Search results for: statistical monitoring

Authors: Thanasuwit Thabhiranrak

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This research aims to study factors that affected the operations of the cassava industrial enterprises in northeast of Thailand. Hypothesis was tested by regress analysis and also the analysis in order to determine the relationship between variables with Pearson correlation and show a class action in cassava process including the owner of business executives and supervisors. The research samples were 400 people in northeast region of Thailand. The research results revealed that success of entrepreneurs related to transformation leadership and knowledge management in a positive way at statistical significance level of 0.01 and respondents also emphasized on the importance of transformational leadership factors. The individual and the use of intelligence affect the success of entrepreneurs in cassava industry at statistical significance level of 0.05. The qualitative data were also collected by interviewing with operational level staff, supervisors, executives, and enterprise owners in the northeast of Thailand. The result was found that knowledge management was important in their business operations. Personnel in the organizations should learn from working experience, develop their skills, and increase knowledge from education.

Keywords: transformational leadership, knowledge management (KM), cassava, northeast of Thailand, industrial

Procedia PDF Downloads 303

Authors: Emmanuel O. Ezim, Idowu A. Olayinka, Michael Oladunjoye, Izuchukwu I. Obiadi

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Monitoring of reservoir properties prior to well placements and production is a requirement for optimisation and efficient oil and gas production. This is usually done using well log analyses and 3-D seismic, which are often prone to errors. However, 4-D (Time-lapse) seismic, incorporating numerous 3-D seismic surveys of the same field with the same acquisition parameters, which portrays the transient changes in the reservoir due to production effects over time, could be utilised because it generates better resolution. There is, however dearth of information on the applicability of this approach in the Niger Delta. This study was therefore designed to apply 4-D seismic, well-log and geologic data in monitoring of reservoirs in the EK field of the Niger Delta. It aimed at locating bypassed accumulations and ensuring effective reservoir management. The Field (EK) covers an area of about 1200km2 belonging to the early (18ma) Miocene. Data covering two 4-D vintages acquired over a fifteen-year interval were obtained from oil companies operating in the field. The data were analysed to determine the seismic structures, horizons, Well-to-Seismic Tie (WST), and wavelets. Well, logs and production history data from fifteen selected wells were also collected from the Oil companies. Formation evaluation, petrophysical analysis and inversion alongside geological data were undertaken using Petrel, Shell-nDi, Techlog and Jason Software. Well-to-seismic tie, formation evaluation and saturation monitoring using petrophysical and geological data and software were used to find bypassed hydrocarbon prospects. The seismic vintages were interpreted, and the amounts of change in the reservoir were defined by the differences in Acoustic Impedance (AI) inversions of the base and the monitor seismic. AI rock properties were estimated from all the seismic amplitudes using controlled sparse-spike inversion. The estimated rock properties were used to produce AI maps. The structural analysis showed the dominance of NW-SE trending rollover collapsed-crest anticlines in EK with hydrocarbons trapped northwards. There were good ties in wells EK 27, 39. Analysed wavelets revealed consistent amplitude and phase for the WST; hence, a good match between the inverted impedance and the good data. Evidence of large pay thickness, ranging from 2875ms (11420 TVDSS-ft) to about 2965ms, were found around EK 39 well with good yield properties. The comparison between the base of the AI and the current monitor and the generated AI maps revealed zones of untapped hydrocarbons as well as assisted in determining fluids movement. The inverted sections through EK 27, 39 (within 3101 m - 3695 m), indicated depletion in the reservoirs. The extent of the present non-uniform gas-oil contact and oil-water contact movements were from 3554 to 3575 m. The 4-D seismic approach led to better reservoir characterization, well development and the location of deeper and bypassed hydrocarbon reservoirs.

Keywords: reservoir monitoring, 4-D seismic, well placements, petrophysical analysis, Niger delta basin

Procedia PDF Downloads 116

Authors: M. A. Wanzala, L. A. Ogallo, F. J. Opijah, J. N. Mutemi

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The usefulness and limitations in climate information are due to uncertainty inherent in the climate system. For any given region to have sustainable development it is important to apply climate information into its socio-economic strategic plans. The overall objective of the study was to assess the performance of the Coupled Model Inter-comparison Project (CMIP5) over the Lake Victoria Basin. The datasets used included the observed point station data, gridded rainfall data from Climate Research Unit (CRU) and hindcast data from eight CMIP5. The methodology included trend analysis, spatial analysis, correlation analysis, Principal Component Analysis (PCA) regression analysis, and categorical statistical skill score. Analysis of the trends in the observed rainfall records indicated an increase in rainfall variability both in space and time for all the seasons. The spatial patterns of the individual models output from the models of MPI, MIROC, EC-EARTH and CNRM were closest to the observed rainfall patterns.

Keywords: categorical statistics, coupled model inter-comparison project, principal component analysis, statistical downscaling

Procedia PDF Downloads 368

Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

Procedia PDF Downloads 327

Authors: Branislav Timotijevic, Yves Petremand, Markus Luetzelschwab, Dara Bayat, Laurent Aebi

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Optical miniaturized sensors with remote readout are required devices for the monitoring in harsh electromagnetic environments. As an example, in turbo and hydro generators, excessively high vibrations of the end-windings can lead to dramatic damages, imposing very high, additional service costs. A significant change of the generator temperature can also be an indicator of the system failure. Continuous monitoring of vibrations, temperature, humidity, and gases is therefore mandatory. The high electromagnetic fields in the generators impose the use of non-conductive devices in order to prevent electromagnetic interferences and to electrically isolate the sensing element to the electronic readout. Metal-free sensors are good candidates for such systems since they are immune to very strong electromagnetic fields and given the fact that they are non-conductive. We have realized miniature optical accelerometer and temperature sensors for a remote sensing of the harsh environments using the common, inexpensive silicon Micro Electro-Mechanical System (MEMS) platform. Both devices show highly linear response. The accelerometer has a deviation within 1% from the linear fit when tested in a range 0 – 40 g. The temperature sensor can provide the measurement accuracy better than 1 °C in a range 20 – 150 °C. The design of other type of sensors for the environments with high electromagnetic interferences has also been discussed.

Keywords: optical MEMS, temperature sensor, accelerometer, remote sensing, harsh environment

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Authors: Yamamah Abdulrazaq, Lahieb A. Abrahim, Samuel E. Davies, Iain Shewring

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An electric water heater (EWH) is a powerful appliance that uses electricity in residential, commercial, and industrial settings, and the ability to control them properly will result in cost savings and the prevention of blackouts on the national grid. This article discusses the usage of timers in EWH control strategies for demand-side management (DSM). Up to the authors' knowledge, there is no systematic mapping review focusing on the utilisation of EWH control strategies in DSM has yet been conducted. Consequently, the purpose of this research is to identify and examine main papers exploring EWH procedures in DSM by quantifying and categorising information with regard to publication year and source, kind of methods, and source of data for monitoring control techniques. In order to answer the research questions, a total of 31 publications published between 1999 and 2023 were selected depending on specific inclusion and exclusion criteria. The data indicate that direct load control (DLC) has been somewhat more prevalent than indirect load control (ILC). Additionally, the mixing method is much lower than the other techniques, and the proportion of Real-time data (RTD) to non-real-time data (NRTD) is about equal.

Keywords: demand side management, direct load control, electric water heater, indirect load control, non real-time data, real-time data

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Authors: Umit Cali

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The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

Procedia PDF Downloads 518

Authors: Mabel Usunobun Olanipekun, Henry Ogbemudia Omoregbee

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Anomalies such as water pipeline and hydraulic or petrochemical pipeline network leakages and bursts have significant implications for economic conditions and the environment. In order to ensure pipeline systems are reliable, they must be efficiently controlled. Wireless Sensor Networks (WSNs) have become a powerful network with critical infrastructure monitoring systems for water, oil and gas pipelines. The loss of water, oil and gas is inevitable and is strongly linked to financial costs and environmental problems, and its avoidance often leads to saving of economic resources. Substantial repair costs and the loss of precious natural resources are part of the financial impact of leaking pipes. Pipeline systems experts have implemented various methodologies in recent decades to identify and locate leakages in water, oil and gas supply networks. These methodologies include, among others, the use of acoustic sensors, measurements, abrupt statistical analysis etc. The issue of leak quantification is to estimate, given some observations about that network, the size and location of one or more leaks in a water pipeline network. In detecting background leakage, however, there is a greater uncertainty in using these methodologies since their output is not so reliable. In this work, we are presenting a scalable concept and simulation where a pressure-driven model (PDM) was used to determine water pipeline leakage in a system network. These pressure data were collected with the use of acoustic sensors located at various node points after a predetermined distance apart. We were able to determine with the use of correlation difference to determine the leakage point locally introduced at a predetermined point between two consecutive nodes, causing a substantial pressure difference between in a pipeline network. After de-noising the signal from the sensors at the nodes, we successfully obtained the exact point where we introduced the local leakage using the correlation difference model we developed.

Keywords: leakage detection, acoustic signals, pipeline network, correlation, wireless sensor networks (WSNs)

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Authors: Suchada Wongsawat

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The objectives of this quasi-experiment were: 1) to compare pretest and posttest scores of the experimental group who were given health education on the “Fruit Diets for Elderly Patients with Type 2 Diabetes Mellitus”; and 2) to compare the posttest scores between experimental group and controlled group. The samples of this study were elderly patients with type 2 Diabetes Mellitus at Tambon Kanai Health Promoting Hospital, Thailand. The samples were randomly assigned to experimental and controlled groups, with 30 patients in each group. Statistics used in the data analysis included frequency, percentage, average, standard deviation, paired t-test and independent t-test. The study revealed that the patients in the experimental group had significantly higher posttest scores than the pretest scores in the health education at the .05 statistical level. The posttest scores of the experimental group in the health education were significantly higher than the controlled group at the .05 statistical level.

Keywords: fruit, health education, elderly, diabetes

Procedia PDF Downloads 283

Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

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Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: R. Farhoud, G. Hermand, S. Delepine-lesoille

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Future underground facility of French radioactive waste disposal, named Cigeo, is designed to store intermediate and high level - long-lived French radioactive waste. Intermediate level waste cells are tunnel-like, about 400m length and 65 m² section, equipped with several concrete layers, which can be grouted in situ or composed of tunnel elements pre-grouted. The operating space into cells, to allow putting or removing waste containers, should be monitored for several decades without any maintenance. To provide the required information, design was performed and tested in situ in Andra’s underground laboratory (URL) at 500m under the surface. Based on distributed optic fiber sensors (OFS) and backscattered Brillouin for strain and Raman for temperature interrogation technics, the design consists of 2 loops of OFS, at 2 different radiuses, around the monitored section (Orthoradiale strains) and longitudinally. Strains measured by distributed OFS cables were compared to classical vibrating wire extensometers (VWE) and platinum probes (Pt). The OFS cables were composed of 2 cables sensitive to strains and temperatures and one only for temperatures. All cables were connected, between sensitive part and instruments, to hybrid cables to reduce cost. The connection has been made according to 2 technics: splicing fibers in situ after installation or preparing each fiber with a connector and only plugging them together in situ. Another challenge was installing OFS cables along a tunnel mad in several parts, without interruption along several parts. First success consists of the survival rate of sensors after installation and quality of measurements. Indeed, 100% of OFS cables, intended for long-term monitoring, survived installation. Few new configurations were tested with relative success. Measurements obtained were very promising. Indeed, after 3 years of data, no difference was observed between cables and connection methods of OFS and strains fit well with VWE and Pt placed at the same location. Data, from Brillouin instrument sensitive to strains and temperatures, were compensated with data provided by Raman instrument only sensitive to temperature and into a separated fiber. These results provide confidence in the next steps of the qualification processes which consists of testing several data treatment approach for direct analyses.

Keywords: monitoring, fiber optic, sensor, data treatment

Procedia PDF Downloads 129

Authors: Ibrahim Tiryakioglu, Mehmet Ali Ugur, Caglar Ozkaymak

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The development of GNSS technology has led to increasingly widespread and successful applications of GNSS surveys for monitoring crustal movements. However, multi-period GPS survey solutions have not been applied in monitoring vertical surface deformation. This study uses long-term GNSS time series that are required to determine vertical deformations. In recent years, the surface deformations that are parallel and semi-parallel to Bolvadin fault have occurred in Western Anatolia. These surface deformations have continued to occur in Bolvadin settlement area that is located mostly on alluvium ground. Due to these surface deformations, a number of cracks in the buildings located in the residential areas and breaks in underground water and sewage systems have been observed. In order to determine the amount of vertical surface deformations, two continuous GNSS stations have been established in the region. The stations have been operating since 2015 and 2017, respectively. In this study, GNSS observations from the mentioned two GNSS stations were processed with GAMIT/GLOBK (GNSS Analysis Massachusetts Institute of Technology/GLOBal Kalman) program package to create a coordinate time series. With the time series analyses, the GNSS stations’ behavior models (linear, periodical, etc.), the causes of these behaviors, and mathematical models were determined. The study results from the time series analysis of these two 2 GNSS stations shows approximately 50-80 mm/yr vertical movement.

Keywords: Bolvadin fault, GAMIT, GNSS time series, surface deformations

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Authors: Farhad Shafiepour Motlagh, Narges Salehi

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The aim of the present study was to investigate the relationship between inspirational leadership style and perceived social capital through the mediation of organizational knowledge resource development. The research method was descriptive-correlational. The statistical population consisted of all 3537 secondary school teachers in Isfahan. Sample selection was based on Cochran's formula volume formula for 338 people and multi-stage random sampling. The research instruments included a researcher-made inspirational leadership style questionnaire, a perceived social capital questionnaire (Putnam, 1999), and a researcher-made questionnaire of perceived organizational knowledge resources. Kolmogorov statistical tests, Pearson correlation, stepwise multiple regression, and structural equation modeling were used to analyze the data. In general, the results showed that there is a significant relationship between inspirational leadership style and the use of perceived social capital at the level of P <0.05. Also, the development of organizational knowledge resources mediates the relationship between inspirational leadership style and the use of perceived social capital at the level of P <0.05.

Keywords: inspirational leadership style, perceived social capital, perceived organizational knowledge

Procedia PDF Downloads 207

Authors: Amar Ranjan, Julieana Durai, Pranay Tanwar

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Background &Introduction: Ovarian cancer is one of the most common malignant tumor in the female. 70% of the cases of ovarian cancer are diagnosed at an advanced stage. The five-year survival rate associated with ovarian cancer is less than 30%. The early diagnosis of ovarian cancer becomes a key factor in improving the survival rate of patients. Presently, CAl25 (carbohydrate antigen125) is used for the diagnosis and therapeutic monitoring of ovarian cancer, but its sensitivity and specificity is not ideal. The introduction of HE4, human epididymis protein 4 has attracted much attention. HE4 has a sensitivity and specificity of 72.9% and 95% for differentiating between benign and malignant adnexal masses, which is better than CA125 detection.  Methods: Serum HE4 and CA -125 were estimated using the chemiluminescence method. Our cases were 40 epithelial ovarian cancer, 9 benign ovarian tumor, 29 benign gynaecological diseases and 13 healthy individuals. This group include healthy woman those who have undergoing family planning and menopause-related medical consultations and they are negative for ovarian mass. Optimal cut off values for HE4 and CA125 were 55.89pmol/L and 40.25U/L respectively (determined by statistical analysis). Results: The level of HE4 was raised in all ovarian cancer patients (n=40) whereas CA125 levels were normal in 6/40 ovarian cancer patients, which were the cases of OC confirmed by histopathology. There is a significant decrease in the level of HE4 with comparison to CA125 in benign ovarian tumor cases. Both the levels of HE4 and CA125 were raised in the nonovarian cancer group, which includes cancer of endometrium and cervix. In the healthy group, HE4 was normal in all patients except in one case of the rudimentary horn, and the reason for this raised HE4 level is due to the incomplete development of uterus whereas CA125 was raised in 3 cases. Conclusions: Findings showed that the serum level of HE4 is an important indicator in the diagnosis of ovarian cancer, and it also distinguishes between benign and malignant pelvic masses. However, a combination of HE4 and CA125 panel will be extremely valuable in improving the diagnostic efficiency of ovarian cancer. These findings of our study need to be validated in the larger cohort of patients.

Keywords: human epididymis protein 4, ovarian cancer, diagnosis, benign lesions

Procedia PDF Downloads 131

Authors: Ahmed Ait Hou

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The wing leading edge and nose cone of the space shuttle are fabricated from a reinforced carbon/carbon material. This material attains its durability from a diffusion coating of silicon carbide (SiC) and a glass sealant. During re-entry into the atmosphere, this material is subject to an oxidizing high-temperature environment. The use of thermochemical calculations resulting at the HSC CHEMISTRY software and its database allows us to interpret the phenomena of oxidation and chloridation observed on the wing leading edge and nose cone of the space shuttle during its mission in space. First study is the monitoring of the oxidation reaction of SiC. It has been demonstrated that thermal oxidation of the SiC gives the two compounds SiO₂(s) and CO(g). In the extreme conditions of very low oxygen partial pressures and high temperatures, there is a reaction between SiC and SiO₂, leading to SiO(g) and CO(g). We had represented the phase stability diagram of Si-C-O system calculated by the use of the HSC Chemistry at 1300°C. The principal characteristic of this diagram of predominance is the line of SiC + SiO₂ coexistence. Second study is the monitoring of the chloridation reaction of SiC. The other problem encountered in addition to oxidation is the phenomenon of chloridation due to the presence of NaCl. Indeed, after many missions, the leading edge wing surfaces have exhibited small pinholes. We have used the HSC Chemistry database to analyze these various reactions. Our calculations concorde with the phenomena we announced in research work resulting in NASA LEWIS Research center.

Keywords: thermochchemicals calculations, HSC software, oxidation and chloridation, wings in space

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Authors: Azam Tabatabaee, Fereshteh Dastgoshadeh, Akram Tabatabaee

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This paper describes the use of by-products as adsorbents for removing heavy metals from aqueous effluent solutions. Products of almond skin, walnut shell, saw dust, rice bran and egg shell were evaluated as metal ion adsorbents in aqueous solutions. A comparative study was done with commercial adsorbents like ion exchange resins and activated carbon too. Batch experiments were investigated to determine the affinity of all of biomasses for, Cd(ΙΙ), Cr(ΙΙΙ), Ni(ΙΙ), and Pb(ΙΙ) metal ions at pH 5. The rate of metal ion removal in the synthetic wastewater by the biomass was evaluated by measuring final concentration of synthetic wastewater. At a concentration of metal ion (50 mg/L), egg shell adsorbed high levels (98.6 – 99.7%) of Pb(ΙΙ) and Cr(ΙΙΙ) and walnut shell adsorbed high levels (35.3 – 65.4%) of Ni(ΙΙ) and Cd(ΙΙ). In this study, it has been shown that by-products were excellent adsorbents for removal of toxic ions from wastewater with efficiency comparable to commercially available adsorbents, but at a reduced cost. Also statistical studies using Independent Sample t Test and ANOVA Oneway for statistical comparison between various elements adsorption showed that there isn’t a significant difference in some elements adsorption percentage by by-products and commercial adsorbents.

Keywords: adsorbents, heavy metals, commercial adsorbents, wastewater, by-products

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Authors: Gurjeet Singh, Rabindra K. Panda

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Soil moisture is a key hydrologic state variable and is intrinsically linked to the Earth's water, climate and carbon cycles. On ecological point of view, the soil moisture is a fundamental natural resource providing the transpirable water for plants. Soil moisture varies both temporally and spatially due to spatiotemporal variation in rainfall, vegetation cover, soil properties and topography. Satellite derived soil moisture provides spatio-temporal extensive data. However, the spatial resolution of a typical satellite (L-band radiometry) is of the order of tens of kilometers, which is not good enough for developing efficient agricultural water management schemes at the field scale. In the present study, the soil moisture from radiometer data has been disaggregated using blending approach to achieve higher resolution soil moisture data. The radiometer estimates of soil moisture at a 40 km resolution have been disaggregated to 10 km, 5 km and 1 km resolutions. The disaggregated soil moisture was compared with the observed data, consisting of continuous sensor based soil moisture profile measurements, at three monitoring sites and extensive spatial near-surface soil moisture measurements, concurrent with satellite monitoring in the 500 km2 study watershed in the Eastern India. The estimated soil moisture status at different spatial scales can help in developing efficient agricultural water management schemes to increase the crop production and water use efficiency.

Keywords: disaggregation, eastern India, radiometers, soil moisture, water use efficiency

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Authors: Osama Sassi, Manal Eltorki, Iftikhar Ahmad

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Poor integrity is one of the major causes of leaks and accidents in gas transmission pipelines. To ensure safe operation, it is must to have efficient and effective pipeline integrity management (PIM) system. The corrosion management is one of the important aspects of successful pipeline integrity management program together design, material selection, operations, risk evaluation and communication aspects to maintain pipelines in a fit-for-service condition. The objective of a corrosion management plan is to design corrosion mitigation, monitoring, and inspection strategy, and for maintenance in a timely manner. This paper presents the experience of corrosion management of a gas transmission pipeline from Wafa field to Mellitah gas plant in Libya. The pipeline is 525.5 km long and having 32 inches diameter. It is a buried pipeline. External corrosion on pipeline is controlled with a combination of coatings and cathodic protection while internal corrosion is controlled with a combination of chemical inhibitors, periodic cleaning and process control. The monitoring and inspection techniques provide a way to measure the effectiveness of corrosion control systems and provide an early warning when changing conditions may be causing a corrosion problem. This paper describes corrosion management system used in Mellitah Oil & Gas BV for its gas transmission pipeline based on standard practices of corrosion mitigation and inspection.

Keywords: corrosion mitigation on gas transmission pipelines, pipeline integrity management, corrosion management of gas pipelines, prevention and inspection of corrosion

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Authors: Armanul Hoque Shaon, Md Baizid Mahmud, Askander Nobi, Md. Raju Ahmed, Md. Jiabul Hoque

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In the Internet of Things (IoT), devices are linked to the internet through a wireless network, allowing them to collect and transmit data without the need for a human operator. Agriculture relies heavily on wireless sensors, which are a vital component of the Internet of Things (IoT). This kind of wireless sensor network monitors physical or environmental variables like temperatures, sound, vibration, pressure, or motion without relying on a central location or sink and collaboratively passes its data across the network to be analyzed. As the primary source of plant nutrients, the soil is critical to the agricultural industry's continued growth. We're excited about the prospect of developing an Internet of Things (IoT) solution. To arrange the network, the sink node collects groundwater levels and sends them to the Gateway, which centralizes the data and forwards it to the sensor nodes. The sink node gathers soil moisture data, transmits the mean to the Gateways, and then forwards it to the website for dissemination. The web server is in charge of storing and presenting the moisture in the soil data to the web application's users. Soil characteristics may be collected using a networked method that we developed to improve rice production. Paddy land is running out as the population of our nation grows. The success of this project will be dependent on the appropriate use of the existing land base.

Keywords: IoT based agriculture monitoring, intelligent irrigation, communicating network, rice production

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Authors: Haiyan Wu, Ying Liu, Shaoyun Shi

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Authorship attribution is to extract features to identify authors of anonymous documents. Many previous works on authorship attribution focus on statistical style features (e.g., sentence/word length), content features (e.g., frequent words, n-grams). Modeling these features by regression or some transparent machine learning methods gives a portrait of the authors' writing style. But these methods do not capture the syntactic (e.g., dependency relationship) or semantic (e.g., topics) information. In recent years, some researchers model syntactic trees or latent semantic information by neural networks. However, few works take them together. Besides, predictions by neural networks are difficult to explain, which is vital in authorship attribution tasks. In this paper, we not only utilize the statistical style and content features but also take advantage of both syntactic and semantic features. Different from an end-to-end neural model, feature selection and prediction are two steps in our method. An attentive n-gram network is utilized to select useful features, and logistic regression is applied to give prediction and understandable representation of writing style. Experiments show that our extracted features can improve the state-of-the-art methods on three benchmark datasets.

Keywords: authorship attribution, attention mechanism, syntactic feature, feature extraction

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Authors: Samir Chawdhury, Guido Morgenthal

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The paper presents a novel extension of Vortex Particle Methods (VPM) where the study aims to reproduce a template simulation of complex flow field that is generated from impulsively started flow past an upstream bluff body at certain Reynolds number Re-Vibration of a structural system under upstream wake flow is often considered its governing design criteria. Therefore, the attention is given in this study especially for the reproduction of wake flow simulation. The basic methodology for the implementation of the flow reproduction requires the downstream velocity sampling from the template flow simulation; therefore, at particular distances from the upstream section the instantaneous velocity components are sampled using a series of square sampling-cells arranged vertically where each of the cell contains four velocity sampling points at its corner. Since the grid free Lagrangian VPM algorithm discretises vorticity on particle elements, the method requires transformation of the velocity components into vortex circulation, and finally the simulation of the reproduction of the template flow field by seeding these vortex circulations or particles into a free stream flow. It is noteworthy that the vortex particles have to be released into the free stream exactly at same rate of velocity sampling. Studies have been done, specifically, in terms of different sampling rates and velocity sampling positions to find their effects on flow reproduction quality. The quality assessments are mainly done, using a downstream flow monitoring profile, by comparing the characteristic wind flow profiles using several statistical turbulence measures. Additionally, the comparisons are performed using velocity time histories, snapshots of the flow fields, and the vibration of a downstream bluff section by performing wake buffeting analyses of the section under the original and reproduced wake flows. Convergence study is performed for the validation of the method. The study also describes the possibilities how to achieve flow reproductions with less computational effort.

Keywords: vortex particle method, wake flow, flow reproduction, wake buffeting analysis

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Authors: Peter Shi

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Algorithmic trading is a rapidly expanding domain within quantitative finance, constituting a substantial portion of trading volumes in the US financial market. The demand for rigorous and robust mathematical theories underpinning these trading algorithms is ever-growing. In this study, the author establishes a new stock market model that integrates the Efficient Market Hypothesis and the statistical arbitrage. The model, for the first time, finds probabilistic relations between the rational price and the market price in terms of the conditional expectation. The theory consequently leads to a mathematical justification of the old market adage: buy-low and sell-high. The thresholds for “low” and “high” are precisely derived using a max-min operation on Bayes’s error. This explicit connection harmonizes the Efficient Market Hypothesis and Statistical Arbitrage, demonstrating their compatibility in explaining market dynamics. The amalgamation represents a pioneering contribution to quantitative finance. The study culminates in comprehensive numerical tests using historical market data, affirming that the “buy-low” and “sell-high” algorithm derived from this theory significantly outperforms the general market over the long term in four out of six distinct market environments.

Keywords: efficient market hypothesis, behavioral finance, Bayes' decision, algorithmic trading, risk control, stock market

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Authors: S. Colclough, V. Costanzo, K. Fabbri, S. Piraccini, P. Griffiths

Abstract:

The near Zero Energy Building (nZEB) standard is required for all buildings from 2020. The Passive House (PH) standard is a well-established low-energy building standard, having been designed over 25 years ago, and could potentially be used to achieve the nZEB standard in combination with renewables. By comparing measured performance with design predictions, this paper considers if there is a performance gap for a number of monitored properties and assesses if the nZEB standard can be achieved by following the well-established PH scheme. Analysis is carried out based on monitoring results from real buildings located in Northern Ireland, the Republic of Ireland and Italy respectively, with particular focus on the indoor air quality including the assumed and measured indoor temperature and heating periods for both standards as recorded during a full annual cycle. An analysis is carried out also on the energy performance certificates of each of the dwellings to determine if they meet the near Zero Energy Buildings primary energy consumption targets set in the respective jurisdictions. Each of the dwellings is certified as complying with the passive house standard, and accordingly have very good insulation levels, heat recovery and ventilation systems of greater than 75% efficiency and an airtightness of less than 0.6 air changes per hour at 50 Pa. It is found that indoor temperature and relative humidity were within the comfort boundaries set in the design stage, while carbon dioxide concentrations are sometimes higher than the values suggested by EN 15251 Standard for comfort class I especially in bedrooms.

Keywords: monitoring campaign, nZEB (near zero energy buildings), Passivhaus, performance gap

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Authors: Deepak Singh, Rail Kuliev

Abstract:

This research article explores the significance of advanced data visualization techniques in enhancing decision-making processes within the oil and gas exploration and production domain. With the oil and gas industry facing numerous challenges, effective interpretation and analysis of vast and diverse datasets are crucial for optimizing exploration strategies, production operations, and risk assessment. The article highlights the importance of data visualization in managing big data, aiding the decision-making process, and facilitating communication with stakeholders. Various advanced data visualization techniques, including 3D visualization, augmented reality (AR), virtual reality (VR), interactive dashboards, and geospatial visualization, are discussed in detail, showcasing their applications and benefits in the oil and gas sector. The article presents case studies demonstrating the successful use of these techniques in optimizing well placement, real-time operations monitoring, and virtual reality training. Additionally, the article addresses the challenges of data integration and scalability, emphasizing the need for future developments in AI-driven visualization. In conclusion, this research emphasizes the immense potential of advanced data visualization in revolutionizing decision-making processes, fostering data-driven strategies, and promoting sustainable growth and improved operational efficiency within the oil and gas exploration and production industry.

Keywords: augmented reality (AR), virtual reality (VR), interactive dashboards, real-time operations monitoring

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Authors: Farzana Esmailkassam, Usakorn Kunanuvat, Zahraa Mohammed Ali

Abstract:

Objective: The key barrier in Clozapine treatment of treatment-resistant schizophrenia (TRS) includes frequent bloods draws to monitor neutropenia, the main drug side effect. WBC and ANC monitoring must occur throughout treatment. Accurate WBC and ANC counts are necessary for clinical decisions to halt, modify or continue clozapine treatment. The CSAN Pronto point-of-care (POC) analyzer generates white blood cells (WBC) and absolute neutrophils (ANC) through image analysis of capillary blood. POC monitoring offers significant advantages over central laboratory testing. This study evaluated the performance of the CSAN Pronto against the Beckman DxH900 Hematology laboratory analyzer. Methods: Forty venous samples (EDTA whole blood) with varying concentrations of WBC and ANC as established on the DxH900 analyzer were tested in duplicates on three CSAN Pronto analyzers. Additionally, both venous and capillary samples were concomitantly collected from 20 volunteers and assessed on the CSAN Pronto and the DxH900 analyzer. The analytical performance including precision using liquid quality controls (QCs) as well as patient samples near the medical decision points, and linearity using a mix of high and low patient samples to create five concentrations was also evaluated. Results: In the precision study for QCs and whole blood, WBC and ANC showed CV inside the limits established according to manufacturer and laboratory acceptability standards. WBC and ANC were found to be linear across the measurement range with a correlation of 0.99. WBC and ANC from all analyzers correlated well in venous samples on the DxH900 across the tested sample ranges with a correlation of > 0.95. Mean bias in ANC obtained on the CSAN pronto versus the DxH900 was 0.07× 109 cells/L (95% L.O.A -0.25 to 0.49) for concentrations <4.0 × 109 cells/L, which includes decision-making cut-offs for continuing clozapine treatment. Mean bias in WBC obtained on the CSAN pronto versus the DxH900 was 0.34× 109 cells/L (95% L.O.A -0.13 to 0.72) for concentrations <5.0 × 109 cells/L. The mean bias was higher (-11% for ANC, 5% for WBC) at higher concentrations. The correlations between capillary and venous samples showed more variability with mean bias of 0.20 × 109 cells/L for the ANC. Conclusions: The CSAN pronto showed acceptable performance in WBC and ANC measurements from venous and capillary samples and was approved for clinical use. This testing will facilitate treatment decisions and improve clozapine uptake and compliance.

Keywords: absolute neutrophil counts, clozapine, point of care, white blood cells

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Authors: Dada Durojaye Joshua

Abstract:

The study examined the combined effect of internal control system and whistle blowing policy while it pursues the following specific objectives, which are to: examine the relationship between monitoring activities and fraud’s detection and prevention; investigate the effect of control activities on fraud’s detection and prevention in Nigerian Deposit Money Banks (DMBs). The population of the study comprises the 89,275 members of staff in the 20 DMBs in Nigeria as at June 2019. Purposive and convenient sampling techniques were used in the selection of the 80 members of staff at the supervisory level of the Internal Audit Departments of the head offices of the sampled banks, that is, selecting 4 respondents (Audit Executive/Head, Internal Control; Manager, Operation Risk Management; Head, Financial Crime Control; the Chief Compliance Officer) from each of the 20 DMBs in Nigeria. A standard questionnaire was adapted from 2017/2018 Internal Control Questionnaire and Assessment, Bureau of Financial Monitoring and Accountability Florida Department of Economic Opportunity. It was modified to serve the purpose for which it was meant to serve. It was self-administered to gather data from the 80 respondents at the respective headquarters of the sampled banks at their respective locations across Nigeria. Two likert-scales was used in achieving the stated objectives. A logit regression was used in analysing the stated hypotheses. It was found that effect of monitoring activities using the construct of conduct of ongoing or separate evaluation (COSE), evaluation and communication of deficiencies (ECD) revealed that monitoring activities is significant and positively related to fraud’s detection and prevention in Nigerian DMBS. So also, it was found that control activities using selection and development of control activities (SDCA), selection and development of general controls over technology to prevent financial fraud (SDGCTF), development of control activities that gives room for transparency through procedures that put policies into actions (DCATPPA) contributed to influence fraud detection and prevention in the Nigerian DMBs. In addition, it was found that transparency, accountability, reliability, independence and value relevance have significant effect on fraud detection and prevention ibn Nigerian DMBs. The study concluded that the board of directors demonstrated independence from management and exercises oversight of the development and performance of internal control. Part of the conclusion was that there was accountability on the part of the owners and preparers of the financial reports and that the system gives room for the members of staff to account for their responsibilities. Among the recommendations was that the management of Nigerian DMBs should create and establish a standard Internal Control System strong enough to deter fraud in order to encourage continuity of operations by ensuring liquidity, solvency and going concern of the banks. It was also recommended that the banks create a structure that encourages whistleblowing to complement the internal control system.

Keywords: internal control, whistleblowing, deposit money banks, fraud prevention, fraud detection

Procedia PDF Downloads 80

Authors: Indu Chandran, Shubham Sharma, Rohan Mehta, Vipin Kizheppatt

Abstract:

Unmanned aerial vehicles are increasingly being explored as the most promising solution to disaster monitoring, assessment, and recovery. Current relief operations heavily rely on intelligent robot swarms to capture the damage caused, provide timely rescue, and create road maps for the victims. To perform these time-critical missions, efficient path planning that ensures quick coverage of the area is vital. This study aims to develop a technically balanced approach to provide maximum coverage of the affected area in a minimum time using the optimal number of UAVs. A coverage trajectory is designed through area decomposition and task assignment. To perform efficient and autonomous coverage mission, solution to a TSP-based optimization problem using meta-heuristic approaches is designed to allocate waypoints to the UAVs of different flight capacities. The study exploits multi-agent simulations like PX4-SITL and QGroundcontrol through the ROS framework and visualizes the dynamics of UAV deployment to different search paths in a 3D Gazebo environment. Through detailed theoretical analysis and simulation tests, we illustrate the optimality and efficiency of the proposed methodologies.

Keywords: area coverage, coverage path planning, heuristic algorithm, mission monitoring, optimization, task assignment, unmanned aerial vehicles

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Authors: Lingling Shui, Shuting Xie

Abstract:

As alternatives to electronic devices, optically active structures from responsive nanomaterials offer great opportunity buildup smart functional sensors. Hereby, we report on droplet microfluidics enabled construction and application of photonic microcapsules (PMCs) for colorimetric temperature microsensors, enabling miniaturization for injectable local micro-area sensing and integration for large-area sensing. Monodispersed PMCs are produced by in-situ photopolymerization of hydrogel shells of cholesteric liquid crystal (CLC)-in-water-in-oil double emulsion droplets prepared using microfluidic devices, with controllable physical structures and chemical compositions. Constructed PMCs exhibit thermal responsive structural color according to the selective Bragg reflection of CLC’s periodical helical structures within the microdroplet’s spherical confinement. Constructed PMCs with tunable size and composition have been successfully applied for monitoring the living cell extracellular temperature via co-incubation with cell suspension, and for detecting human body temperature via a flexible device from assembled PMCs. These PMCs could be flexibly applied in either micro-environment or large-area surface, enabling wide applications for precision temperature monitoring biological activities (e.g. cells or organs), optoelectronic devices working conditions (e.g. temperature indicators under extreme conditions), and etc.

Keywords: droplet, microfluidics, assembly, soft materials, microsensor

Procedia PDF Downloads 81

Authors: Dada Durojaye Joshua

Abstract:

The study examined the combined effect of internal control system and whistle blowing policy while it pursues the following specific objectives, which are to: examine the relationship between monitoring activities and fraud’s detection and prevention; investigate the effect of control activities on fraud’s detection and prevention in Nigerian Deposit Money Banks (DMBs). The population of the study comprises the 89,275 members of staff in the 20 DMBs in Nigeria as at June 2019. Purposive and convenient sampling techniques were used in the selection of the 80 members of staff at the supervisory level of the Internal Audit Departments of the head offices of the sampled banks, that is, selecting 4 respondents (Audit Executive/Head, Internal Control; Manager, Operation Risk Management; Head, Financial Crime Control; the Chief Compliance Officer) from each of the 20 DMBs in Nigeria. A standard questionnaire was adapted from 2017/2018 Internal Control Questionnaire and Assessment, Bureau of Financial Monitoring and Accountability Florida Department of Economic Opportunity. It was modified to serve the purpose for which it was meant to serve. It was self-administered to gather data from the 80 respondents at the respective headquarters of the sampled banks at their respective locations across Nigeria. Two likert-scales was used in achieving the stated objectives. A logit regression was used in analysing the stated hypotheses. It was found that effect of monitoring activities using the construct of conduct of ongoing or separate evaluation (COSE), evaluation and communication of deficiencies (ECD) revealed that monitoring activities is significant and positively related to fraud’s detection and prevention in Nigerian DMBS. So also, it was found that control activities using selection and development of control activities (SDCA), selection and development of general controls over technology to prevent financial fraud (SDGCTF), development of control activities that gives room for transparency through procedures that put policies into actions (DCATPPA) contributed to influence fraud detection and prevention in the Nigerian DMBs. In addition, it was found that transparency, accountability, reliability, independence and value relevance have significant effect on fraud detection and prevention ibn Nigerian DMBs. The study concluded that the board of directors demonstrated independence from management and exercises oversight of the development and performance of internal control. Part of the conclusion was that there was accountability on the part of the owners and preparers of the financial reports and that the system gives room for the members of staff to account for their responsibilities. Among the recommendations was that the management of Nigerian DMBs should create and establish a standard Internal Control System strong enough to deter fraud in order to encourage continuity of operations by ensuring liquidity, solvency and going concern of the banks. It was also recommended that the banks create a structure that encourages whistleblowing to complement the internal control system.

Keywords: internal control, whistleblowing, deposit money banks, fraud prevention, fraud detection

Procedia PDF Downloads 72