Search results for: neural network

Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

Procedia PDF Downloads 238

Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

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Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

Procedia PDF Downloads 67

Authors: Abdulwahab Alalyani, Mahbub Rashid

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Urban Open Space (UOS) a central role to promotes community health, including daily activities, but these resources may not available, accessible enough, and or equitably be distributed. This paper measures and compares spatial equity of the availability and accessibility UOS among low, middle, and high-income neighborhoods in Riyadh city. The measurement mothdulgy for the UOSavailability was by calculating the total of UOS with respect to the population total (m2/inhabitant) and the accessibility indicted by using walking distance of a 0.25 mi (0.4 km) buffering streets network.All UOS were mapped and measured using geographical information systems. To evaluate the significant differences in UOS availability and accessibility across low, medium, and high-income Riyadh neighborhoods, we used a One-way ANOVA analysis of covariance to test the differences.The findings are as follows; finding, UOSavailability was lower than global standers. Riyadh has only 1.13 m2 per capita of UOS, and the coverage accessible area by walking distance to UOS was lower than 50%. The final finding, spatial equity of the availability and accessibility, were significantly different among Riyadh neighborhoods based on socioeconomic status. The future development of UOS should be focused on increasing Urban park availability and should be given priority to those low-income and unhealthy communities.

Keywords: distribution urban open space, urban open space accessibility, spatial equity, riyadh city

Procedia PDF Downloads 68

Authors: Gyoutae Park, Geunjun Lyu, Yeonjae Lee, Jaheon Gu, Sanguk Ahn, Hiesik Kim

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In this paper, we propose a system for preventing gas risks through the use of wireless communication modules and intelligent gas safety appliances. Our system configuration consists of an automatic extinguishing system, detectors, a wall-pad, and a microcomputer controlled micom gas meter to monitor gas flow and pressure as well as the occurrence of earthquakes. The automatic fire extinguishing system checks for both combustible gaseous leaks and monitors the environmental temperature, while the detector array measures smoke and CO gas concentrations. Depending on detected conditions, the micom gas meter cuts off an inner valve and generates a warning, the automatic fire-extinguishing system cuts off an external valve and sprays extinguishing materials, or the sensors generate signals and take further action when smoke or CO are detected. Information on intelligent measures taken by the gas safety appliances and sensors are transmitted to the wall-pad, which in turn relays this as real time data to a server that can be monitored via an external network (BcN) connection to a web or mobile application for the management of gas safety. To validate this smart-home gas management system, we field-tested its suitability for use in Korean apartments under several scenarios.

Keywords: gas sensor, leak, gas safety, gas meter, gas risk, wireless communication

Procedia PDF Downloads 393

Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

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Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

Procedia PDF Downloads 118

Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

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Authors: Mohammad Khazaei, Reza Rostami, Hasan Gharayagh Zandi, Rouhollah Basatnia, Mahbubeh Ghayour Najafabadi

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Objective: Methylphenidate has been demonstrated to enhance attention and cognitive processes, and placebo treatments have also been found to improve attention and cognitive processes. Additionally, methylphenidate may have positive effects on motion perception and sports performance. Nevertheless, additional research is needed to fully comprehend the neural mechanisms underlying the effects of methylphenidate and placebo on cognitive and motor functions. Methods: In this randomized controlled trial, 18 young semi-professional basketball players aged 18-23 years were randomly and equally assigned to either a Ritalin or Placebo group. The participants performed 20 consecutive free throws; their scores were recorded on a 0-3 scale. The participants’ brain activity was recorded using electroencephalography (EEG) for 5 minutes seated with their eyes closed. The Ritalin group received a 10 mg dose of methylphenidate, while the Placebo group received a 10mg dose of placebo. The EEG was obtained 90 minutes after the drug was administere Results: There was no significant difference in the absolute power of brain waves between the pre-test and post-tests in the Placebo group. However, in the Ritalin group, a significant difference in the absolute power of brain waves was observed in the Theta band (5-6 Hz) and Beta band (21-30 Hz) between pre- and post-tests in Fp2, F8, and Fp1. In these areas, the absolute power of Beta waves was higher during the post-test than during the pre-test. The Placebo group showed a more significant difference in free throw scores than the Ritalin group. Conclusions: In conclusion, these results suggest that Ritalin effect on brain activity in areas associated with attention and cognitive processes, as well as improve basketball free throws. However, there was no significant placebo effect on brain activity performance, but it significantly affected the improvement of free throws. Further research is needed to fully understand the effects of methylphenidate and placebo on cognitive and motor functions.

Keywords: methylphenidate, placebo effect, electroencephalography, basketball free throw

Procedia PDF Downloads 51

Authors: Hasan Heydari

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In recent decades, locating urban services is one of the significant discussions in urban planning. Among these considerations, cities require more accurate planning in order to supply citizen needs, especially part of urban safety. In order to gain this goal, one of the main tasks of urban planners and managers is specifying suitable sites to locate firefighting stations. This study has been done to reach this purpose. Therefore effective criteria consist of coverage radius, population density, proximity to pathway network, land use (compatible and incompatible neighborhood) have been specified. After that, descriptive and local information of the criteria was provided and their layers were created in ArcGIS 9.3. Using Analytic Hierarchy Process (AHP) these criteria and their sub-criteria got the weights. These layers were classified regarding their weights and finally were overlaid by Index Overlay Model and provided the final site selection map for firefighting stations of Arak city. The results gained by analyzing in GIS environment indicate the existing fire station don’t cover the whole city sufficiently and some of the stations have established on the unsuitable sites. The output map indicates the best sites to locate firefighting stations of Arak.

Keywords: site-selection, firefighting stations, analytic hierarchy process (AHP), GIS, index overlay model

Procedia PDF Downloads 325

Authors: Todor Bačkalić, Marinko Maslarić, Milosav Georgijević, Sanja Bojić

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Water transport could be the backbone of the future European combined transport system. The future transport policy in landlocked countries from the Danube Region has to be based on inland waterway transport (IWT). The development of the container transport on inland waterways depends directly on technical-exploitative characteristics of the network of inland waterways. Research of navigational abilities of inland waterways is the basic step in transport planning. The size of the vessel’s draught (T) is the limiting value in project tasks and it depends on the depth of the waterway. Navigation characteristics of rivers have to be determined as precise as possible, especially from the aspect of determination of the possible draught of vessels. This article outlines a rationale, why it is necessary to develop competence about infrastructure risk in water transport. Climate changes are evident and require special attention and global monitoring. Current risk assessment methods for Inland waterway transport just consider some dramatic events. We present a new method for the assessment of risk and vulnerability of inland waterway transport where river depth represents a crucial part. The analysis of water level changes in the lower Danube was done for two significant periods (1965-1979 and 1998-2012).

Keywords: container vessel, draught, probability, the Danube

Procedia PDF Downloads 435

Authors: William Xiu Shun Wong, Myungsu Lim, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Kee-Young Kwahk, Namgyu Kim

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Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions.

Keywords: big data, social network analysis, text mining, topic modeling

Procedia PDF Downloads 262

Authors: Omar Hamdy, Schichen Zhao, Hussein Abd El-Atty, Ayman Ragab, Muhammad Salem

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One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as heavy deluge inundates urban areas causing considerable damage to buildings and infrastructure. Moreover, the main problem was the urban sprawl towards this risky area. This paper aims to identify the urban areas located in the risk areas prone to flash floods. Analyzing this phenomenon needs a lot of data to ensure satisfactory results; however, in this case the official data and field data were limited, and therefore, free sources of satellite data were used. This paper used ArcGIS tools to obtain the storm water drains network by analyzing DEM files. Additionally, historical imagery in Google Earth was studied to determine the age of each building. The last step was to overlay the urban area layer and the storm water drains layer to identify the vulnerable areas. The results of this study would be helpful to urban planners and government officials to make the disasters risk estimation and develop primary plans to recover the risky area, especially urban areas located in torrents.

Keywords: risk area, DEM, storm water drains, GIS

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Authors: Berger Saintius, Edna Ariste, Djeamsly Salomon

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Background: Maternal mortality is a preventable global health problem that affects developed, developing, and underdeveloped countries alike. Globally, maternal mortality rates have declined since 1990, but 830 women die every day from pregnancy and childbirth-related causes that are often preventable. Haiti, with a number of 529 maternal deaths per 100,000 live births, is one of the countries with the highest maternal mortality rate in the Caribbean. This study consists of analyzing maternal death surveillance data in Haiti from 2017-2020. Method : A descriptive study was conducted; data were extracted from the National Epidemiological Surveillance Network of maternal deaths from 2017 to 2020. Sociodemographic variables were analyzed. Excel and Epi Info 7.2 were used for data analysis. Frequency and proportion measurements were calculated. Results: 756 deaths were recorded for the study period: 42 (6%) in 2017, 168 (22%) in 2018, 265 (35%) in 2019, and 281 (37%) in 2020. The North Department recorded the highest number of deaths, 167 (22%). 83(11%) in Les Cayes. 96% of these deaths are people aged between 15 and 49. Conclusion. Maternal mortality is a major health problem in Haiti. Mobilization, participation, and involvement of communities, increase in obstetric care coverage and promotion of Family Planning are among the strategies to fight this problem.

Keywords: epidemiology, maternal death, hospital, Haiti

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Authors: M. S. Mrudula, M. R. Gopinathan Nair

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In order to utilize the natural rubber for developing new green polymeric materials for specialty applications, we have prepared natural rubber and polyethylene oxide based polymeric networks by two shot method. The polymeric networks thus formed have been used as chelating exchanger for metal ion binding. Chelating exchangers are, in general, coordinating copolymers containing one or more electron donor atoms such as N, S, O, and P that can form coordinate bonds with metals. Hydrogels are water- swollen network of hydrophilic homopolymer or copolymers. They acquire a great interest due to the facility of the incorporation of different chelating groups into the polymeric networks. Such polymeric hydrogels are promising materials in the field of hydrometallurgical applications and water purification due to their chemical stability. The current study discusses the swelling response of the polymeric networks as a function of time, temperature, pH and [NaCl] and sorption studies. Equilibrium swelling has been observed to depend on both structural aspects of the polymers and environmental factors. Metal ion sorption shows that these polymeric networks can be used for removal, separation, and enrichment of metal ions from aqueous solutions and can play an important role for environmental remediation of municipal and industrial wastewater.

Keywords: block copolymer, adsorption, chelating exchanger, swelling study, polymer, metal complexes

Procedia PDF Downloads 311

Authors: C. C. Liang

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MSN used to be the most popular application for communicating among social networks, but Facebook chat is now the most popular. Facebook and MSN have similar characteristics, including usefulness, ease-of-use, and a similar function, which is the exchanging of information with friends. Facebook outperforms MSN in both of these areas. However, the adoption of Facebook and abandonment of MSN have occurred for other reasons. Functions can be improved, but users’ willingness to use does not just depend on functionality. Flow status has been established to be crucial to users’ adoption of cyber applications and to affects users’ adoption of software applications. If users experience flow in using software application, they will enjoy using it frequently, and even change their preferred application from an old to this new one. However, no investigation has examined choice behavior related to switching from Facebook to MSN based on a consideration of flow experiences and functions. This investigation discusses the flow experiences and functions of social-networking applications. Flow experience is found to affect perceived ease of use and perceived usefulness; perceived ease of use influences information ex-change with friends, and perceived usefulness; information exchange influences perceived usefulness, but information exchange has no effect on flow experience.

Keywords: consumer behavior, social media, technology acceptance model, flow experience

Procedia PDF Downloads 324

Authors: Wang Shuen-Tai, Lin Yu-Ching, Chang Hsi-Ya

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Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML 5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Keywords: web-based, workflow, HTML5, Cloud Computing, Queuing System

Procedia PDF Downloads 283

Authors: Kanika Taneja, V. K. Soni, S. D. Attri, Kafeel Ahmad, Shamshad Ahmad

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Aerosols represent an important component of earth-atmosphere system and have a profound impact on the global and regional climate. With the growing population and urbanization, the aerosol load in the atmosphere over the Indian region is found to be increasing. Several studies have reported that the aerosol optical depth over the northern part of India is higher as compared to the southern part. The northern India along the Indo-Gangetic plain is often influenced with dust transported from the Thar Desert in northwestern India and from Arabian Peninsula during the pre-monsoon season. Seasonal variations in aerosol optical and radiative properties were examined using data retrieved from ground based multi-wavelength Prede Sun/sky radiometer (POM-02) over Delhi, Rohtak, Jodhpur and Varanasi for the period April 2011-April 2013. These stations are part of the Skynet-India network of India Meteorological Department. The Sun/sky radiometer (POM-02) has advantage over other instruments that it can be calibrated on-site. These aerosol optical properties retrieved from skyradiometer observations are further used to analyze the Direct Aerosol Radiative Forcing (DARF) over the study locations.

Keywords: aerosol optical properties, indo- gangetic plain, radiative forcing, sky radiometer

Procedia PDF Downloads 511

Authors: Sarayu Vanga, Jorge Galeano-Cabral, Kaya Wei

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Cerebral hypoxia refers to a condition in which there is a decrease in oxygen supply to the brain. Patients suffering from this condition experience a decrease in their body temperature. While there isn't any cure to treat cerebral hypoxia as of date, certain procedures are utilized to help aid in the treatment of the condition. Regulating the body temperature is an example of one of those procedures. Hypoxia is well known to reduce the body temperature of mammals, although the neural origins of this response remain uncertain. In order to speed recovery from this condition, it is necessary to maintain a stable body temperature. In this study, we present an approach to regulating body temperature for patients who suffer from cerebral hypoxia or other similar conditions. After a thorough literature study, we propose the use of thermoelectric blankets, which are temperature-controlled thermal blankets based on thermoelectric devices. These blankets are capable of heating up and cooling down the patient to stabilize body temperature. This feature is possible through the reversible effect that thermoelectric devices offer while behaving as a thermal sensor, and it is an effective way to stabilize temperature. Thermoelectricity is the direct conversion of thermal to electrical energy and vice versa. This effect is now known as the Seebeck effect, and it is characterized by the Seebeck coefficient. In such a configuration, the device has cooling and heating sides with temperatures that can be interchanged by simply switching the direction of the current input in the system. This design integrates various aspects, including a humidifier, ventilation machine, IV-administered medication, air conditioning, circulation device, and a body temperature regulation system. The proposed design includes thermocouples that will trigger the blanket to increase or decrease a set temperature through a medical temperature sensor. Additionally, the proposed design allows an efficient way to control fluctuations in body temperature while being cost-friendly, with an expected cost of 150 dollars. We are currently working on developing a prototype of the design to collect thermal and electrical data under different conditions and also intend to perform an optimization analysis to improve the design even further. While this proposal was developed for treating cerebral hypoxia, it can also aid in the treatment of other related conditions, as fluctuations in body temperature appear to be a common symptom that patients have for many illnesses.

Keywords: body temperature regulation, cerebral hypoxia, thermoelectric, blanket design

Procedia PDF Downloads 116

Authors: B. Gopal, Pannala Krishna Murthy, G. N. Sreenivas

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The increasing demand of electric power is giving an emphasis on the need for the maximum utilization of renewable energy sources. On the other hand maintaining power quality to satisfaction of utility is an essential requirement. In this paper the design aspects of a Unified Power Quality Conditioner integrated with photovoltaic system in a distributed generation is presented. The proposed system consist of series inverter, shunt inverter are connected back to back on the dc side and share a common dc-link capacitor with Distributed Generation through a boost converter. The primary task of UPQC is to minimize grid voltage and load current disturbances along with reactive and harmonic power compensation. In addition to primary tasks of UPQC, other functionalities such as compensation of voltage interruption and active power transfer to the load and grid in both islanding and interconnected mode have been addressed. The simulation model is design in MATLAB/ Simulation environment and the results are in good agreement with the published work.

Keywords: distributed generation (DG), interconnected mode, islanding mode, maximum power point tracking (mppt), power quality (PQ), unified power quality conditioner (UPQC), photovoltaic array (PV)

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Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

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In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

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Authors: J. Satya Eswari, Ch. Venkateswarlu

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The formulation of a commercial pharmaceutical product involves several composition factors and response characteristics. When the formulation requires to satisfy multiple response characteristics which are conflicting, an optimal solution requires the need for an efficient multiobjective optimization technique. In this work, a regression is combined with a non-dominated sorting differential evolution (NSDE) involving Naïve & Slow and ε constraint techniques to derive different multiobjective optimization strategies, which are then evaluated by means of a trapidil pharmaceutical formulation. The analysis of the results show the effectiveness of the strategy that combines the regression model and NSDE with the integration of both Naïve & Slow and ε constraint techniques for Pareto optimization of trapidil formulation. With this strategy, the optimal formulation at pH=6.8 is obtained with the decision variables of micro crystalline cellulose, hydroxypropyl methylcellulose and compression pressure. The corresponding response characteristics of rate constant and release order are also noted down. The comparison of these results with the experimental data and with those of other multiple regression model based multiobjective evolutionary optimization strategies signify the better performance for optimal trapidil formulation.

Keywords: pharmaceutical formulation, multiple regression model, response surface method, radial basis function network, differential evolution, multiobjective optimization

Procedia PDF Downloads 380

Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

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Authors: Shahadat Uddin, Md Ekramul Hossain, Arif Khan

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The collaboration among physicians during episodes of care for a hospitalised patient has a significant contribution towards effective health outcome. This research aims at improving this health outcome by analysing the attributes of patient-sharing physician collaboration network (PCN) on hospital data. To accomplish this goal, we present a research framework that explores the impact of several types of attributes (such as clique and clan) of PCN on hospitalisation cost and hospital length of stay. We use electronic health insurance claim dataset to construct and explore PCNs. Each PCN is categorised as ‘low’ and ‘high’ in terms of hospitalisation cost and length of stay. The results from the proposed model show that the clique and clan of PCNs affect the hospitalisation cost and length of stay. The clique and clan of PCNs show the difference between ‘low’ and ‘high’ PCNs in terms of hospitalisation cost and length of stay. The findings and insights from this research can potentially help the healthcare stakeholders to better formulate the policy in order to improve quality of care while reducing cost.

Keywords: clique, clan, electronic health records, physician collaboration

Procedia PDF Downloads 117

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

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

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

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Authors: Sanat K. Dash, Rama S. Verma, Sarit K. Das

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A logarithmic microfluidic shear device was designed and fabricated for cellular mechanotransduction studies. The device contains four cell culture chambers in which flow was modulated to achieve a logarithmic increment. Resistance values were optimized to make the device compact. The network of resistances was developed according to a unique combination of series and parallel resistances as found via optimization. Simulation results done in Ansys 16.1 matched the analytical calculations and showed the shear stress distribution at different inlet flow rates. Fabrication of the device was carried out using conventional photolithography and PDMS soft lithography. Flow profile was validated taking DI water as working fluid and measuring the volume collected at all four outlets. Volumes collected at the outlets were in accordance with the simulation results at inlet flow rates ranging from 1 ml/min to 0.1 ml/min. The device can exert fluid shear stresses ranging four orders of magnitude on the culture chamber walls which will cover shear stress values from interstitial flow to blood flow. This will allow studying cell behavior in the long physiological range of shear stress in a single run reducing number of experiments.

Keywords: microfluidics, mechanotransduction, fluid shear stress, physiological shear

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Authors: Maria M. Giannakou, Athanasios K. Ziliaskopoulos

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Transmission pipelines carrying natural gas are often routed through populated cities, industrial and environmentally sensitive areas. While the need for these networks is unquestionable, there are serious concerns about the risk these lifeline networks pose to the people, to their habitat and to the critical infrastructures, especially in view of natural disasters such as earthquakes. This work presents an Integrated Pipeline Risk Management methodology (IPRM) for assessing the hazard associated with a natural gas pipeline failure due to natural or manmade disasters. IPRM aims to optimize the allocation of the available resources to countermeasures in order to minimize the impacts of pipeline failure to humans, the environment, the infrastructure and the economic activity. A proposed knapsack mathematical programming formulation is introduced that optimally selects the proper mitigation policies based on the estimated cost – benefit ratios. The proposed model is demonstrated with a small numerical example. The vulnerability analysis of these pipelines and the quantification of consequences from such failures can be useful for natural gas industries on deciding which mitigation measures to implement on the existing pipeline networks with the minimum cost in an acceptable level of hazard.

Keywords: cost benefit analysis, knapsack problem, natural gas distribution network, risk management, risk mitigation

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Authors: Giovanni Menichini, Salvatore Giacomo Morano, Gloria Terenzi, Luca Salvatori, Maurizio Orlando

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The “Guidelines for Risk Classification, Safety Assessment, and Structural Health Monitoring of Existing Bridges” were recently approved by the Italian Government to define technical standards for managing the national network of existing bridges. These guidelines provide a framework for risk mitigation and safety assessment of bridges, which are essential elements of the built environment and form the basis for the operation of transport systems. Within the guideline framework, a workflow based on three main points was proposed: (1) risk-based, i.e., based on typical parameters of hazard, vulnerability, and exposure; (2) multi-level, i.e., including six assessment levels of increasing complexity; and (3) multirisk, i.e., assessing structural/foundational, seismic, hydrological, and landslide risks. The paper focuses on applying the Italian Guidelines to specific case studies, aiming to identify the parameters that predominantly influence the determination of the “class of attention”. The significance of each parameter is determined via sensitivity analysis. Additionally, recommendations for enhancing the process of assigning the class of attention are proposed.

Keywords: bridge safety assessment, Italian guidelines implementation, risk classification, structural health monitoring

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Authors: Tingkai Zhao, Jingtian Hu, Xiarong Peng, Wenbo Yang, Tiehu Li

Abstract:

Homogeneous amorphous carbon nanotube (ACNT) networks have been synthesized using floating catalyst chemical vapor deposition method on a three-dimensional (3D) graphene aerogel (GA)/BaFe₁₂O₁₉ nanorod (BNR) composite which prepared by a self-propagating combustion process. The as-synthesized ACNT/GA/BNR composite which has 3D network structures could be directly used as a good absorber in the electromagnetic wave absorbent materials. The experimental results indicated that the maximum absorbing peak of ACNT/GA/BNR composite with a thickness of 2 mm was -18.35 dB at 10.64 GHz in the frequency range of 2-18 GHz. The bandwidth of the reflectivity below -10 dB is 3.32 GHz. The 3D graphene aerogel structures which composed of dense interlined tubes and amorphous structure of ACNTs bearing quantities of dihedral angles could consume the incident waves through multiple reflection and scattering inside the 3D web structures. The interlinked ACNTs have both the virtues of amorphous CNTs (multiple reflections inside the wall) and crystalline CNTs (high conductivity), consuming the electromagnetic wave as resistance heat. ACNT/GA/BNR composite has a good electromagnetic wave absorbing performance.

Keywords: amorphous carbon nanotubes, graphene aerogel, barium ferrite nanorod, electromagnetic wave absorption

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Authors: Mahmoud Fouad, Mervat Badr, Marwa Ibrahim

Abstract:

Micro-grid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. Renewable power sources such as wind, solar and hydro offer high potential of benign power for future micro-grid systems. Micro-Grid (MG) is basically a low voltage (LV) or medium voltage (MV) distribution network which consists of a number of called distributed generators (DG’s); micro-sources such as photovoltaic array, fuel cell, wind turbine etc. energy storage systems and loads; operating as a single controllable system, that could be operated in both grid-connected and islanded mode. The capacity of the DG’s is sufficient to support all; or most, of the load connected to the micro-grid. This paper presents a micro-grid system based on wind and solar power sources and addresses issues related to operation, control, and stability of the system. Using Matlab/Simulink, the system is modeled and simulated to identify the relevant technical issues involved in the operation of a micro-grid system based on renewable power generation units.

Keywords: micro-grid system, photovoltaic, wind turbine, energy storage, distributed generation, modeling

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

Abstract:

The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Salha Abdullah Ali Al-Shamrani, Maha Muhammad Dhaher Aljuhani, Eman Ali Ahmed Aldhaheri

Abstract:

With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: internet of things, spoofing, IoT, access control, blockchain, raspberry pi

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