Search results for: control area network (CAN)

Authors: Donghee Kang

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Background: Cancer pain is very difficult to control as the mechanism of pain is varied, and the patient has several co-morbidities. The use of Intravenous Patient-Controlled Analgesia (IV-PCA) can effectively control underlying pain and breakthrough pain. Ketamine is used in many pain patients due to its unique analgesic effect. In this study, it was checked whether there was a difference in the amount of analgesic usage, pain control degree, and side effects between patients who controlled pain with fentanyl-based IV-PCA and those who added Ketamine for pain control. Methods: Among the patients referred to this department for cancer pain, IV-PCA was applied to patients who were taking sufficient oral analgesics but could not control them or had blood clotting disorders that made the procedure difficult, and this patient group was targeted. In IV-PCA, 3000 mcg of Fentanyl, 160 mg of Nefopam, and 0.3 mg of Ramosetrone were mixed with normal saline to make a total volume of 100 ml. Group F used this IV-PCA as it is, and group K mixed 250 mg of Ketamine with normal saline to make a total volume of 100 ml. For IV-PCA, the basal rate was 0.5ml/h, the bolus was set to 1ml when pressed once, and the lockout time was set to 15 minutes. If pain was not controlled after IV-PCA application, 500 mcg of Fentanyl was added, and if excessive sedation or breathing difficulties occurred, the use was stopped for one hour. After that, the degree of daily pain control, analgesic usage, and side effects were investigated for seven days using this IV-PCA. Results: There was no difference between the two groups in the demographic data. Both groups had adequate pain control. Initial morphine milligram equivalents did not differ between the two groups, but the total amount of Fentanyl used for seven days was significantly different between the two groups [p=0.014], and group F used more Fentanyl through IV-PCA. In addition, the amount of sleeping pills used during the seven days was higher in Group F [p<0.01]. Overall, there was no difference in the frequency of side effects between the two groups, but the nausea was more frequent in Group F [p=0.031]. Discussion: When the two groups were compared, pain control was good in both groups. This seems to be because Fentanyl-based IV-PCA showed an adequate pain control effect. However, there was a significant difference in the total amount of opioid (Fentanyl) used, which is thought to be the opioid-sparing effect of Ketamine. Also, among the side effects, nausea was significantly less, which is thought to be possible because the amount of opioids used in the Ketamine group was small. The frequency of requesting sleeping pills was significantly less in the group using Ketamine, and it seems that Ketamine also helped improve sleep quality. In conclusion, using Ketamine with an opioid to control pain seems to have advantages. IV-PCA, which can be used effectively when other procedures are difficult, is more effective and safer when used together with Ketamine than opioids alone.

Keywords: cancer pain, intravenous patient-controlled analgesia, Ketamine, opioid

Procedia PDF Downloads 74

Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

Procedia PDF Downloads 478

Authors: Anton Golubkov, Gleb Ermachkov, Aleksandr Smerdin, Oleg Sidorov, Victor Philippov

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Current collection quality is one of the limiting factors when increasing trains movement speed in the rail sector. With the movement speed growth, the impact forces on the current collector from the rolling stock and the aerodynamic influence increase, which leads to the spread in the contact pressure values, separation of the current collector head from the contact wire, contact arcing and excessive wear of the contact elements. The upcoming trend in resolving this issue is the use of the automatic control systems providing stabilization of the contact pressure value. The present paper considers the features of the contemporary automatic control systems of the current collector’s pressure; their major disadvantages have been stated. A scheme of current collector pressure automatic control has been proposed, distinguished by a proactive influence on undesirable effects. A mathematical model of contact strips wearing has been presented, obtained in accordance with the provisions of the central composition rotatable design program. The analysis of the obtained dependencies has been carried out. The procedures for determining the optimal current collector pressure on the contact wire and the pressure control principle in the pneumatic drive have been described.

Keywords: contact strip, current collector, high-speed running, program control, wear

Procedia PDF Downloads 136

Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

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In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

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Authors: Samira Rabiei, Faezeh Askari, Reza Rastmanesh

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Objective: To evaluate the effects of nutrition education and adherence to a healthy diet on glycemic and lipidemic control in patients with T2DM. Material and Methods: A randomized controlled trial was conducted on 494 patients with T2DM, aged 14-87 years from both sexes who were selected by convenience sampling from referees to Aliebneabitaleb hospital in Ghom. The participants were divided into two 247 person groups by stratified randomization. Both groups received a diet adjusted based on ideal body weight, and the intervention group was additionally educated about healthy food choices regarding diabetes. Information on medications, psychological factors, diet and physical activity was obtained from questionnaires. Blood samples were collected to measure FBS, 2 hPG, HbA1c, cholesterol, and triglyceride. After 2 months, weight and biochemical parameters were measured again. Independent T-test, Mann-Whitney, Chi-square, and Wilcoxon were used as appropriate. Logistic regression was used to determine the odds ratio of abnormal glycemic and lipidemic control according to the intervention. Results: The mean weight, FBS, 2 hPG, cholesterol and triglyceride after intervention were significantly lower than before that (p < 0.05). Discussion: Nutrition education plus a weigh reducer diet is more effective on glycemic and lipidemic control than a weight reducer diet, alone.

Keywords: type 2 diabetes mellitus, nutrition education, glycemic control, lipid profile

Procedia PDF Downloads 191

Authors: Farnaz Fotovvatikhah, Javad Akbari

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Test time of a test architecture is an important factor which depends on the architecture's delay and test patterns. Here a new architecture to store the test results based on network on chip is presented. In addition, simple analytical model is proposed to calculate link test time for built in self-tester (BIST) and external tester (Ext) in multiprocessor systems. The results extracted from the model are verified using FPGA implementation and experimental measurements. Systems consisting 16, 25, and 36 processors are implemented and simulated and test time is calculated. In addition, BIST and Ext are compared in terms of test time at different conditions such as at different number of test patterns and nodes. Using the model the maximum frequency of testing could be calculated and the test structure could be optimized for high speed testing.

Keywords: test, nano on-chip network, JTAG, modelling

Procedia PDF Downloads 475

Authors: Mkhinini Maher, Knani Jilani

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We present in this work the performances of a mobile omnidirectional robot through evaluating its management of the redundancy of actuation. Thus we come to the predictive control implemented. The distribution of the wringer on the robot actions, through the inverse pseudo of Moore-Penrose, corresponds to a -geometric- distribution of efforts. We will show that the load on vehicle wheels would not be equi-distributed in terms of wheels configuration and of robot movement. Thus, the threshold of sliding is not the same for the three wheels of the vehicle. We suggest exploiting the redundancy of actuation to reduce the risk of wheels sliding and to ameliorate, thereby, its accuracy of displacement. This kind of approach was the subject of study for the legged robots.

Keywords: mobile robot, actuation, redundancy, omnidirectional, inverse pseudo moore-penrose, reductive control

Procedia PDF Downloads 501

Authors: Obadiah Nwabueze

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Bodija market is classified as Central Business District (CBD) of Ibadan North Local Government Area of Oyo State (Nigeria) because of socio economic activities, so Crime is a peculiar social issue that causes insecurity. The law enforcement agencies tasked with crime prevention and control such as the Nigerian Police have insufficient manpower, and a resultant effect is the emergence of Vigilante groups as citizen’s response to crime control and prevention (self-help). The research design adopted for this study is a case study design exploring Vigilante activities in Bodija Market. The study utilizes both quantitative and qualitative approach, sources of data includes primary and secondary sources. A sample of 127 respondents randomly picked from the 4 sections of Bodija Market through questionnaire, comprising of 50 male and 77 females which alienates issues of gender bias in addition to the 4 in-depth interview, making a total of 131 respondents. Statistical package for Social Sciences (SPSS) was used. The descriptive statistics of simple frequency, percentage, charts and graphs were computed for the analysis. Finding in the study shows that the market vigilante is able to deter and disrupt criminal activities through strategic spiritual intelligence (SSI), use of charm and juju, physical presence in strategic locations vulnerable to crime occurrence. Findings in the study also show that vigilantes collaborate with the police by assisting them in surveillance, tracking down criminals, identifying black spots, acting as informants to the police, arrest and handover criminal to police. Their challenges include poor equipment, motivation, unhealthy rivalry between the vigilante and the police. The study recommends that the government should support vigilantes with logistics and training, including patrol vehicle and radio communication. The study also recommends the integration of the informal mechanism (juju and charm) of crime detection and prevention into the formal policing strategy, an office should be created in the force commands for use of SSI.

Keywords: central business district, CBD, charm, Juju, strategic spiritual intelligence, SSI

Procedia PDF Downloads 234

Authors: Yuchien Lin

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This study attempted to investigate the changes in electroencephalography (EEG) and emotion regulation following eight-week inward-attention meditation training program. The subjects were 24 adults without meditation experiences divided into meditation and control groups. The quantitatively analyzed changes in psychophysiological parameters during inward-attention meditation, and evaluated the emotion scores assessed by the State-Trait Anxiety Inventory (STAI), the Positive and Negative Affect Schedule (PANAS), and the Emotion Regulation Scale (ERS). The results were found: (1) During meditation, significant EEG increased for theta-band activity in the frontal and the bilateral temporal areas, for alpha-band activity in the left and central frontal areas, and for gamma-band activity in the left frontal and the left temporal areas. (2) The meditation group had significantly higher positive affect in posttest than in pretest. (3) There was no significant difference in the changes of EEG spectral characteristics and emotion scores in posttest and pretest for the control group. In the present study, a unique meditative concentration task with a constant level of moderate mental effort focusing on the center of brain was used, so as to enhance frontal midline theta, alpha, and gamma-band activity. These results suggest that this mental training allows individual reach a specific mental state of relaxed but focused awareness. The gamma-band activity, in particular, enhanced over left frontoparietal area may suggest that inward-attention meditation training involves temporal integrative mechanisms and may induce short-term and long-term emotion regulation abilities.

Keywords: meditation, EEG, emotion regulation, gamma activity

Procedia PDF Downloads 202

Authors: Ebrahim H. Kapeel, Ahmed M. Kamel, Hossam Hendy, Yehia Z. Elhalwagy

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Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control law is designed for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.

Keywords: attitude control, nonlinear PID, dynamic inversion

Procedia PDF Downloads 97

Authors: Vinko Lešić, Mario Vašak, Anita Martinčević, Marko Gulin, Antonio Starčić, Hrvoje Novak

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With 40% of total world energy consumption, building systems are developing into technically complex large energy consumers suitable for application of sophisticated power management approaches to largely increase the energy efficiency and even make them active energy market participants. Centralized control system of building heating and cooling managed by economically-optimal model predictive control shows promising results with estimated 30% of energy efficiency increase. The research is focused on implementation of such a method on a case study performed on two floors of our faculty building with corresponding sensors wireless data acquisition, remote heating/cooling units and central climate controller. Building walls are mathematically modeled with corresponding material types, surface shapes and sizes. Models are then exploited to predict thermal characteristics and changes in different building zones. Exterior influences such as environmental conditions and weather forecast, people behavior and comfort demands are all taken into account for deriving price-optimal climate control. Finally, a DC microgrid with photovoltaics, wind turbine, supercapacitor, batteries and fuel cell stacks is added to make the building a unit capable of active participation in a price-varying energy market. Computational burden of applying model predictive control on such a complex system is relaxed through a hierarchical decomposition of the microgrid and climate control, where the former is designed as higher hierarchical level with pre-calculated price-optimal power flows control, and latter is designed as lower level control responsible to ensure thermal comfort and exploit the optimal supply conditions enabled by microgrid energy flows management. Such an approach is expected to enable the inclusion of more complex building subsystems into consideration in order to further increase the energy efficiency.

Keywords: price-optimal building climate control, Microgrid power flow optimisation, hierarchical model predictive control, energy efficient buildings, energy market participation

Procedia PDF Downloads 455

Authors: M. Sirhan, S. Bekhor, A. Sidess

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In-service pavements deteriorate with time due to traffic wheel loads, environment, and climate conditions. Pavement deterioration leads to a reduction in their serviceability and structural behavior. Consequently, proper maintenance and rehabilitation (M&R) are necessary actions to keep the in-service pavement network at the desired level of serviceability. Due to resource and financial constraints, the pavement management system (PMS) prioritizes roads most in need of maintenance and rehabilitation action. It recommends a suitable action for each pavement based on the performance and surface condition of each road in the network. The pavement performance and condition are usually quantified and evaluated by different types of roughness-based and stress-based indices. Examples of such indices are Pavement Serviceability Index (PSI), Pavement Serviceability Ratio (PSR), Mean Panel Rating (MPR), Pavement Condition Rating (PCR), Ride Number (RN), Profile Index (PI), International Roughness Index (IRI), and Pavement Condition Index (PCI). PCI is commonly used in PMS as an indicator of the extent of the distresses on the pavement surface. PCI values range between 0 and 100; where 0 and 100 represent a highly deteriorated pavement and a newly constructed pavement, respectively. The PCI value is a function of distress type, severity, and density (measured as a percentage of the total pavement area). PCI is usually calculated iteratively using the 'Paver' program developed by the US Army Corps. The use of soft computing techniques, especially Artificial Neural Network (ANN), has become increasingly popular in the modeling of engineering problems. ANN techniques have successfully modeled the performance of the in-service pavements, due to its efficiency in predicting and solving non-linear relationships and dealing with an uncertain large amount of data. Typical regression models, which require a pre-defined relationship, can be replaced by ANN, which was found to be an appropriate tool for predicting the different pavement performance indices versus different factors as well. Subsequently, the objective of the presented study is to develop and train an ANN model that predicts the PCI values. The model’s input consists of percentage areas of 11 different damage types; alligator cracking, swelling, rutting, block cracking, longitudinal/transverse cracking, edge cracking, shoving, raveling, potholes, patching, and lane drop off, at three severity levels (low, medium, high) for each. The developed model was trained using 536,000 samples and tested on 134,000 samples. The samples were collected and prepared by The National Transport Infrastructure Company. The predicted results yielded satisfactory compliance with field measurements. The proposed model predicted PCI values with relatively low standard deviations, suggesting that it could be incorporated into the PMS for PCI determination. It is worth mentioning that the most influencing variables for PCI prediction are damages related to alligator cracking, swelling, rutting, and potholes.

Keywords: artificial neural networks, computer programming, pavement condition index, pavement management, performance prediction

Procedia PDF Downloads 127

Authors: D. Mokhtari

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Any variation in environmental characteristics of geomorphosites would lead to destabilisation of their geotouristic values all around the planet. The Urmia lake, with an area of approximately 5,500 km2 and a catchment area of 51,876 km2, and to which various reasons over time, especially in the last fifty years have seen a sharp decline and have decreased by about 93 % in two recent decades. These variations are not only driving significant changes in the morphology and ecology of the present lake landscape, but at the same time are shaping newly formed morphologies, which vanished some valuable geomorphosites or develop into smaller geomorphosites with significant value from a scientific and cultural point of view. This paper analyses and discusses features and evolution in several representative coastal and island geomorphosites. For this purpose, a total of 23 geomorphosites were studied in two data series (1963 and 2015) and the respective data were compared and analysed. The results showed, The total loss in geomorphosites area in a half century amounted to a loss of more than 90% of the valuable geomorphosites. Moreover, the comparison between the mean yearly value of coastal area lost over the entire period and the yearly average calculated for the shorter period (1998-2014) clearly indicates a pattern of acceleration. This acceleration in the rate of reduction in lake area was seen in most of the southern half of the lake. In the region as well, the general water-level falling is not only causing the loss of a significant water resource, which is followed by major impact on regional ecosystems, but is also driving the most marked recent (last century) changes in the geotouristic landscapes. In fact, the disappearance of geomorphosites means the loss of tourism phenomenon. In this context attention must be paid to the question of conservation. The action needed to safeguard geomorphosites includes: 1) Preventive action, 2) Corrective action, and 3) Sharing knowledge.

Keywords: geomorphosite, environmental changes, changing lake, Urmia lake, northwest of Iran

Procedia PDF Downloads 368

Authors: Medani Khaled Ben Oualid

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Most of researchers solved and analyzed the ORPD problem in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, metaheuristic techniques, whale optimization algorithm, real power loss minimization, contingency conditions

Procedia PDF Downloads 83

Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

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In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: Haraz basin, change detection, land-use, satellite data

Procedia PDF Downloads 405

Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

Procedia PDF Downloads 171

Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

Procedia PDF Downloads 362

Authors: Kejal Joshi Reddy, Sirimavo Nair

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Micronutrient malnutrition affects pregnant women and children extremely with reference to growth manifestations in gestation as well as after birth. Early fetal development affected by iodine and iron deficiency leads to poor life quality. Various researchers have found interesting interrelations between iron and iodine. A few studies on impact assessment of DFS supplementation during pregnancy have been reported in India. Aim To provide meaningful contribution by assessing the efficacy of DFS supplementation on iodine and iron status of pregnant women. Design An interventional study. Setting A semi government hospital of urban Vadodara. Subjects Pregnant women (n=150) enrolled during first trimester (< 12 weeks) and followed up till the end of gestation, n=75 were divided in experimental (DFS supplemented) and control (Non supplemented) group. Results Impact on iron and iodine status was assessed by Hb concentration and UIE respectively. Mean Hb improved significantly (p < 0.001) (+0.42 g/dl) in experimental group and reduced non significantly (-0.20 g/dl) in control group at the end, since DFS provided additional 93 mg of iron within 6 months. Median UIE improved non significantly (278.6 to 299.01µg/L) in experimental group and decreased significantly (p < 0.05) (376.59 to 288.66 µg/L) in control group. Conclusion DFS could improve iron and iodine status of experimental group compared to control group. It is an effective measure to control two essential micronutrient deficiencies together.

Keywords: DFS supplementation, anemia, pregnancy, iodine deficiency, iron

Procedia PDF Downloads 460

Authors: Al-Mutary M., Alhimaidi A., Al-Ghadi M. Iwamoto D., Javed Ahmad. Abdulaziz A. Al-Khedhairy

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The aim of the present study was to evaluate the effect of ovine follicular fluid supplementation during IVM of sheep oocytes on the resumption of meiosis, glutathione (GSH) content and expression of Bax, Bcl-2, and HSPB1 genes. Sheep ovaries were collected from Riyadh slaughterhouse, KSA. Oocytes were aspirated from 3-6 mm follicles. Ovine oocytes were cultured in maturation medium with 0% (control), 10%, 20%, 40% of ovine follicular fluid for 24 h. Results indicated that the rate of oocyte maturation was significantly (P≤0.05) decreased in 40% OFF (36.87%) versus the control (61.3%), 10% OFF (63.95%) and 20% OFF (64.08%). Supplementation of 10% OFF to IVM medium induced an intra-oocyte GSH concentration significantly higher than that found in ovine oocytes cultured with 20% OFF and 40% OFF and similar to the GSH content in oocytes cultured without FF. Real time polymerase chain reaction analysis for gene expression revealed no differences in Bax, Bcl-2, HSPB1 genes between control and 10% OFF group, whereas they were strongly expressed in 20% OFF and 40% OFF (P < 0.05) when compared to the control and 10% OFF. In conclusion the addition of 10% OFF to the IVM culture of sheep oocytes is recommended to support cytoplasmic maturation and increase oocytes competence.

Keywords: IVM, oocyte maturation, gene expression, follicular fluid

Procedia PDF Downloads 356

Authors: Siming Wang, Qing Ni, Yu Wu, Ruihai Xu, Hong Ye

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Porous electric heaters, compared to conventional electric heaters, exhibit excellent heating performance due to their large specific surface area. Porous electric heaters employ porous metallic materials or conductive porous ceramics as the heating element. The former attains a low heating power with a fixed current due to the low electrical resistivity of metal. Although the latter can bypass the inherent challenges of porous metallic materials, the fabrication process of the conductive porous ceramics is complicated and high cost. This work proposed a porous ceramic electric heater with dielectric honeycomb ceramic as a substrate and surface conductive coating as a heating element. The conductive coating was prepared by the sol-gel method using silica sol and methyl trimethoxysilane as raw materials and graphite powder as conductive fillers. The conductive mechanism and degradation reason of the conductive coating was studied by electrical resistivity and thermal stability analysis. The heating performance of the proposed heater was experimentally investigated by heating air and deionized water. The results indicate that the electron transfer is achieved by forming the conductive network through the contact of the graphite flakes. With 30 wt% of graphite, the electrical resistivity of the conductive coating can be as low as 0.88 Ω∙cm. The conductive coating exhibits good electrical stability up to 500°C but degrades beyond 600°C due to the formation of many cracks in the coating caused by the weight loss and thermal expansion. The results also show that the working medium has a great influence on the volume power density of the heater. With air under natural convection as the working medium, the volume power density attains 640.85 kW/m3, which can be increased by 5 times when using deionized water as the working medium. The proposed honeycomb ceramic electric heater has the advantages of the simple fabrication method, low cost, and high volume power density, demonstrating great potential in the fluid heating field.

Keywords: conductive coating, honeycomb ceramic electric heater, high specific surface area, high volume power density

Procedia PDF Downloads 139

Authors: A. Laksanayothin, W. Ariyawong

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Mae Moh Lignite Mine is the largest open-pit mine in Thailand. The mine serves coal to the power plant about 16 million tons per year. This amount of coal can produce electricity accounting for about 10% of Nation’s electric power generation. The mining area of Mae Moh Mine is about 28 km2. At present, the deepest area of the pit is about 280 m from ground level (+40 m. MSL) and in the future the depth of the pit can reach 520 m from ground level (-200 m.MSL). As the size of the pit is quite large, the stability of the pit is seriously important. Furthermore, the preliminary drilling and extended drilling in year 1989-1996 had found high pressure aquifer under the pit. As a result, the pressure of the underground water has to be released in order to control mine pit stability. The study by the consulting experts later found that 3-5 million m3 per year of the underground water is needed to be de-watered for the safety of mining. However, the quality of this discharged water should meet the standard. Therefore, the ground water treatment facility has been implemented, aiming to reduce the amount of naturally contaminated Arsenic (As) in discharged water lower than the standard limit of 10 ppb. The treatment system consists of coagulation and filtration process. The main components include rapid mixing tanks, slow mixing tanks, sedimentation tank, thickener tank and sludge drying bed. The treatment process uses 40% FeCl3 as a coagulant. The FeCl3 will adsorb with As(V), forming floc particles and separating from the water as precipitate. After that, the sludge is dried in the sand bed and then be disposed in the secured land fill. Since 2011, the treatment plant of 12,000 m3/day has been efficiently operated. The average removal efficiency of the process is about 95%.

Keywords: arsenic, coagulant, ferric chloride, groundwater, lignite, coal mine

Procedia PDF Downloads 300

Authors: Valentin P. Velikov

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Automatic program generation saves time, human resources, and allows receiving syntactically clear and logically correct modules. The 4-th generation programming languages are related to drawing the data and the processes of the subject area, as well as, to obtain a frame of the respective information system. The application can be separated in interface and business logic. That means, for an interactive generation of the needed system to be used an already existing toolkit or to be created a new one.

Keywords: computer science, graphical user interface, user dialog interface, dialog frames, data modeling, subject area modeling

Procedia PDF Downloads 291

Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

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Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

Procedia PDF Downloads 92

Authors: Chao Yang, Jinchuan Zhang, Yongqiang Xiong

Abstract:

The Lower Cambrian Niutitang Formation shale (NFS) deposited in the marine deep-shelf environment in Southeast Upper Yangtze (SUY), possess excellent source rock basis for shale gas generation, however, it is currently challenged by being over-mature with strong tectonic deformations, leading to much uncertainty of gas-bearing potential. With emphasis on the shale gas enrichment of the NFS, analyses were made based on the regional gas-bearing differences obtained from field gas-desorption testing of 18 geological survey wells across the study area. Results show that the NFS bears low gas content of 0.2-2.5 m³/t, and the eastern region of SUY is higher than the western region in gas content. Moreover, the methane fraction also presents the similar regional differentiation with the western region less than 10 vol.% while the eastern region generally more than 70 vol.%. Through the analysis of geological theory, the following conclusions are drawn: Depositional environment determines the gas-enriching zones. In the western region, the Dengying Formation underlying the NFS in unconformity contact was mainly plateau facies dolomite with caves and thereby bears poor gas-sealing ability. Whereas the Laobao Formation underling the NFS in eastern region was a set of siliceous rocks of shelf-slope facies, which can effectively prevent the shale gas from escaping away from the NFS. The tectonic conditions control the gas-enriching bands in the SUY, which is located in the fold zones formed by the thrust of the Southern China plate towards to the Sichuan Basin. Compared with the western region located in the trough-like folds, the eastern region at the fold-thrust belts was uplifted early and deformed weakly, resulting in the relatively less mature level and relatively slight tectonic deformation of the NFS. Faults determine whether shale gas can be accumulated in large scale. Four deep and large normal faults in the study area cut through the Niutitang Formation to the Sinian strata, directly causing a large spillover of natural gas in the adjacent areas. For the secondary faults developed within the shale formation, the reverse faults generally have a positive influence on the shale accumulation while the normal faults perform the opposite influence. Overall, shale gas enrichment targets of the NFS, are the areas with certain thickness of siliceous rocks at the basement of the Niutitang Formation, and near the margin of the paleouplift with less developed faults. These findings provide direction for shale gas exploration in South China, and also provide references for the areas with similar geological conditions all over the world.

Keywords: over-mature marine shale, shale gas accumulation, structure-complicated area, Southeast Upper Yangtze

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Authors: Zerihun Ketema Tadesse, Dabbu Suman Reddy

Abstract:

Brain-Computer Interfaces (BCIs) give the possibility for disabled people to communicate and control devices. This work aims at developing steady-state visual evoked potential (SSVEP)-based BCI for patients with limb disabilities. In hospitals, devices like nurse emergency call devices, lights, and TV sets are what patients use most frequently, but these devices are operated manually or using the remote control. Thus, disabled patients are not able to operate these devices by themselves. Hence, SSVEP-based BCI system that can allow disabled patients to control nurse calling device and other devices is proposed in this work. Portable LED visual stimulator that flickers at specific frequencies of 7Hz, 8Hz, 9Hz and 10Hz were developed as part of this project. Disabled patients can stare at specific flickering LED of visual stimulator and Emotiv EPOC used to acquire EEG signal in a non-invasive way. The acquired EEG signal can be processed to generate various control signals depending upon the amplitude and duration of signal components. MATLAB software is used for signal processing and analysis and also for command generation. Arduino is used as a hardware interface device to receive and transmit command signals to the experimental setup. Therefore, this study is focused on the design and development of Steady-state visually evoked potential (SSVEP)-based BCI for limb disabled patients, which helps them to operate and control devices in the hospital room/wards.

Keywords: SSVEP-BCI, Limb Disabled Patients, LED Visual Stimulator, EEG signal, control devices, hospital room/wards

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Authors: Mahsa Oroojeni Mohammad Javad

Abstract:

Globalization of economic activity and rapid growth of information technology has resulted in shorter product lifecycles, reduced transport capacity, dynamic and changing customer behaviors, and an increased focus on supply chain design in recent years. The design of the supply chain network is one of the most important supply chain management decisions. These decisions will have a long-term impact on the efficacy and efficiency of the supply chain. In this paper, a two-objective mixed-integer linear programming (MILP) model is developed for designing and optimizing a closed-loop green supply chain network that, to the greatest extent possible, includes all real-world assumptions such as multi-level supply chain, the multiplicity of production technologies, and multiple modes of transportation, with the goals of minimizing the total cost of the chain (first objective) and minimizing total emissions of emissions (second objective). The ε-constraint and CPLEX Solver have been used to solve the problem as a single-objective problem and validate the problem. Finally, the sensitivity analysis is applied to study the effect of the real-world parameters’ changes on the objective function. The optimal management suggestions and policies are presented.

Keywords: closed-loop supply chain, multi-level green supply chain, mixed-integer programming, transportation modes

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Authors: Alok Saini, Rajkumar Ghosh

Abstract:

Water is nature's important resource for survival of all living things, but freshwater scarcity exists in some parts of world. This study has predicted that Gomti Nagar area (49.2 sq. km.) will harvest about 91110 ML of rainwater till 2051 (assuming constant and present annual rainfall). But 17.71 ML of rainwater was harvested from only 53 buildings in Gomti Nagar area in the year 2021. Water level will be increased (rise) by 13 cm in Gomti Nagar from such groundwater recharge. The total annual groundwater abstraction from Gomti Nagar area was 35332 ML (in 2021). Due to hydrogeological constraints and lower annual rainfall, groundwater recharge is less than groundwater abstraction. The recent scenario is only 0.07% of rainwater recharges by RTRWHs in Gomti Nagar. But if RTRWHs would be installed in all buildings then 12.39% of rainwater could recharge groundwater table in Gomti Nagar area. But if RTRWHs would be installed in all buildings then 12.39% of rainwater could recharge groundwater table in Gomti Nagar area. Gomti Nagar is situated in 'Zone–A' (water distribution area) and groundwater is the primary source of freshwater supply. Current scenario indicates only 0.07% of rainwater recharges by RTRWHs in Gomti Nagar. In Gomti Nagar, the difference between groundwater abstraction and recharge will be 735570 ML in 30 yrs. Statistically, all buildings at Gomti Nagar (new and renovated) could harvest 3037 ML of rainwater through RTRWHs annually. The most recent monsoonal recharge in Gomti Nagar was 10813 ML/yr. Harvested rainwater collected from RTRWHs can be used for rooftop irrigation, and residential kitchen and gardens (home grown fruit and vegetables). According to bylaws, RTRWH installations are required in both newly constructed and existing buildings plot areas of 300 sq. m or above. Harvested rainwater is of higher quality than contaminated groundwater. Harvested rainwater from RTRWHs can be considered water self-sufficient. Rooftop Rainwater Harvesting Systems (RTRWHs) are least expensive, eco-friendly, most sustainable, and alternative water resource for artificial recharge. This study also predicts about 3.9 m of water level rise in Gomti Nagar area till 2051, only when all buildings will install RTRWHs and harvest for groundwater recharging. As a result, this current study responds to an impact assessment study of RTRWHs implementation for the water scarcity problem in the Gomti Nagar area (1.36 sq.km.). This study suggests that common storage tanks (recharge wells) should be built for a group of at least ten (10) households and optimal amount of harvested rainwater will be stored annually. Artificial recharge from alternative water sources will be required to improve the declining water level trend and balance the groundwater table in this area. This over-exploitation of groundwater may lead to land subsidence, and development of vertical cracks.

Keywords: aquifer, aquitard, artificial recharge, bylaws, groundwater, monsoon, rainfall, rooftop rainwater harvesting system, RTRWHs water table, water level

Procedia PDF Downloads 77

Authors: Lea Lenhardt, Ivana Zeković, Tatjana Dramićanin, Miroslav D. Dramićanin

Abstract:

Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) and artificial neural networks (ANN) were used for characterization and classification of honey. Excitation emission spectra were obtained for 95 honey samples of different botanical origin (acacia, sunflower, linden, meadow, and fake honey) by recording emission from 270 to 640 nm with excitation in the range of 240-500 nm. Fluorescence spectra were described with a six-component PARAFAC model, and PARAFAC scores were further processed with two types of ANN’s (feed-forward network and self-organizing maps) to obtain algorithms for classification of honey on the basis of their botanical origin. Both ANN’s detected fake honey samples with 100% sensitivity and specificity.

Keywords: honey, fluorescence, PARAFAC, artificial neural networks

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Authors: Hemlata Chitte, Anita Chorey, V. M. Bhale, Bharti Tijare

Abstract:

A field experiment was conducted during kharif season of 2013-14 at Agronomy research farm, Dr. PDKV, Akola, to study the productivity and nitrogen use efficiency in cotton using organic nitrification inhibitors. The experiment was laid out in factorial randomized block design with three replications each having nine treatment combinations comprising three fertilizer levels viz., 75% RDF (F1), 100% RDF (F2) and 125% RDF (F3) and three nitrification inhibitors viz., neem cake @ 300 kgha-1 (N1), karanj cake @ 300 kgha-1 (N2) and control (N3). The result showed that various growth attributes viz., plant height, number of functional leaves plant-1, monopodial and sympodial branches and leaf area plant-1(dm2) were maximum in fertilizer level 125% RDF over fertilizer level 75% RDF and which at par with 100% RDF. In case of yield attributes and yield, number of bolls per plant, Seed cotton yield and stalk yield kg ha-1 significantly higher in fertilizer level 125% RDF over 100% RDF and 75% RDF. Uptake of NPK kg ha-1 after harvest of cotton crop was significantly higher in fertilizer level 125% RDF over 100% RDF and 75% RDF. Significantly highest nitrogen use efficiency was recorded with fertilizer level 75 % RDF as compared to 100 % RDF and lowest nitrogen use efficiency was recorded with 125% RDF level. Amongst nitrification inhibitors, karanj cake @ 300 kg ha-1 increases potentiality of growth characters, yield attributes, uptake of NPK and NUE as compared to control and at par with neem cake @ 300 kgha-1. Interaction effect between fertilizer level and nitrification inhibitors were found to be non significant at all growth attributes and uptake of nutrient but was significant in respect of seed cotton yield.

Keywords: cotton, fertilizer level, nitrification inhibitor and nitrogen use efficiency, nutrient uptake

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Authors: Laura A. Rodriguez-Villamizar, Alvaro Osornio-Vargas, Brian H. Rowe, Rhonda J. Rosychuk

Abstract:

Introduction/Objectives: The Census Metropolitan Area of Edmonton (CMAE) has important industrial emissions to the air from the Industrial Heartland Alberta (IHA) at the Northeast and the coal-fired power plants (CFPP) at the West. The objective of the study was to explore the presence of clusters of children asthma ED visits in the areas around the IHA and the CFPP. Methods: Retrospective data on children asthma ED visits was collected at the dissemination area (DA) level for children between 2 and 14 years of age, living in the CMAE between April 1, 2004, and March 31, 2010. We conducted a spatial analysis of disease clusters around putative sources with count (ecological) data using descriptive, hypothesis testing, and multivariable modeling analysis. Results: The mean crude rate of asthma ED visits was 9.3/1,000 children population per year during the study period. Circular spatial scan test for cases and events identified a cluster of children asthma ED visits in the DA where the CFPP are located in the Wabamum area. No clusters were identified around the IHA area. The multivariable models suggest that there is a significant decline in risk for children asthma ED visits as distance increases around the CFPP area this effect is modified at the SE direction with mean angle 125.58 degrees, where the risk increases with distance. In contrast, the regression models for IHA suggest that there is a significant increase in risk for children asthma ED visits as distance increases around the IHA area and this effect is modified at SW direction with mean angle 216.52 degrees, where the risk increases at shorter distances. Conclusions: Different methods for detecting clusters of disease consistently suggested the existence of a cluster of children asthma ED visits around the CFPP but not around the IHA within the CMAE. These results are probably explained by the direction of the air pollutants dispersion caused by the predominant and subdominant wind direction at each point. The use of different approaches to detect clusters of disease is valuable to have a better understanding of the presence, shape, direction and size of clusters of disease around pollution sources.

Keywords: air pollution, asthma, disease cluster, industry

Procedia PDF Downloads 276