data from both digital cameras and terrestrial laser scanners. Within the paper, the usage, application and advantages of the technique will be investigated in terms of building high realistic 3D textured model for some parts of the old castle. The model will be used as diagnosing tool of the conservation state of the castle and monitoring mean for future changes.

Keywords: Digital photogrammetry, Terrestrial laser scanners, 3D textured model, archaeological structure

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Authors: Alireza Pirkhaefi

Abstract:

Background: Multiple sclerosis (MS) is one of the most common diseases of the central nervous system (brain and spinal cord). Given the importance of cognitive disorders in patients with multiple sclerosis, the present study was in order to compare cognitive functions (Working memory, Attention and Centralization, and Visual-spatial perception) in patients with relapsing- remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS). Method: Present study was performed as a retrospective study. This research was conducted with Ex-Post Facto method. The samples of research consisted of 60 patients with multiple sclerosis (30 patients relapsing-retrograde and 30 patients secondary progressive), who were selected from Tehran Community of MS Patients Supported as convenience sampling. 30 normal persons were also selected as a comparison group. Montreal Cognitive Assessment (MOCA) was used to assess cognitive functions. Data were analyzed using multivariate analysis of variance. Results: The results showed that there were significant differences among cognitive functioning in patients with RRMS, SPMS, and normal individuals. There were not significant differences in working memory between two groups of patients with RRMS and SPMS; while significant differences in these variables were seen between the two groups and normal individuals. Also, results showed significant differences in attention and centralization and visual-spatial perception among three groups. Conclusions: Results showed that there are differences between cognitive functions of RRMS and SPMS patients so that the functions of RRMS patients are better than SPMS patients. These results have a critical role in improvement of cognitive functions; reduce the factors causing disability due to cognitive impairment, and especially overall health of society.

Keywords: multiple sclerosis, cognitive function, secondary-progressive, normal subjects

Procedia PDF Downloads 221