Search results for: real time control

Authors: S. Alqarni, J. C. McCann, A. Palladino, J. J. Loor

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Seven fistulated Holstein cows were used from 3 weeks prepartum to 4 weeks postpartum to determine the relative abundance of 7 different species of ruminal microorganisms. The prepartum diet was based on corn silage. In the postpartum, diet included ground corn, grain by-products, and alfalfa haylage. Ruminal digesta were collected at five times: -14, -7, 10, 20, and 28 days around parturition. Total DNA from ruminal digesta was isolated and real-time quantitative PCR was used to determine the relative abundance of bacterial species. Eubacterium ruminantium and Selenomonas ruminantium were not affected by time (P>0.05). Megasphaera elsdenii and Prevotella bryantii increased significantly postpartum (P<0.001). Conversely, Butyrivibrio proteoclasticus decreased gradually from -14 through 28 days (P<0.001). Fibrobacter succinogenes was affected by time being lowest at day 10 (P=0.02) while Anaerovibrio lipolytica recorded the lowest abundance at -7 d followed by an increase by 20 days postpartum (P<0.001). Overall, these results indicate that changes in diet after parturition affect the abundance of ruminal bacteria, particularly M. elsdenii (a lactate-utilizing bacteria) and P. bryantii (a starch-degrading bacteria) which increased markedly after parturition likely as a consequence of a higher concentrate intake.

Keywords: rumen bacteria, transition cows, rumen metabolism, peripartal period

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Authors: Wang Yanping Karen, Mohd Rafeah Siti, Park MI Kyoung

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Formalin-fixed paraffin embedded (FFPE) tissue is important in the area of oncological diagnostics. This method of preserving tissues enabling them to be stored easily at ambient temperature for a long time. This decreases the risk of losing the DNA quantity and quality after extraction, reducing sample wastage, and making FFPE more cost effective. However, extracting DNA from FFPE tissue is a challenge as DNA purified is often highly cross-linked, fragmented, and degraded. In addition, this causes problems for many downstream processes. In this study, there will be a comparison of DNA extraction efficiency between One BioMed’s Xceler8 automated platform with commercial available extraction kits (Qiagen and Roche). The FFPE tissue slices were subjected to deparaffinization process, pretreatment and then DNA extraction using the three mentioned platforms. The DNA quantity were determined with real-time PCR (BioRad CFX ) and gel electrophoresis. The amount of DNA extracted with the One BioMed’s X8 platform was found to be comparable with the other two manual extraction kits.

Keywords: DNA extraction, FFPE tissue, qiagen, roche, one biomed X8

Procedia PDF Downloads 109

Authors: Nor Asrina Binti Ramlee

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Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: power quality, voltage sag, voltage swell, wavelet transform

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Authors: J. J. Vargas, N. Prieto, L. A. Toro

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Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

Procedia PDF Downloads 377

Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: Sergio Saponara, Luca Fanucci, Riccardo Cassettari, Ruggero Piernicola, Marco Righetto

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The paper presents an innovative networked radar system for detection of obstacles in a railway level crossing scenario. This Monitoring System (MS) is able to detect moving or still obstacles within the railway level crossing area automatically, avoiding the need of human presence for surveillance. The MS is also connected to the National Railway Information and Signaling System to communicate in real-time the level crossing status. The architecture is compliant with the highest Safety Integrity Level (SIL4) of the CENELEC standard. The number of radar sensors used is configurable at set-up time and depends on how large the level crossing area can be. At least two sensors are expected and up four can be used for larger areas. The whole processing chain that elaborates the output sensor signals, as well as the communication interface, is fully-digital, was designed in VHDL code and implemented onto a Xilinx Virtex 6.

Keywords: radar for safe mobility, railroad crossing, railway, transport safety

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Authors: Camila Plaza, Stefan Felder

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In October 2014, the TARMED reform was implemented in Switzerland. In an effort to even out the financial standing of general practitioners (including pediatricians) relative to that of specialists in the outpatient sector, the reform tackled two aspects: on the one hand, GPs would be able to bill an additional 9 CHF per patient, once per consult per day. This is referred to as the surcharge position. As a second measure, it reduced the fees for certain technical services targeted to specialists (e.g., imaging, surgical technical procedures, etc.). Given the fee-for-service reimbursement system in Switzerland, we predict that physicians reacted to the economic incentives of the reform by increasing the consults per patient and decreasing the average amount of time per consult. Within this framework, our treatment group is formed by GPs and our control group by those specialists who were not affected by the reform. Using monthly insurance claims panel data aggregated at the physician praxis level (provided by SASIS AG), for the period of January 2013-December 2015, we run difference in difference panel data models with physician and time fixed effects in order to test for the causal effects of the reform. We account for seasonality, and control for physician characteristics such as age, gender, specialty, and physician experience. Furthermore, we run the models on subgroups of physicians within our sample so as to account for heterogeneity and treatment intensities. Preliminary results support our hypothesis. We find evidence of an increase in consults per patients and a decrease in time per consult. Robustness checks do not significantly alter the results for our outcome variable of consults per patient. However, we do find a smaller effect of the reform for time per consult. Thus, the results of this paper could provide policymakers a better understanding of physician behavior and their sensitivity to financial incentives of reforms (both past and future) under the current reimbursement system.

Keywords: difference in differences, financial incentives, health reform, physician behavior

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Authors: Beruk Berhanu Desalegn, Gelana Mulu

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Adolescence, especially for females, is a period of an ongoing risk behavior that triggers development of adverse health outcomes during adulthood. This study aimed to investigate the weight control practice and its associated factors among high school female-adolescents in Hawassa town, Ethiopia. A school-based cross-sectional study was conducted on 552 female-adolescents in Hawassa town. The study was conducted between December, 2020 to January, 2021. SPSS version 26 was used to analyse the data from the pre-tested questionnaire of socio-demographic, economic, socio-cultural, and related information. Among the total female-adolescents, 38.6% [95% CI= 34.5-42.8%] took on weight control practices. The study further revealed the condition of the weight control practice to be healthy (20.5%), unhealthy(25.9%, and the rest to be both healthyand unhealthy(7.8%). The multivariate regression model, cutoff p < 0.05, disclosed that predicters like late adolescent age [AOR=1.98; 95% CI=1.33-2.95], middle wealth status [AOR=2.72; 95% CI=1.60-4.63], high wealth status [AOR=5.69; 95% CI=3.43-9.46], normal BMI [AOR=2.36; 95% CI=1.18-4.71], overweight [AOR=2.45; 95% CI=1.13-5.28], mild depression [AOR=1.72; 95% CI=1.12-2.66] and dissatisfied own mid-torso body image [AOR=2.68; 95% CI=1.52-4.73] were found to have significant association with weight control practice. Therefore, it may be benefiting to consider the findings of this study for interventions associated with female adolescents weight control practices.

Keywords: female-adolescents, highschool, weight control practice, Ethiopia

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Authors: N. Sateesh, C. S. P. Rao, K. Satyanarayana, C. Rajashekar

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This paper proposes a development of a CAD/CAM system for complex profiles of various machine members using a synthetic curve i.e. B-spline. Conventional methods in designing and manufacturing of complex profiles are tedious and time consuming. Even programming those on a computer numerical control (CNC) machine can be a difficult job because of the complexity of the profiles. The system developed provides graphical and numerical representation B-spline profile for any given input. In this paper, the system is applicable to represent a cam profile with B-spline and attempt is made to improve the follower motion.

Keywords: plate-cams, cam profile, b-spline, computer numerical control (CNC), computer aided design and computer aided manufacturing (CAD/CAM), R-D-R-D (rise-dwell-return-dwell)

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Authors: Shilpa Balan

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Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

Procedia PDF Downloads 235

Authors: Marcel Heimar Ribeiro Utiyama, Fernanda Caveiro Correia, Dario Henrique Alliprandini

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The importance of the correct allocation of improvement programs is of growing interest in recent years. Due to their limited resources, companies must ensure that their financial resources are directed to the correct workstations in order to be the most effective and survive facing the strong competition. However, to our best knowledge, the literature about allocation of improvement programs does not analyze in depth this problem when the flow shop process has two capacity constrained resources. This is a research gap which is deeply studied in this work. The purpose of this work is to identify the best strategy to allocate improvement programs in a flow shop with two capacity constrained resources. Data were collected from a flow shop process with seven workstations in an industrial control and automation company, which process 13.690 units on average per month. The data were used to conduct a simulation with the System Dynamics-Factory Physics model. The main variables considered, due to their importance on lead time reduction, were the mean time between failures and the mean time to repair. The lead time reduction was the output measure of the simulations. Ten different strategies were created: (i) focused time to repair improvement, (ii) focused time between failures improvement, (iii) distributed time to repair improvement, (iv) distributed time between failures improvement, (v) focused time to repair and time between failures improvement, (vi) distributed time to repair and between failures improvement, (vii) hybrid time to repair improvement, (viii) hybrid time between failures improvements, (ix) time to repair improvement strategy towards the two capacity constrained resources, (x) time between failures improvement strategy towards the two capacity constrained resources. The ten strategies tested are variations of the three main strategies for improvement programs named focused, distributed and hybrid. Several comparisons among the effect of the ten strategies in lead time reduction were performed. The results indicated that for the flow shop analyzed, the focused strategies delivered the best results. When it is not possible to perform a large investment on the capacity constrained resources, companies should use hybrid approaches. An important contribution to the academy is the hybrid approach, which proposes a new way to direct the efforts of improvements. In addition, the study in a flow shop with two strong capacity constrained resources (more than 95% of utilization) is an important contribution to the literature. Another important contribution is the problem of allocation with two CCRs and the possibility of having floating capacity constrained resources. The results provided the best improvement strategies considering the different strategies of allocation of improvement programs and different positions of the capacity constrained resources. Finally, it is possible to state that both strategies, hybrid time to repair improvement and hybrid time between failures improvement, delivered best results compared to the respective distributed strategies. The main limitations of this study are mainly regarding the flow shop analyzed. Future work can further investigate different flow shop configurations like a varying number of workstations, different number of products or even different positions of the two capacity constrained resources.

Keywords: allocation of improvement programs, capacity constrained resource, hybrid strategy, lead time, mean time to repair, mean time between failures

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Authors: Aydan Atalar, Nurcan Cetinkaya

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Corn stover is leftover of the leaves, stalk, husks and tassels in the field after harvesting the grain combined. Corn stover is a low-quality roughage but has mostly been used as roughage source for feeding ruminant animals in developing countries including Turkey; however, it can also be used to make biofuels as in developed countries. The objectives of the present study were to improve the digestibility of corn stover by the treatment of white rod fungus mainly Pleurotus osteritus (PO), Pleurotus eryingii (PE) and Lantinula edudes (LE) at different incubation times and also to determine the most effective fungus and incubation time to prepare fermeted corn stover for ruminant nutrition. The choped corn stover was treated with PO, PE and LE and incubated for 10, 20, 30 and 40 days in incubator at 26 0C. After each incubation time dry matter(DM), organic matter(OM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), neutral detergent lignin (ADL), in-vitro true dry matter digestibility (IVTDMD) and organic matter digestibility (IVTOMD) were determined. The mean IVTDMD and IVTOMD levels were increased by PO, PE and LE treatments in increasing order of incubation times. The obtained IVTDM values were 59.45, 60.51, 60.82 and 60.18 %; 59.45, 70.55, 67.18 and 66.96 %; 59.45, 70.55, 67.18 and 66,96 %; 59.45, 74.90, 69.18 % ; 59.45, 76.50, 71.24 and 73.04 for control, PO, PE and LE treatments at 0, 10, 20, 30 and 40 days incubation times respectively. The obtained IVTOMD values were 56.45,60.26,60.82and 60.18 %; 56.45, 68.70, 67.18 and 66.96 %; 56.45, 71.26, 69.18 and 69.28 %; 56.45, 73.23, 71.24 and 73.04 % for control, PO, PE and LE treatments at 0, 10, 20, 30 and 40 days incubation times respectively. The most effective fungus was PO and the incubation time was 30 days. In conclusion, PO treatment of corn stover with 30 days incubation may be used to prepare fermented corn stover for ruminant nutrition.

Keywords: biological treatment, corn stover, digestibility, Lantinula edudes, Pleurotus eryingii, Pleurotus osteritus

Procedia PDF Downloads 248

Authors: Anna Amato

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Every child needs communication. If spoken language is not or not fully available due to congenital or acquired limitations, those affected need appropriate ways. These can be found in many possibilities of Augmentative and Alternative Communications (AAC). In the communication promotion of severely impaired children, who can use their own body communication forms only to a limited extent for the differentiated understanding, computers with eye control play an essential role. It takes some time to understand the individual forms of communication of the child. Children who depend on the AAC need competent support to learn to communicate in a motivated way in their everyday life. The aim of the present parents' survey (n = 4), which was evaluated descriptively, is to demonstrate the development of communicative abilities as well as the motivation to use complex communication aids with eye control by patients with atypical Rett Syndrome. An increase in communication skills, well-being, self-reliance, and self-esteem, an improvement in social participation, as well as a reduction in anger and screaming events, were noted. The complex visual communication tools were available daily for 3 out of 4 patients with atypical Rett Syndrome. It raises research questions regarding speech understanding and the ability to drive eye control technology in a larger group of atypical Rett Syndrome patients.

Keywords: augmentative and alternative communications, AAC, atypical Rett-syndrome, children, development

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Authors: Düzgün Akmaz, Hüseyin Erişti

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In the last few years, harmonics have been occurred with the increasing use of nonlinear loads, and these harmonics have been an ever increasing problem for the line systems. This situation importantly affects the quality of power and gives large losses to the network. An efficient way to solve these problems is providing harmonic compensation through parallel active power filters. Many methods can be used in the control systems of the parallel active power filters which provide the compensation. These methods efficiently affect the performance of the active power filters. For this reason, the chosen control method is significant. In this study, Fourier analysis (FA) control method and synchronous reference frame (SRF) control method are discussed. These control methods are designed for both eliminate harmonics and perform reactive power compensation in MATLAB/Simulink pack program and are tested. The results have been compared for each two methods.

Keywords: parallel active power filters, harmonic compensation, power quality, harmonics

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Authors: Mohammed Alrefaie, Yaser Miaji

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Greenhouses provide a convenient means to grow plants in the best environment. They achieve this by trapping heat from the sunlight and using artificial means to enhance the environment of the greenhouse. This includes controlling factors such as air flow, light intensity and amount of water among others that can have a big impact on plant growth. The aim of the greenhouse is to give maximum yield from plants possible. This report details the development and testing of greenhouse environment control system that can regulate light intensity, airflow and power supply inside the greenhouse. The details of the module development to control these three factors along with results of testing are presented.

Keywords: greenhouse, control system, light intensity, comprehensive environment

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Authors: Fernando L. P. Santos, Luiz G. Lyra, Helenice O. Florentino, Daniela R. Cantane

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Dengue is a febrile infectious disease caused by a virus of the family Flaviridae. It is transmitted by the bite of mosquitoes, usually of the genus Aedes aegypti. It occurs in tropical and subtropical areas of the world. This disease has been a major public health problem worldwide, especially in tropical countries such as Brazil, and its incidence has increased in recent years. Dengue is a subject of intense research. Efficient forms of mosquito control must be considered. In this work, the mono-objective optimal control problem was solved for analysing the dengue disease problem. Chemical and biological controls were considered in the mathematical aspect. This model describes the dynamics of mosquitoes in water and winged phases. We applied the genetic algorithms (GA) to obtain optimal strategies for the control of dengue. Numerical simulations have been performed to verify the versatility and the applicability of this algorithm. On the basis of the present results we may recommend the GA to solve optimal control problem with a large region of feasibility.

Keywords: genetic algorithm, dengue, Aedes aegypti, biological control, chemical control

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Authors: Jalal Eddine Benmansour, Khouane Boulanoir, Nacera Bekhadda, Elhassen Benfriha

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This paper introduces a novel composite control approach that addresses the challenge of stabilizing the three-axis attitude of a flexible satellite in the presence of vibrations caused by flexible appendages. The key contribution of this research lies in the development of a disturbance observer, which effectively observes and estimates the unwanted torques induced by the vibrations. By utilizing the estimated disturbance, the proposed approach enables efficient compensation for the detrimental effects of vibrations on the satellite system. To govern the attitude angles of the spacecraft, a proportional derivative controller (PD) is specifically designed and proposed. The PD controller ensures precise control over all attitude angles, facilitating stable and accurate spacecraft maneuvering. In order to demonstrate the global stability of the system, the Lyapunov method, a well-established technique in control theory, is employed. Through rigorous analysis, the Lyapunov method verifies the convergence of system dynamics, providing strong evidence of system stability. To evaluate the performance and efficacy of the proposed control algorithm, extensive simulations are conducted. The simulation results validate the effectiveness of the combined approach, showcasing significant improvements in the stabilization and control of the satellite's attitude, even in the presence of disruptive vibrations from flexible appendages. This novel composite control approach presented in this paper contributes to the advancement of satellite attitude control techniques, offering a promising solution for achieving enhanced stability and precision in challenging operational environments.

Keywords: attitude control, flexible satellite, vibration control, disturbance observer

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Authors: Jochen Edmund Kerschenbauer, Roman Salinger, Daniel Strametz

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Insufficient informal communication systems can lead to the first crisis (‘Crisis of Leadership’) for start-ups. Management Control Systems (MCS) are one way for high-technology start-ups to successfully overcome these problems. So far the literature has investigated the incubation of a start-up, but focused less on the post-incubation stage. This paper focuses on the use of MCS in post-incubation and, if failed start-ups agree, on how MCS are used. We conducted 14 semi-structured interviews for this purpose, to obtain our results. The overall conclusion is that the majority of the companies were closed down due to a combination of strategic, operative and financial reasons.

Keywords: closed down, high-technology, incubation, levers of control, management control systems, post-incubation, start-ups

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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Authors: Débora P. Jaeschke, Eduardo A. Merlo, Rosane Rech, Giovana D. Mercali, Ligia D. F. Marczak

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Carotenoids are high value added pigments that can be alternatively extracted from some microalgae species. However, the application of carotenoids synthetized by microalgae is still limited due to the utilization of organic toxic solvents. In this context, studies involving alternative extraction methods have been conducted with more sustainable solvents to replace and reduce the solvent volume and the extraction time. The aim of the present work was to evaluate the extraction time of carotenoids from the microalgae Heterochlorella luteoviridis using moderate electric field (MEF) as a pre-treatment to the extraction. The extraction methodology consisted of a pre-treatment in the presence of MEF (180 V) and ethanol (25 %, v/v) for 10 min, followed by a diffusive step performed for 50 min using a higher ethanol concentration (75 %, v/v). The extraction experiments were conducted at 30 °C and, to keep the temperature at this value, it was used an extraction cell with a water jacket that was connected to a water bath. Also, to enable the evaluation of MEF effect on the extraction, control experiments were performed using the same cell and conditions without voltage application. During the extraction experiments, samples were withdrawn at 1, 5 and 10 min of the pre-treatment and at 1, 5, 30, 40 and 50 min of the diffusive step. Samples were, then, centrifuged and carotenoids analyses were performed in the supernatant. Furthermore, an exhaustive extraction with ethyl acetate and methanol was performed, and the carotenoids content found for this analyses was considered as the total carotenoids content of the microalgae. The results showed that the application of MEF as a pre-treatment to the extraction influenced the extraction yield and the extraction time during the diffusive step; after the MEF pre-treatment and 50 min of the diffusive step, it was possible to extract up to 60 % of the total carotenoids content. Also, results found for carotenoids concentration of the extracts withdrawn at 5 and 30 min of the diffusive step did not presented statistical difference, meaning that carotenoids diffusion occurs mainly in the very beginning of the extraction. On the other hand, the results for control experiments showed that carotenoids diffusion occurs mostly during 30 min of the diffusive step, which evidenced MEF effect on the extraction time. Moreover, carotenoids concentration on samples withdrawn during the pre-treatment (1, 5 and 10 min) were below the quantification limit of the analyses, indicating that the extraction occurred in the diffusive step, when ethanol (75 %, v/v) was added to the medium. It is possible that MEF promoted cell membrane permeabilization and, when ethanol (75 %) was added, carotenoids interacted with the solvent and the diffusion occurred easily. Based on the results, it is possible to infer that MEF promoted the decrease of carotenoids extraction time due to the increasing of the permeability of the cell membrane which facilitates the diffusion from the cell to the medium.

Keywords: moderate electric field (MEF), pigments, microalgae, ethanol

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Authors: Souad Romdhane, Lotfi Belkacem

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When referring to actuarial analysis of lifetime, only models accounting for observable risk factors have been developed. Within this context, Cox proportional hazards model (CPH model) is commonly used to assess the effects of observable covariates as gender, age, smoking habits, on the hazard rates. These covariates may fail to fully account for the true lifetime interval. This may be due to the existence of another random variable (frailty) that is still being ignored. The aim of this paper is to examine the shared frailty issue in the Cox proportional hazard model by including two different parametric forms of frailty into the hazard function. Four estimated methods are used to fit them. The performance of the parameter estimates is assessed and compared between the classical Cox model and these frailty models through a real-life data set from the Quebec Pension Plan and then using a more general simulation study. This performance is investigated in terms of the bias of point estimates and their empirical standard errors in both fixed and random effect parts. Both the simulation and the real dataset studies showed differences between classical Cox model and shared frailty model.

Keywords: life insurance-pension plan, survival analysis, risk factors, cox proportional hazards model, multivariate failure-time data, shared frailty, simulations study

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Authors: Hamish Love, Navjot Bhullar, Nicola Schutte

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Self-control and related psychological constructs have been shown to have a large role in the improvement and maintenance of healthful dietary behaviour. However, self-control for diet, and related constructs such as motivation, level of conflict between tempting desires and dietary goals, and attentional bias for tempting food, have not been studied together to establish their relationships, to the author’s best knowledge. Therefore the aim of this paper was to conduct model testing on these constructs and evaluate how they relate to affect dietary outcomes. 400 Australian adult participants will be recruited via the Qualtrics platform and will be representative across age and gender. They will complete survey and reaction timing surveys to gather data on the five target constructs: Trait Self-control, Attentional Bias for Food, Dietary Goal-Desire Incongruence, Motivation for Dietary Self-control, and Satisfaction with Dietary Behaviour. A model of moderated mediation is predicted, whereby the initial predictor (Dietary Goal-Desire Incongruence) predicts the level of the outcome variable, Satisfaction with Dietary Behaviour. We hypothesise that the relationship between these two variables will be mediated by Trait Self-Control and that the extent that Trait Self-control is allowed to mediate dietary outcome is moderated by both Attentional Bias for Food and Motivation for Dietary Self-control. The analysis will be conducted using the PROCESS module in SPSS 23. The results of model testing in this current study will be valuable to direct future research and inform which constructs could be important targets for intervention to improve dietary outcomes.

Keywords: self-control, diet, model testing, attentional bias, motivation

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Authors: Nafisa Komilova, Plamena Angelova, Andrey Abramov, Ulugbek Mirkhodjaev

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Parkinson’s disease (PD) is a progressive neurodegenerative disorder which is induced by the loss of dopaminergic neurons in the midbrain. The mechanism of neurodegeneration is associated with the aggregation of misfolded proteins, oxidative stress, and mitochondrial disfunction. Considering this, the process of removal of unwanted organelles or proteins by autophagy is vitally important in neurons, and activation of these processes could be protective in PD. Short-time acidification of cytosol can activate mitophagy and autophagy, and here we used sodium pyruvate and sodium lactate in human fibroblasts with PD mutations (Pink1, Pink1/Park2, α-syn triplication, A53T) to induce changes in intracellular pH. We have found that both lactate and pyruvate in millimolar concentrations can induce short-time acidification of cytosol in these cells. It induced activation of mitophagy and autophagy in control and PD fibroblasts and protected against cell death. Importantly, the application of lactate to acute brain slices of control and Pink1 knockout mice also induced a reduction of pH in neurons and astrocytes that increase the level of mitophagy. Thus, acidification of cytosol by compounds which play important role in cell metabolism also can activate mitophagy and autophagy and protect cells in the familial form of PD.

Keywords: Parkinson's disease, mutations, mitophagy, autophagy

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Authors: Xinhuang Wu, Yousef Sardahi

Abstract:

A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: Wiyanti Fransisca Simanullang, Shinya Yamanaka

Abstract:

Grinding method was used to control the active site and to improve the specific surface area (SSA) of calcium oxide (CaO) derived from scallop shell as a sustainable resource. The dry grinding of CaO with acetone and tertiary butanol as a liquid additive was carried out using a planetary ball mill with a laboratory scale. The experiments were operated by stepwise addition with time variations to determine the grinding limit. The active site of CaO was measured by X-Ray Diffraction and FT-IR. The SSA variations of products with grinding time were measured by BET method. The morphology structure of CaO was observed by SEM. The use of liquid additive was effective for increasing the SSA and controlling the active site of CaO. SSA of CaO was increased in proportion to the amount of the liquid additive and the grinding time. The performance of CaO as a solid base catalyst for biodiesel production was tested in the transesterification reaction of used cooking oil to produce fatty acid methyl ester (FAME).

Keywords: active site, calcium oxide, grinding, specific surface area

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Authors: Kasbparast Mehdi, Hassani Zainab

Abstract:

Aim: The purpose of this research was to investigate the effectiveness of therapeutical sensorimotor exercise. The statistical population of women who were diagnosed with patellofemoral pain syndrome by a doctor and were between the ages of 35 and 45 and registered for the first time in a sports club in the 4th district of Tehran, 30 people by random sampling and according to The include and exclude criteria were selected and divided into 2 equal control and experimental and homogeneous groups (in terms of height, weight and BMI).In both control and experimental groups, the pain was measured using a Visual Analog Scale(VAS) functionality was measured using the step-down test and quality of life was measured using a World Health Organization Quality of Life Scale (WHOQOL-BREF) (pre-test). Then, only the experimental group performed sensorimotor exercises for 12 weeks and 3 sessions each week, a total of 24 sessions and each session for 1 hour, and during this period, the control group only continued their daily activities. After the end of the training period, the desired factors were evaluated again (post-test) in the same way as the pre-test was done for them (experimental group and control group), with the same quality. Findings: The statistical results showed that in the experimental group, the amount of pain, function and quality of life had a statistical improvement (P≤0.05). Conclusion: In general conclusion, it can be stated that using sensorimotor exercises not only improved functionality and quality of life but also reduced the amount of pain in people with patellofemoral pain syndrome.

Keywords: pain, PFPS, sensori motor training, functionality

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Authors: Abu Salim Mustafa

Abstract:

Brucellosis is a zoonotic disease endemic in Kuwait. Human brucellosis can be caused by several Brucella species with Brucella melitensis causing the most severe and Brucella abortus the least severe disease. Furthermore, relapses are common after successful chemotherapy of patients. The classical biochemical methods of culture and serology for identification of Brucellae provide information about the species and serotypes only. However, to differentiate between relapse and reinfection/epidemiological investigations, the identification of genotypes using molecular methods is essential. In this study, four molecular methods [16S rRNA gene sequencing, real-time PCR, enterobacterial repetitive intergenic consensus (ERIC)-PCR and multilocus variable-number tandem-repeat analysis (MLVA)-16] were evaluated for the identification and typing of 75 strains of Brucella isolated in Kuwait. The 16S rRNA gene sequencing suggested that all the strains were B. melitensis and real-time PCR confirmed their species identity as B. melitensis. The ERIC-PCR band profiles produced a dendrogram of 75 branches suggesting each strain to be of a unique type. The cluster classification, based on ~ 80% similarity, divided all the ERIC genotypes into two clusters, A and B. Cluster A consisted of 9 ERIC genotypes (A1-A9) corresponding to 9 individual strains. Cluster B comprised of 13 ERIC genotypes (B1-B13) with B5 forming the largest cluster of 51 strains. MLVA-16 identified all isolates as B. melitensis and divided them into 71 MLVA-types. The cluster analysis of MLVA-16-types suggested that most of the strains in Kuwait originated from the East Mediterranean Region, a few from the African group and one new genotype closely matched with the West Mediterranean region. In conclusion, this work demonstrates that B. melitensis, the most pathogenic species of Brucella, is prevalent in Kuwait. Furthermore, MLVA-16 is the best molecular method, which can identify the Brucella species and genotypes as well as determine their origin in the global context. Supported by Kuwait University Research Sector grants MI04/15 and SRUL02/13.

Keywords: Brucella, ERIC-PCR, MLVA-16, RT-PCR, 16S rRNA gene sequencing

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

Abstract:

The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

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Authors: Fay A. Al-Khalifa, Fariel Khan, Anamika Jiwane

Abstract:

Responding to some governmentally enforced building sustainability criteria is today becoming an unavoidable challenge to the real estate development industry and is no longer an extra that allows developers to gain competitive advantages. Previous studies suggested that using green technologies, if done under the right circumstances, could lead to positive incentives, tax breaks, higher rents, cost savings and higher property values in the long run. This is all in addition to the marketing benefits of the green label. There are, however, still countries, mostly in the developing world, that lack the implementation of such sustainability guidelines and assessment tools. This research aspires to investigate the market’s readiness to implement such criteria, its perception of sustainable architecture and building users motivation to use and/or invest in sustainable buildings. The study showed via a survey administered to 385 inhabitants and investors in commercial real estate in Bahrain that the respondents have a limited understanding of the benefits of green buildings and are unlikely to want to occupy or invest in a green building under the current social, economic and industrial conditions. Reliability of green technology, effectiveness, price and the questionable long-term financial benefits were among the major concerns. The study suggests that the promotion of sustainable architecture should respond to the current market concerns in a more direct way to trigger an interest in investors and users of commercial real estate project. This stimulated attention should consequently encourage developers to consider incorporating sustainability measures, apply for green building assessment programs and invest in green technologies, all of which need higher capitals that are nonetheless financially justifiable on the long run.

Keywords: investment, real estate, sustainability, clients perception, Bahrain

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Authors: Faizul Azly Abd Dzubir, Muhammad F. Othman

Abstract:

Conventional structural health monitoring approach for mechanical equipment uses inspection data from Non-Destructive Testing (NDT) during plant shut down window and fitness for service evaluation to estimate the integrity of the equipment that is prone to crack damage. Yet, this forecast is fraught with uncertainty because it is often based on assumptions of future operational parameters, and the prediction is not continuous or online. Advanced Diagnostic and Prognostic Technology (ADaPT) uses Acoustic Emission (AE) technology and a stochastic prognostic model to provide real-time monitoring and prediction of mechanical defects or cracks. The forecast can help the plant authority handle their cracked equipment before it ruptures, causing an unscheduled shutdown of the facility. The ADaPT employs process historical data trending, finite element analysis, fitness for service, and probabilistic statistical analysis to develop a prediction model for crack initiation and growth due to mechanical damage. The prediction model is combined with live equipment operating data for real-time prediction of the remaining life span owing to fracture. ADaPT was devised at a hot combined feed exchanger (HCFE) that had suffered creep crack damage. The ADaPT tool predicts the initiation of a crack at the top weldment area by April 2019. During the shutdown window in April 2019, a crack was discovered and repaired. Furthermore, ADaPT successfully advised the plant owner to run at full capacity and improve output by up to 7% by April 2019. ADaPT was also used on a coke drum that had extensive fatigue cracking. The initial cracks are declared safe with ADaPT, with remaining crack lifetimes extended another five (5) months, just in time for another planned facility downtime to execute repair. The prediction model, when combined with plant information data, allows plant operators to continuously monitor crack propagation caused by mechanical damage for improved maintenance planning and to avoid costly shutdowns to repair immediately.

Keywords: mechanical damage, cracks, continuous monitoring tool, remaining life, acoustic emission, prognostic model

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