Search results for: holter monitor

Authors: Amal Abo El-Maaty, Amira Mohamed, Nashwa Abu-Aita, Hisham Morgan

Abstract:

For estimating markers of overweight or obesity of brood mares used for riding and training, 17 mares of different body conditions were subjected to blood sampling and ultrasound examination to measure rump fat thickness and monitor ovulation for six consecutive weeks. Also length (L), heart girth (G) and withers height (H) were measured to estimate body weight (BW), body fat %, body fat mass (BFM) and body mass index (BMI). Mares were classified into three groups according to both body condition score (BCS) and rump back fat (BF). Overweight mares (O) were having BCS > 7 and BF thickness >7mm, moderate body condition (M) mares were having BCS >3and ≤7and BF <3and <7mm, and emaciated mares (E) were having BCS ≤3 and BF ≤3mm. glucose, triglycerides, nitric oxide, ovarian, thyroid, insulin, insulin like growth factor-I (IGF-1), and leptin hormones were measured. Results revealed that BCS, G, L, L*G*H, BW, BF, fat %, BFM were significantly (P<0.0001) decreasing linearly from O to E. T4 concentrations of E were significantly high (P=0.04) compared to M and O but T3 concentrations tended to decrease in E (P>0.05). Insulin and IGF-1 concentrations tended to be high in O (P>0.05) and decrease with the decrease of body condition. M had (P=0.007) the highest leptin, but E mares had the lowest P4 concentrations (P=0.01). Concentrations of glucose and NO decreased with the decrease of BCS and BF but triglycerides of O were insignificantly high. In conclusion, exercise could prevent the development of metabolic syndrome in horses and back fat and morphometric measurements were the easiest and simple assessment of overweight and deviation to obesity.

Keywords: body condition score, insulin, leptin, mares, rump fat

Procedia PDF Downloads 309

Authors: Matthew Olanrewaju Ibiyomi

Abstract:

The study examined the abundance of free-range natural inhabitants of the Federal University of Agriculture, Abeokuta (FUNAAB) Zoo Park. A baseline data of free-ranging inhabitants of the Park is essential to monitor trends and institute conservation plans through unsustainable natural resources exploitation and habitat destruction. Four transects were selected across the study area. Each transect was traversed for a period of four months and observations was carried out twice a day. The Four existing tracks explored during the study were the aviary, reptile, carnivore and primate tracks. Data were analyzed using descriptive statistics. The findings from this study revealed that 8 species of natural inhabitants were identified, which were the Vervet monkey (Chlorocebuspygerythrus), Maxwell duiker(Philantombamaxwellii), Mongoose (Herpestidaespp), Bushbuck(Tragelaphusscriptus), Cobra (Najanaja), Ground squirrel (Marmotinispp), Senegal coucal(Centropus senegalensis), Black kite (Milvus migrans). The result further showed that a total of 115 animals were encountered in the primate transect, 77 animals in the carnivores transect, 46 animals in the aviary transect and 34 animals in the ungulates transect by the representative of 43.3%, 28.3%, 15.8% and 12.5% respectively. Human activities and level of disturbance were observed to have affected the abundance and distribution of animals at Funaab Zoo Park. Continuous field inventory is recommended to ascertain the dynamics of animals observed as free-range inhabitants in this study.

Keywords: abundance, ecosystem, extinction, free-range

Procedia PDF Downloads 66

Authors: Samuel Knox, Verdon Crann, Peyman Amiri, William Crowther

Abstract:

There exists a shortage of open-source firmware for allowing researchers to focus on implementing high-level planning and control strategies for multi aerial robotic systems in simulation and experiment. Within this body of work, practical firmware is presented, which performs all supplementary tasks, including communications, pre and post-experiment procedures, and emergency safety measures. This allows researchers to implement high-level planning and control algorithms for path planning, traffic management, flight formation and swarming of aerial robots. The framework is built in Python using the MAVSDK library, which is compatible with flight controllers running PX4 firmware and onboard computers based on Linux. Communication is performed using Wi-Fi and the MQTT protocol, currently implemented using a centralized broker. Finally, a graphical user interface (GUI) has been developed to send general commands and monitor the agents. This framework enables researchers to prepare customized planning and control algorithms in a modular manner. Studies can be performed experimentally and in simulation using PX4 software in the loop (SITL) and the Gazebo simulator. An example experimental use case of the framework is presented using novel distributed planning and control strategies. The demonstration is performed using off-the-shelf components and minimal setup.

Keywords: aerial robotics, distributed framework, experimental, planning and control

Procedia PDF Downloads 101

Authors: Bindu Kumari, Bindu Kumari Singh

Abstract:

Endosulfan is known to be one of the highly toxic agricultural pesticides commonly used in our societies. With the widespread use of Endosulfan in agriculture, human beings are most likely to be exposed to it, either orally by eating Endosulfan-contaminated foods or by nose and whole body inhalation in the farms during its application. The present study was conducted to observe the changes in the serum uric acid level of the Swiss albino rats due to the administration of Endosulfan. 3.0 mg Endosulfan/kg body weight was daily administered orally to albino rats for 28 days period. Alterations in their K.F.T. parameters were recorded at a regular interval of 7 days within this 28 days period and were compared with those of control rats. All rats were monitored for any observable toxic symptoms throughout the experimental period and they also were weighted weekly to monitor body weight gain. Alteration recorded in K.F.T. parameters within the groups were due to Endosulfan exposure and serum uric acid level was significantly elevated in the 3mg/kg dose group. Pathological changes of rats treated with Endosulfan were observed with typical signs of toxicity. Uric acid is a heterocyclic compound formed as an end product of metabolism of purine nucleotides. It forms ions and salts known as urate and acid urate which are harmful to our health. Uric acid clearance is one of the numerous important functions of the kidney. Defects in this process resulted in Gout, kidney stone or Kidney failure.

Keywords: KFT parameters, blood uric acid level, endosulfan, eat

Procedia PDF Downloads 277

Authors: Mattia Dimitri, Martina Ricci, Margherita Romiti, Filippo Bigi, Andrea Corvi

Abstract:

Tissue engineering has reached a significant milestone with the integration of 3D printing for the creation of complex bioconstructs equipped with vascular networks, crucial for cell maintenance and growth. This study aims to demonstrate the effectiveness of a portable microperfusion system designed to adapt dynamically to the evolving conditions of cell growth within 3D-printed bioconstructs. The microperfusion system was developed to provide a constant and controlled flow of nutrients and oxygen through the integrated vessels in the bioconstruct, replicating in vivo physiological conditions. Through a series of preliminary experiments, we evaluated the system's ability to maintain a favourable environment for cell proliferation and differentiation. Measurements of cell density and viability were performed to monitor the health and functionality of the tissue over time. Preliminary results indicate that the portable microperfusion system not only supports but optimizes cell growth, effectively adapting to changes in metabolic needs during the bioconstruct maturation process. This research opens new perspectives in tissue engineering, demonstrating that a portable microperfusion system can be successfully integrated into 3D-printed bioconstructs, promoting sustainable and uniform cell growth. The implications of this study are far-reaching, with potential applications in regenerative medicine and pharmacological research, providing an innovative platform for the development of functional and complex tissues.

Keywords: microfluidics, biofabrication, micro-perfusion system, 3d bioprinting

Procedia PDF Downloads 6

Authors: Philip Edinger, Christian Ludwig

Abstract:

The formation and control of tars remain one of the major challenges in the implementation of biomass gasification technologies. Robust, on-line analytical methods are needed to investigate the fate of tar compounds when different measures for their reduction are applied. This work establishes an on-line UV-Vis method, based on a liquid quench sampling system, to monitor tar compounds in biomass gasification processes. Recorded spectra from the liquid phase were analyzed for their tar composition by means of a classical least squares (CLS) and partial least squares (PLS) approach. This allowed for the detection of UV-Vis active tar compounds with detection limits in the low part per million by volume (ppmV) region. The developed method was then applied to two case studies. The first involved a lab-scale reactor, intended to investigate the decomposition of a limited number of tar compounds across a catalyst. The second study involved a gas scrubber as part of a pilot scale wood gasification plant. Tar compound quantification results showed good agreement with off-line based reference methods (GC-FID) when the complexity of tar composition was limited. The two case studies show that the developed method can provide rapid, qualitative information on the tar composition for the purpose of process monitoring. In cases with a limited number of tar species, quantitative information about the individual tar compound concentrations provides an additional benefit of the analytical method.

Keywords: biomass gasification, on-line, tar, UV-Vis

Procedia PDF Downloads 243

Authors: Dalyah Y. Al-Jamal, Maryam H. Eshtaiwi, Liyakathunisa Syed

Abstract:

Connecting health services with technology has a huge demand as people health situations are becoming worse day by day. In fact, engaging new technologies such as Internet of Things (IOT) into the medical services can enhance the patient care services. Specifically, patients suffering from chronic diseases such as cardiac patients need a special care and monitoring. In reality, some efforts were previously taken to automate and improve the patient monitoring systems. However, the previous efforts have some limitations and lack the real-time feature needed for chronic kind of diseases. In this paper, an improved process model for patient monitoring system specialized for cardiac patients is presented. A survey was distributed and interviews were conducted to gather the needed requirements to improve the cardiac patient monitoring system. Business Process Model and Notation (BPMN) language was used to model the proposed process. In fact, the proposed system uses the IOT Technology to assist doctors to remotely monitor and follow-up with their heart patients in real-time. In order to validate the effectiveness of the proposed solution, simulation analysis was performed using Bizagi Modeler tool. Analysis results show performance improvements in the heart monitoring process. For the future, authors suggest enhancing the proposed system to cover all the chronic diseases.

Keywords: IoT, process model, remote patient monitoring system, smart watch

Procedia PDF Downloads 315

Authors: A. Degale Desta, Cheng Jian

Abstract:

Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

Procedia PDF Downloads 141

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

Abstract:

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

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

Procedia PDF Downloads 96

Authors: B. Lokuketagoda, M. Weerakoon, U. Madushan, A. N. Senaratne, K. Y. Abeywardena

Abstract:

Ransomware has become a common threat in past few years and the recent threat reports show an increase of growth in Ransomware infections. Researchers have identified different variants of Ransomware families since 2015. Lack of knowledge of the user about the threat is a major concern. Ransomware detection methodologies are still growing through the industry. Email is the easiest method to send Ransomware to its victims. Uninformed users tend to click on links and attachments without much consideration assuming the emails are genuine. As a solution to this in this paper R-Killer Ransomware detection tool is introduced. Tool can be integrated with existing email services. The core detection Engine (CDE) discussed in the paper focuses on separating suspicious samples from emails and handling them until a decision is made regarding the suspicious mail. It has the capability of preventing execution of identified ransomware processes. On the other hand, Sandboxing and URL analyzing system has the capability of communication with public threat intelligence services to gather known threat intelligence. The R-Killer has its own mechanism developed in its Proactive Monitoring System (PMS) which can monitor the processes created by downloaded email attachments and identify potential Ransomware activities. R-killer is capable of gathering threat intelligence without exposing the user’s data to public threat intelligence services, hence protecting the confidentiality of user data.

Keywords: ransomware, deep learning, recurrent neural networks, email, core detection engine

Procedia PDF Downloads 189

Authors: Mehrnaz Farzingohar, Mehran Yasemi, Ahmad Savari

Abstract:

The oil products are imported and exported via Rajaee’s tanker terminal. Within loading and discharging in several cases the oil is released into the berths and made oil spills. The spills are distributed within short time and seriously affected Rajaee port’s environment and even extended areas. The trajectory and fate of oil spills investigated by modeling and parted by three risk levels base on the modeling results. First GNOME (General NOAA Operational Modeling Environment) applied to trajectory the liquid oil. Second, ALOHA (Areal Location Of Hazardous Atmosphere) air quality model, is integrated to predict the oil evaporation path within the air. Base on the identified zones the high risk areas are signed by colored dots which their densities calculated and clarified on a map which displayed the harm places. Wind and water circulation moved the pollution to the East of Rajaee Port that accumulated about 12 km of coastline. Approximately 20 km of north east of Qeshm Island shore is covered by the three levels of risky areas. Since the main wind direction is SSW the pollution pushed to the east and the highest risk zones formed on the crests edges hence the low risk appeared on the concavities. This assessment help the management and emergency systems to monitor the exposure places base on the priority factors and find the best approaches to protect the environment.

Keywords: oil spill, modeling, pollution, risk assessment

Procedia PDF Downloads 366

Authors: Krishan P. Sharma, T. P. Sharma

Abstract:

Wireless sensor nodes are resource constrained battery powered devices usually deployed in hostile and ill-disposed areas to cooperatively monitor physical or environmental conditions. Due to their limited power supply, the major challenge for researchers is to utilize their battery power for enhancing the lifetime of whole network. Communication and sensing are two major sources of energy consumption in sensor networks. In this paper, we propose a deployment strategy for enhancing the average lifetime of a sensor network by effectively utilizing communication and sensing energy to provide full coverage. The proposed scheme is based on the fact that due to heavy relaying load, sensor nodes near to the sink drain energy at much faster rate than other nodes in the network and consequently die much earlier. To cover this imbalance, proposed scheme finds optimal communication and sensing ranges according to effective load at each node and uses a non-uniform deployment strategy where there is a comparatively high density of nodes near to the sink. Probable relaying load factor at particular node is calculated and accordingly optimal communication distance and sensing range for each sensor node is adjusted. Thus, sensor nodes are placed at locations that optimize energy during network operation. Formal mathematical analysis for calculating optimized locations is reported in present work.

Keywords: load factor, network lifetime, non-uniform deployment, sensing range

Procedia PDF Downloads 362

Authors: Omnia M. Kandil, Noha M. F. Hassan, Doaa Sedky, Hatem A. Shalaby, Heba M. Ashry, Nadia M. T. Abu El Ezz, Sahar M. Kandeel, Mohamed S. Abdelfattah Ying L, Ebtesam M. Al-Olayan

Abstract:

The aim of the present study was to determine the prevalence of bovine cysticercosis in both cattle and buffaloes in Egypt and to assess the cysticidal efficacy of Balanites aegyptiacafruits (B. aegyptiaca) and Moringa oleiferaseeds (M. oleifera) extracts in experimentally infected mice. The study detected the level of tumor necrosis factor (TNF-α) to monitor the immune and inflammatory responses of experimentally infected mice. Through meat inspection, a total number of 2125 male bovines, 2 to 5 years old (1125 cattle and 1000 buffaloes) were examined at official abattoirs in Cairo Governorate. The prevalence of the disease among bovine was 7.8%, (6.31% of cattle and 9.5% of buffaloes). A decrease in the number of cysticerci was found in all treated mice groups, and up to 88% reduction was achieved in the B. aegyptiaca-treated group; higher than that was recorded in both M. oleifera (72.23%) and albendazole-treated ones (80.56%). Postmortem findings proved that M. oleifera and B. aegyptiaca reduced cysticerci numbers comparable to a commercial anthelmintic. The study showed a significant decrease (P<0.001) in TNF-α levels after treatment with Balanites and Moringa extracts, compared with the untreated control and the albendazole-treated groups.

Keywords: prevalence, bovine cysticercossis, extracts, mice

Procedia PDF Downloads 69

Authors: Matias Micheletto, Rodrigo Santos, Sergio F. Ochoa

Abstract:

In developing countries, the most roads in rural areas are dirt road. They require frequent maintenance since are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the main-tenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like in Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision

Procedia PDF Downloads 182

Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

Procedia PDF Downloads 504

Authors: Faisal Alsaaq

Abstract:

Hydrographic surveys have traditionally relied on the availability of tide information for the reduction of sounding observations to a common datum. In most cases, tide information is obtained from tide gauge observations and/or tide predictions over space and time using local, regional or global tide models. While the latter often provides a rather crude approximation, the former relies on tide gauge stations that are spatially restricted, and often have sparse and limited distribution. A more recent method that is increasingly being used is Global Navigation Satellite System (GNSS) positioning which can be utilised to monitor height variations of a vessel or buoy, thus providing information on sea level variations during the time of a hydrographic survey. However, GNSS heights obtained under the dynamic environment of a survey vessel are affected by “non-tidal” processes such as wave activity and the attitude of the vessel (roll, pitch, heave and dynamic draft). This research seeks to examine techniques that separate the tide signal from other non-tidal signals that may be contained in GNSS heights. This requires an investigation of the processes involved and their temporal, spectral and stochastic properties in order to apply suitable recovery techniques of tide information. In addition, different post-mission and near real-time GNSS positioning techniques will be investigated with focus on estimation of height at ocean. Furthermore, the study will investigate the possibility to transfer the chart datums at the location of tide gauges.

Keywords: hydrography, GNSS, datum, tide gauge

Procedia PDF Downloads 246

Authors: Sheng-Hung Chen, Grace Mmametena Mahlangu, Hui-Cheng Wang

Abstract:

This study aims to explore the trends of the Entrepreneurial Framework Conditions (EFCs) in the five African regions. The Global Entrepreneur Monitor (GEM) is the primary source of data. The data drawn were organized into a panel (2000-2021) and obtained from the National Expert Survey (NES) databases as harmonized by the (GEM). The Methodology used is descriptive and uses mainly charts and tables; this is in line with the approach used by the GEM. The GEM draws its data from the National Expert Survey (NES). The survey by the NES is administered to experts in each country. The GEM collects entrepreneurship data specific to each country. It provides information about entrepreneurial ecosystems and their impact on entrepreneurship. The secondary source is from the literature review. This study focuses on the following GEM indicators: Financing for Entrepreneurs, Government support and Policies, Taxes and Bureaucracy, Government programs, Basic School Entrepreneurial Education and Training, Post school Entrepreneurial Education and Training, R&D Transfer, Commercial And Professional Infrastructure, Internal Market Dynamics, Internal Market Openness, Physical and Service Infrastructure, and Cultural And Social Norms, based on GEM Report 2020/21. The limitation of the study is the lack of updated data from some countries. Countries have to fund their own regional studies; African countries do not regularly participate due to a lack of resources.

Keywords: trend analysis, entrepreneurial framework conditions (EFCs), African region, government programs

Procedia PDF Downloads 51

Authors: E. E. S. Uy, T. Noda, K. Nakai, J. R. Dungca

Abstract:

Cyclic threshold shear strain is the cyclic shear strain amplitude that serves as the indicator of the development of pore water pressure. The parameter can be obtained by performing either cyclic triaxial test, shaking table test, cyclic simple shear or resonant column. In a cyclic triaxial test, other researchers install measuring devices in close proximity of the soil to measure the parameter. In this study, an attempt was made to estimate the cyclic threshold shear strain parameter using full-field measurement technique. The technique uses a camera to monitor and measure the movement of the soil. For this study, the technique was incorporated in a strain-controlled consolidated undrained cyclic triaxial test. Calibration of the camera was first performed to ensure that the camera can properly measure the deformation under cyclic loading. Its capacity to measure deformation was also investigated using a cylindrical rubber dummy. Two-dimensional image processing was implemented. Lucas and Kanade optical flow algorithm was applied to track the movement of the soil particles. Results from the full-field measurement technique were compared with the results from the linear variable displacement transducer. A range of values was determined from the estimation. This was due to the nonhomogeneous deformation of the soil observed during the cyclic loading. The minimum values were in the order of 10-2% in some areas of the specimen.

Keywords: cyclic loading, cyclic threshold shear strain, full-field measurement, optical flow

Procedia PDF Downloads 219

Authors: Amós García Montaño

Abstract:

In a democracy, a public policy must be developed within the regulatory framework and considering citizen participation in its planning, design, execution, and evaluation stages, necessary factors to have both legal support and sufficient legitimacy for its operation. However, the complexity and magnitude of certain public problems results in difficulties for the generation of consensus among society members, leading to unstable and unsuccessful scenarios for the exercise of the right to citizen participation and the generation of effective and efficient public policies. This is the case of public policies against corruption, an issue that in Mexico is difficult to define and generates conflicting opinions. To provide a possible solution to this delicate reality, this paper analyzes the principle of reasonableness as a tool for identifying the basic elements that guarantee a fundamental level of the exercise of the right to citizen participation in the fight against corruption, adopting elements of human rights indicator methodologies. In this sense, the relevance of having a legal framework that establishes obligations to incorporate proactive and transversal citizen participation in the matter is observed. It is also noted the need to monitor the operation of various citizen participation mechanisms in the decision-making processes of the institutions involved in the fight and prevention of corruption, which lead to an increase in the improvement of the perception of the citizen role as a relevant actor in this field. It is concluded that the principle of reasonableness is presented as a very useful tool for the identification of basic elements that facilitate the fulfillment of human rights commitments in the field of public policies.

Keywords: anticorruption, public participation, public policies, reasonableness

Procedia PDF Downloads 69

Authors: Jiraphorn Satechan, Thanaphon Khamthieng, Warunee Phanwong

Abstract:

This action research aimed at designing and developing the cleaning equipment to preventing dust diffusion of bus air filter. Quantitative and qualitative data collection methods were used to conduct data from October 1st, 2018 to September 30th, 2019. All of participants were male (100.0%) with aged 40- 49 years and 57.15%, of them finish bachelor degree. 71.43% of them was a driver and 57.15% of them had the working experience between 10 and 15 years. Research revealed that the participants assessed the quality of the bus air filter cleaning equipment for preventing dust diffusion at a moderate level (σ= 0.29), and 71.43 of them also suggested the development methods in order to improve the quality of bus air filters cleaning equipment as follows: 1) to install the circuit breaker for cutting the electricity and controlling the on-off of the equipment and to change the motor to the DC system, 2) should install the display monitor for wind pressure and electricity system as well as to install the air pressure gauge, 3) should install the tank lid lock for preventing air leakage and dust diffusion by increasing the blowing force and sucking power, 4) to stabilize the holding points for preventing the filter shaking while rotating and blowing for cleaning and to reduce the rotation speed in order to allow the filters to move slowly for the air system to blow for cleaning more thoroughly, 5) the amount of dust should be measured before and after cleaning and should be designed the cleaning equipment to be able to clean with a variety of filters, and sizes. Moreover, the light-weight materials should be used to build the cleaning equipment and the wheels should be installed at the base of the equipment in order to make it easier to move.

Keywords: Cleaning Equipment, Bus Air Filters, Preventing Dust Diffusion, Innovation

Procedia PDF Downloads 92

Authors: Kamélia Bouderbala, Hichem Nouira, Etienne Videcoq, Manuel Girault, Daniel Petit

Abstract:

Thermal drifts caused by the power dissipated by the mechanical guiding systems constitute the main limit to enhance the accuracy of an ultra-high precision cylindricity measuring machine. For this reason, a high precision compact prototype has been designed to simulate the behaviour of the instrument. It ensures in situ calibration of four capacitive displacement probes by comparison with four laser interferometers. The set-up includes three heating wires for simulating the powers dissipated by the mechanical guiding systems, four additional heating wires located between each laser interferometer head and its respective holder, 19 Platinum resistance thermometers (Pt100) to observe the temperature evolution inside the set-up and four Pt100 sensors to monitor the ambient temperature. Both a Reduced Model (RM), based on the Modal Identification Method (MIM) was developed and optimized by comparison with the experimental results. Thereafter, time dependent tests were performed under several conditions to measure the temperature variation at 19 fixed positions in the system and compared to the calculated RM results. The RM results show good agreement with experiment and reproduce as well the temperature variations, revealing the importance of the RM proposed for the evaluation of the thermal behaviour of the system.

Keywords: modal identification method (MIM), thermal behavior and drift, dimensional metrology, measurement

Procedia PDF Downloads 382

Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

Abstract:

The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

Procedia PDF Downloads 179

Authors: Jing Hu, Dong Yang

Abstract:

With the increasingly difficult development and operating environment of exploration, there are many new challenges and difficulties in developing and exploiting oil and gas resources. These include the ability to dynamically monitor wells and provide data and assurance for the completion and production of high-cost and complex wells. A key technology in providing these assurances and maximizing oilfield profitability is real-time permanent reservoir monitoring. The emergence of optical fiber sensing systems has gradually begun to replace traditional electronic systems. Traditional temperature sensors can only achieve single-point temperature monitoring, but fiber optic sensing systems based on the Bragg grating principle have a high level of reliability, accuracy, stability, and resolution, enabling cost-effective monitoring, which can be done in real-time, anytime, and without well intervention. Continuous data acquisition is performed along the entire wellbore. The integrated package with the downhole pressure gauge, packer, and surface system can also realize real-time dynamic monitoring of the pressure in some sections of the downhole, avoiding oil well intervention and eliminating the production delay and operational risks of conventional surveys. Real-time information obtained through permanent optical fibers can also provide critical reservoir monitoring data for production and recovery optimization.

Keywords: PDHM, optical fiber, coiled tubing, photoelectric composite cable, digital-oilfield

Procedia PDF Downloads 62

Authors: Chin Ku, Han liang Lin

Abstract:

The purpose of this study is to visualize how the rule related to urban design influences the building form by 3D modeling software CityEngine. In order to make the goal of urban design clearly connect to urban form, urban planner or designer should understand how the rule affects the form, especially the building form. In Taiwan, the rule pertained to urban design includes traditional zoning, urban design review and building codes. However, zoning cannot precisely expect the outcome of building form and lack of thinking about public realm and 3D form. In addition to that, urban design review is based on case by case, do not have a comprehensive regulation plan and the building code is just for general regulation. Therefore, rule cannot make the urban form reach the vision or goal of the urban design. Consequently, another kind of zoning called Form-based code (FBC) has arisen. This study uses the component of FBC which pertained to urban fabric such as street width, block and plot size, etc., to be the variants of building form, and find out the relationship between the rule and building form. There are three stages of this research, it will start from a field survey of Taichung City in Taiwan to induce the rule-building form relationship by using cluster analysis and descriptive Statistics. Second, visualize the relationship through the parameterized and codified process in CityEngine which is the procedural modeling, and can analyze, monitor and visualize the 3D world. Last, compare the CityEngine result with real world to examine how extent do this model represent the real world appearance.

Keywords: 3D visualization, CityEngine, form-based code, urban form

Procedia PDF Downloads 533

Authors: Donglian Sun, Yu Li, Paul Houser, Xiwu Zhan

Abstract:

California experienced severe drought conditions in the past years. In this study, the drought conditions in California are analyzed using soil moisture anomalies derived from integrated optical and microwave satellite observations along with auxiliary land surface data. Based on the U.S. Drought Monitor (USDM) classifications, three typical drought conditions were selected for the analysis: extreme drought conditions in 2007 and 2013, severe drought conditions in 2004 and 2009, and normal conditions in 2005 and 2006. Drought is defined as negative soil moisture anomaly. To estimate soil moisture at high spatial resolutions, three approaches are explored in this study: the universal triangle model that estimates soil moisture from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST); the basic model that estimates soil moisture under different conditions with auxiliary data like precipitation, soil texture, topography, and surface types; and the refined model that uses accumulated precipitation and its lagging effects. It is found that the basic model shows better agreements with the USDM classifications than the universal triangle model, while the refined model using precipitation accumulated from the previous summer to current time demonstrated the closest agreements with the USDM patterns.

Keywords: soil moisture, high resolution, regional drought, analysis and monitoring

Procedia PDF Downloads 120

Authors: Yong Sun, Vladimir Luzin, Zhen Qian, William J. T. Daniel, Mingxing Zhang, Shichao Ding

Abstract:

The residual stresses in roll formed products are generally very high and un-predictable. This is due to the occurrence of redundant plastic deformation in roll forming process and it can cause various product defects. Although the residual stresses of a roll formed product consist of longitudinal and transverse residual stresses components, but the longitudinal residual stresses plays a key role to the product defects of a roll formed product and therefore, only the longitudinal residual stresses concerned by the roll forming scholars and engineers. However, how to inspect the residual stresses of a product quickly and economically as a routine operation is still a challenge. This paper introduces a residual stresses measurement method called slope cutting method to study the longitudinal residual stresses through layers geometrically to a roll formed products or a product with similar process such as a rolled sheet. The detailed measuring procedure is given and discussed. The residual stresses variation through the layer can be derived based on the variation of curvature in different layers and steps. The slope cutting method has been explored and validated by experimental study on a roll-formed square tube. The neutron diffraction method is applied to validate the accuracy of the newly proposed layering removal materials results. The two set results agree with each other very well and therefore, the method is expected to be a routine testing method to monitor the quality of a product been formed and that is a great impact to roll forming industry.

Keywords: roll forming, residual stress, measurement method, neutron diffraction

Procedia PDF Downloads 350

Authors: Sarra Zaied, Arthur Bonpain, Pierre Yves Fravallo

Abstract:

The permanent supply of marine litter implies their accumulation in the oceans, which causes the presence of more compact wastes layers. Their Spatio-temporal distribution is never homogeneous and depends mainly on the hydrodynamic characteristics of the environment and the size and location of the wastes. As part of optimizing collect of marine plastic wastes, it is important to measure and monitor their evolution over time. For this, many research studies have been dedicated to describing the wastes behavior in order to identify their accumulation in oceans areas. Several models are therefore developed to understand the mechanisms that allow the accumulation and the displacements of marine litter. These models are able to accurately simulate the drift of wastes to study their behavior and stranding. However, these works aim to study the wastes behavior over a long period of time and not at the time of waste collection. This work investigates the transport of floating marine litter (FML) to provide basic information that can help in optimizing wastes collection by proposing a model for predicting their behavior during collection. The proposed study is based on a Lagrangian modeling approach that uses the main factors influencing the dynamics of the waste. The performance of the proposed method was assessed on real data collected from the Copernicus Marine Environment Monitoring Service (CMEMS). Evaluation results in the Java Sea (Indonesia) prove that the proposed model can effectively predict the position and the velocity of marine wastes during collection.

Keywords: floating marine litter, lagrangian transport, particle-tracking model, wastes drift

Procedia PDF Downloads 175

Authors: Adel Ali Elshaibani

Abstract:

Risk management indicators augment the reporting infrastructure, particularly for the board and senior management, to identify, monitor, and manage risks. This enhancement facilitates improved decision-making throughout the banking organization. Decision tree analysis is a tool that visually outlines potential outcomes, costs, and consequences of complex decisions. It is particularly beneficial for analyzing quantitative data and making decisions based on numerical values. By calculating the expected value of each outcome, decision tree analysis can help assess the best course of action. In the context of banking, decision tree analysis can assist lenders in evaluating a customer’s creditworthiness, thereby preventing losses. However, applying these tools in developing countries may face several limitations, such as data availability, lack of technological infrastructure and resources, lack of skilled professionals, cultural factors, and cost. Moreover, decision trees can create overly complex models that do not generalize well to new data, known as overfitting. They can also be sensitive to small changes in the data, which can result in different tree structures and can become computationally expensive when dealing with large datasets. In conclusion, while risk management indicators and decision tree analysis are beneficial for decision-making in banks, their effectiveness is contingent upon how they are implemented and utilized by the board of directors, especially in the context of developing countries. It’s important to consider these limitations when planning to implement these tools in developing countries.

Keywords: risk management indicators, decision tree analysis, developing countries, board of directors, bank performance, risk management strategy, banking institutions

Procedia PDF Downloads 41

Authors: Brandon Foggo, Nanpeng Yu

Abstract:

Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

Procedia PDF Downloads 280

Authors: Majid Farsadrooh, Najmeh Sabbaghi, Seyed Mohammad Mostashari, Abolhasan Moradi

Abstract:

Phenolic compounds are chief environmental contaminants on account of their hazardous and toxic nature on human health. The preparation of sensitive and potent chemosensors to monitor emerging pollution in water and effluent samples has received great consideration. A novel and versatile nanocomposite sensor based on poly pyrogallol is presented for the first time in this study, and its electrochemical behavior for simultaneous detection of hydroquinone (HQ), catechol (CT), and resorcinol (RS) in the presence of nitrite is evaluated. The physicochemical characteristics of the fabricated nanocomposite were investigated by emission-scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDS), and Brunauer-Emmett-Teller (BET). The electrochemical response of the proposed sensor to the detection of HQ, CT, RS, and nitrite is studied using cyclic voltammetry (CV), chronoamperometry (CA), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). The kinetic characterization of the prepared sensor showed that both adsorption and diffusion processes can control reactions at the electrode. In the optimized conditions, the new chemosensor provides a wide linear range of 0.5-236.3, 0.8-236.3, 0.9-236.3, and 1.2-236.3 μM with a low limit of detection of 21.1, 51.4, 98.9, and 110.8 nM (S/N = 3) for HQ, CT and RS, and nitrite, respectively. Remarkably, the electrochemical sensor has outstanding selectivity, repeatability, and stability and is successfully employed for the detection of RS, CT, HQ, and nitrite in real water samples with the recovery of 96.2%–102.4%, 97.8%-102.6%, 98.0%–102.4% and 98.4%–103.2% for RS, CT, HQ, and nitrite, respectively. These outcomes illustrate that poly pyrogallol is a promising candidate for effective electrochemical detection of dihydroxybenzene isomers in the presence of nitrite.

Keywords: electrochemical sensor, poly pyrogallol, phenolic compounds, simultaneous determination

Procedia PDF Downloads 53