Search results for: improved sparrow search algorithm

Authors: Peng Zhang, Lihui Zheng, Xiangchun Wang, Xiaopan Kou

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Quantitative research on the main control factors of lost circulation has few considerations and single data source. Using Unmanned Intervention Algorithm to find the main control factors of lost circulation adopts all measurable parameters. The degree of lost circulation is characterized by the loss rate as the objective function. Geological, engineering and fluid data are used as layers, and 27 factors such as wellhead coordinates and WOB are used as dimensions. Data classification is implemented to determine function independent variables. The mathematical equation of loss rate and 27 influencing factors is established by multiple regression method, and the undetermined coefficient method is used to solve the undetermined coefficient of the equation. Only three factors in t-test are greater than the test value 40, and the F-test value is 96.557%, indicating that the correlation of the model is good. The funnel viscosity, final shear force and drilling time were selected as the main control factors by elimination method, contribution rate method and functional method. The calculated values of the two wells used for verification differ from the actual values by -3.036m3/h and -2.374m3/h, with errors of 7.21% and 6.35%. The influence of engineering factors on the loss rate is greater than that of funnel viscosity and final shear force, and the influence of the three factors is less than that of geological factors. Quantitatively calculate the best combination of funnel viscosity, final shear force and drilling time. The minimum loss rate of lost circulation wells in Shunbei area is 10m3/h. It can be seen that man-made main control factors can only slow down the leakage, but cannot fundamentally eliminate it. This is more in line with the characteristics of karst caves and fractures in Shunbei fault solution oil and gas reservoir.

Keywords: drilling and completion, drilling fluid, lost circulation, loss rate, main controlling factors, unmanned intervention algorithm

Procedia PDF Downloads 112

Authors: Hassnen M. Jafer, W. Atherton, F. Ruddock, E. Loffill

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This study represents the results of an experimental work using two types of fly ashes as a cement replacement in soft soil stabilisation. The fly ashes (FA1 and FA2) used in this study are by-products resulting from an incineration processes between 800 and 1200 ˚C. The stabilised soil in this study was an intermediate plasticity silty clayey soil with medium organic matter content. The experimental works were initially conducted on soil treated with different percentages of FA1 (0, 3, 6, 9, 12, and 15%) to identify the optimum FA1 content. Then FA1 was chemically activated by FA2 which has high alkalinity by blending the optimum content of FA1 with different portions of FA2. The improvement levels were evaluated dependent on the results obtained from consistency limits and compaction tests along with the results of unconfined compressive strength (UCS) tests which were conducted on specimens of soil treated with FA1 and FA2 and exposed to different periods of curing (zero, 7, 14, and 28 days). The results indicated that the FA1 and FA2 used in this study effectively improved the physical and geotechnical properties of the soft soil where the index of plasticity (IP) was decreased significantly from 21 to 13.17 with 12% of FA1; however, there was a slight increase in IP with the use of FA2. Meanwhile, 12% of FA1 was identified as the optimum percentage improving the UCS of stabilised soil significantly. Furthermore, FA2 was found effective as a chemical activator to FA1 where the UCS was improved significantly after using FA2.

Keywords: fly ashes, soft soil stabilisation, waste materials, unconfined compressive strength

Procedia PDF Downloads 235

Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words (BOVW), classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar (PolSAR)

Procedia PDF Downloads 209

Authors: Sheikh Omar Sillah

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Introduction: Monitoring is an important means of ensuring the smooth implementation and quality of clinical trials. For many years, traditional site monitoring approaches have been critical in detecting data errors but not optimal in identifying fabricated and implanted data as well as non-random data distributions that may significantly invalidate study results. The objective of this paper was to provide recommendations based on best statistical monitoring practices for detecting data-integrity issues suggestive of fabrication and implantation early in the study conduct to allow implementation of meaningful corrective and preventive actions. Methodology: Electronic bibliographic databases (Medline, Embase, PubMed, Scopus, and Web of Science) were used for the literature search, and both qualitative and quantitative studies were sought. Search results were uploaded into Eppi-Reviewer Software, and only publications written in the English language from 2012 were included in the review. Gray literature not considered to present reproducible methods was excluded. Results: A total of 18 peer-reviewed publications were included in the review. The publications demonstrated that traditional site monitoring techniques are not efficient in detecting data anomalies. By specifying project-specific parameters such as laboratory reference range values, visit schedules, etc., with appropriate interactive data monitoring, statistical monitoring can offer early signals of data anomalies to study teams. The review further revealed that statistical monitoring is useful to identify unusual data patterns that might be revealing issues that could impact data integrity or may potentially impact study participants' safety. However, subjective measures may not be good candidates for statistical monitoring. Conclusion: The statistical monitoring approach requires a combination of education, training, and experience sufficient to implement its principles in detecting data anomalies for the statistical aspects of a clinical trial.

Keywords: statistical monitoring, data anomalies, clinical trials, traditional monitoring

Procedia PDF Downloads 77

Authors: Ivan Tolj

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Water produced during electrochemical reaction in Proton Exchange Membrane (PEM) fuel cell can be used for internal humidification of reactant gases; hydrogen and air. On such a way it is possible to eliminate expensive external humidifiers and simplify fuel cell balance-of-plant (BoP). When fuel cell operates at constant temperature (usually between 60 °C and 80 °C) relatively cold and dry ambient air heats up quickly upon entering channels which cause further drop in relative humidity (below 20%). Low relative humidity of reactant gases dries up polymer membrane and decrease its proton conductivity which results in fuel cell performance drop. It is possible to maintain such temperature profile throughout fuel cell cathode channel which will result in close to 100 % RH. In order to achieve this, passive heat exchanger was designed using commercial CFD software (ANSYS Fluent). Such passive heat exchanger (with variable surface area) is suitable for small scale PEM fuel cells. In this study, passive heat exchanger for single PEM fuel cell segment (with 20 x 1 cm active area) was developed. Results show close to 100 % RH of air throughout cathode channel with increased fuel cell performance (mainly improved polarization curve) and improved durability.

Keywords: PEM fuel cell, passive heat exchange, relative humidity, thermal management

Procedia PDF Downloads 277

Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

Procedia PDF Downloads 295

Authors: Philippa C. Ojimelukwe, Felix C. Okpalanma, Emmanuel A. Mazi

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The carotenoid content, vitamins (ascorbic acid, riboflavin, thiamin, niacin and vitamin K) and mineral contents (K, Ca, Mg, Zn and Fe) of raw, cooked (moist heat treatment) and stored Gnetum africanum and Pterocarpus mildbraedii leaves were investigated in the present research. Raw G. africanum contained higher total carotenoids (246.93µg/g edible portion) than P. mildbraedii (83.53µg/g edible portion) However, moist heat treatment significantly improved the total carotenoid content of P. mildbraedii. The carotenoid profiles of P. mildbraedii and G. africanum showed improved contents of beta cryptoxanthin , 9-cis, 11-cis and 13 cis beta carotenes due to moist heat treatment. Lutein contents of the two green leafy vegetables were quite high in raw, heat treated and stored samples. The two green leafy vegetables were good sources of vitamin K (118-120 µg). Moist heat treatment significantly (p < 0.05) increased the mineral contents of P.mildbraedii and G. africanum. The vitamin contents were reduced. Storage at ambient temperature (30oC) in the dark led to good retention of the minerals but not the vitamins.

Keywords: Gnetum africanum, Pterocarpus mildbraedii, carotenoid profile, vitamins, minerals

Procedia PDF Downloads 490

Authors: Fariba Azizi, Firoozeh Haghighi, Viliam Makis

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In this paper, we propose a method to model the relationship between failure time and degradation for a simple step stress test where underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to shorten failure time of products and a tampered failure rate (TFR) model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates (MLEs) of the model parameters are obtained through an expectation-maximization (EM) algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real example is analyzed to illustrate the application of the proposed methods.

Keywords: cause of failure, linear degradation path, reliability function, expectation-maximization algorithm, intensity, masked data

Procedia PDF Downloads 334

Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

Procedia PDF Downloads 475

Authors: Norma Kok, Diemo Masuko, Thandokazi Dlongwana, Komala Pillay

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CONTEXT: While many school principals have been outstanding teachers and have inherent leadership potential, many have not had access to the quality of leadership development or support that empowers them to produce high-quality education outcomes in extremely challenging circumstances. Further, school leaders in under-served communities face formidable challenges arising from insufficient infrastructure, overcrowded classrooms, socio-economic challenges within the community, and insufficient parental involvement, all of which put a strain on principals’ ability to lead their schools effectively. In addition few school leaders have access to other supportive networks, and many do not know how to build and leverage social capital to create opportunities for their schools and learners. Moreover, we know that fostering parental involvement in their children’s learning improves a child’s morale, attitude, and academic achievement across all subject areas, and promotes better behaviour and social adjustment. Citizen Leader Lab facilitates the Partners for Possibility (PfP) programme to provide leadership development and support to school leaders serving under-resourced communities in South Africa to create effective environments of learning. This is done by creating partnerships between school leaders and private-sector business leaders over a 12-month period. (185) OBJECTIVES: To explore school leaders’ perceptions of their leadership capacities and changes at their schools after being exposed to a year-long leadership development training programme. METHODS: School leaders gained new leadership capacities e.g. resilience, improved confidence, communication and conflict resolution skills - catalysing into improved cultures of collaborative decision-making and environments for enhanced teaching and learningprogramme based on the 70:20:10 model whereby: 10% of learning comes from workshops, 20% of learning takes place through peer learning and 70% of learning occurs through experiential learning as partnerships work together to identify and tackle challenges in targeted schools. Participants completed a post-programme questionnaire consisting of structured and unstructured questions and semi-structured interviews were conducted with them and their business leader. The interviews were audio-recorded, transcribed and thematic content analysis was undertaken. The analysis was inductive and emerging themes were identified. A code list was generated after coding was undertaken using computer software (Dedoose). Quantitative data gathered from surveys was aggregated and analysed. RESULTS: School leadership found the programme interesting and rewarding. They gained new leadership capacities such as resilience, improved confidence, communication and conflict resolution skills - catalyzing into improved cultures of collaborative decision-making and environments for enhanced teaching and learning. New networks resulted in tangible outcomes such as upgrades to school infrastructure, water and sanitation, vegetable gardens at schools resulting in nutrition for learners and/or intangible outcomes such as skills for members of school management teams (SMTs). Collaborative leadership led to SMTs being more aligned, efficient, and cohesive; and teachers being more engaged and motivated. Notable positive changes at the school inspired parents and community members to become more actively involved in the school and in their children’s education. CONCLUSION: The PfP programme leads to improved leadership capacities and improved school culture which leads to improved teaching and learning and new resources for schools.

Keywords: collaborative decision-making, collaborative leadership, community involvement, confidence

Procedia PDF Downloads 91

Authors: Isaac Diaka, Matsui Kenichi

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Ghana’s rice production has increased mainly because of increased cultivated areas. On this point, scholars who promoted crop production increase for food security have overlooked the fact that its per-acre yield has not increased. Also, Ghana’s domestic rice production has not contributed much to domestic rice consumption especially in major cities where consumers tend to rely on imported rice from Asia. Considering these points, the paper seeks to understand why smallholder rice farmers have not been able to increase per acre rice yield. It also examines smallholder rice farmers’ rice yield improvement needs, and the relationship that exist between rice farmers’ socioeconomic factors and their yield levels by rice varieties. The study adopted a simple random sampling technique to select 154 rice farmers for a questionnaire survey between October and November 2020. The data was analyzed by performing a correlation analysis, an independent t-test, and Kendall’s coefficient of concordance. The results showed that 58.4% of the respondents cultivated popular high-yield varieties like AGRA and Jasmine. The rest used local varieties. Regarding respondents’ yield differentials, AGRA and Jasmine had an average yield of 2.6 mt/ha, which is higher than that of local varieties (1.6mt/ha). The study found untimely availability of improved seed varieties and high cost of inputs some of the major reasons affecting yield in the area. For respondents’ yield improvement needs, Kendall’s coefficient of concordance showed that access to improved varieties, irrigation infrastructure, and row planting were respondents’ major technological needs. As to their non-technological needs, the respondents needed timely information about rice production, access to credit support options, and extension services. The correlation analysis revealed that farm size and off-farm income exhibited a positive and negative association towards respondents’ yield level, respectively. This paper then discusses recommendations for providing with improved rice production technologies to farmers.

Keywords: Ghana, rice, smallholder farmers, yield improvement.

Procedia PDF Downloads 93

Authors: Farhad Ahmadi, Mehran Mohammadi Khah, Fariba Rahimi, N. Vejdani Far

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The aim of present research was to investigate the effect of different levels of protexin (PRT) and Curcuma longa (CUR) on performance, serum lipid and indices of immune system in broiler chickens at the starter stage. A total of 300, one-day-old male broiler (Ross-308) were allotted, in a 2×2+1 factorial design contain 2 levels of protexin (10 and 40 mg/kg diet) and 2 levels of Curcuma longa (200 and 400 mg/kg diet) with four replicate and 15 birds per pens. Experimental diets were: T1 control (basal diet); T2 (2g/kg CUR+0.1g PRT/kg diet), T3 (2g CUR/kg+0.2g PRT/kg diet), T4 (4g CUR/kg+0.1g PRT/kg) and T5 (4g CUR/kg+0.2g PRT/kg). Results indicated that body weight gain and feed conversion ratio had significantly improved (P < 0.05) in birds that fed diet inclusion any levels of additive. The highest BWG and lowest FCR observed in T5 birds group as compared to control (P < 0.05). Relative bursa of Fabricius and spleen weight in T5 and T3 birds groups were higher than control (P > 0.05). The serum of cholesterol, TG, LDL had significantly decreased (P < 0.05). As well, HDL was higher (P < 0.05) in T5 birds group compared to control. In conclusion, results of present trial indicated that blend of mention additive was better than using individual of those and improved performance traits.

Keywords: broiler, Curcuma longa, performance, protexin, serum

Procedia PDF Downloads 382

Authors: Maja Ruzic-Baf, Vedrana Keteles, Andrea Debeljuh

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Younger and younger children are now using a smartphone, a device which has become ‘a must have’ and the life of children would be almost ‘unthinkable’ without one. Devices are becoming lighter and lighter but offering an array of options and applications as well as the unavoidable access to the Internet, without which it would be almost unusable. Numerous features such as taking of photographs, listening to music, information search on the Internet, access to social networks, usage of some of the chatting and messaging services, are only some of the numerous features offered by ‘smart’ devices. They have replaced the alarm clock, home phone, camera, tablet and other devices. Their use and possession have become a part of the everyday image of young people. Apart from the positive aspects, the use of smartphones has also some downsides. For instance, free time was usually spent in nature, playing, doing sports or other activities enabling children an adequate psychophysiological growth and development. The greater usage of smartphones during classes to check statuses on social networks, message your friends, play online games, are just some of the possible negative aspects of their application. Considering that the age of the population using smartphones is decreasing and that smartphones are no longer ‘foreign’ to children of pre-school age (smartphones are used at home or in coffee shops or shopping centers while waiting for their parents, playing video games often inappropriate to their age), particular attention must be paid to a very sensitive group, the teenagers who almost never separate from their ‘pets’. This paper is divided into two sections, theoretical and empirical ones. The theoretical section gives an overview of the pros and cons of the usage of smartphones, while the empirical section presents the results of a research conducted in three elementary schools regarding the usage of smartphones and, specifically, their usage during classes, during breaks and to search information on the Internet, check status updates and 'likes’ on the Facebook social network.

Keywords: education, smartphone, social networks, teenagers

Procedia PDF Downloads 453

Authors: Matthew Lee Turnbough

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In 2007 Spain began to experience the effects of a deep economic crisis, which would generate a situation characterised by instability and uncertainty. This has been an obstacle, especially acute for the youth of this country seeking to enter the workforce. As a result of the impact of COVID-19, the youth in Spain are now suffering the effects of a new crisis that has deepened an already fragile labour environment. In this paper, we analyse the discourses that have emerged from a precarious labour market, specifically from two companies dedicated to operating job portals and job listings in Spain, Job Today, and CornerJob. These two start-up businesses have developed mobile applications geared towards young adults in search of employment in the service sector, two of the companies with the highest user rates in Spain. Utilizing a discourse analysis approach, we explore the impact of individualization and how the process of psychologization may contribute to an increasing reliance on individual solutions to social problems. As such, we seek to highlight the expectations and demands that are placed upon young workers and the type of subjectivity that this dynamic could foster, all this within an unstable framework seemingly marked by chance, a context which is key for the emergence of individualization. Furthermore, we consider the extent to which young adults incorporate these discourses and the strategies they employ basing our analysis on the VULSOCU (New Forms of Socio-Existential Vulnerability, Supports, and Care in Spain) research project, specifically the results of nineteen in-depth interviews and three discussion groups with young adults in this country. Consequently, we seek to elucidate the argumentative threads rooted in the process of individualization and underline the implications of this dynamic for the young worker and his/her labour insertion while also identifying manifestations of the goddess of fortune as a representation of chance in this context. Finally, we approach this panorama of social change in Spain from the perspective of the individuals or young adults who find themselves immersed in this transition from one crisis to another.

Keywords: chance, crisis, discourses, individualization, work, youth

Procedia PDF Downloads 117

Authors: Hasan Ustun Basaran

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Diesel engines are widely used in transportation sector due to their high thermal efficiency. However, they also release high rates of NOₓ and PM (particulate matter) emissions into the environment which have hazardous effects on human health. Therefore, environmental protection agencies have issued strict emission regulations on automotive diesel engines. Recently, these regulations are even increasingly strengthened. Engine producers search novel on-engine methods such as advanced combustion techniques, utilization of renewable fuels, exhaust gas recirculation, advanced fuel injection methods or use exhaust after-treatment (EAT) systems in order to reduce emission rates on diesel engines. Although those aforementioned on-engine methods are effective to curb emission rates, they result in inefficiency or cannot decrease emission rates satisfactorily at all operating conditions. Therefore, engine manufacturers apply both on-engine techniques and EAT systems to meet the stringent emission norms. EAT systems are highly effective to diminish emission rates, however, they perform inefficiently at low loads due to low exhaust gas temperatures (below 250°C). Therefore, the objective of this study is to demonstrate that engine-out temperatures can be elevated above 250°C at low-loaded cases via cylinder disablement. The engine studied and modeled via Lotus Engine Simulation (LES) software is a six-cylinder turbocharged and intercooled diesel engine. Exhaust temperatures and mass flow rates are predicted at 1200 rpm engine speed and several low loaded conditions using LES program. It is seen that cylinder deactivation results in a considerable exhaust temperature rise (up to 100°C) at low loads which ensures effective EAT management. The method also improves fuel efficiency through reduced total pumping loss. Decreased total air induction due to inactive cylinders is thought to be responsible for improved engine pumping loss. The technique reduces exhaust gas flow rate as air flow is cut off on disabled cylinders. Still, heat transfer rates to the after-treatment catalyst bed do not decrease that much since exhaust temperatures are increased sufficiently. Simulation results are promising; however, further experimental studies are needed to identify the true potential of the method on fuel consumption and EAT improvement.

Keywords: cylinder disablement, diesel engines, exhaust after-treatment, exhaust temperature, fuel efficiency

Procedia PDF Downloads 176

Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks

Procedia PDF Downloads 241

Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

Procedia PDF Downloads 103

Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 336

Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

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Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

Procedia PDF Downloads 284

Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

Procedia PDF Downloads 139

Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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Authors: Irsa Ejaz, Siyang He, Wei Li, Naiyue Hu, Chaochen Tang, Songbo Li, Meng Li, Boubacar Diallo, Guanghui Xie, Kang Yu

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Background: Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. Previously reported NIR model calibrations using the whole grain spectra had moderate accuracy. Improved predictions are achievable by using the spectra of whole grains, when compared with the use of spectra collected from the flour samples. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Objectives: To evaluate the feasibility of using NIRS and the influence of four sample types (whole grains, flours, hulled grain flours, and hull-less grain flours) on the prediction of chemical components to improve the grain sorting efficiency for human food, animal feed, and biofuel. Methods: NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. Results: The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. Conclusion: The established PLSR models could enable food, feed, and fuel producers to efficiently evaluate a large number of samples by predicting the required biochemical components in sorghum grains without destruction.

Keywords: FT-NIR, sorghum grains, biochemical composition, food, feed, fuel, PLSR

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Authors: Surangrat Srisurapanon, Chatchawal Wongjitrat, Navin Horthongkham, Ruengpung Sutthent

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HBV infection causes a potential serious public health problem. The ability to detect the HBV DNA concentration is of the importance and improved continuously. By using quantitative Polymerase Chain Reaction (qPCR), several factors in standardized; source of material, calibration standard curve and PCR efficiency are inconsistent. Digital PCR (dPCR) is an alternative PCR-based technique for absolute quantification using Poisson's statistics without requiring a standard curve. Therefore, the aim of this study is to compare the data set of HBV DNA generated between dPCR and qPCR methods. All samples were quantified by Abbott’s real time PCR and 54 samples with 2 -6 log10 HBV DNA were selected for comparison with dPCR. Of these 54 samples, there were two outlier samples defined as negative by dPCR. Of these two, samples were defined as negative by dPCR, whereas 52 samples were positive by both the tests. The difference between the two assays was less than 0.25 log IU/mL in 24/52 samples (46%) of paired samples; less than 0.5 log IU/mL in 46/52 samples (88%) and less than 1 log in 50/52 samples (96%). The correlation coefficient was r=0.788 and P-value <0.0001. Comparison to qPCR, data generated by dPCR tend to be the overestimation in the sample with low HBV DNA concentration and underestimated in the sample with high viral load. The variation in DNA by dPCR measurement might be due to the pre-amplification bias, template. Moreover, a minor drawback of dPCR is the large quantity of DNA had to be used when compare to the qPCR. Since the technology is relatively new, the limitations of this assay will be improved.

Keywords: hepatitis B virus, real time PCR, digital PCR, DNA quantification

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Authors: Chayanika Hazarika Bordoloi

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This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

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Authors: Duygu Çelgin

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Until the new Occupational Health and Safety Law of Turkey, most of the workers were excluded from the mandatory occupational health and safety services. This new law, made the OHS services mandatory for all workers from all sectors including both public and private. However, in the application some problems and disadvantageous cases are occurred and the government also considered these cases. In this study, the new OHS law of Turkey and the regulations prepared according to the law are studied with the literature search.

Keywords: occupational health and safety in Turkey, OHS servicing in Turkey, safety experts, OHS support

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Authors: Muhammad R. Ahmed, Mohammed Aseeri

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Wireless Sensor Network (WSN) consists of low-cost and multi functional resources constrain nodes that communicate at short distances through wireless links. It is open media and underpinned by an application driven technology for information gathering and processing. It can be used for many different applications range from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. With its nature and application scenario, security of WSN had drawn a great attention. It is known to be valuable to variety of attacks for the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or internal attacker has gained prominence and poses the most challenging attacks to WSN. Many works have been done to secure WSN from internal attacks but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure a WSN needs to find the internal attacks is a challenge. In this paper we present an internal attack detection method based on maximum entropy model. The final experimental works showed that the proposed algorithm does work well at the designed level.

Keywords: internal attack, wireless sensor network, network security, entropy

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Authors: Huang Wei-Yi

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Purpose: Oral cancer patients undergoing skin flap reconstruction may have wounds in the oral cavity, leading to accumulation of blood, clots, and secretions. Inadequate oral care by nursing staff can result in oral infections and pain. Methods: An investigation revealed that ICU nurses' knowledge and adherence to oral care standards were below acceptable levels. Key issues identified included lack of hands-on training opportunities, insufficient experience, absence of oral care standards and regular audits, no in-service education programs, and a lack of oral care educational materials. Interventions: The following measures were implemented: 1) in-service education programs, 2) development of care standards, 3) creation of a monitoring plan, 4) bedside demonstration teaching, and 5) revision of educational materials. Results: The intervention demonstrated that ICU nurses' knowledge and adherence to oral care standards improved, leading to better quality oral care and reduced pain for patients. Conclusion: Through in-service education, bedside demonstrations, establishment of oral care standards, and regular audits, the oral care skills of ICU nurses were significantly enhanced, resulting in improved oral care quality and decreased patient pain.

Keywords: oral care, ICU, improving, oral cancer

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Authors: Veerapat Kitsawat, Muenduen Phisalaphong

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Green natural rubber (NR) composites reinforced with synthetic graphite, using alginate as thickening and dispersing agent, were developed to improve mechanical properties and electrical conductivity. The film fabrication was performed using a latex aqueous microdispersion process. The research found that up to 60 parts per hundred rubbers (phr) of graphite could be successfully integrated into the NR matrix without causing agglomeration and phase separation. Accordingly, the mechanical properties, in terms of tensile strength and Young’s modulus of the composite films, were significantly increased, while the elongation at break decreased with higher graphite loading. The reinforcement strongly improved the hydrophilicity of the composite films, resulting in a higher water absorption rate compared to the neat NR film. Moreover, the incorporation of synthetic graphite significantly improved the chemical resistance of the composite films when exposed to toluene. It is demonstrated that the electrical conductivity of the composite films was considerably enhanced with graphite loading. According to the obtained properties, the developed composites offer potential for further development as conductive substrate for electronic applications.

Keywords: alginate, composite, graphite, natural rubber

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Authors: Rim Chang Hyon, Song Hak Jin, Song Kwang Hyok, Jong Ki Hun

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The calibration of the articulated arm coordinate measuring machine (AACMM) is key to improving calibration accuracy and saving calibration time. To reduce the time consumed for calibration, we should choose the proper calibration gauges and develop a reasonable calibration method. In addition, we should get the exact optimal solution by accurately removing the rough errors within the experimental data. In this paper, we present a calibration method of the portable coordinate measuring arm (PCMA) using the 1.2m long bar guage with cone-holes. First, we determine the locations of the bar gauge and establish an optimal objective function for identifying the structural parameter errors. Next, we make a mathematical model of the calibration algorithm and present a new mathematical method to remove the rough errors within calibration data. Finally, we find the optimal solution to identify the kinematic parameter errors by using Levenberg-Marquardt algorithm. The experimental results show that our calibration method is very effective in saving the calibration time and improving the calibration accuracy.

Keywords: AACMM, kinematic model, parameter identify, measurement accuracy, calibration

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Authors: Nam Kyu Kim, Hee Jun Cha, Jae Jin Seo, Dong Jun Won

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Output power of a photovoltaic (PV) generator depends on incident solar irradiance. If the clouds pass or the climate condition is bad, the PV output fluctuates frequently. When PV generator is connected to the grid, these fluctuations adversely affect power quality. Thus, ramp rate control with battery energy storage system (BESS) is needed to reduce PV output fluctuations. At the same time, for effective BESS operation and sizing the optimal BESS capacity, managing state of charge (SOC) is the most important part. In addition, managing SOC helps to avoid violating the SOC operating range of BESS when performing renewable integration (RI) continuously. As PV and BESS increase, the SOC management of BESS will become more important in the future. This paper presents the SOC management algorithm which helps to operate effectively BESS, and has focused on method to manage SOC while reducing PV output fluctuations. A simulation model is developed in PSCAD/EMTDC software. The simulation results show that the SOC is maintained within the operating range by adjusting the output distribution according to the SOC of the BESS.

Keywords: battery energy storage system, ramp rate control, renewable integration, SOC management

Procedia PDF Downloads 180